@article{Shein-Idelson2017,
title = {Large-scale mapping of cortical synaptic projections with extracellular electrode arrays},
author = {Mark Shein-Idelson and Lorenz Pammer and Mike Hemberger and Gilles Laurent},
url = {http://www.nature.com/doifinder/10.1038/nmeth.4393},
doi = {10.1038/nmeth.4393},
issn = {1548-7091},
year = {2017},
date = {2017-08-14},
journal = {Nature Methods},
volume = {14},
number = {9},
pages = {882--889},
abstract = {Understanding circuit computation in the nervous system requires sampling activity over large neural populations and maximizing the number of features that can be extracted. By combining planar arrays of extracellular electrodes with the three-layered cortex of turtles, we show that synaptic signals induced along individual axons as well as action potentials can be easily captured. Two types of information can be extracted from these signals, the neuronal subtype (inhibitory or excitatory)—whose identification is more reliable than with traditional measures such as action potential width—and a (partial) spatial map of functional axonal projections from individual neurons. Because our approach is algorithmic, it can be carried out in parallel on hundreds of simultaneously recorded neurons. Combining our approach with soma triangulation, we reveal an axonal projection bias among a population of pyramidal neurons in turtle cortex and confirm this bias through anatomical reconstructions.},
keywords = {Brain Slice, MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Understanding circuit computation in the nervous system requires sampling activity over large neural populations and maximizing the number of features that can be extracted. By combining planar arrays of extracellular electrodes with the three-layered cortex of turtles, we show that synaptic signals induced along individual axons as well as action potentials can be easily captured. Two types of information can be extracted from these signals, the neuronal subtype (inhibitory or excitatory)—whose identification is more reliable than with traditional measures such as action potential width—and a (partial) spatial map of functional axonal projections from individual neurons. Because our approach is algorithmic, it can be carried out in parallel on hundreds of simultaneously recorded neurons. Combining our approach with soma triangulation, we reveal an axonal projection bias among a population of pyramidal neurons in turtle cortex and confirm this bias through anatomical reconstructions.
@conference{Obien2017,
title = {Mapping neuron cluster development based on axonal action potential propagation},
author = {Marie Engelene J. Obien and Giulio Zorzi and Andreas Hierlemann},
year = {2017},
date = {2017-07-20},
address = {Chiba, Japan},
organization = {The 40th Annual Meeting of the Japan Neuroscience Society},
keywords = {Action Potential, Neuronal Networks},
pubstate = {published},
tppubtype = {conference}
}
@conference{Diggelmann2017,
title = {Pre-whitening as a means to improve dimensionality reduction and simplify clustering in spike-sorters for multi-electrode recordings},
author = {Roland Diggelmann and Michele Fiscella and Andreas Hierlemann and Felix Franke},
url = {https://bmcneurosci.biomedcentral.com/articles/10.1186/s12868-017-0371-2},
year = {2017},
date = {2017-07-15},
address = {Antwerp, Belgium },
organization = {26th Annual Computational Neuroscience Meeting (CNS2017)},
abstract = {Spike sorting is the process to extract single neuronal activity from extracellular recordings. It makes use of the fact that spikes from a single neuron feature highly similar waveforms, whereas spikes from different neurons have different waveforms. Clustering algorithms are used to find groups of similar spikes that putatively originated from the same neuron. However, since spike waveforms especially in multi-electrode recordings can have a high dimensionality, their dimensionality needs to be reduced before clustering. Principal component analysis (PCA) is one of the most commonly employed dimensionality reduction methods for this purpose [1]. It reduces the dimensions to those where the variance of the data was highest, presumably those along which the waveforms of separate neurons differ most strongly, However, if the noise is not uniform in all dimensions, high variability can also mean high noise, which would render a dimension useless for discrimination. We, therefore, propose an additional pre-whitening step before PCA and discuss two beneficial effects on the subsequent clustering. We illustrate these effects by using spikes from retinal ganglion cells recorded with high-density multi-electrode arrays (HD-MEA).},
keywords = {Spike Sorting},
pubstate = {published},
tppubtype = {conference}
}
Spike sorting is the process to extract single neuronal activity from extracellular recordings. It makes use of the fact that spikes from a single neuron feature highly similar waveforms, whereas spikes from different neurons have different waveforms. Clustering algorithms are used to find groups of similar spikes that putatively originated from the same neuron. However, since spike waveforms especially in multi-electrode recordings can have a high dimensionality, their dimensionality needs to be reduced before clustering. Principal component analysis (PCA) is one of the most commonly employed dimensionality reduction methods for this purpose [1]. It reduces the dimensions to those where the variance of the data was highest, presumably those along which the waveforms of separate neurons differ most strongly, However, if the noise is not uniform in all dimensions, high variability can also mean high noise, which would render a dimension useless for discrimination. We, therefore, propose an additional pre-whitening step before PCA and discuss two beneficial effects on the subsequent clustering. We illustrate these effects by using spikes from retinal ganglion cells recorded with high-density multi-electrode arrays (HD-MEA).
@conference{Viswam2017c,
title = {High-density mapping of brain slices using a large multi-functional high-density CMOS microelectrode array system},
author = {Vijay Viswam and Raziyeh Bounik and Amir Shadmani and Jelena Dragas and Marie Obien and Jan Müller and Yihui Chen and Andreas Hierlemann1},
url = {https://ieeexplore.ieee.org/document/7994006},
doi = {10.1109/TRANSDUCERS.2017.7994006},
year = {2017},
date = {2017-06-18},
organization = {2017 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS)},
abstract = {We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitrowith multiple readout modalities. The 4.48×2.43 mm2 array consists of 59,760 micro-electrodes at 13.5 μm pitch (5487 electrodes/mm2). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/ current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.},
keywords = {ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {conference}
}
We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitrowith multiple readout modalities. The 4.48×2.43 mm2 array consists of 59,760 micro-electrodes at 13.5 μm pitch (5487 electrodes/mm2). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/ current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.
@conference{Viswam2017b,
title = {High-density Mapping of Brain Slices Using a Large Multi-functional High-density CMOS Microelectrode Array System},
author = {Vijay Viswam and Raziyeh Bounik and Amir Shadmani and Jelena Dragas and Marie Engelene J. Obien and Jan Muller and Yihui Chen and Andreas Hierlemann },
url = {https://ieeexplore.ieee.org/abstract/document/7994006},
doi = {10.1109/TRANSDUCERS.2017.7994006},
issn = {2167-0021},
year = {2017},
date = {2017-06-18},
pages = {135-138},
address = {Kaohsiung, Taiwan},
organization = {19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS)},
abstract = {We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitro with multiple readout modalities. The 4.48×2.43 mm 2 array consists of 59,760 micro-electrodes at 13.5 μm pitch (5487 electrodes/mm 2 ). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.},
keywords = {Brain Slice, ETH-CMOS-MEA, HD-MEA},
pubstate = {published},
tppubtype = {conference}
}
We present a CMOS-based high-density microelectrode array (HD-MEA) system that enables high-density mapping of brain slices in-vitro with multiple readout modalities. The 4.48×2.43 mm 2 array consists of 59,760 micro-electrodes at 13.5 μm pitch (5487 electrodes/mm 2 ). The overall system features 2048 action-potential, 32 local-field-potential and 32 current recording channels, 32 impedance-measurement and 28 neurotransmitter-detection channels and 16 voltage/current stimulation channels. The system enables real-time and label-free monitoring of position, size, morphology and electrical activity of brain slices.
@conference{Frey2017,
title = {Technology Trends and Commercialization of High-density Microelectrode Arrays for Advanced In-vitro Electrophysiology},
author = {Urs Frey and Marie Engelene J. Obien and Jan Muller and Andreas Hierlemann},
url = {https://ieeexplore.ieee.org/document/8050215/},
doi = {10.1109/ISCAS.2017.8050215},
issn = {2379-447X},
year = {2017},
date = {2017-05-28},
address = {Baltimore, MD, USA},
organization = {IEEE International Symposium on Circuits and Systems (ISCAS},
abstract = {Microelectrode arrays (MEAs) enable fast and high-throughput readout of cell's electrical signals. MEAs are currently used for phenotype characterization and drug toxicity/efficacy testing with iPSC-derived neurons and cardiomyocytes. A key advantage of MEAs is the capability to record and stimulate individual neurons at multiple sites simultaneously. We will present ongoing advancements of MEA technology, with a focus on achieving higher quality recordings by means of monolithic co-integration of circuitry on chip by using CMOS technology [1]. Such high-density MEAs with more than 3000 electrodes per mm2 are a suitable tool for capturing neuronal activity across various scales, including axons, somas, dendrites, entire neurons, and networks.},
keywords = {HD-MEA, In-Vitro},
pubstate = {published},
tppubtype = {conference}
}
Microelectrode arrays (MEAs) enable fast and high-throughput readout of cell's electrical signals. MEAs are currently used for phenotype characterization and drug toxicity/efficacy testing with iPSC-derived neurons and cardiomyocytes. A key advantage of MEAs is the capability to record and stimulate individual neurons at multiple sites simultaneously. We will present ongoing advancements of MEA technology, with a focus on achieving higher quality recordings by means of monolithic co-integration of circuitry on chip by using CMOS technology [1]. Such high-density MEAs with more than 3000 electrodes per mm2 are a suitable tool for capturing neuronal activity across various scales, including axons, somas, dendrites, entire neurons, and networks.
@article{Hillier2017,
title = {Causal evidence for retina-dependent and -independent visual motion computations in mouse cortex},
author = {Daniel Hillier and Michele Fiscella and Antonia Drinnenberg and Stuart Trenholm and Santiago B Rompani and Zoltan Raics and Gergely Katona and Josephine Jüttner and Andreas Hierlemann and Balazs Rozsa and Botond Roska},
url = {http://www.nature.com/doifinder/10.1038/nn.4566},
doi = {10.1038/nn.4566},
issn = {1097-6256},
year = {2017},
date = {2017-05-22},
journal = {Nature Neuroscience},
volume = {20},
number = {7},
pages = {960--968},
abstract = {How neuronal computations in the sensory periphery contribute to computations in the cortex is not well understood. We examined this question in the context of visual-motion processing in the retina and primary visual cortex (V1) of mice. We disrupted retinal direction selectivity, either exclusively along the horizontal axis using FRMD7 mutants or along all directions by ablating starburst amacrine cells, and monitored neuronal activity in layer 2/3 of V1 during stimulation with visual motion. In control mice, we found an over-representation of cortical cells preferring posterior visual motion, the dominant motion direction an animal experiences when it moves forward. In mice with disrupted retinal direction selectivity, the over-representation of posterior-motion-preferring cortical cells disappeared, and their responses at higher stimulus speeds were reduced. This work reveals the existence of two functionally distinct, sensory-periphery-dependent and -independent computations of visual motion in the cortex.},
keywords = {MaxOne, Retina},
pubstate = {published},
tppubtype = {article}
}
How neuronal computations in the sensory periphery contribute to computations in the cortex is not well understood. We examined this question in the context of visual-motion processing in the retina and primary visual cortex (V1) of mice. We disrupted retinal direction selectivity, either exclusively along the horizontal axis using FRMD7 mutants or along all directions by ablating starburst amacrine cells, and monitored neuronal activity in layer 2/3 of V1 during stimulation with visual motion. In control mice, we found an over-representation of cortical cells preferring posterior visual motion, the dominant motion direction an animal experiences when it moves forward. In mice with disrupted retinal direction selectivity, the over-representation of posterior-motion-preferring cortical cells disappeared, and their responses at higher stimulus speeds were reduced. This work reveals the existence of two functionally distinct, sensory-periphery-dependent and -independent computations of visual motion in the cortex.
@article{Bullmann2017,
title = {Network Analysis Of High-Density Microelectrode Recordings},
author = {Bullmann, Torsten; Radivojevic, Milos; Huber, Stefan T: Deligkaris, Kosmas; Hierlemann, Andreas; Frey, Urs },
url = {https://www.biorxiv.org/content/early/2017/05/18/139436
},
doi = {10.1101/139436},
year = {2017},
date = {2017-05-18},
journal = {bioRxiv },
number = {139436},
pages = {1-23},
abstract = {Extracellular voltage fields produced by a neuron's action potentials provide a primary means for studying neuron function, yet their biophysical sources remain ambiguous. The neuron's soma and dendrites are thought to drive the extracellular action potential (EAP), while the axon is usually ignored. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices at hundreds of sites, we find instead that the axon initial segment dominates the EAP, and, surprisingly, the soma shows little or no influence. As expected, this signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage field is important for interpreting results from all electrical readout schemes. Moreover, this finding shows that changes in the AIS position and function can be observed in high spatiotemporal detail by means of high-density extracellular electrophysiology.},
keywords = {ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Extracellular voltage fields produced by a neuron's action potentials provide a primary means for studying neuron function, yet their biophysical sources remain ambiguous. The neuron's soma and dendrites are thought to drive the extracellular action potential (EAP), while the axon is usually ignored. However, by recording voltages of single neurons in dissociated rat cortical cultures and Purkinje cells in acute mouse cerebellar slices at hundreds of sites, we find instead that the axon initial segment dominates the EAP, and, surprisingly, the soma shows little or no influence. As expected, this signal has negative polarity (charge entering the cell) and initiates at the distal end. Interestingly, signals with positive polarity (charge exiting the cell) occur near some but not all dendritic branches and occur after a delay. Such basic knowledge about which neuronal compartments contribute to the extracellular voltage field is important for interpreting results from all electrical readout schemes. Moreover, this finding shows that changes in the AIS position and function can be observed in high spatiotemporal detail by means of high-density extracellular electrophysiology.
@article{Dragas2017,
title = {A Multi-Functional Microelectrode Array Featuring 59760 Electrodes, 2048 Electrophysiology Channels, Stimulation, Impedance Measurement and Neurotransmitter Detection Channels},
author = {Jelena Dragas and Vijay Viswam and Amir Shadmani and Yihui Chen and Raziyeh Bounik and Alexander Stettler and Milos Radivojevic and Sydney Geissler and Marie Engelene J Obien and Jan Müller and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/7913669/},
doi = {10.1109/JSSC.2017.2686580},
issn = {0018-9200},
year = {2017},
date = {2017-04-27},
journal = {IEEE journal of solid-state circuits},
volume = {52},
number = {6},
pages = {1576-1590},
abstract = {Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm(2)) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 mum electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
Biological cells are characterized by highly complex phenomena and processes that are, to a great extent, interdependent. To gain detailed insights, devices designed to study cellular phenomena need to enable tracking and manipulation of multiple cell parameters in parallel; they have to provide high signal quality and high spatiotemporal resolution. To this end, we have developed a CMOS-based microelectrode array system that integrates six measurement and stimulation functions, the largest number to date. Moreover, the system features the largest active electrode array area to date (4.48×2.43 mm(2)) to accommodate 59,760 electrodes, while its power consumption, noise characteristics, and spatial resolution (13.5 mum electrode pitch) are comparable to the best state-of-the-art devices. The system includes: 2,048 action-potential (AP, bandwidth: 300 Hz to 10 kHz) recording units, 32 local-field-potential (LFP, bandwidth: 1 Hz to 300 Hz) recording units, 32 current recording units, 32 impedance measurement units, and 28 neurotransmitter detection units, in addition to the 16 dual-mode voltage-only or current/voltage-controlled stimulation units. The electrode array architecture is based on a switch matrix, which allows for connecting any measurement/stimulation unit to any electrode in the array and for performing different measurement/stimulation functions in parallel.
@article{Jackel2017,
title = {Combination of High-density Microelectrode Array and Patch Clamp Recordings to Enable Studies of Multisynaptic Integration},
author = {David Jäckel and Douglas J Bakkum and Thomas L Russell and Jan Müller and Milos Radivojevic and Urs Frey and Felix Franke and Andreas Hierlemann},
url = {http://www.nature.com/articles/s41598-017-00981-4},
doi = {10.1038/s41598-017-00981-4},
issn = {2045-2322},
year = {2017},
date = {2017-04-20},
journal = {Scientific Reports},
volume = {7},
number = {1},
pages = {978},
abstract = {We present a novel, all-electric approach to record and to precisely control the activity of tens of individual presynaptic neurons. The method allows for parallel mapping of the efficacy of multiple synapses and of the resulting dynamics of postsynaptic neurons in a cortical culture. For the measurements, we combine an extracellular high-density microelectrode array, featuring 11'000 electrodes for extracellular recording and stimulation, with intracellular patch-clamp recording. We are able to identify the contributions of individual presynaptic neurons - including inhibitory and excitatory synaptic inputs - to postsynaptic potentials, which enables us to study dendritic integration. Since the electrical stimuli can be controlled at microsecond resolution, our method enables to evoke action potentials at tens of presynaptic cells in precisely orchestrated sequences of high reliability and minimum jitter. We demonstrate the potential of this method by evoking short- and long-term synaptic plasticity through manipulation of multiple synaptic inputs to a specific neuron.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
We present a novel, all-electric approach to record and to precisely control the activity of tens of individual presynaptic neurons. The method allows for parallel mapping of the efficacy of multiple synapses and of the resulting dynamics of postsynaptic neurons in a cortical culture. For the measurements, we combine an extracellular high-density microelectrode array, featuring 11'000 electrodes for extracellular recording and stimulation, with intracellular patch-clamp recording. We are able to identify the contributions of individual presynaptic neurons - including inhibitory and excitatory synaptic inputs - to postsynaptic potentials, which enables us to study dendritic integration. Since the electrical stimuli can be controlled at microsecond resolution, our method enables to evoke action potentials at tens of presynaptic cells in precisely orchestrated sequences of high reliability and minimum jitter. We demonstrate the potential of this method by evoking short- and long-term synaptic plasticity through manipulation of multiple synaptic inputs to a specific neuron.
@article{Seichepine2017,
title = {Dielectrophoresis‐Assisted Integration of 1024 Carbon Nanotube Sensors into a CMOS Microsystem},
author = {Florent Seichepine and Jorg Rothe and Alexandra Dudina and Andreas Hierlemann and Urs Frey},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/adma.201606852},
doi = {10.1002/adma.201606852},
year = {2017},
date = {2017-03-15},
journal = {Advanced Materials},
volume = {29},
number = {17},
abstract = {Carbon‐nanotube (CNT)‐based sensors offer the potential to detect single‐molecule events and picomolar analyte concentrations. An important step toward applications of such nanosensors is their integration in large arrays. The availability of large arrays would enable multiplexed and parallel sensing, and the simultaneously obtained sensor signals would facilitate statistical analysis. A reliable method to fabricate an array of 1024 CNT‐based sensors on a fully processed complementary‐metal‐oxide‐semiconductor microsystem is presented. A high‐yield process for the deposition of CNTs from a suspension by means of liquid‐coupled floating‐electrode dielectrophoresis (DEP), which yielded 80% of the sensor devices featuring between one and five CNTs, is developed. The mechanism of floating‐electrode DEP on full arrays and individual devices to understand its self‐limiting behavior is studied. The resistance distributions across the array of CNT devices with respect to different DEP parameters are characterized. The CNT devices are then operated as liquid‐gated CNT field‐effect‐transistors (LG‐CNTFET) in liquid environment. Current dependency to the gate voltage of up to two orders of magnitude is recorded. Finally, the sensors are validated by studying the pH dependency of the LG‐CNTFET conductance and it is demonstrated that 73% of the CNT sensors of a given microsystem show a resistance decrease upon increasing the pH value.},
keywords = {ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Carbon‐nanotube (CNT)‐based sensors offer the potential to detect single‐molecule events and picomolar analyte concentrations. An important step toward applications of such nanosensors is their integration in large arrays. The availability of large arrays would enable multiplexed and parallel sensing, and the simultaneously obtained sensor signals would facilitate statistical analysis. A reliable method to fabricate an array of 1024 CNT‐based sensors on a fully processed complementary‐metal‐oxide‐semiconductor microsystem is presented. A high‐yield process for the deposition of CNTs from a suspension by means of liquid‐coupled floating‐electrode dielectrophoresis (DEP), which yielded 80% of the sensor devices featuring between one and five CNTs, is developed. The mechanism of floating‐electrode DEP on full arrays and individual devices to understand its self‐limiting behavior is studied. The resistance distributions across the array of CNT devices with respect to different DEP parameters are characterized. The CNT devices are then operated as liquid‐gated CNT field‐effect‐transistors (LG‐CNTFET) in liquid environment. Current dependency to the gate voltage of up to two orders of magnitude is recorded. Finally, the sensors are validated by studying the pH dependency of the LG‐CNTFET conductance and it is demonstrated that 73% of the CNT sensors of a given microsystem show a resistance decrease upon increasing the pH value.
@article{Takahashi2017,
title = {Development of neural population activity toward self-organized criticality},
author = {Yuichiro Yada and Takeshi Mita and Akihiro Sanada and Ryuichi Yano and Ryohei Kanzaki and Douglas J Bakkum and Andreas Hierlemann and Hirokazu Takahashi},
url = {http://www.sciencedirect.com/science/article/pii/S0306452216306522},
doi = {10.1016/j.neuroscience.2016.11.031},
issn = {0306-4522},
year = {2017},
date = {2017-02-20},
journal = {Neuroscience},
volume = {343},
pages = {55-65},
abstract = {Self-organized criticality (SoC), a spontaneous dynamic state established and maintained in networks of moderate complexity, is a universal characteristic of neural systems. Such systems produce cascades of spontaneous activity that are typically characterized by power-law distributions and rich, stable spatiotemporal patterns (i.e., neuronal avalanches). Since the dynamics of the critical state confer advantages in information processing within neuronal networks, it is of great interest to determine how criticality emerges during development. One possible mechanism is developmental, and includes axonal elongation during synaptogenesis and subsequent synaptic pruning in combination with the maturation of GABAergic inhibition (i.e., the integration then fragmentation process). Because experimental evidence for this mechanism remains inconclusive, we studied the developmental variation of neuronal avalanches in dissociated cortical neurons using high-density complementary metal-oxide semiconductor (CMOS) microelectrode arrays (MEAs). The spontaneous activities of nine cultures were monitored using CMOS MEAs from 4 to 30 days in vitro (DIV) at single-cell spatial resolution. While cells were immature, cultures demonstrated random-like patterns of activity and an exponential avalanche size distribution; this distribution was followed by a bimodal distribution, and finally a power-law-like distribution. The bimodal distribution was associated with a large-scale avalanche with a homogeneous spatiotemporal pattern, while the subsequent power-law distribution was associated with diverse patterns. These results suggest that the SoC emerges through a two-step process: the integration process accompanying the characteristic large-scale avalanche and the fragmentation process associated with diverse middle-size avalanches.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Self-organized criticality (SoC), a spontaneous dynamic state established and maintained in networks of moderate complexity, is a universal characteristic of neural systems. Such systems produce cascades of spontaneous activity that are typically characterized by power-law distributions and rich, stable spatiotemporal patterns (i.e., neuronal avalanches). Since the dynamics of the critical state confer advantages in information processing within neuronal networks, it is of great interest to determine how criticality emerges during development. One possible mechanism is developmental, and includes axonal elongation during synaptogenesis and subsequent synaptic pruning in combination with the maturation of GABAergic inhibition (i.e., the integration then fragmentation process). Because experimental evidence for this mechanism remains inconclusive, we studied the developmental variation of neuronal avalanches in dissociated cortical neurons using high-density complementary metal-oxide semiconductor (CMOS) microelectrode arrays (MEAs). The spontaneous activities of nine cultures were monitored using CMOS MEAs from 4 to 30 days in vitro (DIV) at single-cell spatial resolution. While cells were immature, cultures demonstrated random-like patterns of activity and an exponential avalanche size distribution; this distribution was followed by a bimodal distribution, and finally a power-law-like distribution. The bimodal distribution was associated with a large-scale avalanche with a homogeneous spatiotemporal pattern, while the subsequent power-law distribution was associated with diverse patterns. These results suggest that the SoC emerges through a two-step process: the integration process accompanying the characteristic large-scale avalanche and the fragmentation process associated with diverse middle-size avalanches.
@article{Gong2016,
title = {Multiple single-unit long-term tracking on organotypic hippocampal slices using high-density microelectrode arrays},
author = {Wei Gong and Jure Sencar and Douglas J Bakkum and David Jäckel and Marie Engelene J Obien and Milos Radivojevic and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2016.00537/full},
doi = {10.3389/fnins.2016.00537},
issn = {1662453X},
year = {2016},
date = {2016-11-22},
journal = {Frontiers in Neuroscience},
volume = {10},
pages = {1-16},
abstract = {A novel system to cultivate and record from organotypic brain slices directly on high-density microelectrode arrays (HD-MEA) was developed. This system allows for continuous recording of electrical activity of specific individual neurons at high spatial resolution while monitoring at the same time, neuronal network activity. For the first time, the electrical activity patterns of single neurons and the corresponding neuronal network in an organotypic hippocampal slice culture were studied during several consecutive weeks at daily intervals. An unsupervised iterative spike-sorting algorithm, based on PCA and k-means clustering, was developed to assign the activities to the single units. Spike-triggered average extracellular waveforms of an action potential recorded across neighboring electrodes, termed ‘footprints' of single-units were generated and tracked over weeks. The developed system offers the potential to study chronic impacts of drugs or genetic modifications on individual neurons in slice preparations over extended times.},
keywords = {Brain Slice, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
A novel system to cultivate and record from organotypic brain slices directly on high-density microelectrode arrays (HD-MEA) was developed. This system allows for continuous recording of electrical activity of specific individual neurons at high spatial resolution while monitoring at the same time, neuronal network activity. For the first time, the electrical activity patterns of single neurons and the corresponding neuronal network in an organotypic hippocampal slice culture were studied during several consecutive weeks at daily intervals. An unsupervised iterative spike-sorting algorithm, based on PCA and k-means clustering, was developed to assign the activities to the single units. Spike-triggered average extracellular waveforms of an action potential recorded across neighboring electrodes, termed ‘footprints' of single-units were generated and tracked over weeks. The developed system offers the potential to study chronic impacts of drugs or genetic modifications on individual neurons in slice preparations over extended times.
@article{Frey2016,
title = {Extracellularly Recorded Somatic and Neuritic Signal Shapes and Classification Algorithms for High-Density Microelectrode Array Electrophysiology},
author = {Kosmas Deligkaris and Torsten Bullmann and Urs Frey},
url = {https://www.frontiersin.org/article/10.3389/fnins.2016.00421},
doi = {10.3389/fnins.2016.00421},
issn = {1662-453X},
year = {2016},
date = {2016-09-14},
journal = {Frontiers in Neuroscience},
volume = {10},
pages = {421},
abstract = {High-density microelectrode arrays (HDMEA) have been recently introduced to study principles of neural function at high spatial resolution. However, the exact nature of the experimentally observed extracellular action potentials (EAPs) is still incompletely understood. The soma, axon and dendrites of a neuron can all exhibit regenerative action potentials that could be sensed with HDMEA electrodes. Here, we investigate the contribution of distinct neuronal sources of activity in HDMEA recordings from low-density neuronal cultures. We recorded EAPs with HDMEAs having 11,011 electrodes and then fixed and immunostained the cultures with beta3-tubulin for high-resolution fluorescence imaging. Immunofluorescence images overlaid with the activity maps showed EAPs both at neuronal somata and distal neurites. Neuritic EAPs had mostly narrow triphasic shapes, consisting of a positive, a pronounced negative peak and a second positive peak. EAPs near somata had wide monophasic or biphasic shapes with a main negative peak, and following optional positive peak. We show that about 86% of EAP recordings consist of somatic spikes, while the remaining 14% represent neuritic spikes. Furthermore, the adaptation of the waveform shape during bursts of these neuritic spikes suggested that they originate from axons, rather than from dendrites. Our study improves the understanding of HDMEA signals and can aid in the identification of the source of EAPs.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
High-density microelectrode arrays (HDMEA) have been recently introduced to study principles of neural function at high spatial resolution. However, the exact nature of the experimentally observed extracellular action potentials (EAPs) is still incompletely understood. The soma, axon and dendrites of a neuron can all exhibit regenerative action potentials that could be sensed with HDMEA electrodes. Here, we investigate the contribution of distinct neuronal sources of activity in HDMEA recordings from low-density neuronal cultures. We recorded EAPs with HDMEAs having 11,011 electrodes and then fixed and immunostained the cultures with beta3-tubulin for high-resolution fluorescence imaging. Immunofluorescence images overlaid with the activity maps showed EAPs both at neuronal somata and distal neurites. Neuritic EAPs had mostly narrow triphasic shapes, consisting of a positive, a pronounced negative peak and a second positive peak. EAPs near somata had wide monophasic or biphasic shapes with a main negative peak, and following optional positive peak. We show that about 86% of EAP recordings consist of somatic spikes, while the remaining 14% represent neuritic spikes. Furthermore, the adaptation of the waveform shape during bursts of these neuritic spikes suggested that they originate from axons, rather than from dendrites. Our study improves the understanding of HDMEA signals and can aid in the identification of the source of EAPs.
@article{Radivojevic2016,
title = {Electrical Identification and Selective Microstimulation of Neuronal Compartments Based on Features of Extracellular Action Potentials},
author = {Milos Radivojevic and David Jäckel and Michael Altermatt and Jan Müller and Vijay Viswam and Andreas Hierlemann and Douglas J Bakkum},
url = {http://www.nature.com/articles/srep31332},
doi = {10.1038/srep31332},
issn = {2045-2322},
year = {2016},
date = {2016-08-11},
journal = {Scientific Reports},
volume = {6},
number = {1},
pages = {1-20},
abstract = {A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.},
keywords = {ETH-CMOS-MEA, Neuronal Networks, Stimulation},
pubstate = {published},
tppubtype = {article}
}
A detailed, high-spatiotemporal-resolution characterization of neuronal responses to local electrical fields and the capability of precise extracellular microstimulation of selected neurons are pivotal for studying and manipulating neuronal activity and circuits in networks and for developing neural prosthetics. Here, we studied cultured neocortical neurons by using high-density microelectrode arrays and optical imaging, complemented by the patch-clamp technique, and with the aim to correlate morphological and electrical features of neuronal compartments with their responsiveness to extracellular stimulation. We developed strategies to electrically identify any neuron in the network, while subcellular spatial resolution recording of extracellular action potential (AP) traces enabled their assignment to the axon initial segment (AIS), axonal arbor and proximal somatodendritic compartments. Stimulation at the AIS required low voltages and provided immediate, selective and reliable neuronal activation, whereas stimulation at the soma required high voltages and produced delayed and unreliable responses. Subthreshold stimulation at the soma depolarized the somatic membrane potential without eliciting APs.
@article{Lewandowska2016,
title = {Cortical axons, isolated in channels, display activity-dependent signal modulation as a result of targeted stimulation},
author = {Marta K Lewandowska and Milos Radivojevic and David Jäckel and Jan Müller and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2016.00083/full},
doi = {10.3389/fnins.2016.00083},
issn = {1662453X},
year = {2016},
date = {2016-03-07},
journal = {Frontiers in Neuroscience},
volume = {10},
pages = {83},
abstract = {Mammalian cortical axons are extremely thin processes that are difficult to study as a result of their small diameter: they are too narrow to patch while intact, and super-resolution microscopy is needed to resolve single axons. We present a method for studying axonal physiology by pairing a high-density microelectrode array with a microfluidic axonal isolation device, and use it to study activity-dependent modulation of axonal signal propagation evoked by stimulation near the soma. Up to three axonal branches from a single neuron, isolated in different channels, were recorded from simultaneously using 10-20 electrodes per channel. The axonal channels amplified spikes such that propagations of individual signals along tens of electrodes could easily be discerned with high signal to noise. Stimulation from 10 up to 160 Hz demonstrated similar qualitative results from all of the cells studied: extracellular action potential characteristics changed drastically in response to stimulation. Spike height decreased, spike width increased, and latency increased, as a result of reduced propagation velocity, as the number of stimulations and the stimulation frequencies increased. Quantitatively, the strength of these changes manifested itself differently in cells at different frequencies of stimulation. Some cells' signal fidelity fell to 80% already at 10 Hz, while others maintained 80% signal fidelity at 80 Hz. Differences in modulation by axonal branches of the same cell were also seen for different stimulation frequencies, starting at 10 Hz. Potassium ion concentration changes altered the behavior of the cells causing propagation failures at lower concentrations and improving signal fidelity at higher concentrations.},
keywords = {MaxOne, Neuronal Networks, u-Tunnels},
pubstate = {published},
tppubtype = {article}
}
Mammalian cortical axons are extremely thin processes that are difficult to study as a result of their small diameter: they are too narrow to patch while intact, and super-resolution microscopy is needed to resolve single axons. We present a method for studying axonal physiology by pairing a high-density microelectrode array with a microfluidic axonal isolation device, and use it to study activity-dependent modulation of axonal signal propagation evoked by stimulation near the soma. Up to three axonal branches from a single neuron, isolated in different channels, were recorded from simultaneously using 10-20 electrodes per channel. The axonal channels amplified spikes such that propagations of individual signals along tens of electrodes could easily be discerned with high signal to noise. Stimulation from 10 up to 160 Hz demonstrated similar qualitative results from all of the cells studied: extracellular action potential characteristics changed drastically in response to stimulation. Spike height decreased, spike width increased, and latency increased, as a result of reduced propagation velocity, as the number of stimulations and the stimulation frequencies increased. Quantitatively, the strength of these changes manifested itself differently in cells at different frequencies of stimulation. Some cells' signal fidelity fell to 80% already at 10 Hz, while others maintained 80% signal fidelity at 80 Hz. Differences in modulation by axonal branches of the same cell were also seen for different stimulation frequencies, starting at 10 Hz. Potassium ion concentration changes altered the behavior of the cells causing propagation failures at lower concentrations and improving signal fidelity at higher concentrations.
@article{Franke2016,
title = {Structures of Neural Correlation and How They Favor Coding},
author = {Felix Franke and Michele Fiscella and Maksim Sevelev and Botond Roska and Andreas Hierlemann and Rava {Azeredo da Silveira}},
url = {http://www.sciencedirect.com/science/article/pii/S0896627315011393?via%3Dihub},
doi = {10.1016/j.neuron.2015.12.037},
issn = {10974199},
year = {2016},
date = {2016-01-20},
journal = {Neuron},
volume = {89},
number = {2},
pages = {409-422},
publisher = {Elsevier Inc.},
abstract = {The neural representation of information suffers from "noise"-the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. Coding in the brain suffers from the variability of neural responses. Using experiment and theory, Franke et al. show that this "noise" comes with a particular structure, which emerges from circuit properties and which counteracts the harmful effect of variability.},
keywords = {Data Analysis, ETH-CMOS-MEA, Neuronal Networks, Retina},
pubstate = {published},
tppubtype = {article}
}
The neural representation of information suffers from "noise"-the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. Coding in the brain suffers from the variability of neural responses. Using experiment and theory, Franke et al. show that this "noise" comes with a particular structure, which emerges from circuit properties and which counteracts the harmful effect of variability.
@article{Yonehara2016,
title = {Congenital Nystagmus Gene FRMD7 Is Necessary for Establishing a Neuronal Circuit Asymmetry for Direction Selectivity},
author = {Keisuke Yonehara and Michele Fiscella and Antonia Drinnenberg and Federico Esposti and Stuart Trenholm and Jacek Krol and Felix Franke and Brigitte Gross Scherf and Akos Kusnyerik and Jan Müller and Arnold Szabo and Josephine Jüttner and Francisco Cordoba and Ashrithpal Police Reddy and János Németh and Zoltán Zsolt Nagy and Francis Munier and Andreas Hierlemann and Botond Roska},
url = {http://www.sciencedirect.com/science/article/pii/S0896627315010387?via%3Dihub},
doi = {10.1016/j.neuron.2015.11.032},
issn = {10974199},
year = {2016},
date = {2016-01-06},
journal = {Neuron},
volume = {89},
number = {1},
pages = {177-193},
abstract = {Neuronal circuit asymmetries are important components of brain circuits, but the molecular pathways leading to their establishment remain unknown. Here we found that the mutation of FRMD7, a gene that is defective in human congenital nystagmus, leads to the selective loss of the horizontal optokinetic reflex in mice, as it does in humans. This is accompanied by the selective loss of horizontal direction selectivity in retinal ganglion cells and the transition from asymmetric to symmetric inhibitory input to horizontal direction-selective ganglion cells. In wild-type retinas, we found FRMD7 specifically expressed in starburst amacrine cells, the interneuron type that provides asymmetric inhibition to direction-selective retinal ganglion cells. This work identifies FRMD7 as a key regulator in establishing a neuronal circuit asymmetry, and it suggests the involvement of a specific inhibitory neuron type in the pathophysiology of a neurological disease.},
keywords = {ETH-CMOS-MEA, Retina},
pubstate = {published},
tppubtype = {article}
}
Neuronal circuit asymmetries are important components of brain circuits, but the molecular pathways leading to their establishment remain unknown. Here we found that the mutation of FRMD7, a gene that is defective in human congenital nystagmus, leads to the selective loss of the horizontal optokinetic reflex in mice, as it does in humans. This is accompanied by the selective loss of horizontal direction selectivity in retinal ganglion cells and the transition from asymmetric to symmetric inhibitory input to horizontal direction-selective ganglion cells. In wild-type retinas, we found FRMD7 specifically expressed in starburst amacrine cells, the interneuron type that provides asymmetric inhibition to direction-selective retinal ganglion cells. This work identifies FRMD7 as a key regulator in establishing a neuronal circuit asymmetry, and it suggests the involvement of a specific inhibitory neuron type in the pathophysiology of a neurological disease.
@conference{Viswam2016,
title = {22.8 Multi-functional microelectrode array system featuring 59,760 electrodes, 2048 electrophysiology channels, impedance and neurotransmitter measurement units},
author = {Vijay Viswam and Jelena Dragas and Amir Shadmani and Yihui Chen and Alexander Stettler and Jan Müller and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/7418073/},
doi = {10.1109/ISSCC.2016.7418073},
year = {2016},
date = {2016-01-01},
booktitle = {2016 IEEE International Solid-State Circuits Conference (ISSCC)},
journal = {2016 IEEE International Solid-State Circuits Conference (ISSCC)},
abstract = {Various CMOS-based micro-electrode arrays (MEAs) have been developed in recent years for extracellular electrophysiological recording/stimulation of electrogenic cells [1–5]. Mostly two approaches have been used: (i) the activepixel approach (APS) [2–4], which features simultaneous readout of all electrodes, however, at the expense of a comparably high noise level, and (ii) the switchmatrix (SM) approach, which yields better noise performance, whereas only a subset of electrodes (e.g.,1024) is simultaneously read out [5]. All systems feature, at most, voltage recording and/or voltage/current stimulation functionalities.},
keywords = {Action Potential, ETH-CMOS-MEA, HD-MEA, MEA Technology},
pubstate = {published},
tppubtype = {conference}
}
Various CMOS-based micro-electrode arrays (MEAs) have been developed in recent years for extracellular electrophysiological recording/stimulation of electrogenic cells [1–5]. Mostly two approaches have been used: (i) the activepixel approach (APS) [2–4], which features simultaneous readout of all electrodes, however, at the expense of a comparably high noise level, and (ii) the switchmatrix (SM) approach, which yields better noise performance, whereas only a subset of electrodes (e.g.,1024) is simultaneously read out [5]. All systems feature, at most, voltage recording and/or voltage/current stimulation functionalities.
@article{Jones2015,
title = {A method for electrophysiological characterization of hamster retinal ganglion cells using a high-density CMOS microelectrode array},
author = {Ian L Jones and Thomas L Russell and Karl Farrow and Michele Fiscella and Felix Franke and Jan Müller and David Jäckel and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2015.00360/full},
doi = {10.3389/fnins.2015.00360},
issn = {1662453X},
year = {2015},
date = {2015-10-13},
journal = {Frontiers in Neuroscience},
volume = {9},
pages = {360},
abstract = {Knowledge of neuronal cell types in the mammalian retina is important for the understanding of human retinal disease and the advancement of sight-restoring technology, such as retinal prosthetic devices. A somewhat less utilized animal model for retinal research is the hamster, which has a visual system that is characterized by an area centralis and a wide visual field with a broad binocular component. The hamster retina is optimally suited for recording on the microelectrode array (MEA), because it intrinsically lies flat on the MEA surface and yields robust, large-amplitude signals. However, information in the literature about hamster retinal ganglion cell functional types is scarce. The goal of our work is to develop a method featuring a high-density (HD) Complementary metal-oxide-semiconductor (CMOS) MEA technology along with a sequence of standardized visual stimuli in order to categorize ganglion cells in isolated Syrian Hamster (Mesocricetus auratus) retina. Since the HD-MEA is capable of recording at a higher spatial resolution than most MEA systems (17.5 um electrode pitch), we capitalized on this feature and were able to record from a large proportion of RGCs within a selected region. Secondly, we chose our stimuli so that they could be run during the experiment without intervention or computation steps. The visual stimulus set was designed to activate the receptive fields of most ganglion cells in parallel and to incorporate various visual features to which different cell types respond uniquely. Based on the ganglion cell responses, basic cell properties were determined: direction selectivity, speed tuning, width tuning, transience and latency. These properties were clustered in order to identify ganglion cell types in the hamster retina. Ultimately, we recorded up to a cell density 2780 cells/mm2 at 2 mm (42°) from the optic nerve head. Using 5 parameters extracted from the responses to visual stimuli, we obtained 7 ganglion cell types.},
keywords = {ETH-CMOS-MEA, Retina},
pubstate = {published},
tppubtype = {article}
}
Knowledge of neuronal cell types in the mammalian retina is important for the understanding of human retinal disease and the advancement of sight-restoring technology, such as retinal prosthetic devices. A somewhat less utilized animal model for retinal research is the hamster, which has a visual system that is characterized by an area centralis and a wide visual field with a broad binocular component. The hamster retina is optimally suited for recording on the microelectrode array (MEA), because it intrinsically lies flat on the MEA surface and yields robust, large-amplitude signals. However, information in the literature about hamster retinal ganglion cell functional types is scarce. The goal of our work is to develop a method featuring a high-density (HD) Complementary metal-oxide-semiconductor (CMOS) MEA technology along with a sequence of standardized visual stimuli in order to categorize ganglion cells in isolated Syrian Hamster (Mesocricetus auratus) retina. Since the HD-MEA is capable of recording at a higher spatial resolution than most MEA systems (17.5 um electrode pitch), we capitalized on this feature and were able to record from a large proportion of RGCs within a selected region. Secondly, we chose our stimuli so that they could be run during the experiment without intervention or computation steps. The visual stimulus set was designed to activate the receptive fields of most ganglion cells in parallel and to incorporate various visual features to which different cell types respond uniquely. Based on the ganglion cell responses, basic cell properties were determined: direction selectivity, speed tuning, width tuning, transience and latency. These properties were clustered in order to identify ganglion cell types in the hamster retina. Ultimately, we recorded up to a cell density 2780 cells/mm2 at 2 mm (42°) from the optic nerve head. Using 5 parameters extracted from the responses to visual stimuli, we obtained 7 ganglion cell types.
@article{Fiscella2015,
title = {Visual coding with a population of direction-selective neurons},
author = {Michele Fiscella and Felix Franke and Karl Farrow and Jan Müller and Botond Roska and Rava {Azeredo da Silveira} and Andreas Hierlemann},
url = {http://jn.physiology.org/lookup/doi/10.1152/jn.00919.2014},
doi = {10.1152/jn.00919.2014},
issn = {0022-3077},
year = {2015},
date = {2015-08-19},
journal = {Journal of Neurophysiology},
volume = {114},
number = {4},
pages = {2485-2499},
abstract = {The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions.},
keywords = {Data Analysis, ETH-CMOS-MEA, Retina},
pubstate = {published},
tppubtype = {article}
}
The brain decodes the visual scene from the action potentials of ∼20 retinal ganglion cell types. Among the retinal ganglion cells, direction-selective ganglion cells (DSGCs) encode motion direction. Several studies have focused on the encoding or decoding of motion direction by recording multiunit activity, mainly in the visual cortex. In this study, we simultaneously recorded from all four types of ON-OFF DSGCs of the rabbit retina using a microelectronics-based high-density microelectrode array (HDMEA) and decoded their concerted activity using probabilistic and linear decoders. Furthermore, we investigated how the modification of stimulus parameters (velocity, size, angle of moving object) and the use of different tuning curve fits influenced decoding precision. Finally, we simulated ON-OFF DSGC activity, based on real data, in order to understand how tuning curve widths and the angular distribution of the cells' preferred directions influence decoding performance. We found that probabilistic decoding strategies outperformed, on average, linear methods and that decoding precision was robust to changes in stimulus parameters such as velocity. The removal of noise correlations among cells, by random shuffling trials, caused a drop in decoding precision. Moreover, we found that tuning curves are broad in order to minimize large errors at the expense of a higher average error, and that the retinal direction-selective system would not substantially benefit, on average, from having more than four types of ON-OFF DSGCs or from a perfect alignment of the cells' preferred directions.
@article{Muller2015,
title = {High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels},
author = {Jan Müller and Marco Ballini and Paolo Livi and Yihui Chen and Milos Radivojevic and Amir Shadmani and Vijay Viswam and Ian L Jones and Michele Fiscella and Roland Diggelmann and Alexander Stettler and Urs Frey and Douglas J Bakkum and Andreas Hierlemann},
url = {http://pubs.rsc.org/en/Content/ArticleLanding/2015/LC/C5LC00133A#!divAbstract},
doi = {10.1039/C5LC00133A},
issn = {1473-0197},
year = {2015},
date = {2015-07-07},
journal = {Lab Chip},
volume = {15},
number = {13},
pages = {2767-2780},
publisher = {Royal Society of Chemistry},
abstract = {Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 um) within a large overall sensing area (3.85 × 2.10 mm2). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.},
keywords = {MaxOne, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Studies on information processing and learning properties of neuronal networks would benefit from simultaneous and parallel access to the activity of a large fraction of all neurons in such networks. Here, we present a CMOS-based device, capable of simultaneously recording the electrical activity of over a thousand cells in in vitro neuronal networks. The device provides sufficiently high spatiotemporal resolution to enable, at the same time, access to neuronal preparations on subcellular, cellular, and network level. The key feature is a rapidly reconfigurable array of 26 400 microelectrodes arranged at low pitch (17.5 um) within a large overall sensing area (3.85 × 2.10 mm2). An arbitrary subset of the electrodes can be simultaneously connected to 1024 low-noise readout channels as well as 32 stimulation units. Each electrode or electrode subset can be used to electrically stimulate or record the signals of virtually any neuron on the array. We demonstrate the applicability and potential of this device for various different experimental paradigms: large-scale recordings from whole networks of neurons as well as investigations of axonal properties of individual neurons.
@article{Krol2015,
title = {A network comprising short and long noncoding RNAs and RNA helicase controls mouse retina architecture.},
author = {Jacek Krol and Ilona Krol and Claudia Patricia Patino Alvarez and Michele Fiscella and Andreas Hierlemann and Botond Roska and Witold Filipowicz},
url = {https://www.nature.com/articles/ncomms8305},
doi = {10.1038/ncomms8305},
issn = {2041-1723},
year = {2015},
date = {2015-06-04},
journal = {Nature Communications},
volume = {6},
pages = {7305},
publisher = {Nature Publishing Group},
abstract = {Brain regions, such as the cortex and retina, are composed of layers of uniform thickness. The molecular mechanism that controls this uniformity is not well understood. Here we show that during mouse postnatal development the timed expression of Rncr4, a retina-specific long noncoding RNA, regulates the similarly timed processing of pri-miR-183/96/182, which is repressed at an earlier developmental stage by RNA helicase Ddx3x. Shifting the timing of mature miR-183/96/182 accumulation or interfering with Ddx3x expression leads to the disorganization of retinal architecture, with the photoreceptor layer being most affected. We identify Crb1, a component of the adhesion belt between glial and photoreceptor cells, as a link between Rncr4-regulated miRNA metabolism and uniform retina layering. Our results suggest that the precise timing of glia-neuron interaction controlled by noncoding RNAs and Ddx3x is important for the even distribution of cells across layers.},
keywords = {MaxOne, Retina},
pubstate = {published},
tppubtype = {article}
}
Brain regions, such as the cortex and retina, are composed of layers of uniform thickness. The molecular mechanism that controls this uniformity is not well understood. Here we show that during mouse postnatal development the timed expression of Rncr4, a retina-specific long noncoding RNA, regulates the similarly timed processing of pri-miR-183/96/182, which is repressed at an earlier developmental stage by RNA helicase Ddx3x. Shifting the timing of mature miR-183/96/182 accumulation or interfering with Ddx3x expression leads to the disorganization of retinal architecture, with the photoreceptor layer being most affected. We identify Crb1, a component of the adhesion belt between glial and photoreceptor cells, as a link between Rncr4-regulated miRNA metabolism and uniform retina layering. Our results suggest that the precise timing of glia-neuron interaction controlled by noncoding RNAs and Ddx3x is important for the even distribution of cells across layers.
@article{Takahashi2015,
title = {Chronic Co-Variation of Neural Network Configuration and Activity in Mature Dissociated Cultures},
author = {Satoru Okawa and Takeshi Mita and Douglas J Bakkum and Urs Frey and Andreas Hierlemann and Ryohei Kanzaki and Hirokazu Takahashi},
url = {http://onlinelibrary.wiley.com/doi/10.1002/ecj.11736/abstract;jsessionid=791557FA80CF36B1F78DC538C1618924.f03t02},
doi = {10.1002/ecj.11736},
issn = {1942-9541},
year = {2015},
date = {2015-04-08},
journal = {Electronics and Communications in Japan},
volume = {98},
number = {5},
pages = {34-42},
abstract = {Spatiotemporal neural patterns depend on the physical structure of neural circuits. Neural plasticity can thus be associated with changes in the circuit structure. For example, newborn neurons migrate toward existing, already matured, neural networks in order to participate in neural computation. In the present study, we have conducted two experiments to investigate how neural migration is associated with the development of neural activity in primary dissociated cultures of neuronal cells. In Experiment 1, using a mature culture, a high-density CMOS microelectrode array was used to continuously monitor neural migration and activity for more than two weeks. Consequently, we found that even in mature neuronal cultures neurons moved 2.0 ± 1.0 mum a day and that the moving distance was negatively correlated with their firing rate, suggesting that neurons featuring low firing rates tend to migrate actively. In Experiment 2 using a co-culture of mature and immature neurons, we found that immature neurons moved more actively than matured neurons to achieve functional connections to other neurons. These findings suggest that neurons with low firing rates as well as newborn neurons actively migrate in order to establish their connections and function in a neuronal network.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Spatiotemporal neural patterns depend on the physical structure of neural circuits. Neural plasticity can thus be associated with changes in the circuit structure. For example, newborn neurons migrate toward existing, already matured, neural networks in order to participate in neural computation. In the present study, we have conducted two experiments to investigate how neural migration is associated with the development of neural activity in primary dissociated cultures of neuronal cells. In Experiment 1, using a mature culture, a high-density CMOS microelectrode array was used to continuously monitor neural migration and activity for more than two weeks. Consequently, we found that even in mature neuronal cultures neurons moved 2.0 ± 1.0 mum a day and that the moving distance was negatively correlated with their firing rate, suggesting that neurons featuring low firing rates tend to migrate actively. In Experiment 2 using a co-culture of mature and immature neurons, we found that immature neurons moved more actively than matured neurons to achieve functional connections to other neurons. These findings suggest that neurons with low firing rates as well as newborn neurons actively migrate in order to establish their connections and function in a neuronal network.
@article{Lewandowska2015,
title = {Recording large extracellular spikes in microchannels along many axonal sites from individual neurons},
author = {Marta K Lewandowska and Douglas J Bakkum and Santiago B Rompani and Andreas Hierlemann},
url = {http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0118514},
doi = {10.1371/journal.pone.0118514},
issn = {19326203},
year = {2015},
date = {2015-03-03},
journal = {PLoS ONE},
volume = {10},
number = {3},
pages = {1-24},
abstract = {The numerous connections between neuronal cell bodies, made by their dendrites and axons, are vital for information processing in the brain. While dendrites and synapses have been extensively studied, axons have remained elusive to a large extent. We present a novel platform to study axonal physiology and information processing based on combining an 11,011-electrode high-density complementary metal-oxide semiconductor microelectrode array with a poly(dimethylsiloxane) channel device, which isolates axons from somas and, importantly, significantly amplifies recorded axonal signals. The combination of the microelectrode array with recording and stimulation capability with the microfluidic isolation channels permitted us to study axonal signal behavior at great detail. The device, featuring two culture chambers with over 30 channels spanning in between, enabled long-term recording of single spikes from isolated axons with signal amplitudes of 100 uV up to 2 mV. Propagating signals along axons could be recorded with 10 to 50 electrodes per channel. We (i) describe the performance and capabilities of our device for axonal electrophysiology, and (ii) present novel data on axonal signals facilitated by the device. Spontaneous action potentials with characteristic shapes propagated from somas along axons between the two compartments, and these unique shapes could be used to identify individual axons within channels that contained many axonal branches. Stimulation through the electrode array facilitated the identification of somas and their respective axons, enabling interfacing with different compartments of a single cell. Complex spike shapes observed in channels were traced back to single cells, and we show that more complicated spike shapes originate from a linear superposition of multiple axonal signals rather than signal distortion by the channels.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
The numerous connections between neuronal cell bodies, made by their dendrites and axons, are vital for information processing in the brain. While dendrites and synapses have been extensively studied, axons have remained elusive to a large extent. We present a novel platform to study axonal physiology and information processing based on combining an 11,011-electrode high-density complementary metal-oxide semiconductor microelectrode array with a poly(dimethylsiloxane) channel device, which isolates axons from somas and, importantly, significantly amplifies recorded axonal signals. The combination of the microelectrode array with recording and stimulation capability with the microfluidic isolation channels permitted us to study axonal signal behavior at great detail. The device, featuring two culture chambers with over 30 channels spanning in between, enabled long-term recording of single spikes from isolated axons with signal amplitudes of 100 uV up to 2 mV. Propagating signals along axons could be recorded with 10 to 50 electrodes per channel. We (i) describe the performance and capabilities of our device for axonal electrophysiology, and (ii) present novel data on axonal signals facilitated by the device. Spontaneous action potentials with characteristic shapes propagated from somas along axons between the two compartments, and these unique shapes could be used to identify individual axons within channels that contained many axonal branches. Stimulation through the electrode array facilitated the identification of somas and their respective axons, enabling interfacing with different compartments of a single cell. Complex spike shapes observed in channels were traced back to single cells, and we show that more complicated spike shapes originate from a linear superposition of multiple axonal signals rather than signal distortion by the channels.
@article{Dragas2015,
title = {Complexity Optimization and High-Throughput Low-Latency Hardware Implementation of a Multi-Electrode Spike-Sorting Algorithm},
author = {Jelena Dragas and David Jäckel and Andreas Hierlemann and Felix Franke},
url = {http://ieeexplore.ieee.org/document/6955847/},
doi = {10.1109/TNSRE.2014.2370510},
issn = {15344320},
year = {2015},
date = {2015-03-01},
journal = {IEEE Transactions on Neural Systems and Rehabilitation Engineering},
volume = {23},
number = {2},
pages = {149--158},
abstract = {Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimisation techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the non-stationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.},
keywords = {Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Reliable real-time low-latency spike sorting with large data throughput is essential for studies of neural network dynamics and for brain-machine interfaces (BMIs), in which the stimulation of neural networks is based on the networks' most recent activity. However, the majority of existing multi-electrode spike-sorting algorithms are unsuited for processing high quantities of simultaneously recorded data. Recording from large neuronal networks using large high-density electrode sets (thousands of electrodes) imposes high demands on the data-processing hardware regarding computational complexity and data transmission bandwidth; this, in turn, entails demanding requirements in terms of chip area, memory resources and processing latency. This paper presents computational complexity optimisation techniques, which facilitate the use of spike-sorting algorithms in large multi-electrode-based recording systems. The techniques are then applied to a previously published algorithm, on its own, unsuited for large electrode set recordings. Further, a real-time low-latency high-performance VLSI hardware architecture of the modified algorithm is presented, featuring a folded structure capable of processing the activity of hundreds of neurons simultaneously. The hardware is reconfigurable “on-the-fly” and adaptable to the non-stationarities of neuronal recordings. By transmitting exclusively spike time stamps and/or spike waveforms, its real-time processing offers the possibility of data bandwidth and data storage reduction.
@article{Obien2015,
title = {Revealing neuronal function through microelectrode array recordings},
author = {Marie Engelene J Obien and Kosmas Deligkaris and Torsten Bullmann and Douglas J Bakkum and Urs Frey},
url = {https://www.frontiersin.org/articles/10.3389/fnins.2014.00423/full},
doi = {10.3389/fnins.2014.00423},
issn = {1662453X},
year = {2015},
date = {2015-01-06},
journal = {Frontiers in Neuroscience},
volume = {9},
pages = {423},
abstract = {Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.},
keywords = {MEA Technology, Review},
pubstate = {published},
tppubtype = {article}
}
Microelectrode arrays and microprobes have been widely utilized to measure neuronal activity, both in vitro and in vivo. The key advantage is the capability to record and stimulate neurons at multiple sites simultaneously. However, unlike the single-cell or single-channel resolution of intracellular recording, microelectrodes detect signals from all possible sources around every sensor. Here, we review the current understanding of microelectrode signals and the techniques for analyzing them. We introduce the ongoing advancements in microelectrode technology, with focus on achieving higher resolution and quality of recordings by means of monolithic integration with on-chip circuitry. We show how recent advanced microelectrode array measurement methods facilitate the understanding of single neurons as well as network function.
@article{Ballini2014,
title = {A 1024-channel CMOS microelectrode array with 26,400 electrodes for recording and stimulation of electrogenic cells in vitro},
author = {Marco Ballini and Jan Müller and Paolo Livi and Yihui Chen and Urs Frey and Alexander Stettler and Amir Shadmani and Vijay Viswam and Ian L Jones and David Jäckel and Milos Radivojevic and Marta K Lewandowska and Wei Gong and Michele Fiscella and Douglas J Bakkum and Flavio Heer and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/6923484/},
doi = {10.1109/JSSC.2014.2359219},
issn = {00189200},
year = {2014},
date = {2014-10-14},
journal = {IEEE Journal of Solid-State Circuits},
volume = {49},
number = {11},
pages = {2705-2719},
abstract = {To advance our understanding of the functioning of neuronal ensembles, systems are needed to enable simultaneous recording from a large number of individual neurons at high spa-tiotemporal resolution and good signal-to-noise ratio. Moreover, stimulation capability is highly desirable for investigating, for example, plasticity and learning processes. Here, we present a microelectrode array (MEA) system on a single CMOS die for in vitro recording and stimulation. The system incorporates 26,400 platinum electrodes, fabricated by in-house post-processing, over a large sensing area (3.85 2.10 mm) with sub-cellular spatial resolution (pitch of 17.5 µm). Owing to an area and power efficient implementation, we were able to integrate 1024 readout channels on chip to record extracellular signals from a user-specified selection of electrodes. These channels feature noise values of 2.4 µV in the action-potential band (300 Hz–10 kHz) and 5.4 µV in the local-field-potential band (1 Hz–300 Hz), and provide programmable gain (up to 78 dB) to accommodate various biological preparations. Amplified and filtered signals are digitized by 10 bit parallel single-slope ADCs at 20 kSamples/s. The system also includes 32 stimulation units, which can elicit neural spikes through either current or voltage pulses. The chip consumes only 75 mW in total, which obviates the need of active cooling even for sensitive cell cultures.},
keywords = {MaxOne, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
To advance our understanding of the functioning of neuronal ensembles, systems are needed to enable simultaneous recording from a large number of individual neurons at high spa-tiotemporal resolution and good signal-to-noise ratio. Moreover, stimulation capability is highly desirable for investigating, for example, plasticity and learning processes. Here, we present a microelectrode array (MEA) system on a single CMOS die for in vitro recording and stimulation. The system incorporates 26,400 platinum electrodes, fabricated by in-house post-processing, over a large sensing area (3.85 2.10 mm) with sub-cellular spatial resolution (pitch of 17.5 µm). Owing to an area and power efficient implementation, we were able to integrate 1024 readout channels on chip to record extracellular signals from a user-specified selection of electrodes. These channels feature noise values of 2.4 µV in the action-potential band (300 Hz–10 kHz) and 5.4 µV in the local-field-potential band (1 Hz–300 Hz), and provide programmable gain (up to 78 dB) to accommodate various biological preparations. Amplified and filtered signals are digitized by 10 bit parallel single-slope ADCs at 20 kSamples/s. The system also includes 32 stimulation units, which can elicit neural spikes through either current or voltage pulses. The chip consumes only 75 mW in total, which obviates the need of active cooling even for sensitive cell cultures.
@article{Bakkum2014,
title = {Parameters for burst detection},
author = {Douglas J Bakkum and Milos Radivojevic and Urs Frey and Felix Franke and Andreas Hierlemann and Hirokazu Takahashi},
url = {http://journal.frontiersin.org/article/10.3389/fncom.2013.00193/abstract},
doi = {10.3389/fncom.2013.00193},
issn = {1662-5188},
year = {2014},
date = {2014-01-13},
journal = {Frontiers in Computational Neuroscience},
volume = {7},
pages = {1-12},
abstract = {Bursts of action potentials within neurons and throughout networks are believed to serve roles in how neurons handle and store information, both in vivo and in vitro. Accurate detection of burst occurrences and durations are therefore crucial for many studies. A number of algorithms have been proposed to do so, but a standard method has not been adopted. This is due, in part, to many algorithms requiring the adjustment of multiple ad-hoc parameters and further post-hoc criteria in order to produce satisfactory results. Here, we broadly catalog existing approaches and present a new approach requiring the selection of only a single parameter: the number of spikes N comprising the smallest burst to consider. A burst was identified if N spikes occurred in less than T ms, where the threshold T was automatically determined from observing a probability distribution of inter-spike-intervals. Performance was compared vs. different classes of detectors on data gathered from in vitro neuronal networks grown over microelectrode arrays. Our approach offered a number of useful features including: a simple implementation, no need for ad-hoc or post-hoc criteria, and precise assignment of burst boundary time points. Unlike existing approaches, detection was not biased toward larger bursts, allowing identification and analysis of a greater range of neuronal and network dynamics.},
keywords = {Data Analysis, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Bursts of action potentials within neurons and throughout networks are believed to serve roles in how neurons handle and store information, both in vivo and in vitro. Accurate detection of burst occurrences and durations are therefore crucial for many studies. A number of algorithms have been proposed to do so, but a standard method has not been adopted. This is due, in part, to many algorithms requiring the adjustment of multiple ad-hoc parameters and further post-hoc criteria in order to produce satisfactory results. Here, we broadly catalog existing approaches and present a new approach requiring the selection of only a single parameter: the number of spikes N comprising the smallest burst to consider. A burst was identified if N spikes occurred in less than T ms, where the threshold T was automatically determined from observing a probability distribution of inter-spike-intervals. Performance was compared vs. different classes of detectors on data gathered from in vitro neuronal networks grown over microelectrode arrays. Our approach offered a number of useful features including: a simple implementation, no need for ad-hoc or post-hoc criteria, and precise assignment of burst boundary time points. Unlike existing approaches, detection was not biased toward larger bursts, allowing identification and analysis of a greater range of neuronal and network dynamics.
@article{Bakkum2013,
title = {Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites},
author = {Douglas J Bakkum and Urs Frey and Milos Radivojevic and Thomas L Russell and Jan Müller and Michele Fiscella and Hirokazu Takahashi and Andreas Hierlemann},
url = {http://www.nature.com/doifinder/10.1038/ncomms3181},
doi = {10.1038/ncomms3181},
issn = {2041-1723},
year = {2013},
date = {2013-07-19},
journal = {Nature Communications},
volume = {4},
pages = {1-12},
abstract = {Axons are traditionally considered stable transmission cables, but evidence of the regulation of action potential propagation demonstrates that axons may have more important roles. However, their small diameters render intracellular recordings challenging, and low-magnitude extracellular signals are difficult to detect and assign. Better experimental access to axonal function would help to advance this field. Here we report methods to electrically visualize action potential propagation and network topology in cortical neurons grown over custom arrays, which contain 11,011 microelectrodes and are fabricated using complementary metal oxide semiconductor technology. Any neuron lying on the array can be recorded at high spatio-temporal resolution, and simultaneously precisely stimulated with little artifact. We find substantial velocity differences occurring locally within single axons, suggesting that the temporal control of a neuron's output may contribute to neuronal information processing.},
keywords = {Data Analysis, ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
Axons are traditionally considered stable transmission cables, but evidence of the regulation of action potential propagation demonstrates that axons may have more important roles. However, their small diameters render intracellular recordings challenging, and low-magnitude extracellular signals are difficult to detect and assign. Better experimental access to axonal function would help to advance this field. Here we report methods to electrically visualize action potential propagation and network topology in cortical neurons grown over custom arrays, which contain 11,011 microelectrodes and are fabricated using complementary metal oxide semiconductor technology. Any neuron lying on the array can be recorded at high spatio-temporal resolution, and simultaneously precisely stimulated with little artifact. We find substantial velocity differences occurring locally within single axons, suggesting that the temporal control of a neuron's output may contribute to neuronal information processing.
@article{Muller2012,
title = {Sub-millisecond closed-loop feedback stimulation between arbitrary sets of individual neurons.},
author = {Jan Müller and Douglas J Bakkum and Andreas Hierlemann},
url = {https://www.frontiersin.org/articles/10.3389/fncir.2012.00121/full},
doi = {10.3389/fncir.2012.00121},
issn = {1662-5110},
year = {2013},
date = {2013-01-10},
journal = {Frontiers in Neural Circuits},
volume = {6},
pages = {121},
abstract = {We present a system to artificially correlate the spike timing between sets of arbitrary neurons that were interfaced to a complementary metal-oxide-semiconductor (CMOS) high-density microelectrode array (MEA). The system features a novel reprogrammable and flexible event engine unit to detect arbitrary spatio-temporal patterns of recorded action potentials and is capable of delivering sub-millisecond closed-loop feedback of electrical stimulation upon trigger events in real-time. The relative timing between action potentials of individual neurons as well as the temporal pattern among multiple neurons, or neuronal assemblies, is considered an important factor governing memory and learning in the brain. Artificially changing timings between arbitrary sets of spiking neurons with our system could provide a "knob" to tune information processing in the network.},
keywords = {ETH-CMOS-MEA, MEA Technology, Neuronal Networks, Stimulation},
pubstate = {published},
tppubtype = {article}
}
We present a system to artificially correlate the spike timing between sets of arbitrary neurons that were interfaced to a complementary metal-oxide-semiconductor (CMOS) high-density microelectrode array (MEA). The system features a novel reprogrammable and flexible event engine unit to detect arbitrary spatio-temporal patterns of recorded action potentials and is capable of delivering sub-millisecond closed-loop feedback of electrical stimulation upon trigger events in real-time. The relative timing between action potentials of individual neurons as well as the temporal pattern among multiple neurons, or neuronal assemblies, is considered an important factor governing memory and learning in the brain. Artificially changing timings between arbitrary sets of spiking neurons with our system could provide a "knob" to tune information processing in the network.
@article{Hierlemann2012,
title = {High-density microelectrode array recordings and real-time spike sorting for closed-loop experiments: an emerging technology to study neural plasticity},
author = {Felix Franke and David Jackel and Jelena Dragas and Jan Muller and Milos Radivojevic and Douglas J Bakkum and Andreas Hierlemann},
url = {https://www.frontiersin.org/article/10.3389/fncir.2012.00105},
doi = {10.3389/fncir.2012.00105},
issn = {1662-5110},
year = {2012},
date = {2012-12-20},
journal = {Frontiers in Neural Circuits},
volume = {6},
pages = {105},
abstract = {Understanding plasticity of neural networks is a key to comprehending their development and function. A powerful technique to study neural plasticity includes recording and control of pre- and postsynaptic neural activity, e.g., by using simultaneous intracellular recording and stimulation of several neurons. Intracellular recording is, however, a demanding technique and has its limitations in that only a small number of neurons can be stimulated and recorded from at the same time. Extracellular techniques offer the possibility to simultaneously record from larger numbers of neurons with relative ease, at the expenses of increased efforts to sort out single neuronal activities from the recorded mixture, which is a time consuming and error prone step, referred to as spike sorting. In this mini-review, we describe recent technological developments in two separate fields, namely CMOS-based high-density microelectrode arrays, which also allow for extracellular stimulation of neurons, and real-time spike sorting. We argue that these techniques, when combined, will provide a powerful tool to study plasticity in neural networks consisting of several thousand neurons in vitro.},
keywords = {Neuronal Networks, Review, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Understanding plasticity of neural networks is a key to comprehending their development and function. A powerful technique to study neural plasticity includes recording and control of pre- and postsynaptic neural activity, e.g., by using simultaneous intracellular recording and stimulation of several neurons. Intracellular recording is, however, a demanding technique and has its limitations in that only a small number of neurons can be stimulated and recorded from at the same time. Extracellular techniques offer the possibility to simultaneously record from larger numbers of neurons with relative ease, at the expenses of increased efforts to sort out single neuronal activities from the recorded mixture, which is a time consuming and error prone step, referred to as spike sorting. In this mini-review, we describe recent technological developments in two separate fields, namely CMOS-based high-density microelectrode arrays, which also allow for extracellular stimulation of neurons, and real-time spike sorting. We argue that these techniques, when combined, will provide a powerful tool to study plasticity in neural networks consisting of several thousand neurons in vitro.
@article{Fiscella2012,
title = {Recording from defined populations of retinal ganglion cells using a high-density CMOS-integrated microelectrode array with real-time switchable electrode selection},
author = {Michele Fiscella and Karl Farrow and Ian L Jones and David Jäckel and Jan Müller and Urs Frey and Douglas J Bakkum and Péter Hantz and Botond Roska and Andreas Hierlemann},
url = {http://www.sciencedirect.com/science/article/pii/S0165027012003287?via%3Dihub},
doi = {10.1016/j.jneumeth.2012.08.017},
issn = {01650270},
year = {2012},
date = {2012-08-16},
journal = {Journal of Neuroscience Methods},
volume = {211},
number = {1},
pages = {103-113},
publisher = {Elsevier B.V.},
abstract = {In order to understand how retinal circuits encode visual scenes, the neural activity of defined populations of retinal ganglion cells (RGCs) has to be investigated. Here we report on a method for stimulating, detecting, and subsequently targeting defined populations of RGCs. The possibility to select a distinct population of RGCs for extracellular recording enables the design of experiments that can increase our understanding of how these neurons extract precise spatio-temporal features from the visual scene, and how the brain interprets retinal signals. We used light stimulation to elicit a response from physiologically distinct types of RGCs and then utilized the dynamic-configurability capabilities of a microelectronics-based high-density microelectrode array (MEA) to record their synchronous action potentials. The layout characteristics of the MEA made it possible to stimulate and record from multiple, highly overlapping RGCs simultaneously without light-induced artifacts. The high-density of electrodes and the high signal-to-noise ratio of the MEA circuitry allowed for recording of the activity of each RGC on 14 ± 7 electrodes. The spatial features of the electrical activity of each RGC greatly facilitated spike sorting. We were thus able to localize, identify and record from defined RGCs within a region of mouse retina. In addition, we stimulated and recorded from genetically modified RGCs to demonstrate the applicability of optogenetic methods, which introduces an additional feature to target a defined cell type. The developed methodologies can likewise be applied to other neuronal preparations including brain slices or cultured neurons.},
keywords = {ETH-CMOS-MEA, Retina},
pubstate = {published},
tppubtype = {article}
}
In order to understand how retinal circuits encode visual scenes, the neural activity of defined populations of retinal ganglion cells (RGCs) has to be investigated. Here we report on a method for stimulating, detecting, and subsequently targeting defined populations of RGCs. The possibility to select a distinct population of RGCs for extracellular recording enables the design of experiments that can increase our understanding of how these neurons extract precise spatio-temporal features from the visual scene, and how the brain interprets retinal signals. We used light stimulation to elicit a response from physiologically distinct types of RGCs and then utilized the dynamic-configurability capabilities of a microelectronics-based high-density microelectrode array (MEA) to record their synchronous action potentials. The layout characteristics of the MEA made it possible to stimulate and record from multiple, highly overlapping RGCs simultaneously without light-induced artifacts. The high-density of electrodes and the high signal-to-noise ratio of the MEA circuitry allowed for recording of the activity of each RGC on 14 ± 7 electrodes. The spatial features of the electrical activity of each RGC greatly facilitated spike sorting. We were thus able to localize, identify and record from defined RGCs within a region of mouse retina. In addition, we stimulated and recorded from genetically modified RGCs to demonstrate the applicability of optogenetic methods, which introduces an additional feature to target a defined cell type. The developed methodologies can likewise be applied to other neuronal preparations including brain slices or cultured neurons.
@article{Jackel2012,
title = {Applicability of independent component analysis on high-density microelectrode array recordings},
author = {David Jäckel and Urs Frey and Michele Fiscella and Felix Franke and Andreas Hierlemann},
url = {http://jn.physiology.org/cgi/doi/10.1152/jn.01106.2011},
doi = {10.1152/jn.01106.2011},
issn = {0022-3077},
year = {2012},
date = {2012-04-04},
journal = {Journal of Neurophysiology},
volume = {108},
number = {1},
pages = {334-348},
abstract = {Emerging complementary metal oxide semiconductor (CMOS)-based, high-density microelectrode array (HD-MEA) devices provide high spatial resolution at subcellular level and a large number of readout channels. These devices allow for simultaneous recording of extracellular activity of a large number of neurons with every neuron being detected by multiple electrodes. To analyze the recorded signals, spiking events have to be assigned to individual neurons, a process referred to as "spike sorting." For a set of observed signals, which constitute a linear mixture of a set of source signals, independent component (IC) analysis (ICA) can be used to demix blindly the data and extract the individual source signals. This technique offers great potential to alleviate the problem of spike sorting in HD-MEA recordings, as it represents an unsupervised method to separate the neuronal sources. The separated sources or ICs then constitute estimates of single-neuron signals, and threshold detection on the ICs yields the sorted spike times. However, it is unknown to what extent extracellular neuronal recordings meet the requirements of ICA. In this paper, we evaluate the applicability of ICA to spike sorting of HD-MEA recordings. The analysis of extracellular neuronal signals, recorded at high spatiotemporal resolution, reveals that the recorded data cannot be modeled as a purely linear mixture. As a consequence, ICA fails to separate completely the neuronal signals and cannot be used as a stand-alone method for spike sorting in HD-MEA recordings. We assessed the demixing performance of ICA using simulated data sets and found that the performance strongly depends on neuronal density and spike amplitude. Furthermore, we show how postprocessing techniques can be used to overcome the most severe limitations of ICA. In combination with these postprocessing techniques, ICA represents a viable method to facilitate rapid spike sorting of multidimensional neuronal recordings.},
keywords = {ETH-CMOS-MEA, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}
Emerging complementary metal oxide semiconductor (CMOS)-based, high-density microelectrode array (HD-MEA) devices provide high spatial resolution at subcellular level and a large number of readout channels. These devices allow for simultaneous recording of extracellular activity of a large number of neurons with every neuron being detected by multiple electrodes. To analyze the recorded signals, spiking events have to be assigned to individual neurons, a process referred to as "spike sorting." For a set of observed signals, which constitute a linear mixture of a set of source signals, independent component (IC) analysis (ICA) can be used to demix blindly the data and extract the individual source signals. This technique offers great potential to alleviate the problem of spike sorting in HD-MEA recordings, as it represents an unsupervised method to separate the neuronal sources. The separated sources or ICs then constitute estimates of single-neuron signals, and threshold detection on the ICs yields the sorted spike times. However, it is unknown to what extent extracellular neuronal recordings meet the requirements of ICA. In this paper, we evaluate the applicability of ICA to spike sorting of HD-MEA recordings. The analysis of extracellular neuronal signals, recorded at high spatiotemporal resolution, reveals that the recorded data cannot be modeled as a purely linear mixture. As a consequence, ICA fails to separate completely the neuronal signals and cannot be used as a stand-alone method for spike sorting in HD-MEA recordings. We assessed the demixing performance of ICA using simulated data sets and found that the performance strongly depends on neuronal density and spike amplitude. Furthermore, we show how postprocessing techniques can be used to overcome the most severe limitations of ICA. In combination with these postprocessing techniques, ICA represents a viable method to facilitate rapid spike sorting of multidimensional neuronal recordings.
@article{Jones2011,
title = {The potential of microelectrode arrays and microelectronics for biomedical research and diagnostics},
author = {Ian L Jones and Paolo Livi and Marta K Lewandowska and Michele Fiscella and Branka Roscic and Andreas Hierlemann},
url = {https://link.springer.com/article/10.1007%2Fs00216-010-3968-1},
doi = {10.1007/s00216-010-3968-1},
issn = {1618-2650},
year = {2011},
date = {2011-07-31},
journal = {Analytical and Bioanalytical Chemistry},
volume = {399},
number = {7},
pages = {2313-2329},
abstract = {Planar microelectrode arrays (MEAs) are devices that can be used in biomedical and basic in vitro research to provide extracellular electrophysiological information about biological systems at high spatial and temporal resolution. Complementary metal oxide semiconductor (CMOS) is a technology with which MEAs can be produced on a microscale featuring high spatial resolution and excellent signal-to-noise characteristics. CMOS MEAs are specialized for the analysis of complete electrogenic cellular networks at the cellular or subcellular level in dissociated cultures, organotypic cultures, and acute tissue slices; they can also function as biosensors to detect biochemical events. Models of disease or the response of cellular networks to pharmacological compounds can be studied in vitro, allowing one to investigate pathologies, such as cardiac arrhythmias, memory impairment due to Alzheimer's disease, or vision impairment caused by ganglion cell degeneration in the retina.},
keywords = {Review},
pubstate = {published},
tppubtype = {article}
}
Planar microelectrode arrays (MEAs) are devices that can be used in biomedical and basic in vitro research to provide extracellular electrophysiological information about biological systems at high spatial and temporal resolution. Complementary metal oxide semiconductor (CMOS) is a technology with which MEAs can be produced on a microscale featuring high spatial resolution and excellent signal-to-noise characteristics. CMOS MEAs are specialized for the analysis of complete electrogenic cellular networks at the cellular or subcellular level in dissociated cultures, organotypic cultures, and acute tissue slices; they can also function as biosensors to detect biochemical events. Models of disease or the response of cellular networks to pharmacological compounds can be studied in vitro, allowing one to investigate pathologies, such as cardiac arrhythmias, memory impairment due to Alzheimer's disease, or vision impairment caused by ganglion cell degeneration in the retina.
@article{Hierlemann2011,
title = {Growing cells atop microelectronic chips: Interfacing electrogenic cells in vitro with CMOS-based microelectrode arrays},
author = {Andreas Hierlemann and Urs Frey and Sadik Hafizovic and Flavio Heer},
url = {http://ieeexplore.ieee.org/document/5594982/},
doi = {10.1109/JPROC.2010.2066532},
issn = {00189219},
year = {2011},
date = {2011-02-01},
journal = {Proceedings of the IEEE},
volume = {99},
number = {2},
pages = {252-284},
abstract = {Complementary semiconductor-metal-oxide (CMOS) technology is a very powerful technology that can be more or less directly interfaced to electrogenic cells, like heart or brain cells in vitro. To this end, the cells are cultured directly atop the CMOS chips, which usually undergo dedicated postprocessing to obtain a reliable bidirectional interface via noble-metal microelectrodes or high-k dielectrics. The big advantages of using CMOS integrated circuits (ICs) include connectivity, the possibility to address a large number of microelectrodes on a tiny chip, and signal quality, the possibility to condition small signals right at the spot of their generation. CMOS will be demonstrated to constitute an enabling technology that opens a route to high-spatio-temporal-resolution and low-noise electrophysiological recordings from a variety of biological preparations, such as brain slices, or cultured cardiac and brain cells. The recording technique is extracellular and noninvasive, and the CMOS chips do not leak out any toxic compounds, so that the cells remain viable for extended times. In turn, the CMOS chips have been demonstrated to survive several months of culturing while being fully immersed in saline solution and being exposed to cellular metabolic products. The latter requires dedicated passivation and packaging techniques as will be shown. Fully integrated, monolithic microelectrode systems, which feature large numbers of tightly spaced microelectrodes and the associated circuitry units for bidirectional interaction (stimulation and recording), will be in the focus of this review. The respective dense microelectrode arrays (MEAs) with small pixels enable subcellular-resolution investigation of regions of interest in, e.g., neurobiological preparations, and, at the same time, the large number of electrodes allows for studying the activity of entire neuronal networks . Application areas include neuroscience, as the devices enable fundamental neurophysiological insights at the cellular and circuit level, as well as medical diagnostics and pharmacology.},
keywords = {ETH-CMOS-MEA, MEA Technology, Review},
pubstate = {published},
tppubtype = {article}
}
Complementary semiconductor-metal-oxide (CMOS) technology is a very powerful technology that can be more or less directly interfaced to electrogenic cells, like heart or brain cells in vitro. To this end, the cells are cultured directly atop the CMOS chips, which usually undergo dedicated postprocessing to obtain a reliable bidirectional interface via noble-metal microelectrodes or high-k dielectrics. The big advantages of using CMOS integrated circuits (ICs) include connectivity, the possibility to address a large number of microelectrodes on a tiny chip, and signal quality, the possibility to condition small signals right at the spot of their generation. CMOS will be demonstrated to constitute an enabling technology that opens a route to high-spatio-temporal-resolution and low-noise electrophysiological recordings from a variety of biological preparations, such as brain slices, or cultured cardiac and brain cells. The recording technique is extracellular and noninvasive, and the CMOS chips do not leak out any toxic compounds, so that the cells remain viable for extended times. In turn, the CMOS chips have been demonstrated to survive several months of culturing while being fully immersed in saline solution and being exposed to cellular metabolic products. The latter requires dedicated passivation and packaging techniques as will be shown. Fully integrated, monolithic microelectrode systems, which feature large numbers of tightly spaced microelectrodes and the associated circuitry units for bidirectional interaction (stimulation and recording), will be in the focus of this review. The respective dense microelectrode arrays (MEAs) with small pixels enable subcellular-resolution investigation of regions of interest in, e.g., neurobiological preparations, and, at the same time, the large number of electrodes allows for studying the activity of entire neuronal networks . Application areas include neuroscience, as the devices enable fundamental neurophysiological insights at the cellular and circuit level, as well as medical diagnostics and pharmacology.
@article{Livi2010,
title = {Compact voltage and current stimulation buffer for high-density microelectrode arrays},
author = {Paolo Livi and Flavio Heer and Urs Frey and Douglas J Bakkum and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/5617318/},
doi = {10.1109/TBCAS.2010.2080676},
issn = {19324545},
year = {2010},
date = {2010-11-01},
journal = {IEEE Transactions on Biomedical Circuits and Systems},
volume = {4},
number = {6},
pages = {372-378},
abstract = {We report on a compact (0.02 mm2 ) buffer for both voltage and current stimulation of electrogenic cells on a complementary metal-oxide semiconductor microelectrode array. In voltage mode, the circuit is a high-current class-AB voltage follower, based on a local common-mode feedback (LCMFB) amplifier. In current mode, the circuit is a current conveyor of type II, using the same LCMFB amplifier with cascode stages to increase the gain. The circuit shows good linearity in the 0.5-3.5 V input range and has extensively been used for stimulation of neuronal cultures.},
keywords = {ETH-CMOS-MEA, MEA Technology, Stimulation},
pubstate = {published},
tppubtype = {article}
}
We report on a compact (0.02 mm2 ) buffer for both voltage and current stimulation of electrogenic cells on a complementary metal-oxide semiconductor microelectrode array. In voltage mode, the circuit is a high-current class-AB voltage follower, based on a local common-mode feedback (LCMFB) amplifier. In current mode, the circuit is a current conveyor of type II, using the same LCMFB amplifier with cascode stages to increase the gain. The circuit shows good linearity in the 0.5-3.5 V input range and has extensively been used for stimulation of neuronal cultures.
@article{Frey2010,
title = {Switch-matrix-based high-density microelectrode array in CMOS technology},
author = {Urs Frey and Jan Sedivy and Flavio Heer and Rene Pedron and Marco Ballini and Jan Müller and Douglas J Bakkum and Sadik Hafizovic and Francesca D Faraci and Frauke Greve and Kay Uwe Kirstein and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/5405139/},
doi = {10.1109/JSSC.2009.2035196},
issn = {00189200},
year = {2010},
date = {2010-02-02},
journal = {IEEE Journal of Solid-State Circuits},
volume = {45},
number = {2},
pages = {467-482},
abstract = {We report on a CMOS-based microelectrode array (MEA) featuring 11, 011 metal electrodes and 126 channels, each of which comprises recording and stimulation electronics, for extracellular bidirectional communication with electrogenic cells, such as neurons or cardiomyocytes. The important features include: (i) high spatial resolution at (sub)cellular level with 3150 electrodes per mm2 (electrode diameter 7 um, electrode pitch 18 um); (ii) a reconflgurable routing of the recording sites to the 126 channels; and (iii) low noise levels.},
keywords = {ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
We report on a CMOS-based microelectrode array (MEA) featuring 11, 011 metal electrodes and 126 channels, each of which comprises recording and stimulation electronics, for extracellular bidirectional communication with electrogenic cells, such as neurons or cardiomyocytes. The important features include: (i) high spatial resolution at (sub)cellular level with 3150 electrodes per mm2 (electrode diameter 7 um, electrode pitch 18 um); (ii) a reconflgurable routing of the recording sites to the 126 channels; and (iii) low noise levels.
@conference{Frey2009b,
title = {Depth Recording Capabilities of Planar High-Density Microelectrode Arrays},
author = {U. Frey and U. Egert and D. Jäckel and J. Sedivy and M. Ballini and P. Livi and F. Faraci and F. Heer, S. Hafizovic and B. Roscic and A. Hierlemann},
url = {https://ieeexplore.ieee.org/document/5109270},
doi = {10.1109/NER.2009.5109270},
year = {2009},
date = {2009-04-01},
organization = {2009 4th International IEEE/EMBS Conference on Neural Engineering},
abstract = {We use a planar, CMOS-based microelectrode array (MEA) featuring 3,150 metal electrodes per mm2 and 126 recording channels to record spatially highly resolved extracellular action potentials (EAPs) from Purkinje cells (PCs) in acute cerebellar slices. An IndependentComponent-Analysis-based (ICA) spike sorter is used to reveal EAPs of single cells at subcellular resolution. Those EAPs are then used to set up a compartment model of a PC. The model is used to make and finetune estimations of the distance between MEA surface and PC soma. This distance is estimated using the amplitude-independent part of the shape of the EAPs obtained from recordings. The estimation shows that, in our preparations, we can record from PCs with the center of their soma at approximately 35 μm and 90 μm vertical distance to the chip surface.},
keywords = {2D Neuronal Culture, Brain Slice, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {conference}
}
We use a planar, CMOS-based microelectrode array (MEA) featuring 3,150 metal electrodes per mm2 and 126 recording channels to record spatially highly resolved extracellular action potentials (EAPs) from Purkinje cells (PCs) in acute cerebellar slices. An IndependentComponent-Analysis-based (ICA) spike sorter is used to reveal EAPs of single cells at subcellular resolution. Those EAPs are then used to set up a compartment model of a PC. The model is used to make and finetune estimations of the distance between MEA surface and PC soma. This distance is estimated using the amplitude-independent part of the shape of the EAPs obtained from recordings. The estimation shows that, in our preparations, we can record from PCs with the center of their soma at approximately 35 μm and 90 μm vertical distance to the chip surface.
@article{Frey2009,
title = {Microelectronic system for high-resolution mapping of extracellular electric fields applied to brain slices},
author = {Urs Frey and Ulrich Egert and Flavio Heer and Sadik Hafizovic and Andreas Hierlemann},
url = {http://www.sciencedirect.com/science/article/pii/S095656630800643X?via%3Dihub},
doi = {10.1016/j.bios.2008.11.028},
issn = {09565663},
year = {2009},
date = {2009-03-15},
journal = {Biosensors and Bioelectronics},
volume = {24},
number = {7},
pages = {2191-2198},
abstract = {There is an enduring quest for technologies that provide - temporally and spatially - highly resolved information on electric neuronal or cardiac activity in functional tissues or cell cultures. Here, we present a planar high-density, low-noise microelectrode system realized in microelectronics technology that features 11,011 microelectrodes (3,150 electrodes per mm2), 126 of which can be arbitrarily selected and can, via a reconfigurable routing scheme, be connected to on-chip recording and stimulation circuits. This device enables long-term extracellular electrical-activity recordings at subcellular spatial resolution and microsecond temporal resolution to capture the entire dynamics of the cellular electrical signals. To illustrate the device performance, extracellular potentials of Purkinje cells (PCs) in acute slices of the cerebellum have been analyzed. A detailed and comprehensive picture of the distribution and dynamics of action potentials (APs) in the somatic and dendritic regions of a single cell was obtained from the recordings by applying spike sorting and spike-triggered averaging methods to the collected data. An analysis of the measured local current densities revealed a reproducible sink/source pattern within a single cell during an AP. The experimental data substantiated compartmental models and can be used to extend those models to better understand extracellular single-cell potential patterns and their contributions to the population activity. The presented devices can be conveniently applied to a broad variety of biological preparations, i.e., neural or cardiac tissues, slices, or cell cultures can be grown or placed directly atop of the chips for fundamental mechanistic or pharmacological studies.},
keywords = {Brain Slice, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
There is an enduring quest for technologies that provide - temporally and spatially - highly resolved information on electric neuronal or cardiac activity in functional tissues or cell cultures. Here, we present a planar high-density, low-noise microelectrode system realized in microelectronics technology that features 11,011 microelectrodes (3,150 electrodes per mm2), 126 of which can be arbitrarily selected and can, via a reconfigurable routing scheme, be connected to on-chip recording and stimulation circuits. This device enables long-term extracellular electrical-activity recordings at subcellular spatial resolution and microsecond temporal resolution to capture the entire dynamics of the cellular electrical signals. To illustrate the device performance, extracellular potentials of Purkinje cells (PCs) in acute slices of the cerebellum have been analyzed. A detailed and comprehensive picture of the distribution and dynamics of action potentials (APs) in the somatic and dendritic regions of a single cell was obtained from the recordings by applying spike sorting and spike-triggered averaging methods to the collected data. An analysis of the measured local current densities revealed a reproducible sink/source pattern within a single cell during an AP. The experimental data substantiated compartmental models and can be used to extend those models to better understand extracellular single-cell potential patterns and their contributions to the population activity. The presented devices can be conveniently applied to a broad variety of biological preparations, i.e., neural or cardiac tissues, slices, or cell cultures can be grown or placed directly atop of the chips for fundamental mechanistic or pharmacological studies.
@article{Weber2009,
title = {A synthetic mammalian electro-genetic transcription circuit},
author = {Wilfried Weber and Stefan Luzi and Maria Karlsson and Carlota Diaz Sanchez-Bustamante and Urs Frey and Andreas Hierlemann and Martin Fussenegger},
url = {https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkp014},
doi = {10.1093/nar/gkp014},
issn = {03051048},
year = {2009},
date = {2009-02-03},
journal = {Nucleic Acids Research},
volume = {37},
number = {4},
pages = {1-8},
abstract = {Electric signal processing has evolved to manage rapid information transfer in neuronal networks and muscular contraction in multicellular organisms and controls the most sophisticated man-built devices. Using a synthetic biology approach to assemble electronic parts with genetic control units engineered into mammalian cells, we designed an electric power-adjustable transcription control circuit able to integrate the intensity of a direct current over time, to translate the amplitude or frequency of an alternating current into an adjustable genetic readout or to modulate the beating frequency of primary heart cells. Successful miniaturization of the electro-genetic devices may pave the way for the design of novel hybrid electrogenetic implants assembled from electronic and genetic parts.},
keywords = {Cardiomyocytes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Electric signal processing has evolved to manage rapid information transfer in neuronal networks and muscular contraction in multicellular organisms and controls the most sophisticated man-built devices. Using a synthetic biology approach to assemble electronic parts with genetic control units engineered into mammalian cells, we designed an electric power-adjustable transcription control circuit able to integrate the intensity of a direct current over time, to translate the amplitude or frequency of an alternating current into an adjustable genetic readout or to modulate the beating frequency of primary heart cells. Successful miniaturization of the electro-genetic devices may pave the way for the design of novel hybrid electrogenetic implants assembled from electronic and genetic parts.
@article{Sanchez-Bustamante2008,
title = {Modulation of cardiomyocyte electrical properties using regulated bone morphogenetic protein-2 expression.},
author = {Carlota Diaz Sanchez-Bustamante and Urs Frey and Jens M Kelm and Andreas Hierlemann and Martin Fussenegger},
url = {http://online.liebertpub.com/doi/abs/10.1089/ten.tea.2007.0302?url_ver=Z39.88-2003&rfr_id=ori%3Arid%3Acrossref.org&rfr_dat=cr_pub%3Dpubmed},
doi = {10.1089/ten.tea.2007.0302},
issn = {1937-3341},
year = {2008},
date = {2008-11-19},
journal = {Tissue Engineering. Part A},
volume = {14},
number = {12},
pages = {1969-1988},
abstract = {Because cardiomyocytes lose their ability to divide after birth, any subsequent cell loss or dysfunction results in pathologic cardiac rhythm initiation or impulse conduction. Strategies to restore and control the electrophysiological activity of the heart may, therefore, greatly affect the regeneration of cardiac tissue functionality. Using lentivirus-derived particles to regulate the bone morphogenetic protein-2 (BMP-2) gene expression in a pristinamycin- or gaseous acetaldehyde-inducible manner, we demonstrated the adjustment of cardiomyocyte electrophysiological characteristics. Complementary metal oxide semiconductor-based high-density microelectrode arrays (HD-MEAs) were used to monitor the electrophysiological activity of neonatal rat cardiomyocytes (NRCs) cultured as monolayers (NRCml) or as microtissues (NRCmt). NRCmt more closely resembled heart tissue physiology than did NRCml and could be conveniently monitored using HD-MEAs because of their ability to detect low-signal events and to sub-select the region of interest, namely, areas where the microtissues were placed. Cardiomyocyte-forming microtissues, transduced using lentiviral vectors encoding BMP-2, were capable of restoring myocardial microtissue electrical activity. We also engineered NRCmt to functionally couple within a cardiomyocyte monolayer, thus showing pacemaker-like activity upon local regulation of transgenic BMP-2 expression. The controlled expression of therapeutic transgenes represents a crucial advance for clinical interventions and gene-function analysis.},
keywords = {Cardiomyocytes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
Because cardiomyocytes lose their ability to divide after birth, any subsequent cell loss or dysfunction results in pathologic cardiac rhythm initiation or impulse conduction. Strategies to restore and control the electrophysiological activity of the heart may, therefore, greatly affect the regeneration of cardiac tissue functionality. Using lentivirus-derived particles to regulate the bone morphogenetic protein-2 (BMP-2) gene expression in a pristinamycin- or gaseous acetaldehyde-inducible manner, we demonstrated the adjustment of cardiomyocyte electrophysiological characteristics. Complementary metal oxide semiconductor-based high-density microelectrode arrays (HD-MEAs) were used to monitor the electrophysiological activity of neonatal rat cardiomyocytes (NRCs) cultured as monolayers (NRCml) or as microtissues (NRCmt). NRCmt more closely resembled heart tissue physiology than did NRCml and could be conveniently monitored using HD-MEAs because of their ability to detect low-signal events and to sub-select the region of interest, namely, areas where the microtissues were placed. Cardiomyocyte-forming microtissues, transduced using lentiviral vectors encoding BMP-2, were capable of restoring myocardial microtissue electrical activity. We also engineered NRCmt to functionally couple within a cardiomyocyte monolayer, thus showing pacemaker-like activity upon local regulation of transgenic BMP-2 expression. The controlled expression of therapeutic transgenes represents a crucial advance for clinical interventions and gene-function analysis.
@article{Hierlemann2007,
title = {A CMOS-based microelectrode array for interaction with neuronal cultures},
author = {Flavio Heer and Sadik Hafizovic and T Ugniwenko and Urs Frey and Axel Blau and Christiane Ziegler and Andreas Hierlemann},
url = {http://linkinghub.elsevier.com/retrieve/pii/S0165027007001781},
doi = {10.1016/j.jneumeth.2007.04.006},
issn = {0165-0270},
year = {2007},
date = {2007-04-19},
journal = {Journal of Neuroscience Methods},
volume = {164},
number = {1},
pages = {93-106},
abstract = {We report on the system integration of a CMOS chip that is capable of bidirectionally communicating (stimulation and recording) with electrogenic cells such as neurons or cardiomyocytes and that is targeted at investigating electrical signal propagation within cellular networks in vitro. The overall system consists of three major subunits: first, the core component is a 6.5 mm × 6.5 mm CMOS chip, on top of which the cells are cultured. It features 128 bidirectional electrodes, each equipped with dedicated analog filters and amplification stages and a stimulation buffer. The electrodes are sampled at 20 kHz with 8-bit resolution. The measured input-referred circuitry noise is 5.9 muV root mean square (10 Hz to 100 kHz), which allows to reliably detect the cell signals ranging from 1 mVpp down to 40 muVpp. Additionally, temperature sensors, a digital-to-analog converter for stimulation, and a digital interface for data transmission are integrated. Second, there is a reconfigurable logic device, which provides chip control, event detection, data buffering and an USB interface, capable of processing the 2.56 million samples per second. The third element includes software that is running on a standard PC performing data capturing, processing, and visualization. Experiments involving the stimulation of neurons with two different spatio-temporal patterns and the recording of the triggered spiking activity have been carried out. The response patterns have been successfully classified (83% correct) with respect to the different stimulation patterns. The advantages over current microelectrode arrays, as has been demonstrated in the experiments, include the capability to stimulate (voltage stimulation, 8 bit, 60 kHz) spatio-temporal patterns on arbitrary sets of electrodes and the fast stimulation reset mechanism that allows to record neuronal signals on a stimulating electrode 5 ms after stimulation (instantaneously on all other electrodes). Other advantages of the overall system include the small number of needed electrical connections due to the digital interface and the short latency time that allows to initiate a stimulation less than 2 ms after the detection of an action potential in closed-loop configurations.},
keywords = {ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
We report on the system integration of a CMOS chip that is capable of bidirectionally communicating (stimulation and recording) with electrogenic cells such as neurons or cardiomyocytes and that is targeted at investigating electrical signal propagation within cellular networks in vitro. The overall system consists of three major subunits: first, the core component is a 6.5 mm × 6.5 mm CMOS chip, on top of which the cells are cultured. It features 128 bidirectional electrodes, each equipped with dedicated analog filters and amplification stages and a stimulation buffer. The electrodes are sampled at 20 kHz with 8-bit resolution. The measured input-referred circuitry noise is 5.9 muV root mean square (10 Hz to 100 kHz), which allows to reliably detect the cell signals ranging from 1 mVpp down to 40 muVpp. Additionally, temperature sensors, a digital-to-analog converter for stimulation, and a digital interface for data transmission are integrated. Second, there is a reconfigurable logic device, which provides chip control, event detection, data buffering and an USB interface, capable of processing the 2.56 million samples per second. The third element includes software that is running on a standard PC performing data capturing, processing, and visualization. Experiments involving the stimulation of neurons with two different spatio-temporal patterns and the recording of the triggered spiking activity have been carried out. The response patterns have been successfully classified (83% correct) with respect to the different stimulation patterns. The advantages over current microelectrode arrays, as has been demonstrated in the experiments, include the capability to stimulate (voltage stimulation, 8 bit, 60 kHz) spatio-temporal patterns on arbitrary sets of electrodes and the fast stimulation reset mechanism that allows to record neuronal signals on a stimulating electrode 5 ms after stimulation (instantaneously on all other electrodes). Other advantages of the overall system include the small number of needed electrical connections due to the digital interface and the short latency time that allows to initiate a stimulation less than 2 ms after the detection of an action potential in closed-loop configurations.
@article{Greve2007,
title = {A perforated CMOS microchip platform for immobilization and activity monitoring of electrogenic cells},
author = {Frauke Greve and Jan Lichtenberg and Kay Uwe Kirstein and Urs Frey and Jean Claude Perriard and Andreas Hierlemann},
url = {http://iopscience.iop.org/article/10.1088/0960-1317/17/3/007/},
doi = {10.1088/0960-1317/17/3/007},
issn = {0960-1317},
year = {2007},
date = {2007-01-30},
journal = {Journal of Micromechanics and Microengineering},
volume = {17},
number = {3},
pages = {462-471},
abstract = {CMOS-based microelectrode systems offer decisive advantages over conventional micro-electrode arrays, which include the possibility to perform on-chip signal conditioning or to efficiently use larger numbers of electrodes to obtain statistically relevant data, e.g., in pharmacological drug screening. A larger number of electrodes can only be realized with the help of on-chip multiplexing and readout schemes, which require integrated electronics. Another fundamental issue in performing high-fidelity recordings from electrogenic cells is a good electrical coupling between the cells and the microelectrodes, in particular, since the recorded extracellular signals are in the range of only 10–1000 µV. In this paper we present the first CMOS microelectrode system with integrated micromechanical cell-placement features fabricated in a commercial CMOS process with subsequent post-CMOS bulk micromachining. This new microdevice aims at enabling the precise placement of single cells in the center of the electrodes to ensure an efficient use of the available electrodes, even for low-density cell cultures. Small through-chip holes have been generated at the metal-electrode sites by using a combination of bulk micromachining and reactive-ion etching. These holes act as orifices so that cell immobilization can be achieved by means of pneumatic anchoring. The chip additionally hosts integrated circuitry, i.e., multiplexers to select the respective readout electrodes, an amplifier with selectable gain (2×, 10×, 100×), and a high-pass filter (100 Hz cut-off). In this paper we show that electrical signals from most of the electrodes can be recorded, even in low-density cultures of neonatal rat cardiomyocytes, by using perforated metal electrodes and by applying a small underpressure from the backside of the chip. The measurements evidenced that, in most cases, about 90% of the electrodes were covered with single cells, approximately 4% were covered with more than one cell due to clustering and approximately 6% were not covered with any cell, mostly as a consequence of orifice clogging. After 4 days of culturing, the cells were still in place on the electrodes so that the cell electrical activity could be measured using the on-chip circuitry. Measured signal amplitudes were in the range of 500–700 µV, while the input-referred noise of the readout was below 15 µVrms (100 Hz–4 kHz bandwidth). We report on the development and fabrication of this new cell-biological tool and present first results collected during the characterization and evaluation of the chip. The recordings of electrical potentials of neonatal rat cardiomyocytes after several days in vitro, which, on the one hand, were conventionally cultured (no pneumatic anchoring) and, on the other hand, were anchored and immobilized, will be detailed.},
keywords = {2D Neuronal Culture, Cardiomyocytes, ETH-CMOS-MEA, MEA Technology},
pubstate = {published},
tppubtype = {article}
}
CMOS-based microelectrode systems offer decisive advantages over conventional micro-electrode arrays, which include the possibility to perform on-chip signal conditioning or to efficiently use larger numbers of electrodes to obtain statistically relevant data, e.g., in pharmacological drug screening. A larger number of electrodes can only be realized with the help of on-chip multiplexing and readout schemes, which require integrated electronics. Another fundamental issue in performing high-fidelity recordings from electrogenic cells is a good electrical coupling between the cells and the microelectrodes, in particular, since the recorded extracellular signals are in the range of only 10–1000 µV. In this paper we present the first CMOS microelectrode system with integrated micromechanical cell-placement features fabricated in a commercial CMOS process with subsequent post-CMOS bulk micromachining. This new microdevice aims at enabling the precise placement of single cells in the center of the electrodes to ensure an efficient use of the available electrodes, even for low-density cell cultures. Small through-chip holes have been generated at the metal-electrode sites by using a combination of bulk micromachining and reactive-ion etching. These holes act as orifices so that cell immobilization can be achieved by means of pneumatic anchoring. The chip additionally hosts integrated circuitry, i.e., multiplexers to select the respective readout electrodes, an amplifier with selectable gain (2×, 10×, 100×), and a high-pass filter (100 Hz cut-off). In this paper we show that electrical signals from most of the electrodes can be recorded, even in low-density cultures of neonatal rat cardiomyocytes, by using perforated metal electrodes and by applying a small underpressure from the backside of the chip. The measurements evidenced that, in most cases, about 90% of the electrodes were covered with single cells, approximately 4% were covered with more than one cell due to clustering and approximately 6% were not covered with any cell, mostly as a consequence of orifice clogging. After 4 days of culturing, the cells were still in place on the electrodes so that the cell electrical activity could be measured using the on-chip circuitry. Measured signal amplitudes were in the range of 500–700 µV, while the input-referred noise of the readout was below 15 µVrms (100 Hz–4 kHz bandwidth). We report on the development and fabrication of this new cell-biological tool and present first results collected during the characterization and evaluation of the chip. The recordings of electrical potentials of neonatal rat cardiomyocytes after several days in vitro, which, on the one hand, were conventionally cultured (no pneumatic anchoring) and, on the other hand, were anchored and immobilized, will be detailed.
@conference{Frey2007,
title = {11'000 Electrode-, 126 channel-CMOS microelectrode array for electrogenic cells},
author = {U. Frey and F. Heer and R. Pedro and F. Greve and S. Hafizovic and K.-U. Kirstein and A. Hierlemann},
url = {http://ieeexplore.ieee.org/document/4433154/},
doi = {10.1109/MEMSYS.2007.4433154},
year = {2007},
date = {2007-01-01},
booktitle = {2007 IEEE 20th International Conference on Micro Electro Mechanical Systems (MEMS)},
journal = {2007 IEEE 20th International Conference on Micro Electro Mechanical Systems (MEMS)},
abstract = {We present a CMOS-based microelectrode array with 11'016 metal electrodes and 126 on-chip channels, each of which includes recording and stimulation electronics for bidirectional communication with electrogenic cells (neurons or cardiomyocytes). The features of this chip include high spatial resolution with 3200 electrodes per mm2 to attain cellular or subcellular resolution (electrode diameter 7 μm, pitch 18 μm, honeycomb pattern), great flexibility in routing the 126 channels to the 11’016 recording sites, and low noise levels in the recordings (2.4 μVrms) so that single action potentials from mammalian cells can be monitored. The low noise levels also enable the recording of single-unit spike activity in acute slice preparations.},
keywords = {Action Potential, Brain Slice, Cardiomyocytes, ETH-CMOS-MEA, HD-MEA, MEA Technology, Spike Sorting},
pubstate = {published},
tppubtype = {conference}
}
We present a CMOS-based microelectrode array with 11'016 metal electrodes and 126 on-chip channels, each of which includes recording and stimulation electronics for bidirectional communication with electrogenic cells (neurons or cardiomyocytes). The features of this chip include high spatial resolution with 3200 electrodes per mm2 to attain cellular or subcellular resolution (electrode diameter 7 μm, pitch 18 μm, honeycomb pattern), great flexibility in routing the 126 channels to the 11’016 recording sites, and low noise levels in the recordings (2.4 μVrms) so that single action potentials from mammalian cells can be monitored. The low noise levels also enable the recording of single-unit spike activity in acute slice preparations.
@article{Hierlemann2006,
title = {Single-chip microelectronic system to interface with living cells},
author = {Flavio Heer and Sadik Hafizovic and T Ugniwenko and Urs Frey and Wendy Franks and Evelyne Perriard and Jean Claude Perriard and Axel Blau and Christiane Ziegler and Andreas Hierlemann},
url = {http://www.sciencedirect.com/science/article/pii/S0956566306004891?via%3Dihub},
doi = {10.1016/j.bios.2006.10.003},
issn = {0956-5663},
year = {2006},
date = {2006-11-13},
journal = {Biosensors & Bioelectronics},
volume = {22},
number = {11},
pages = {2546-2553},
abstract = {A high degree of connectivity and the coordinated electrical activity of neural cells or networks are believed to be the reason that the brain is capable of highly sophisticated information processing. Likewise, the effectiveness of an animal heart largely depends on such coordinated cell activity. To advance our understanding of these complex biological systems, high spatiotemporal-resolution techniques to monitor the cell electrical activity and an ideally seamless interaction between cells and recording devices are desired. Here we present a monolithic microsystem in complementary metal oxide semiconductor (CMOS) technology that provides bidirectional communication (stimulation and recording) between standard electronics technology and cultured electrogenic cells. The microchip can be directly used as a substrate for cell culturing, it features circuitry units per electrode for stimulation and immediate cell signal treatment, and it provides on-chip signal transformation as well as a digital interface so that a very fast, almost real-time interaction (2ms loop time from event recognition to, e.g., a defined stimulation) is possible at remarkable signal quality. The corresponding spontaneous and stimulated electrical activity recordings with neuronal and cardiac cell cultures will be presented. The system can be used to, e.g., study the development of neural networks, reveal the effects of neuronal plasticity and study cellular or network activity in response to pharmacological treatments.},
keywords = {Cardiomyocytes, ETH-CMOS-MEA, Neuronal Networks},
pubstate = {published},
tppubtype = {article}
}
A high degree of connectivity and the coordinated electrical activity of neural cells or networks are believed to be the reason that the brain is capable of highly sophisticated information processing. Likewise, the effectiveness of an animal heart largely depends on such coordinated cell activity. To advance our understanding of these complex biological systems, high spatiotemporal-resolution techniques to monitor the cell electrical activity and an ideally seamless interaction between cells and recording devices are desired. Here we present a monolithic microsystem in complementary metal oxide semiconductor (CMOS) technology that provides bidirectional communication (stimulation and recording) between standard electronics technology and cultured electrogenic cells. The microchip can be directly used as a substrate for cell culturing, it features circuitry units per electrode for stimulation and immediate cell signal treatment, and it provides on-chip signal transformation as well as a digital interface so that a very fast, almost real-time interaction (2ms loop time from event recognition to, e.g., a defined stimulation) is possible at remarkable signal quality. The corresponding spontaneous and stimulated electrical activity recordings with neuronal and cardiac cell cultures will be presented. The system can be used to, e.g., study the development of neural networks, reveal the effects of neuronal plasticity and study cellular or network activity in response to pharmacological treatments.
@article{Hierlemann2006b,
title = {Patterned cell adhesion by self-assembled structures for use with a CMOS cell-based biosensor},
author = {Wendy Franks and Samuele Tosatti and Flavio Heer and Philipp Seif and Marcus Textor and Andreas Hierlemann},
url = {http://www.sciencedirect.com/science/article/pii/S095656630600282X?via%3Dihub},
doi = {10.1016/j.bios.2006.06.031},
issn = {0956-5663},
year = {2006},
date = {2006-10-19},
journal = {Biosensors & Bioelectronics},
volume = {22},
number = {7},
pages = {1426-1433},
abstract = {A strategy for patterned cell adhesion based on chemical surface modification is presented. To confine cell adhesion to specific locations, an engineered surface for high-contrast protein adsorption and, hence, cell attachment has been developed. Surface functionalization is based on selective molecular-assembly patterning (SMAP). An amine-terminated self-assembled monolayer is used to define areas of cell adhesion. A protein-repellent grafted copolymer, poly(l-lysine)-graft-poly(ethylene glycol) (PLL-g-PEG), is used to render the surrounding silicon dioxide resistant to protein adsorption. X-ray photoelectron spectroscopy, scanning ellipsometry and fluorescence microscopy techniques were used to monitor the individual steps of the patterning process. Successful guided growth using these layers is demonstrated with primary neonatal rat cardiomyocytes, up to 4 days in vitro, and with the HL-1 cardiomyocyte cell line, up to 7 days in vitro. The advantage of the presented method is that high-resolution engineered surfaces can be realized using a simple, cost-effective, dip-and-rinse process. The technique has been developed for application on a CMOS cell-based biosensor, which comprises an array of microelectrodes to extracellularly record electrical activity from cardiomyocytes.},
keywords = {Cardiomyocytes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
A strategy for patterned cell adhesion based on chemical surface modification is presented. To confine cell adhesion to specific locations, an engineered surface for high-contrast protein adsorption and, hence, cell attachment has been developed. Surface functionalization is based on selective molecular-assembly patterning (SMAP). An amine-terminated self-assembled monolayer is used to define areas of cell adhesion. A protein-repellent grafted copolymer, poly(l-lysine)-graft-poly(ethylene glycol) (PLL-g-PEG), is used to render the surrounding silicon dioxide resistant to protein adsorption. X-ray photoelectron spectroscopy, scanning ellipsometry and fluorescence microscopy techniques were used to monitor the individual steps of the patterning process. Successful guided growth using these layers is demonstrated with primary neonatal rat cardiomyocytes, up to 4 days in vitro, and with the HL-1 cardiomyocyte cell line, up to 7 days in vitro. The advantage of the presented method is that high-resolution engineered surfaces can be realized using a simple, cost-effective, dip-and-rinse process. The technique has been developed for application on a CMOS cell-based biosensor, which comprises an array of microelectrodes to extracellularly record electrical activity from cardiomyocytes.
@article{Heer2006,
title = {CMOS microelectrode array for bidirectional interaction with neuronal networks},
author = {Flavio Heer and Sadik Hafizovic and Wendy Franks and Axel Blau and Christiane Ziegler and Andreas Hierlemann},
url = {http://ieeexplore.ieee.org/document/1644873/},
doi = {10.1109/JSSC.2006.873677},
issn = {0018-9200},
year = {2006},
date = {2006-07-07},
journal = {IEEE Journal of Solid-State Circuits},
volume = {41},
number = {7},
pages = {1620-1629},
abstract = {A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented.},
keywords = {2D Neuronal Culture, ETH-CMOS-MEA, MEA Technology, Neuronal Networks, Stimulation},
pubstate = {published},
tppubtype = {article}
}
A CMOS metal-electrode-based micro system for bidirectional communication (stimulation and recording) with neuronal cells in vitro is presented. The chip overcomes the interconnect challenge that limits today's bidirectional microelectrode arrays. The microsystem has been fabricated in an industrial CMOS technology with several post-CMOS processing steps to realize 128 biocompatible electrodes and to ensure chip stability in physiological saline. The system comprises all necessary control circuitry and on-chip A/D and D/A conversion. A modular design has been implemented, where individual stimulation- and signal-conditioning circuitry units are associated with each electrode. Stimulation signals with a resolution of 8 bits can be sent to any subset of electrodes at a rate of 60 kHz, while all electrodes of the chip are continuously sampled at a rate of 20 kHz. The circuitry at each electrode can be individually reset to its operating point in order to suppress artifacts evoked by the stimulation pulses. Biological measurements from cultured neuronal networks originating from dissociated cortical tissue of fertilized chicken eggs with amplitudes of up to 500 muVpp are presented.
@article{Linder2006,
title = {Microfluidics/CMOS orthogonal capabilities for cell biology},
author = {Vincent Linder and Sander Koster and Wendy Franks and Tobias Kraus and Elisabeth Verpoorte and Flavio Heer and Andreas Hierlemann and Nico F de Rooij},
url = {https://link.springer.com/article/10.1007%2Fs10544-006-7711-9},
doi = {10.1007/s10544-006-7711-9},
issn = {1572-8781},
year = {2006},
date = {2006-06-01},
journal = {Biomedical Microdevices},
volume = {8},
number = {2},
pages = {159-166},
abstract = {The study of individual cells and cellular networks can greatly benefit from the capabilities of microfabricated devices for the stimulation and the recording of electrical cellular events. In this contribution, we describe the development of a device, which combines capabilities for both electrical and pharmacological cell stimulation, and the subsequent recording of electrical cellular activity. The device combines the unique advantages of integrated circuitry (CMOS technology) for signal processing and microfluidics for drug delivery. Both techniques are ideally suited to study electrogenic mammalian cells, because feature sizes are of the same order as the cell diameter, ∼50 mum. Despite these attractive features, we observe a size mismatch between microfluidic devices, with bulky fluidic connections to the outside world, and highly miniaturized CMOS chips. To overcome this problem, we developed a microfluidic flow cell that accommodates a small CMOS chip. We simulated the performances of a flow cell based on a 3-D microfluidic system, and then fabricated the device to experimentally verify the nutrient delivery and localized drug delivery performance. The flow-cell has a constant nutrient flow, and six drug inlets that can individually deliver a drug to the cells. The experimental analysis of the nutrient and drug flow mass transfer properties in the flowcell are in good agreement with our simulations. For an experimental proof-of-principle, we successfully delivered, in a spatially resolved manner, a `drug' to a culture of HL-1 cardiac myocytes.},
keywords = {Cardiomyocytes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
The study of individual cells and cellular networks can greatly benefit from the capabilities of microfabricated devices for the stimulation and the recording of electrical cellular events. In this contribution, we describe the development of a device, which combines capabilities for both electrical and pharmacological cell stimulation, and the subsequent recording of electrical cellular activity. The device combines the unique advantages of integrated circuitry (CMOS technology) for signal processing and microfluidics for drug delivery. Both techniques are ideally suited to study electrogenic mammalian cells, because feature sizes are of the same order as the cell diameter, ∼50 mum. Despite these attractive features, we observe a size mismatch between microfluidic devices, with bulky fluidic connections to the outside world, and highly miniaturized CMOS chips. To overcome this problem, we developed a microfluidic flow cell that accommodates a small CMOS chip. We simulated the performances of a flow cell based on a 3-D microfluidic system, and then fabricated the device to experimentally verify the nutrient delivery and localized drug delivery performance. The flow-cell has a constant nutrient flow, and six drug inlets that can individually deliver a drug to the cells. The experimental analysis of the nutrient and drug flow mass transfer properties in the flowcell are in good agreement with our simulations. For an experimental proof-of-principle, we successfully delivered, in a spatially resolved manner, a `drug' to a culture of HL-1 cardiac myocytes.
@article{Koster2006,
title = {Characterization of a microfluidic dispensing system for localised stimulation of cellular networks},
author = {Tobias Kraus and Elisabeth Verpoorte and Vincent Linder and Wendy Franks and Andreas Hierlemann and Flavio Heer and Sadik Hafizovic and Teruo Fujii and Nico F de Rooij and Sander Koster},
url = {http://pubs.rsc.org/en/Content/ArticleLanding/2006/LC/b511768b#!divAbstract},
doi = {10.1039/B511768B},
year = {2006},
date = {2006-01-04},
journal = {Lab Chip},
volume = {6},
number = {2},
pages = {218-229},
publisher = {The Royal Society of Chemistry},
abstract = {We present a 3-D microfluidic device designed for localized drug delivery to cellular networks. The device features a flow cell comprising a main channel for nutrient delivery as well as multiple channels for drug delivery. This device is one key component of a larger, fully integrated system now under development, based upon a microelectrode array (MEA) with on-chip CMOS circuitry for recording and stimulation of electrogenic cells (e.g. neurons, cardiomyocytes). As a critical system unit, the microfluidics must be carefully designed and characterized to ensure that candidate drugs are delivered to specific regions of the culture at known concentrations. Furthermore, microfluidic design and functionality is dictated by the size, geometry, and material/electrical characteristics of the CMOS MEA. Therefore, this paper reports on the design considerations and fabrication of the flow cell, including theoretical and experimental analysis of the mass transfer properties of the nutrient and drug flows, which are in good agreement with one another. To demonstrate proof of concept, the flow cell was mounted on a dummy CMOS chip, which had been plated with HL-1 cardiomyocytes. A test chemical compound was delivered to the cell culture in a spatially resolved manner. Envisioned applications of this stand-alone system include simultaneous toxicological testing of multiple compounds and chemical stimulation of natural neural networks for neuroscience investigations},
keywords = {Cardiomyocytes, ETH-CMOS-MEA},
pubstate = {published},
tppubtype = {article}
}
We present a 3-D microfluidic device designed for localized drug delivery to cellular networks. The device features a flow cell comprising a main channel for nutrient delivery as well as multiple channels for drug delivery. This device is one key component of a larger, fully integrated system now under development, based upon a microelectrode array (MEA) with on-chip CMOS circuitry for recording and stimulation of electrogenic cells (e.g. neurons, cardiomyocytes). As a critical system unit, the microfluidics must be carefully designed and characterized to ensure that candidate drugs are delivered to specific regions of the culture at known concentrations. Furthermore, microfluidic design and functionality is dictated by the size, geometry, and material/electrical characteristics of the CMOS MEA. Therefore, this paper reports on the design considerations and fabrication of the flow cell, including theoretical and experimental analysis of the mass transfer properties of the nutrient and drug flows, which are in good agreement with one another. To demonstrate proof of concept, the flow cell was mounted on a dummy CMOS chip, which had been plated with HL-1 cardiomyocytes. A test chemical compound was delivered to the cell culture in a spatially resolved manner. Envisioned applications of this stand-alone system include simultaneous toxicological testing of multiple compounds and chemical stimulation of natural neural networks for neuroscience investigations
Presenting measurements of neuronal preparations with a novel CMOS-based microelectrode array at high-spatiotemporal-resolution on subcellular, cellular, and network level.
J. Müller, M. Ballini, P. Livi, Y. Chen, M. Radivojevic, A. Shadmani, V. Viswam, I. L. Jones, M. Fiscella, R. Diggelmann, A. Stettler, U. Frey, D. J. Bakkum, and A. Hierlemann, “High-resolution CMOS MEA platform to study neurons at subcellular, cellular, and network levels,” Lab Chip, vol. 15, no. 13, pp. 2767–2780, May 2015.
Reviewing the current understanding of microelectrode signals and the techniques for analyzing them, with focus on the ongoing advancements in microelectrode technology (in vivo and in vitro) and recent advanced microelectrode array measurement methods that facilitate the understanding of single neurons and network function.
M. E. J. Obien, K. Deligkaris, T. Bullmann, D. J. Bakkum, and U. Frey, “Revealing Neuronal Function through Microelectrode Array Recordings,” Front. Neurosci., 8:423, Jan 2015.
A high-resolution CMOS-based microelectrode array featuring 1,024 low-noise readout channels, 26,400 electrodes at a density of 3,265 electrodes per mm2, including on-chip 10bit ADCs and consuming only 75 mW.
M. Ballini, J. Muller, P. Livi, Y. Chen, U. Frey, A. Stettler, A. Shadmani, V. Viswam, I. L. Jones, D. Jackel, M. Radivojevic, M. K. Lewandowska, W. Gong, M. Fiscella, D. J. Bakkum, F. Heer, and A. Hierlemann, “A 1024-Channel CMOS Microelectrode Array With 26,400 Electrodes for Recording and Stimulation of Electrogenic Cells In Vitro,” IEEE Journal of Solid-State Circuits, vol. 49, no. 11, pp. 2705-2719, 2014.
Demonstrating a method to electrically visualize action potential propagation on axons and revealing
large variations in velocity.
D. J. Bakkum, U. Frey, M. Radivojevic, T. L. Russell, J. Muller, M. Fiscella, H. Takahashi, and A. Hierlemann, “Tracking axonal action potential propagation on a high-density microelectrode array across hundreds of sites,” Nature Communications, 4:2181, Jul 2013.
Recording and modeling extracellular action potentials of Purkinje cells at subcellular resolution.
U. Frey, U. Egert, F. Heer, S. Hafizovic, and A. Hierlemann, “Microelectronic System for High-Resolution Mapping of Extracellular Electric Fields Applied to Brain Slices,” Biosensors and Bioelectronics, vol. 24, no. 7, pp. 2191-2198, 2009.
Controlling BMP-2 expression to modulate the electrophysiological properties of cardiomyocytes using an HD-MEA for detailed monitoring.
C. D. Sanchez-Bustamante, U. Frey, J. M. Kelm, A. Hierlemann, and M. Fussenegger,
“Modulation of Cardiomyocyte Electrical Properties Using Regulated Bone Morphogenetic Protein-2 Expression,” Tissue Engineering Part A, vol. 14, no. 12, pp. 1969-1988, 2008.
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