@article{Duru2023c,
title = {Driving electrochemical reactions at the microscale using CMOS microelectrode arrays},
author = {Jens Duru and Arielle Rüfenacht and Josephine Löhle and Marcello Pozzi and Csaba Forró and Linus Ledermann and Aeneas Bernardi and Michael Matter and André Renia and Benjamin Simona and Christina M. Tringides and Stéphane Bernhard and Stephan J. Ihle and Julian Hengsteler and Benedikt Maurer and Xinyu Zhanga and Nako Nakatsuka},
url = {https://pubs.rsc.org/en/content/articlelanding/2023/lc/d3lc00630a},
doi = {10.1039/D3LC00630A},
issn = {1473-0189},
year = {2023},
date = {2023-10-30},
journal = {Lab on a Chip},
abstract = {Precise control of pH values at electrode interfaces enables the systematic investigation of pH-dependent processes by electrochemical means. In this work, we employed high-density complementary metal-oxide-semiconductor (CMOS) microelectrode arrays (MEAs) as miniaturized systems to induce and confine electrochemical reactions in areas corresponding to the pitch of single electrodes (17.5 μm). First, we present a strategy for generating localized pH patterns on the surface of the CMOS MEA with unprecedented spatial resolution. Leveraging the versatile routing capabilities of the switch matrix beneath the CMOS MEA, we created arbitrary combinations of anodic and cathodic electrodes and hence pH patterns. Moreover, we utilized the system to produce polymeric surface patterns by additive and subtractive methods. For additive patterning, we controlled the in situ formation of polydopamine at the microelectrode surface through oxidation of free dopamine above a threshold pH > 8.5. For subtractive patterning, we removed cell-adhesive poly-L-lysine from the electrode surface and backfilled the voids with antifouling polymers. Such polymers were chosen to provide a proof-of-concept application of controlling neuronal growth via electrochemically-induced patterns on the CMOS MEA surface. Importantly, our platform is compatible with commercially available high-density MEAs and requires no custom equipment, rendering the findings generalizable and accessible.},
keywords = {HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation},
pubstate = {published},
tppubtype = {article}
}

@article{Silverman2023,
title = {Hyperexcitability and translational phenotypes in a preclinical model of SYNGAP1mutations},
author = {Jill L. Silverman and Timothy Fenton and Olivia Haouchine and Elizabeth Hallam and Emily Smith and Kiya Jackson and Darlene Rahbarian and Cesar Canales and Anna Adhikari and Alex Nord and Roy Ben-Shalom},
url = {https://www.researchsquare.com/article/rs-3246655/v1},
doi = {https://doi.org/10.21203/rs.3.rs-3246655/v1},
year = {2023},
date = {2023-09-13},
journal = {Research Square},
abstract = {SYNGAP1is a critical gene for neuronal development, synaptic structure, and function. Although rare, the disruption of SYNGAP1directly causes a genetically identi able neurodevelopmental disorder (NDD) called SYNGAP1-related intellectual disability. Without functional SynGAP1 protein, patients present with intellectual disability, motor impairments, and epilepsy. Previous work using mouse models with a variety of germline and conditional mutations has helped delineate SynGAP1’s critical roles in neuronal structure and function, as well as key biochemical signaling pathways essential to synapse integrity. Homozygous loss of SYNGAP1is embryonically lethal. Heterozygous mutations of SynGAP1result in a broad range of phenotypes including increased locomotor activity, impaired working spatial memory, impaired cued fear memory, and increased stereotypic behavior. Ourinvivofunctional data, using the original germline mutation mouse line from the Huganir laboratory, corroborated robust hyperactivity and learning and memory de cits. Here, we describe impairments in the translational biomarker domain of sleep, characterized using neurophysiological data collected with wireless telemetric electroencephalography (EEG). We discoveredSyngap1+/− mice exhibited elevated spike trains in both number and duration, in addition to elevated power, most notably in the delta power band. Primary neurons fromSyngap1+/− mice displayed increased network ring activity, greater spikes per burst, and shorter inter-burst intervals between peaks using high density micro-electrode arrays (HD-MEA). This work is translational, innovative, and highly signi cant as it outlines functional impairments in Syngap1mutant mice. Simultaneously, the work utilized untethered, wireless neurophysiology that can discover potential biomarkers of Syngap1RID, for clinical trials, as it has done with other NDDs. Our work is substantial forward progress toward translational work for SynGAP1R-ID as it bridges in-vitroelectrophysiological neuronal activity and function with invivoneurophysiological brain activity and function. These data elucidate multiple quantitative, translational biomarkers invivoand invitrofor the development of treatments for SYNGAP1-related intellectual disability.},
keywords = {2D Neuronal Culture, Activity Scan Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Habibollahi2023,
title = {Critical dynamics arise during structured information presentation within embodied in vitro neuronal networks},
author = {Forough Habibollahi and Brett J. Kagan and Anthony N. Burkitt and Chris French },
url = {https://www.nature.com/articles/s41467-023-41020-3},
doi = {https://doi.org/10.1038/s41467-023-41020-3},
year = {2023},
date = {2023-08-30},
journal = {Nature Communications},
abstract = {Understanding how brains process information is an incredibly difficult task. Amongst the metrics characterising information processing in the brain, observations of dynamic near-critical states have generated significant interest. However, theoretical and experimental limitations associated with human and animal models have precluded a definite answer about when and why neural criticality arises with links from attention, to cognition, and even to consciousness. To explore this topic, we used an in vitro neural network of cortical neurons that was trained to play a simplified game of ‘Pong’ to demonstrate Synthetic Biological Intelligence (SBI). We demonstrate that critical dynamics emerge when neural networks receive task-related structured sensory input, reorganizing the system to a near-critical state. Additionally, better task performance correlated with proximity to critical dynamics. However, criticality alone is insufficient for a neuronal network to demonstrate learning in the absence of additional information regarding the consequences of previous actions. These findings offer compelling support that neural criticality arises as a base feature of incoming structured information processing without the need for higher order cognition.},
keywords = {2D Neuronal Culture, HD-MEA, IPSC, MaxOne, MEA Metrics, MEA Technology, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Radivojevic2023_2,
title = {Functional imaging of conduction dynamics in cortical and spinal axons},
author = {Milos Radivojevic and Anna Rostedt Punga},
url = {https://elifesciences.org/articles/86512},
doi = {https://doi.org/10.7554/eLife.86512},
year = {2023},
date = {2023-08-22},
journal = {eLife},
abstract = {Mammalian axons are specialized for transmitting action potentials to targets within the central and peripheral nervous system. A growing body of evidence suggests that, besides signal conduction, axons play essential roles in neural information processing, and their malfunctions are common hallmarks of neurodegenerative diseases. The technologies available to study axonal function and structure integrally limit the comprehension of axon neurobiology. High-density microelectrode arrays (HD-MEAs) allow for accessing axonal action potentials at high spatiotemporal resolution, but provide no insights on axonal morphology. Here, we demonstrate a method for electrical visualization of axonal morphologies based on extracellular action potentials recorded from cortical and motor neurons using HD-MEAs. The method enabled us to reconstruct up to 5-cm-long axonal arbors and directly monitor axonal conduction across thousands of recording sites. We reconstructed 1.86 m of cortical and spinal axons in total and found specific features in their structure and function.},
keywords = {2D Neuronal Culture, Axon Tracking Assay, MaxOne, MEA Technology, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Girardi2023,
title = {Cultured Vagal Afferent Neurons as Sensors for Intestinal Effector Molecules},
author = {Gregory Girardi and Danielle Zumpano and Noah Goshi and Helen Raybould and Erkin Seker},
url = {https://www.mdpi.com/2079-6374/13/6/601},
doi = {10.3390/bios13060601},
year = {2023},
date = {2023-05-31},
journal = {biosensors},
abstract = {The gut–brain axis embodies the bi-directional communication between the gastrointestinal tract and the central nervous system (CNS), where vagal afferent neurons (VANs) serve as sensors for a variety of gut-derived signals. The gut is colonized by a large and diverse population of microorganisms that communicate via small (effector) molecules, which also act on the VAN terminals situated in the gut viscera and consequently influence many CNS processes. However, the convoluted in vivo environment makes it difficult to study the causative impact of the effector molecules on VAN activation or desensitization. Here, we report on a VAN culture and its proof-of-principle demonstration as a cell-based sensor to monitor the influence of gastrointestinal effector molecules on neuronal behavior. We initially compared the effect of surface coatings (poly-L-lysine vs. Matrigel) and culture media composition (serum vs. growth factor supplement) on neurite growth as a surrogate of VAN regeneration following tissue harvesting, where the Matrigel coating, but not the media composition, played a significant role in the increased neurite growth. We then used both live-cell calcium imaging and extracellular electrophysiological recordings to show that the VANs responded to classical effector molecules of endogenous and exogenous origin (cholecystokinin serotonin and capsaicin) in a complex fashion. We expect this study to enable platforms for screening various effector molecules and their influence on VAN activity, assessed by their information-rich electrophysiological fingerprints.},
keywords = {2D Neuronal Culture, HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Bartram2023b,
title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking},
author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann},
url = {https://elifesciences.org/reviewed-preprints/86820},
doi = {10.7554/eLife.86820},
year = {2023},
date = {2023-05-17},
journal = {eLife},
abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. Yet, the precise relationship between the synaptic input patterns and the spiking output of individual neurons remains largely unresolved. Here, we developed, validated and applied a novel in vitro experimental platform and analytical procedures that provide – for individual neurons – simultaneous excitatory and inhibitory synaptic activity estimates during recurrent network activity. Our approach combines whole-network high-density microelectrode array (HD-MEA) recordings from rat neuronal cultures with patch clamping and enables a comprehensive mapping and characterization of active incoming connections to single postsynaptic neurons. We found that, during network states with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided precisely with the maxima of fast fluctuations in the input E/I ratio. These spike-associated E/I ratio escalations were largely due to a rapid bidirectional change in synaptic inhibition that was modulated by the network-activity level. Our approach also uncovered the underlying circuit architecture and we show that individual neurons received a few key inhibitory connections – often from special hub neurons – that were instrumental in controlling postsynaptic spiking. Balanced network theory predicts dynamical regimes governed by small and rapid input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of cortical networks in general.},
keywords = {HD-MEA, MaxOne, MEA Metrics, MEA Technology, Modeling, Primary Neuronal Cell Culture, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}

@article{Duru2023,
title = {Investigation of the input-output relationship of engineered neural networks using high-density microelectrode arrays},
author = {Jens Duru and Benedikt Maurer and Ciara Giles Doran and Robert Jelitto and Joël Küchler and Stephan J. Ihle and Tobias Ruff and Robert John and Barbara Genocchi and János Vörös},
url = {https://www.ssrn.com/abstract=4427959},
doi = {DOI: 10.2139/ssrn.4427959},
year = {2023},
date = {2023-04-24},
journal = {SSRN},
abstract = {Bottom-up neuroscience utilizes small, engineered biological neural networks to study neuronal activity in systems of reduced complexity. We present a platform that establishes up to six independent networks formed by primary rat neurons on planar complementary metal–oxide–semiconductor (CMOS) microelectrode arrays (MEAs). We introduce an approach that allows repetitive stimulation and recording of network activity at any of the over 700 electrodes underlying a network. We demonstrate that the continuous application of a repetitive super-threshold stimulus yields a reproducible network answer within a 15 ms post-stimulus window. This response can be tracked with high spatiotemporal resolution across the whole extent of the network. Moreover, we show that the location of the stimulation plays a significant role in the networks’ early response to the stimulus. By applying a stimulation pattern to all network-underlying electrodes in sequence, the sensitivity of the whole network to the stimulus can be visualized. We demonstrate that microchannels reduce the voltage stimulation threshold and induce the strongest network response. By varying the stimulation amplitude and frequency we reveal discrete network transition points. Finally, we introduce vector fields to follow stimulation-induced spike propagation pathways within the network. Overall we show that our defined neural networks on CMOS MEAs enable us to elicit highly reproducible activity patterns that can be precisely modulated by stimulation amplitude, stimulation frequency and the site of stimulation.},
keywords = {HD-MEA, MaxOne, MEA Technology, Primary Neuronal Cell Culture, Spike Sorting, Stimulation},
pubstate = {published},
tppubtype = {article}
}

@article{Taehoon2023,
title = {Predicting in vitro single-neuron firing rates upon pharmacological perturbation using Graph Neural Networks},
author = {Taehoon Kim and Dexiong Chen and Philipp Hornauer and Vishalini Emmenegger and Julian Bartram and Silvia Ronchi and Andreas Hierlemann and Manuel Schröter and Damian Roqueiro},
url = {https://www.frontiersin.org/articles/10.3389/fninf.2022.1032538/full},
doi = {10.3389/fninf.2022.1032538},
year = {2023},
date = {2023-01-11},
journal = {Frontiers in Neuroinformatics},
abstract = {Modern Graph Neural Networks (GNNs) provide opportunities to study the determinants underlying the complex activity patterns of biological neuronal networks. In this study, we applied GNNs to a large-scale electrophysiological dataset of rodent primary neuronal networks obtained by means of high-density microelectrode arrays (HD-MEAs). HD-MEAs allow for long-term recording of extracellular spiking activity of individual neurons and networks and enable the extraction of physiologically relevant features at the single- neuron and population level. We employed established GNNs to generate a combined representation of single-neuron and connectivity features obtained from HD-MEA data, with the ultimate goal of predicting changes in single-neuron firing rate induced by a pharmacological perturbation. The aim of the main prediction task was to assess whether single-neuron and functional connectivity features, inferred under baseline conditions, were informative for predicting changes in neuronal activity in response to a perturbation with Bicuculline, a GABAA receptor antagonist. Our results suggest that the joint representation of node features and functional connectivity, extracted from a baseline recording, was informative for predicting firing rate changes of individual neurons after the perturbation. Specifically, our implementation of a GNN model with inductive learning capability (GraphSAGE) outperformed other prediction models that relied only on single-neuron features. We tested the generalizability of the results on two additional datasets of HD-MEA recordings–a second dataset with cultures perturbed with Bicuculline and a dataset perturbed with the GABAA receptor antagonist Gabazine. GraphSAGE models showed improved prediction accuracy over other prediction models. Our results demonstrate the added value of taking into account the functional connectivity between neurons and the potential of GNNs to study complex interactions between neurons.},
keywords = {MaxTwo, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Bartram2023,
title = {Parallel reconstruction of the excitatory and inhibitory inputs received by single neurons reveals the synaptic basis of recurrent spiking},
author = {Julian Bartram and Felix Franke and Sreedhar Saseendran Kumar and Alessio Paolo Buccino and Xiaohan Xue and Tobias Gänswein and Manuel Schröter and Taehoon Kim and Krishna Chaitanya Kasuba and Andreas Hierlemann},
url = {https://www.biorxiv.org/content/10.1101/2023.01.06.523018v2},
doi = {https://doi.org/10.1101/2023.01.06.523018},
year = {2023},
date = {2023-01-08},
journal = {bioRxiv},
abstract = {Self-sustained recurrent activity in cortical networks is thought to be important for multiple crucial processes, including circuit development and homeostasis. However, the precise relationship between synaptic input patterns and spiking output of individual neurons remains unresolved during spontaneous network activity. Here, using whole-network high-density microelectrode array (HD-MEA) recordings and patch clamping, we developed a novel experimental approach and analytical tools that provide a comprehensive long-term input-output characterization of individual neurons in cortical cell cultures. We found that, during in vivo-like network activity with excitation(E)-inhibition(I) balance, postsynaptic spiking coincided with the maxima of rapid, network state-dependent fluctuations in the input E/I ratio. Our approach also uncovered the underlying circuit architecture and we identified a few key inhibitory inputs – often from special hub neurons – that were instrumental in mediating these E/I ratio changes. Balanced network theory predicts dynamical regimes governed by input fluctuation and featuring a fast neuronal responsiveness. Our findings – obtained in self-organized neuronal cultures – suggest that the emergence of these favorable regimes and associated network architectures is an inherent property of all cortical networks.},
keywords = {CMOS, HD-MEA, Modeling, Primary Neuronal Cell Culture, Spike Sorting},
pubstate = {published},
tppubtype = {article}
}

@article{Han2022,
title = {A functional neuron maturation device provides convenient application on microelectrode array for neural network measurement},
author = {Xiaobo Han and Naoki Matsuda and Yuto Ishibashi and Aoi Odawara and Sayuri Takahashi and Norie Tooi and Koshi Kinoshita and Ikuro Suzuki },
url = {https://biomaterialsres.biomedcentral.com/articles/10.1186/s40824-022-00324-z},
doi = {https://doi.org/10.1186/s40824-022-00324-z},
year = {2022},
date = {2022-12-20},
journal = {Biomaterials Research},
abstract = {Background
Microelectrode array (MEA) systems are valuable for in vitro assessment of neurotoxicity and drug efficiency. However, several difficulties such as protracted functional maturation and high experimental costs hinder the use of MEA analysis requiring human induced pluripotent stem cells (hiPSCs). Neural network functional parameters are also needed for in vitro to in vivo extrapolation.

Methods
In the present study, we produced a cost effective nanofiber culture platform, the SCAD device, for long-term culture of hiPSC-derived neurons and primary peripheral neurons. The notable advantage of SCAD device is convenient application on multiple MEA systems for neuron functional analysis.

Results
We showed that the SCAD device could promote functional maturation of cultured hiPSC-derived neurons, and neurons responded appropriately to convulsant agents. Furthermore, we successfully analyzed parameters for in vitro to in vivo extrapolation, i.e., low-frequency components and synaptic propagation velocity of the signal, potentially reflecting neural network functions from neurons cultured on SCAD device. Finally, we measured the axonal conduction velocity of peripheral neurons. Conclusions: Neurons cultured on SCAD devices might constitute a reliable in vitro platform to investigate neuron functions, drug efficacy and toxicity, and neuropathological mechanisms by MEA.},
keywords = {HD-MEA, IPSC, MaxOne, Neuronal cell culture, Organoids, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Kagan2022,
title = {In vitro neurons learn and exhibit sentience when embodied in a simulated game-world},
author = {Brett J. Kagan and Andy C. Kitchen and Nhi T. Tran and Forough Habibollahi and Moein Khajehnejad and Bradyn J. Parker and Anjali Bhat and Ben Rollo and Adeel Razi and Karl J. Friston},
url = {https://www.cell.com/neuron/fulltext/S0896-6273(22)00806-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0896627322008066%3Fshowall%3Dtrue#articleInformation},
doi = {https://doi.org/10.1016/j.neuron.2022.09.001},
year = {2022},
date = {2022-10-12},
journal = {Neuron},
abstract = {Integrating neurons into digital systems may enable performance infeasible with silicon alone. Here, we develop DishBrain, a system that harnesses the inherent adaptive computation of neurons in a structured environment. In vitro neural networks from human or rodent origins are integrated with in silico computing via a high-density multielectrode array. Through electrophysiological stimulation and recording, cultures are embedded in a simulated game-world, mimicking the arcade game ‘‘Pong.’’ Applying implications from the theory of active inference via the free energy principle, we find apparent learning within five minutes of real-time gameplay not observed in control conditions. Further experiments demonstrate the importance of closed-loop structured feedback in eliciting learning over time. Cultures display the ability to self-organize activity in a goal-directed manner in response to sparse sensory information about the consequences of their actions, which we term synthetic biological intelligence. Future applications may provide further insights into the cellular correlates of intelligence.},
keywords = {CMOS, HD-MEA, IPSC, MaxOne, Primary Neuronal Cell Culture},
pubstate = {published},
tppubtype = {article}
}

@article{Xue2022b,
title = {Inferring monosynaptic connections from paired dendritic spine Ca2+ imaging and large-scale recording of extracellular spiking},
author = {Xiaohan Xue and Alessio Paolo Buccino and Sreedhar Saseendran Kumar and Andreas Hierlemann and Julian Bartram},
doi = {https://doi.org/10.1088/1741-2552/ac8765},
year = {2022},
date = {2022-08-11},
journal = {Journal of Neural Engineering},
abstract = {Techniques to identify monosynaptic connections between neurons have been vital for neuroscience research, facilitating important advancements concerning network topology, synaptic plasticity, and synaptic integration, among others. Here, we introduce a novel approach to identify and monitor monosynaptic connections using high-resolution dendritic spine Ca2+ imaging combined with simultaneous large-scale recording of extracellular electrical activity by means of high-density microelectrode arrays (HD-MEAs). We introduce an easily adoptable analysis pipeline that associates the imaged spine with its presynaptic unit and test it on in vitro recordings. The method is further validated and optimized by simulating synaptically-evoked spine Ca2+ transients based on measured spike trains in order to obtain simulated ground-truth connections. The proposed approach offers unique advantages as i) it can be used to identify monosynaptic connections with an accurate localization of the synapse within the dendritic tree, ii) it provides precise information of presynaptic spiking, and iii) postsynaptic spine Ca2+ signals and, finally, iv) the non-invasive nature of the proposed method allows for long-term measurements. The analysis toolkit together with the rich data sets that were acquired are made publicly available for further exploration by the research community.},
keywords = {2D Neuronal Culture, Activity Assay, HD-MEA, MaxOne, Network Assay, Primary Neuronal Cell Culture, Publication},
pubstate = {published},
tppubtype = {article}
}

@article{Kubota2023,
title = {Unifying framework for information processing in stochastically driven dynamical systems},
author = {Tomoyuki Kubota and Hirokazu Takahashi and and Kohei Nakajima},
url = {https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.3.043135},
doi = {https://doi.org/10.1103/PhysRevResearch.3.043135},
year = {2021},
date = {2021-11-23},
journal = {Physical Review Research},
abstract = {A dynamical system is an information processing apparatus that encodes input streams from the external environment to its state and processes them through state transitions. The information processing capacity (IPC) is an excellent tool that comprehensively evaluates these processed inputs, providing details of unknown information processing in black box systems; however, this measure can be applied only to time-invariant systems. This paper extends the applicable range to time-variant systems and further reveals that the IPC is equivalent to coefficients of polynomial chaos (PC) expansion in more general dynamical systems. To achieve this objective, we tackle three issues. First, we establish a connection between the IPC for time-invariant systems and PC expansion, which is a type of polynomial expansion using orthogonal functions of input history as bases. We prove that the IPC corresponds to the squared norm of the coefficient vector of the basis in the PC expansion. Second, we show that an input following an arbitrary distribution can be used for the IPC, removing previous restrictions to specific input distributions. Third, we extend the conventional orthogonal bases to functions of both time and input history and propose the IPC for time-variant systems. To show the significance of our approach, we demonstrate that our measure can reveal information representations in not only machine learning networks but also a real, cultured neural network. Our generalized measure paves the way for unveiling the information processing capabilities of a wide variety of physical dynamics which have been left behind in nature.},
keywords = {2D Neuronal Culture, HD-MEA, MaxOne, Primary Neuronal Cell Culture, Stimulation},
pubstate = {published},
tppubtype = {article}
}