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Kobayashi R, Shinomoto S. Inference of monosynaptic connections from parallel spike trains: A review. Neurosci Res 2024:S0168-0102(24)00097-X. [PMID: 39098768 DOI: 10.1016/j.neures.2024.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 07/12/2024] [Accepted: 07/19/2024] [Indexed: 08/06/2024]
Abstract
This article presents a mini-review about the progress in inferring monosynaptic connections from spike trains of multiple neurons over the past twenty years. First, we explain a variety of meanings of "neuronal connectivity" in different research areas of neuroscience, such as structural connectivity, monosynaptic connectivity, and functional connectivity. Among these, we focus on the methods used to infer the monosynaptic connectivity from spike data. We then summarize the inference methods based on two main approaches, i.e., correlation-based and model-based approaches. Finally, we describe available source codes for connectivity inference and future challenges. Although inference will never be perfect, the accuracy of identifying the monosynaptic connections has improved dramatically in recent years due to continuous efforts.
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Affiliation(s)
- Ryota Kobayashi
- Graduate School of Frontier Sciences, The University of Tokyo, Chiba 277-8561, Japan; Mathematics and Informatics Center, The University of Tokyo, Tokyo 113-8656, Japan.
| | - Shigeru Shinomoto
- Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan; Research Organization of Open Innovation and Collaboration, Ritsumeikan University, Osaka 567-8570, Japan
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2
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Bardella G, Giuffrida V, Giarrocco F, Brunamonti E, Pani P, Ferraina S. Response inhibition in premotor cortex corresponds to a complex reshuffle of the mesoscopic information network. Netw Neurosci 2024; 8:597-622. [PMID: 38952814 PMCID: PMC11168728 DOI: 10.1162/netn_a_00365] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Recent studies have explored functional and effective neural networks in animal models; however, the dynamics of information propagation among functional modules under cognitive control remain largely unknown. Here, we addressed the issue using transfer entropy and graph theory methods on mesoscopic neural activities recorded in the dorsal premotor cortex of rhesus monkeys. We focused our study on the decision time of a Stop-signal task, looking for patterns in the network configuration that could influence motor plan maturation when the Stop signal is provided. When comparing trials with successful inhibition to those with generated movement, the nodes of the network resulted organized into four clusters, hierarchically arranged, and distinctly involved in information transfer. Interestingly, the hierarchies and the strength of information transmission between clusters varied throughout the task, distinguishing between generated movements and canceled ones and corresponding to measurable levels of network complexity. Our results suggest a putative mechanism for motor inhibition in premotor cortex: a topological reshuffle of the information exchanged among ensembles of neurons.
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Affiliation(s)
- Giampiero Bardella
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Valentina Giuffrida
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Franco Giarrocco
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Emiliano Brunamonti
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Pierpaolo Pani
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
| | - Stefano Ferraina
- Department of Physiology and Pharmacology, Sapienza University of Rome, Rome, Italy
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3
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Chini M, Hnida M, Kostka JK, Chen YN, Hanganu-Opatz IL. Preconfigured architecture of the developing mouse brain. Cell Rep 2024; 43:114267. [PMID: 38795344 DOI: 10.1016/j.celrep.2024.114267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/13/2024] [Accepted: 05/08/2024] [Indexed: 05/27/2024] Open
Abstract
In the adult brain, structural and functional parameters, such as synaptic sizes and neuronal firing rates, follow right-skewed and heavy-tailed distributions. While this organization is thought to have significant implications, its development is still largely unknown. Here, we address this knowledge gap by investigating a large-scale dataset recorded from the prefrontal cortex and the olfactory bulb of mice aged 4-60 postnatal days. We show that firing rates and spike train interactions have a largely stable distribution shape throughout the first 60 postnatal days and that the prefrontal cortex displays a functional small-world architecture. Moreover, early brain activity exhibits an oligarchical organization, where high-firing neurons have hub-like properties. In a neural network model, we show that analogously right-skewed and heavy-tailed synaptic parameters are instrumental to consistently recapitulate the experimental data. Thus, functional and structural parameters in the developing brain are already extremely distributed, suggesting that this organization is preconfigured and not experience dependent.
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Affiliation(s)
- Mattia Chini
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | - Marilena Hnida
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Johanna K Kostka
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Yu-Nan Chen
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Ileana L Hanganu-Opatz
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
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4
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Breffle J, Germaine H, Shin JD, Jadhav SP, Miller P. Intrinsic dynamics of randomly clustered networks generate place fields and preplay of novel environments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.26.564173. [PMID: 37961479 PMCID: PMC10634993 DOI: 10.1101/2023.10.26.564173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
During both sleep and awake immobility, hippocampal place cells reactivate time-compressed versions of sequences representing recently experienced trajectories in a phenomenon known as replay. Intriguingly, spontaneous sequences can also correspond to forthcoming trajectories in novel environments experienced later, in a phenomenon known as preplay. Here, we present a model showing that sequences of spikes correlated with the place fields underlying spatial trajectories in both previously experienced and future novel environments can arise spontaneously in neural circuits with random, clustered connectivity rather than pre-configured spatial maps. Moreover, the realistic place fields themselves arise in the circuit from minimal, landmark-based inputs. We find that preplay quality depends on the network's balance of cluster isolation and overlap, with optimal preplay occurring in small-world regimes of high clustering yet short path lengths. We validate the results of our model by applying the same place field and preplay analyses to previously published rat hippocampal place cell data. Our results show that clustered recurrent connectivity can generate spontaneous preplay and immediate replay of novel environments. These findings support a framework whereby novel sensory experiences become associated with preexisting "pluripotent" internal neural activity patterns.
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Affiliation(s)
- Jordan Breffle
- Neuroscience Program, Brandeis University, 415 South St., Waltham, MA 02454
| | - Hannah Germaine
- Neuroscience Program, Brandeis University, 415 South St., Waltham, MA 02454
| | - Justin D Shin
- Neuroscience Program, Brandeis University, 415 South St., Waltham, MA 02454
- Volen National Center for Complex Systems, Brandeis University, 415 South St., Waltham, MA 02454
- Department of Psychology, Brandeis University, 415 South St., Waltham, MA 02454
| | - Shantanu P Jadhav
- Neuroscience Program, Brandeis University, 415 South St., Waltham, MA 02454
- Volen National Center for Complex Systems, Brandeis University, 415 South St., Waltham, MA 02454
- Department of Psychology, Brandeis University, 415 South St., Waltham, MA 02454
| | - Paul Miller
- Neuroscience Program, Brandeis University, 415 South St., Waltham, MA 02454
- Volen National Center for Complex Systems, Brandeis University, 415 South St., Waltham, MA 02454
- Department of Biology, Brandeis University, 415 South St., Waltham, MA 02454
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5
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Donner C, Bartram J, Hornauer P, Kim T, Roqueiro D, Hierlemann A, Obozinski G, Schröter M. Ensemble learning and ground-truth validation of synaptic connectivity inferred from spike trains. PLoS Comput Biol 2024; 20:e1011964. [PMID: 38683881 PMCID: PMC11081509 DOI: 10.1371/journal.pcbi.1011964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 05/09/2024] [Accepted: 03/02/2024] [Indexed: 05/02/2024] Open
Abstract
Probing the architecture of neuronal circuits and the principles that underlie their functional organization remains an important challenge of modern neurosciences. This holds true, in particular, for the inference of neuronal connectivity from large-scale extracellular recordings. Despite the popularity of this approach and a number of elaborate methods to reconstruct networks, the degree to which synaptic connections can be reconstructed from spike-train recordings alone remains controversial. Here, we provide a framework to probe and compare connectivity inference algorithms, using a combination of synthetic ground-truth and in vitro data sets, where the connectivity labels were obtained from simultaneous high-density microelectrode array (HD-MEA) and patch-clamp recordings. We find that reconstruction performance critically depends on the regularity of the recorded spontaneous activity, i.e., their dynamical regime, the type of connectivity, and the amount of available spike-train data. We therefore introduce an ensemble artificial neural network (eANN) to improve connectivity inference. We train the eANN on the validated outputs of six established inference algorithms and show how it improves network reconstruction accuracy and robustness. Overall, the eANN demonstrated strong performance across different dynamical regimes, worked well on smaller datasets, and improved the detection of synaptic connectivity, especially inhibitory connections. Results indicated that the eANN also improved the topological characterization of neuronal networks. The presented methodology contributes to advancing the performance of inference algorithms and facilitates our understanding of how neuronal activity relates to synaptic connectivity.
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Affiliation(s)
- Christian Donner
- Swiss Data Science Center, ETH Zürich & EPFL, Zürich & Lausanne, Switzerland
| | - Julian Bartram
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Philipp Hornauer
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Taehoon Kim
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Damian Roqueiro
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Guillaume Obozinski
- Swiss Data Science Center, ETH Zürich & EPFL, Zürich & Lausanne, Switzerland
| | - Manuel Schröter
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
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Irani M, Alderson TH. Tuning Criticality through Modularity in Biological Neural Networks. J Neurosci 2023; 43:5881-5882. [PMID: 37586856 PMCID: PMC10436681 DOI: 10.1523/jneurosci.0865-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/21/2023] [Accepted: 06/22/2023] [Indexed: 08/18/2023] Open
Affiliation(s)
- Martín Irani
- Neuroscience Program, University of Illinois Urbana-Champaign, Urbana, Illinois 61801
- Beckman Institute, University of Illinois Urbana-Champaign, Urbana, Illinois 61801
| | - Thomas H Alderson
- Beckman Institute, University of Illinois Urbana-Champaign, Urbana, Illinois 61801
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Neuronal Cultures: Exploring Biophysics, Complex Systems, and Medicine in a Dish. BIOPHYSICA 2023. [DOI: 10.3390/biophysica3010012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Neuronal cultures are one of the most important experimental models in modern interdisciplinary neuroscience, allowing to investigate in a control environment the emergence of complex behavior from an ensemble of interconnected neurons. Here, I review the research that we have conducted at the neurophysics laboratory at the University of Barcelona over the last 15 years, describing first the neuronal cultures that we prepare and the associated tools to acquire and analyze data, to next delve into the different research projects in which we actively participated to progress in the understanding of open questions, extend neuroscience research on new paradigms, and advance the treatment of neurological disorders. I finish the review by discussing the drawbacks and limitations of neuronal cultures, particularly in the context of brain-like models and biomedicine.
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Li XW, Ren Y, Shi DQ, Qi L, Xu F, Xiao Y, Lau PM, Bi GQ. Biphasic Cholinergic Modulation of Reverberatory Activity in Neuronal Networks. Neurosci Bull 2023; 39:731-744. [PMID: 36670292 PMCID: PMC10170002 DOI: 10.1007/s12264-022-01012-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 09/04/2022] [Indexed: 01/22/2023] Open
Abstract
Acetylcholine (ACh) is an important neuromodulator in various cognitive functions. However, it is unclear how ACh influences neural circuit dynamics by altering cellular properties. Here, we investigated how ACh influences reverberatory activity in cultured neuronal networks. We found that ACh suppressed the occurrence of evoked reverberation at low to moderate doses, but to a much lesser extent at high doses. Moreover, high doses of ACh caused a longer duration of evoked reverberation, and a higher occurrence of spontaneous activity. With whole-cell recording from single neurons, we found that ACh inhibited excitatory postsynaptic currents (EPSCs) while elevating neuronal firing in a dose-dependent manner. Furthermore, all ACh-induced cellular and network changes were blocked by muscarinic, but not nicotinic receptor antagonists. With computational modeling, we found that simulated changes in EPSCs and the excitability of single cells mimicking the effects of ACh indeed modulated the evoked network reverberation similar to experimental observations. Thus, ACh modulates network dynamics in a biphasic fashion, probably by inhibiting excitatory synaptic transmission and facilitating neuronal excitability through muscarinic signaling pathways.
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Affiliation(s)
- Xiao-Wei Li
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Yi Ren
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Dong-Qing Shi
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Lei Qi
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Fang Xu
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
| | - Yanyang Xiao
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
| | - Pak-Ming Lau
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China. .,CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
| | - Guo-Qiang Bi
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China.,CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
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9
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Weir JS, Christiansen N, Sandvig A, Sandvig I. Selective inhibition of excitatory synaptic transmission alters the emergent bursting dynamics of in vitro neural networks. Front Neural Circuits 2023; 17:1020487. [PMID: 36874945 PMCID: PMC9978115 DOI: 10.3389/fncir.2023.1020487] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 01/31/2023] [Indexed: 02/18/2023] Open
Abstract
Neurons in vitro connect to each other and form neural networks that display emergent electrophysiological activity. This activity begins as spontaneous uncorrelated firing in the early phase of development, and as functional excitatory and inhibitory synapses mature, the activity typically emerges as spontaneous network bursts. Network bursts are events of coordinated global activation among many neurons interspersed with periods of silencing and are important for synaptic plasticity, neural information processing, and network computation. While bursting is the consequence of balanced excitatory-inhibitory (E/I) interactions, the functional mechanisms underlying their evolution from physiological to potentially pathophysiological states, such as decreasing or increasing in synchrony, are still poorly understood. Synaptic activity, especially that related to maturity of E/I synaptic transmission, is known to strongly influence these processes. In this study, we used selective chemogenetic inhibition to target and disrupt excitatory synaptic transmission in in vitro neural networks to study functional response and recovery of spontaneous network bursts over time. We found that over time, inhibition resulted in increases in both network burstiness and synchrony. Our results indicate that the disruption in excitatory synaptic transmission during early network development likely affected inhibitory synaptic maturity which resulted in an overall decrease in network inhibition at later stages. These findings lend support to the importance of E/I balance in maintaining physiological bursting dynamics and, conceivably, information processing capacity in neural networks.
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Affiliation(s)
- Janelle Shari Weir
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Nicholas Christiansen
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Axel Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Neurology and Clinical Neurophysiology, St. Olav's University Hospital, Trondheim, Norway.,Division of Neuro, Head and Neck, Department of Pharmacology and Clinical Neurosciences, Umeå University Hospital, Umeå, Sweden.,Division of Neuro, Head and Neck, Department of Community Medicine and Rehabilitation, Umeå University Hospital, Umeå, Sweden
| | - Ioanna Sandvig
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
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Hingorani M, Viviani AML, Sanfilippo JE, Janušonis S. High-resolution spatiotemporal analysis of single serotonergic axons in an in vitro system. Front Neurosci 2022; 16:994735. [PMID: 36353595 PMCID: PMC9638127 DOI: 10.3389/fnins.2022.994735] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/28/2022] [Indexed: 12/04/2022] Open
Abstract
Vertebrate brains have a dual structure, composed of (i) axons that can be well-captured with graph-theoretical methods and (ii) axons that form a dense matrix in which neurons with precise connections operate. A core part of this matrix is formed by axons (fibers) that store and release 5-hydroxytryptamine (5-HT, serotonin), an ancient neurotransmitter that supports neuroplasticity and has profound implications for mental health. The self-organization of the serotonergic matrix is not well understood, despite recent advances in experimental and theoretical approaches. In particular, individual serotonergic axons produce highly stochastic trajectories, fundamental to the construction of regional fiber densities, but further advances in predictive computer simulations require more accurate experimental information. This study examined single serotonergic axons in culture systems (co-cultures and monolayers), by using a set of complementary high-resolution methods: confocal microscopy, holotomography (refractive index-based live imaging), and super-resolution (STED) microscopy. It shows that serotonergic axon walks in neural tissue may strongly reflect the stochastic geometry of this tissue and it also provides new insights into the morphology and branching properties of serotonergic axons. The proposed experimental platform can support next-generation analyses of the serotonergic matrix, including seamless integration with supercomputing approaches.
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Habibey R, Striebel J, Schmieder F, Czarske J, Busskamp V. Long-term morphological and functional dynamics of human stem cell-derived neuronal networks on high-density micro-electrode arrays. Front Neurosci 2022; 16:951964. [PMID: 36267241 PMCID: PMC9578684 DOI: 10.3389/fnins.2022.951964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2022] [Accepted: 09/06/2022] [Indexed: 11/13/2022] Open
Abstract
Comprehensive electrophysiological characterizations of human induced pluripotent stem cell (hiPSC)-derived neuronal networks are essential to determine to what extent these in vitro models recapitulate the functional features of in vivo neuronal circuits. High-density micro-electrode arrays (HD-MEAs) offer non-invasive recording with the best spatial and temporal resolution possible to date. For 3 months, we tracked the morphology and activity features of developing networks derived from a transgenic hiPSC line in which neurogenesis is inducible by neurogenic transcription factor overexpression. Our morphological data revealed large-scale structural changes from homogeneously distributed neurons in the first month to the formation of neuronal clusters over time. This led to a constant shift in position of neuronal cells and clusters on HD-MEAs and corresponding changes in spatial distribution of the network activity maps. Network activity appeared as scarce action potentials (APs), evolved as local bursts with longer duration and changed to network-wide synchronized bursts with higher frequencies but shorter duration over time, resembling the emerging burst features found in the developing human brain. Instantaneous firing rate data indicated that the fraction of fast spiking neurons (150–600 Hz) increases sharply after 63 days post induction (dpi). Inhibition of glutamatergic synapses erased burst features from network activity profiles and confirmed the presence of mature excitatory neurotransmission. The application of GABAergic receptor antagonists profoundly changed the bursting profile of the network at 120 dpi. This indicated a GABAergic switch from excitatory to inhibitory neurotransmission during circuit development and maturation. Our results suggested that an emerging GABAergic system at older culture ages is involved in regulating spontaneous network bursts. In conclusion, our data showed that long-term and continuous microscopy and electrophysiology readouts are crucial for a meaningful characterization of morphological and functional maturation in stem cell-derived human networks. Most importantly, assessing the level and duration of functional maturation is key to subject these human neuronal circuits on HD-MEAs for basic and biomedical applications.
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Affiliation(s)
- Rouhollah Habibey
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
| | - Johannes Striebel
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
| | - Felix Schmieder
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Dresden, Germany
| | - Jürgen Czarske
- Laboratory of Measurement and Sensor System Technique, Faculty of Electrical and Computer Engineering, TU Dresden, Dresden, Germany
- Competence Center for Biomedical Computational Laser Systems (BIOLAS), TU Dresden, Dresden, Germany
- Cluster of Excellence Physics of Life, TU Dresden, Dresden, Germany
- School of Science, Institute of Applied Physics, TU Dresden, Dresden, Germany
| | - Volker Busskamp
- Department of Ophthalmology, Universitäts-Augenklinik Bonn, University of Bonn, Bonn, Germany
- *Correspondence: Volker Busskamp,
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