English
繁體中文
日本語
MaxOne for Brain Slice Studies 
MaxOne enables researchers to perform label-free analysis of intact brain networks in vitro:
- Acute brain slices
- Organotypic brain slice cultures and organoids
- Ex-vivo brain preparation (e.g., eye-brain from turtles)
What You Can Do
Capture Single Neuron and Network-Wide Field Potentials
MaxOne enables recording of neuronal activity across multiple scales at high spatio-temporal resolution.
- Both local field potentials and spikes from intact brain networks can be detected simultaneously.
- Low noise signals facilitate the extraction of neuronal activity features from experiments.
- Propagating field potentials across brain areas can be captured and analyzed.
Perform Large-Scale Mapping of Cells and Synaptic Projections
Extract and analyze the action potential spatial fields, axonal projections, and postsynaptic signals of every active neuron in the brain tissue. MaxOne can detect spiking neurons in brain slices and can elicit neuronal activity by electrical stimulation.
- A neuronal activity map can be extracted to identify areas of the brain slice with spiking neurons.
- Spiking frequency
- Postsynaptic events can be revealed by spike-trigerred averaging as a slow +/- signal post-spike. (M. Shein-Idelson, et al., Nat. Methods, 2017)
MaxOne Tissue Holder
MaxOne Tissue Holder flattens the brain slice on the MEA for stable and reprocible experiments.
The tissue holder keeps the tissue pressed and fixed on the MEA throughout the experiment, in the presence of solution perfusion.
Selected Publications
Andrews, John P; Geng, Jinghui; Voitiuk, Kateryna; Elliott, Matthew A T; Shin, David; Robbins, Ash; Spaeth, Alex; Wang, Albert; Li, Lin; Solis, Daniel; Keefe, Matthew G; Sevetson, Jessica L; de Jesús, Julio Rivera A; Donohue, Kevin C; Larson, Hanh H; Ehrlich, Drew; Auguste, Kurtis I; Salama, Sofie; Sohal, Vikaas; Sharf, Tal; Haussler, David; Cadwell, Cathryn R; Schaffer, David V; Chang, Edward F; Teodorescu, Mircea; Nowakowski, Tomasz Jan Multimodal Evaluation of Network Activity and Optogenetic Interventions in Human Hippocampal Slices Journal Article Nature Neuroscience , 2024. Elliott, Matthew A T; Andrews, John P; van der Molen, Tjitse; Geng, Jinghui; Spaeth, Alex; Voituik, Kateryna; Core, Cordero; Gillespie, Thomas; Sinervo, Ari; Parks, David F; Robbins, Ash; Solís, Daniel; Chang, Edward F; Nowakowski, Tomasz Jan; Teodorescu, Mircea; Haussler, David; Sharf, Tal Pathological Microcircuits Initiate Epileptiform Events in Patient Hippocampal Slices Journal Article bioRxiv, 2024. Geng, Jinghui; Voitiuk, Kateryna; Parks, David F; Robbins, Ash; Alex
Spaeth, ; Sevetson, Jessica L; Hernandez, Sebastian; Schweiger, Hunter E; Andrews, John P; Seiler, Spencer T; Elliott, Matthew A T; Chang, Edward F; Nowakowski, Tomasz J; Currie, Rob; Mostajo-Radji, Mohammed A; Haussler, David; Sharf, Tal; Salama, Sofie R; Teodorescu, Mircea Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization Journal Article bioRxiv, 2024. Kasuba, Krishna Chaitanya; Buccino, Alessio Paolo; Bartram, Julian; Gaub, Benjamin M; Fauser, Felix J; Ronchi, Silvia; Kumar, Sreedhar Saseendran; Geissler, Sydney; Nava, Michele M; Hierlemann, Andreas; Müller, Daniel J Nature Nanotechnology, 2024. Nakajima, Ryota; Shirakami, Arata; Tsumura, Hayato; Matsuda, Kouki; Nakamura, Eita; Shimono, Masanori Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation Journal Article Communications Biology, 2023. hiya Lv,; He, Enhui; Luo, Jinping; Liu, Yaoyao; Liang, Wei; Xu, Shihong; Zhang, Kui; Yang, Yan; Wang, Mixia; Song, Yilin; Wu, Yirong; Cai, Xinxia Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review Journal Article Advanced Science, 2023. Cerina, Marta; Piastra, Maria Carla; Frega, Monica The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research Journal Article Progress in Biomedical Engineering, 2023. Al-Absi, Abdel-Rahman; Thambiappaa, Sakeerthi Kethees; Khanc, Ahmad Raza; Glerup, Simon; Sanchez, Connie; Landau, Anne M; Nyengaard, Jens R Molecular and Cellular Neuroscience, 2022. Kajiwara Motoki; Nomura, Ritsuki; Goetze Felix; Kawabata Masanori; Isomura Yoshikazu; Akutsu Tatsuya; Shimono Masanori; Inhibitory neurons exhibit high controlling ability in the cortical microconnectome Journal Article PLOS Computational Biology, 2021. Obien, Marie Engelene J; Hierlemann, Andreas; Frey, Urs Accurate signal-source localization in brain slices by means of high-density microelectrode arrays Journal Article Scientific Reports, 9 (788), 2019. Shein-Idelson, Mark; Pammer, Lorenz; Hemberger, Mike; Laurent, Gilles Large-scale mapping of cortical synaptic projections with extracellular electrode arrays Journal Article Nature Methods, 14 (9), pp. 882–889, 2017, ISSN: 1548-7091. Viswam, Vijay; Bounik, Raziyeh; Shadmani, Amir; Dragas, Jelena; Obien, Marie Engelene J; Muller, Jan; Chen, Yihui; Hierlemann, Andreas 19th International Conference on Solid-State Sensors, Actuators and Microsystems (TRANSDUCERS) Kaohsiung, Taiwan, 2017, ISSN: 2167-0021. Gong, Wei; Sencar, Jure; Bakkum, Douglas J; Jäckel, David; Obien, Marie Engelene J; Radivojevic, Milos; Hierlemann, Andreas Multiple single-unit long-term tracking on organotypic hippocampal slices using high-density microelectrode arrays Journal Article Frontiers in Neuroscience, 10 , pp. 1-16, 2016, ISSN: 1662453X. Frey, U; Egert, U; Jäckel, D; Sedivy, J; Ballini, M; Livi, P; Faraci, F; F. Heer, Hafizovic S; Roscic, B; Hierlemann, A Depth Recording Capabilities of Planar High-Density Microelectrode Arrays Conference 2009 4th International IEEE/EMBS Conference on Neural Engineering 2009. Frey, Urs; Egert, Ulrich; Heer, Flavio; Hafizovic, Sadik; Hierlemann, Andreas Microelectronic system for high-resolution mapping of extracellular electric fields applied to brain slices Journal Article Biosensors and Bioelectronics, 24 (7), pp. 2191-2198, 2009, ISSN: 09565663. Frey, U; Heer, F; Pedro, R; Greve, F; Hafizovic, S; Kirstein, K -U; Hierlemann, A 11'000 Electrode-, 126 channel-CMOS microelectrode array for electrogenic cells Conference 2007 IEEE 20th International Conference on Micro Electro Mechanical Systems (MEMS), 2007.
title = {Multimodal Evaluation of Network Activity and Optogenetic Interventions in Human Hippocampal Slices},
author = {John P. Andrews and Jinghui Geng and Kateryna Voitiuk and Matthew A. T. Elliott and David Shin and Ash Robbins and Alex Spaeth and Albert Wang and Lin Li and Daniel Solis and Matthew G. Keefe and Jessica L. Sevetson and Julio A. Rivera de Jesús and Kevin C. Donohue and H. Hanh Larson and Drew Ehrlich and Kurtis I. Auguste and Sofie Salama and Vikaas Sohal and Tal Sharf and David Haussler and Cathryn R. Cadwell and David V. Schaffer and Edward F. Chang and Mircea Teodorescu and Tomasz Jan Nowakowski},
url = {https://www.nature.com/articles/s41593-024-01782-5},
doi = {10.1038/s41593-024-01782-5},
year = {2024},
date = {2024-11-15},
journal = {Nature Neuroscience },
abstract = {Seizures are made up of the coordinated activity of networks of neurons, suggesting that control of neurons in the pathologic circuits of epilepsy could allow for control of the disease. Optogenetics has been effective at stopping seizure-like activity in non-human disease models by increasing inhibitory tone or decreasing excitation, although this effect has not been shown in human brain tissue. Many of the genetic means for achieving c hannelrhodopsin expression in non-human models are not possible in humans, and vector-mediated methods are susceptible to species-specific tropism that may affect translational potential. Here we demonstrate adeno-associated virus–mediated, optogenetic reductions in network firing rates of human hippocampal slices recorded on high-density microelectrode arrays under several hyperactivity-provoking conditions. This platform can serve to bridge the gap between human and animal studies by exploring genetic interventions on network activity in human brain tissue.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Pathological Microcircuits Initiate Epileptiform Events in Patient Hippocampal Slices},
author = {Matthew A.T. Elliott and John P. Andrews and Tjitse van der Molen and Jinghui Geng and Alex Spaeth and Kateryna Voituik and Cordero Core and Thomas Gillespie and Ari Sinervo and David F. Parks and Ash Robbins and Daniel Solís and Edward F. Chang and Tomasz Jan Nowakowski and Mircea Teodorescu and David Haussler and Tal Sharf},
url = {https://www.biorxiv.org/content/10.1101/2024.11.13.623525v1},
doi = {https://doi.org/10.1101/2024.11.13.623525},
year = {2024},
date = {2024-11-14},
journal = {bioRxiv},
abstract = {How seizures begin at the level of microscopic neural circuits remains unknown. High-density CMOS microelectrode arrays provide a new avenue for investigating neuronal network activity, with unprecedented spatial and temporal resolution. We use high-density CMOS-based microelectrode arrays to probe the network activity of human hippocampal brain slices from six patients with mesial temporal lobe epilepsy in the presence of hyperactivity promoting media. Two slices from the dentate gyrus exhibited epileptiform activity in the presence of low magnesium media with kainic acid. Both slices displayed an electrophysiological phenotype consistent with a reciprocally connected circuit, suggesting a recurrent feedback loop is a key driver of epileptiform onset. Larger prospective studies are needed, but these findings have the potential to elucidate the network signals underlying the initiation of seizure behavior.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Multiscale Cloud-based Pipeline for Neuronal Electrophysiology Analysis and Visualization},
author = {Jinghui Geng and Kateryna Voitiuk and David F. Parks and Ash Robbins and Alex
Spaeth and Jessica L. Sevetson and Sebastian Hernandez and Hunter E. Schweiger
and John P. Andrews and Spencer T. Seiler and Matthew A.T. Elliott and Edward F. Chang and Tomasz J. Nowakowski and Rob Currie and Mohammed A. Mostajo-Radji and David Haussler and Tal Sharf and Sofie R. Salama and Mircea Teodorescu},
url = {https://www.biorxiv.org/content/10.1101/2024.11.14.623530v1},
doi = {https://doi.org/10.1101/2024.11.14.623530},
year = {2024},
date = {2024-11-14},
journal = {bioRxiv},
abstract = {Electrophysiology offers a high-resolution method for real-time measurement of neural activity. The vast amount of data generated requires efficient storage and sophisticated processing to extract neural function and network dynamics. However, analysis is often challenging due to the need for multiple software tools with different runtime dependencies. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage, complicating data management, sharing, and backup. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the analysis algorithms to serve as scalable and flexible building blocks within the pipeline. We designed graphical user interfaces and command line tools to remove the requirement of programming skills. The interactive visualizations provide multi-modality information on various neuronal features. This cloud-based pipeline is an efficient solution for electrophysiology data processing, the limitations of local software tools, and storage constraints. It simplifies the electrophysiology data analysis process and facilitates understanding neuronal activity. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Mechanical stimulation and electrophysiological monitoring at subcellular resolution reveals differential mechanosensation of neurons within networks},
author = {Krishna Chaitanya Kasuba and Alessio Paolo Buccino and Julian Bartram and Benjamin M. Gaub and Felix J. Fauser and Silvia Ronchi and Sreedhar Saseendran Kumar and Sydney Geissler and Michele M. Nava and Andreas Hierlemann and Daniel J. Müller },
url = {https://www.nature.com/articles/s41565-024-01609-1},
doi = {10.1038/s41565-024-01609-1},
year = {2024},
date = {2024-02-20},
journal = {Nature Nanotechnology},
abstract = {A growing consensus that the brain is a mechanosensitive organ is driving the need for tools that mechanically stimulate and simultaneously record the electrophysiological response of neurons within neuronal networks. Here we introduce a synchronized combination of atomic force microscopy, high-density microelectrode array and fluorescence microscopy to monitor neuronal networks and to mechanically characterize and stimulate individual neurons at piconewton force sensitivity and nanometre precision while monitoring their electrophysiological activity at subcellular spatial and millisecond temporal resolution. No correlation is found between mechanical stiffness and electrophysiological activity of neuronal compartments. Furthermore, spontaneously active neurons show exceptional functional resilience to static mechanical compression of their soma. However, application of fast transient (∼500 ms) mechanical stimuli to the neuronal soma can evoke action potentials, which depend on the anchoring of neuronal membrane and actin cytoskeleton. Neurons show higher responsivity, including bursts of action potentials, to slower transient mechanical stimuli (∼60 s). Moreover, transient and repetitive application of the same compression modulates the neuronal firing rate. Seemingly, neuronal networks can differentiate and respond to specific characteristics of mechanical stimulation. Ultimately, the developed multiparametric tool opens the door to explore manifold nanomechanobiological responses of neuronal systems and new ways of mechanical control.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Mutual generation in neuronal activity across the brain via deep neural approach, and its network interpretation},
author = {Ryota Nakajima and Arata Shirakami and Hayato Tsumura and Kouki Matsuda and Eita Nakamura and Masanori Shimono},
url = {https://www.nature.com/articles/s42003-023-05453-2},
doi = {10.1038/s42003-023-05453-2},
year = {2023},
date = {2023-10-31},
journal = {Communications Biology},
abstract = {In the brain, many regions work in a network-like association, yet it is not known how durable these associations are in terms of activity and could survive without structural connections. To assess the association or similarity between brain regions with a generating approach, this study evaluated the similarity of activities of neurons within each region after disconnecting between regions. The “generation” approach here refers to using a multi-layer LSTM (Long Short-Term Memory) model to learn the rules of activity generation in one region and then apply that knowledge to generate activity in other regions. Surprisingly, the results revealed that activity generation from one region to disconnected regions was possible with similar accuracy to generation between the same regions in many cases. Notably, firing rates and synchronization of firing between neuron pairs, often used as neuronal representations, could be reproduced with precision. Additionally, accuracies were associated with the relative angle between brain regions and the strength of the structural connections that initially connected them. This outcome enables us to look into trends governing non-uniformity of the cortex based on the potential to generate informative data and reduces the need for animal experiments.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Using Human-Induced Pluripotent Stem Cell Derived Neurons on Microelectrode Arrays to Model Neurological Disease: A Review},
author = {hiya Lv and Enhui He and Jinping Luo and Yaoyao Liu and Wei Liang and Shihong Xu and Kui Zhang and Yan Yang and Mixia Wang and Yilin Song and Yirong Wu and Xinxia Cai},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/advs.202301828},
doi = {10.1002/advs.202301828},
year = {2023},
date = {2023-10-23},
journal = {Advanced Science},
abstract = {In situ physiological signals of in vitro neural disease models are essential for studying pathogenesis and drug screening. Currently, an increasing number of in vitro neural disease models are established using human-induced pluripotent stem cell (hiPSC) derived neurons (hiPSC-DNs) to overcome interspecific gene expression differences. Microelectrode arrays (MEAs) can be readily interfaced with two-dimensional (2D), and more recently, three-dimensional (3D) neural stem cell-derived in vitro models of the human brain to monitor their physiological activity in real time. Therefore, MEAs are emerging and useful tools to model neurological disorders and disease in vitro using human iPSCs. This is enabling a real-time window into neuronal signaling at the network scale from patient derived. This paper provides a comprehensive review of MEA’s role in analyzing neural disease models established by hiPSC-DNs. It covers the significance of MEA fabrication, surface structure and modification schemes for hiPSC-DNs culturing and signal detection. Additionally, this review discusses advances in the development and use of MEA technology to study in vitro neural disease models, including epilepsy, autism spectrum developmental disorder (ASD), and others established using hiPSC-DNs. The paper also highlights the application of MEAs combined with hiPSC-DNs in detecting in vitro neurotoxic substances. Finally, the future development and outlook of multifunctional and integrated devices for in vitro medical diagnostics and treatment are discussed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {The potential of in vitro neuronal networks cultured on Micro Electrode Arrays for biomedical research},
author = {Marta Cerina and Maria Carla Piastra and Monica Frega},
url = {https://iopscience.iop.org/article/10.1088/2516-1091/acce12},
doi = {10.1088/2516-1091/acce12},
year = {2023},
date = {2023-04-18},
journal = {Progress in Biomedical Engineering},
abstract = {In vitro neuronal models have become an important tool to study healthy and diseased neuronal circuits. The growing interest of neuroscientists to explore the dynamics of neuronal systems and the increasing need to observe, measure and manipulate not only single neurons but populations of cells pushed for technological advancement. In this sense, Micro-Electrode Arrays (MEAs) emerged as a promising technique, made of cell culture dishes with embedded micro-electrodes allowing non-invasive and relatively simple measurement of the activity of neuronal cultures at the network level. In the past decade, MEAs popularity has rapidly grown. MEA devices have been extensively used to measure the activity of neuronal cultures mainly derived from rodents. Rodent neuronal cultures on MEAs have been employed to investigate physiological mechanisms, study the effect of chemicals in neurotoxicity screenings, and model the electrophysiological phenotype of neuronal networks in different pathological conditions. With the advancements in human induced pluripotent stem cells (hiPSCs) technology, the differentiation of human neurons from the cells of adult donors became possible. hiPSCsderived neuronal networks on MEAs have been employed to develop patient-specific in vitro platforms to characterize the pathophysiological phenotype and to test drugs, paving the way towards personalized medicine. In this review, we first describe MEA technology and the information that can be obtained from MEA recordings. Then, we give an overview of studies in which MEAs have been used in combination with different neuronal systems (i.e., rodent 2D and 3D neuronal cultures, organotypic brain slices, hiPSCs-derived 2D and 3D neuronal cultures, and brain organoids) for biomedical research, including physiology studies, neurotoxicity screenings, disease modeling, and drug testing. We end by discussing potential, challenges and future perspectives of MEA technology, and providing some guidance for the choice of the neuronal model and MEA device, experimental design, data analysis and reporting for scientific publications.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Df(h22q11)/+ mouse model exhibits reduced binding levels of GABAA receptors and structural and functional dysregulation in the inhibitory and excitatory networks of hippocampus},
author = {Abdel-Rahman Al-Absi and Sakeerthi Kethees Thambiappaa and Ahmad Raza Khanc and Simon Glerup and Connie Sanchez and Anne M. Landau and Jens R. Nyengaard},
url = {https://www.sciencedirect.com/science/article/pii/S1044743122000756?via%3Dihub},
doi = {https://doi.org/10.1016/j.mcn.2022.103769},
year = {2022},
date = {2022-08-18},
journal = {Molecular and Cellular Neuroscience},
abstract = {The 22q11.2 hemizygous deletion confers high risk for multiple neurodevelopmental disorders. Inhibitory signaling, largely regulated through GABAA receptors, is suggested to serve a multitude of brain functions that are disrupted in the 22q11.2 deletion syndrome.
We investigated the putative deficit of GABAA receptors and the potential substrates contributing to the inhibitory and excitatory dysregulations in hippocampal networks of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. The Df(h22q11)/+ mice exhibited impairments in several hippocampus-related functional domains, represented by impaired spatial memory and sensory gating functions. Autoradiography using the [3H]muscimol tracer revealed a significant reduction in GABAA receptor binding in the CA1 and CA3 subregions, together with a loss of GAD67+ interneurons in CA1 of Df(h22q11)/+ mice. Furthermore, electro- physiology recordings exhibited significantly higher neuronal activity in CA3, in response to the GABAA receptor antagonist, bicuculline, as compared with wild type mice. Density and volume of dendritic spines in pyramidal neurons were reduced and Sholl analysis also showed a reduction in the complexity of basal dendritic tree in CA1 and CA3 subregions of Df(h22q11)/+ mice.
Overall, our findings demonstrate that hemizygous deletion in the 22q11.2 locus leads to dysregulations in the inhibitory circuits, involving reduced binding levels of GABAA receptors, in addition to functional and structural modulations of the excitatory networks of hippocampus.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We investigated the putative deficit of GABAA receptors and the potential substrates contributing to the inhibitory and excitatory dysregulations in hippocampal networks of the Df(h22q11)/+ mouse model of the 22q11.2 hemizygous deletion. The Df(h22q11)/+ mice exhibited impairments in several hippocampus-related functional domains, represented by impaired spatial memory and sensory gating functions. Autoradiography using the [3H]muscimol tracer revealed a significant reduction in GABAA receptor binding in the CA1 and CA3 subregions, together with a loss of GAD67+ interneurons in CA1 of Df(h22q11)/+ mice. Furthermore, electro- physiology recordings exhibited significantly higher neuronal activity in CA3, in response to the GABAA receptor antagonist, bicuculline, as compared with wild type mice. Density and volume of dendritic spines in pyramidal neurons were reduced and Sholl analysis also showed a reduction in the complexity of basal dendritic tree in CA1 and CA3 subregions of Df(h22q11)/+ mice.
Overall, our findings demonstrate that hemizygous deletion in the 22q11.2 locus leads to dysregulations in the inhibitory circuits, involving reduced binding levels of GABAA receptors, in addition to functional and structural modulations of the excitatory networks of hippocampus.
title = {Inhibitory neurons exhibit high controlling ability in the cortical microconnectome},
author = {Kajiwara, Motoki; Nomura, Ritsuki; Goetze, Felix; Kawabata, Masanori; Isomura, Yoshikazu; Akutsu, Tatsuya; Shimono, Masanori; },
url = {https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008846},
year = {2021},
date = {2021-04-08},
journal = {PLOS Computational Biology},
abstract = {The brain is a network system in which excitatory and inhibitory neurons keep activity bal- anced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neu- rons in the cortex. So, in general, how inhibitory neurons can keep the balance with the sur- rounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the rela- tively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and con- trolling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibi- tory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimu- late E/I imbalanced disease states.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
title = {Accurate signal-source localization in brain slices by means of high-density microelectrode arrays},
author = {Marie Engelene J. Obien and Andreas Hierlemann and Urs Frey},
url = {https://www.nature.com/articles/s41598-018-36895-y},
doi = {10.1038/s41598-018-36895-y},
year = {2019},
date = {2019-01-28},
journal = {Scientific Reports},
volume = {9},
number = {788},
abstract = {Extracellular recordings by means of high-density microelectrode arrays (HD-MEAs) have become a powerful tool to resolve subcellular details of single neurons in active networks grown from dissociated cells. To extend the application of this technology to slice preparations, we developed models describing how extracellular signals, produced by neuronal cells in slices, are detected by microelectrode arrays. The models help to analyze and understand the electrical-potential landscape in an in vitro HD-MEA-recording scenario based on point-current sources. We employed two modeling schemes, (i) a simple analytical approach, based on the method of images (MoI), and (ii) an approach, based on finite-element methods (FEM). We compared and validated the models with large-scale, high-spatiotemporal-resolution recordings of slice preparations by means of HD-MEAs. We then developed a model-based localization algorithm and compared the performance of MoI and FEM models. Both models provided accurate localization results and a comparable and negligible systematic error, when the point source was in saline, a condition similar to cell-culture experiments. Moreover, the relative random error in the x-y-z-localization amounted only up to 4.3% for z-distances up to 200 μm from the HD-MEA surface. In tissue, the systematic errors of both, MoI and FEM models were significantly higher, and a pre-calibration was required. Nevertheless, the FEM values proved to be closer to the tissue experimental results, yielding 5.2 μm systematic mean error, compared to 22.0 μm obtained with MoI. These results suggest that the medium volume or “saline height”, the brain slice thickness and anisotropy, and the location of the reference electrode, which were included in the FEM model, considerably affect the extracellular signal and localization performance, when the signal source is at larger distance to the array. After pre-calibration, the relative random error of the z-localization in tissue was only 3% for z-distances up to 200 μm. We then applied the model and related detailed understanding of extracellular recordings to achieve an electrically-guided navigation of a stimulating micropipette, solely based on the measured HD-MEA signals, and managed to target spontaneously active neurons in an acute brain slice for electroporation.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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 = {},
pubstate = {published},
tppubtype = {article}
}
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 = {},
pubstate = {published},
tppubtype = {conference}
}
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 = {},
pubstate = {published},
tppubtype = {article}
}
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 = {},
pubstate = {published},
tppubtype = {conference}
}
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 = {},
pubstate = {published},
tppubtype = {article}
}
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 = {},
pubstate = {published},
tppubtype = {conference}
}
Contact Us
We would love to chat with you! Book a one-to-one call with one of our scientist to discuss how MaxWell Biosystems’ high-content electrophysiology solutions can bring new key insights to your project or request a quote.