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Ma X, Miraucourt LS, Qiu H, Xu M, Cook EP, Krishnaswamy A, Sharif-Naeini R, Khadra A. ElecFeX is a user-friendly toolbox for efficient feature extraction from single-cell electrophysiological recordings. CELL REPORTS METHODS 2024; 4:100791. [PMID: 38848714 PMCID: PMC11228277 DOI: 10.1016/j.crmeth.2024.100791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 02/17/2024] [Accepted: 05/14/2024] [Indexed: 06/09/2024]
Abstract
Characterizing neurons by their electrophysiological phenotypes is essential for understanding the neural basis of behavioral and cognitive functions. Technological developments have enabled the collection of hundreds of neural recordings; this calls for new tools capable of performing feature extraction efficiently. To address the urgent need for a powerful and accessible tool, we developed ElecFeX, an open-source MATLAB-based toolbox that (1) has an intuitive graphical user interface, (2) provides customizable measurements for a wide range of electrophysiological features, (3) processes large-size datasets effortlessly via batch analysis, and (4) yields formatted output for further analysis. We implemented ElecFeX on a diverse set of neural recordings; demonstrated its functionality, versatility, and efficiency in capturing electrical features; and established its significance in distinguishing neuronal subgroups across brain regions and species. ElecFeX is thus presented as a user-friendly toolbox to benefit the neuroscience community by minimizing the time required for extracting features from their electrophysiological datasets.
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Affiliation(s)
- Xinyue Ma
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Loïs S Miraucourt
- Alan Edwards Center for Research on Pain, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Haoyi Qiu
- Alan Edwards Center for Research on Pain, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Mengyi Xu
- Alan Edwards Center for Research on Pain, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Erik P Cook
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Quantitative Life Sciences, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Arjun Krishnaswamy
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Quantitative Life Sciences, McGill University, Montreal, QC H3G 1Y6, Canada
| | - Reza Sharif-Naeini
- Alan Edwards Center for Research on Pain, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada.
| | - Anmar Khadra
- Integrated Program in Neuroscience, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Physiology, McGill University, Montreal, QC H3G 1Y6, Canada; Department of Quantitative Life Sciences, McGill University, Montreal, QC H3G 1Y6, Canada.
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Weiler S, Rahmati V, Isstas M, Wutke J, Stark AW, Franke C, Graf J, Geis C, Witte OW, Hübener M, Bolz J, Margrie TW, Holthoff K, Teichert M. A primary sensory cortical interareal feedforward inhibitory circuit for tacto-visual integration. Nat Commun 2024; 15:3081. [PMID: 38594279 PMCID: PMC11003985 DOI: 10.1038/s41467-024-47459-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 04/03/2024] [Indexed: 04/11/2024] Open
Abstract
Tactile sensation and vision are often both utilized for the exploration of objects that are within reach though it is not known whether or how these two distinct sensory systems combine such information. Here in mice, we used a combination of stereo photogrammetry for 3D reconstruction of the whisker array, brain-wide anatomical tracing and functional connectivity analysis to explore the possibility of tacto-visual convergence in sensory space and within the circuitry of the primary visual cortex (VISp). Strikingly, we find that stimulation of the contralateral whisker array suppresses visually evoked activity in a tacto-visual sub-region of VISp whose visual space representation closely overlaps with the whisker search space. This suppression is mediated by local fast-spiking interneurons that receive a direct cortico-cortical input predominantly from layer 6 neurons located in the posterior primary somatosensory barrel cortex (SSp-bfd). These data demonstrate functional convergence within and between two primary sensory cortical areas for multisensory object detection and recognition.
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Affiliation(s)
- Simon Weiler
- Sainsbury Wellcome Centre for Neuronal Circuits and Behaviour, University College London, 25 Howland Street, London, W1T 4JG, UK
| | - Vahid Rahmati
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany
| | - Marcel Isstas
- Friedrich Schiller University Jena, Institute of General Zoology and Animal Physiology, Erbertstraße 1, 07743, Jena, Germany
| | - Johann Wutke
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany
| | - Andreas Walter Stark
- Friedrich Schiller University Jena, Institute of Applied Optics and Biophysics, Fröbelstieg 1, 07743, Jena, Germany
| | - Christian Franke
- Friedrich Schiller University Jena, Institute of Applied Optics and Biophysics, Fröbelstieg 1, 07743, Jena, Germany
- Friedrich Schiller University Jena, Jena Center for Soft Matter, Philosophenweg 7, 07743, Jena, Germany
- Friedrich Schiller University Jena, Abbe Center of Photonics, Albert-Einstein-Straße 6, 07745, Jena, Germany
| | - Jürgen Graf
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany
| | - Christian Geis
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany
| | - Otto W Witte
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany
| | - Mark Hübener
- Max Planck Institute for Biological Intelligence, Am Klopferspitz 18, 82152, Martinsried, Germany
| | - Jürgen Bolz
- Friedrich Schiller University Jena, Institute of General Zoology and Animal Physiology, Erbertstraße 1, 07743, Jena, Germany
| | - Troy W Margrie
- Sainsbury Wellcome Centre for Neuronal Circuits and Behaviour, University College London, 25 Howland Street, London, W1T 4JG, UK
| | - Knut Holthoff
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany
| | - Manuel Teichert
- Jena University Hospital, Department of Neurology, Am Klinikum 1, 07747, Jena, Germany.
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3
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Weiler S, Guggiana Nilo D, Bonhoeffer T, Hübener M, Rose T, Scheuss V. Functional and structural features of L2/3 pyramidal cells continuously covary with pial depth in mouse visual cortex. Cereb Cortex 2022; 33:3715-3733. [PMID: 36017976 PMCID: PMC10068292 DOI: 10.1093/cercor/bhac303] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 07/12/2022] [Accepted: 07/12/2022] [Indexed: 11/13/2022] Open
Abstract
Pyramidal cells of neocortical layer 2/3 (L2/3 PyrCs) integrate signals from numerous brain areas and project throughout the neocortex. These PyrCs show pial depth-dependent functional and structural specializations, indicating participation in different functional microcircuits. However, whether these depth-dependent differences result from separable PyrC subtypes or whether their features display a continuum correlated with pial depth is unknown. Here, we assessed the stimulus selectivity, electrophysiological properties, dendritic morphology, and excitatory and inhibitory connectivity across the depth of L2/3 in the binocular visual cortex of mice. We find that the apical, but not the basal dendritic tree structure, varies with pial depth, which is accompanied by variation in subthreshold electrophysiological properties. Lower L2/3 PyrCs receive increased input from L4, while upper L2/3 PyrCs receive a larger proportion of intralaminar input. In vivo calcium imaging revealed a systematic change in visual responsiveness, with deeper PyrCs showing more robust responses than superficial PyrCs. Furthermore, deeper PyrCs are more driven by contralateral than ipsilateral eye stimulation. Importantly, the property value transitions are gradual, and L2/3 PyrCs do not display discrete subtypes based on these parameters. Therefore, L2/3 PyrCs' multiple functional and structural properties systematically correlate with their depth, forming a continuum rather than discrete subtypes.
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Affiliation(s)
- Simon Weiler
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität München, Großhaderner Str. 2, Planegg 82152, Germany.,Sainsbury Wellcome Centre for Neural Circuits and Behaviour, University College London, 25 Howland Street, London W1T 4JG, United Kingdom
| | - Drago Guggiana Nilo
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Max Planck Institute for Biological Intelligence, in foundation, Martinsried, Germany
| | - Tobias Bonhoeffer
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Max Planck Institute for Biological Intelligence, in foundation, Martinsried, Germany
| | - Mark Hübener
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Max Planck Institute for Biological Intelligence, in foundation, Martinsried, Germany
| | - Tobias Rose
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Institute for Experimental Epileptology and Cognition Research, University of Bonn, Venusberg-Campus 1, Bonn 53127, Germany
| | - Volker Scheuss
- Max Planck Institute of Neurobiology, Am Klopferspitz 18, Martinsried 82152, Germany.,Department of Psychiatry, Ludwig-Maximilians-Universität München, Nussbaumstr. 7, München 80336, Germany
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4
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Synaptic Strengths Dominate Phasing of Motor Circuit: Intrinsic Conductances of Neuron Types Need Not Vary across Animals. eNeuro 2019; 6:ENEURO.0417-18.2019. [PMID: 31270128 PMCID: PMC6709225 DOI: 10.1523/eneuro.0417-18.2019] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 06/20/2019] [Accepted: 06/27/2019] [Indexed: 11/21/2022] Open
Abstract
Identified neurons and the networks they compose produce stereotypical, albeit individually unique, activity across members of a species. We propose, for a motor circuit driven by a central pattern generator (CPG), that the uniqueness derives mainly from differences in synaptic strength rather than from differences in intrinsic membrane conductances. We studied a dataset of recordings from six leech (Hirudo sp.) heartbeat control networks, containing complete spiking activity patterns from inhibitory premotor interneurons, motor output spike patterns, and synaptic strength patterns to investigate the source of uniqueness. We used a conductance-based multicompartmental motor neuron model to construct a bilateral motor circuit model, and controlled it by playing recorded input spike trains from premotor interneurons to generate output inhibitory synaptic patterns similar to experimental measurements. By generating different synaptic conductance parameter sets of this circuit model, we found that relative premotor synaptic strengths impinging onto motor neurons must be different across individuals to produce animal-specific output burst phasing. Obtaining unique outputs from each individual’s circuit model did not require different intrinsic ionic conductance parameters. Furthermore, changing intrinsic conductances failed to compensate for modified synaptic strength patterns. Thus, the pattern of synaptic strengths of motor neuron inputs is critical for the phasing of this motor circuit and can explain individual differences. When intrinsic conductances were allowed to vary, they exhibited the same conductance correlations across individuals, suggesting a motor neuron “type” required for proper network function. Our results are general and may translate to other systems and neuronal networks that control output phasing.
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5
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Mahmud M, Vassanelli S. Open-Source Tools for Processing and Analysis of In Vitro Extracellular Neuronal Signals. ADVANCES IN NEUROBIOLOGY 2019; 22:233-250. [PMID: 31073939 DOI: 10.1007/978-3-030-11135-9_10] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
The recent years have seen unprecedented growth in the manufacturing of neurotechnological tools. The latest technological advancements presented the neuroscientific community with neuronal probes containing thousands of recording sites. These next-generation probes are capable of simultaneously recording neuronal signals from a large number of channels. Numerically, a simple 128-channel neuronal data acquisition system equipped with a 16 bits A/D converter digitizing the acquired analog waveforms at a sampling frequency of 20 kHz will generate approximately 17 GB uncompressed data per hour. Today's biggest challenge is to mine this staggering amount of data and find useful information which can later be used in decoding brain functions, diagnosing diseases, and devising treatments. To this goal, many automated processing and analysis tools have been developed and reported in the literature. A good amount of them are also available as open source for others to adapt them to individual needs. Focusing on extracellularly recorded neuronal signals in vitro, this chapter provides an overview of the popular open-source tools applicable on these signals for spike trains and local field potentials analysis, and spike sorting. Towards the end, several future research directions have also been outlined.
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Affiliation(s)
- Mufti Mahmud
- Computing and Technology, School of Science and Technology, Nottingham Trent University, Nottingham, UK.
| | - Stefano Vassanelli
- NeuroChip Lab, Department of Biomedical Sciences, University of Padova, Padova, Italy
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6
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Integrating the Allen Brain Institute Cell Types Database into Automated Neuroscience Workflow. Neuroinformatics 2018; 15:333-342. [PMID: 28770487 DOI: 10.1007/s12021-017-9337-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
We developed software tools to download, extract features, and organize the Cell Types Database from the Allen Brain Institute (ABI) in order to integrate its whole cell patch clamp characterization data into the automated modeling/data analysis cycle. To expand the potential user base we employed both Python and MATLAB. The basic set of tools downloads selected raw data and extracts cell, sweep, and spike features, using ABI's feature extraction code. To facilitate data manipulation we added a tool to build a local specialized database of raw data plus extracted features. Finally, to maximize automation, we extended our NeuroManager workflow automation suite to include these tools plus a separate investigation database. The extended suite allows the user to integrate ABI experimental and modeling data into an automated workflow deployed on heterogeneous computer infrastructures, from local servers, to high performance computing environments, to the cloud. Since our approach is focused on workflow procedures our tools can be modified to interact with the increasing number of neuroscience databases being developed to cover all scales and properties of the nervous system.
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7
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Wenning A, Norris BJ, Günay C, Kueh D, Calabrese RL. Output variability across animals and levels in a motor system. eLife 2018; 7:31123. [PMID: 29345614 PMCID: PMC5773184 DOI: 10.7554/elife.31123] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 11/22/2017] [Indexed: 01/10/2023] Open
Abstract
Rhythmic behaviors vary across individuals. We investigated the sources of this output variability across a motor system, from the central pattern generator (CPG) to the motor plant. In the bilaterally symmetric leech heartbeat system, the CPG orchestrates two coordinations in the bilateral hearts with different intersegmental phase relations (Δϕ) and periodic side-to-side switches. Population variability is large. We show that the system is precise within a coordination, that differences in repetitions of a coordination contribute little to population output variability, but that differences between bilaterally homologous cells may contribute to some of this variability. Nevertheless, much output variability is likely associated with genetic and life history differences among individuals. Variability of Δϕ were coordination-specific: similar at all levels in one, but significantly lower for the motor pattern than the CPG pattern in the other. Mechanisms that transform CPG output to motor neurons may limit output variability in the motor pattern.
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Affiliation(s)
- Angela Wenning
- Biology Department, Emory University, Atlanta, United States
| | - Brian J Norris
- Biology Department, Emory University, Atlanta, United States.,Biological Sciences, California State University, San Marcos, United States
| | - Cengiz Günay
- Biology Department, Emory University, Atlanta, United States.,School of Science and Technology, Georgia Gwinnett College, Lawrenceville, United States
| | - Daniel Kueh
- Biology Department, Emory University, Atlanta, United States
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8
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Boles NC, Stone T, Bergeron C, Kiehl TR. Big Data access and infrastructure for modern biology: case studies in data repository utility. Ann N Y Acad Sci 2016; 1387:112-123. [DOI: 10.1111/nyas.13281] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2016] [Revised: 09/16/2016] [Accepted: 09/26/2016] [Indexed: 01/26/2023]
Affiliation(s)
| | - Tyler Stone
- Albany College of Pharmacy and Health Sciences; Albany New York
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9
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Neymotin SA, Suter BA, Dura-Bernal S, Shepherd GMG, Migliore M, Lytton WW. Optimizing computer models of corticospinal neurons to replicate in vitro dynamics. J Neurophysiol 2016; 117:148-162. [PMID: 27760819 DOI: 10.1152/jn.00570.2016] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2016] [Accepted: 10/13/2016] [Indexed: 11/22/2022] Open
Abstract
Corticospinal neurons (SPI), thick-tufted pyramidal neurons in motor cortex layer 5B that project caudally via the medullary pyramids, display distinct class-specific electrophysiological properties in vitro: strong sag with hyperpolarization, lack of adaptation, and a nearly linear frequency-current (F-I) relationship. We used our electrophysiological data to produce a pair of large archives of SPI neuron computer models in two model classes: 1) detailed models with full reconstruction; and 2) simplified models with six compartments. We used a PRAXIS and an evolutionary multiobjective optimization (EMO) in sequence to determine ion channel conductances. EMO selected good models from each of the two model classes to form the two model archives. Archived models showed tradeoffs across fitness functions. For example, parameters that produced excellent F-I fit produced a less-optimal fit for interspike voltage trajectory. Because of these tradeoffs, there was no single best model but rather models that would be best for particular usages for either single neuron or network explorations. Further exploration of exemplar models with strong F-I fit demonstrated that both the detailed and simple models produced excellent matches to the experimental data. Although dendritic ion identities and densities cannot yet be fully determined experimentally, we explored the consequences of a demonstrated proximal to distal density gradient of Ih, demonstrating that this would lead to a gradient of resonance properties with increased resonant frequencies more distally. We suggest that this dynamical feature could serve to make the cell particularly responsive to major frequency bands that differ by cortical layer. NEW & NOTEWORTHY We developed models of motor cortex corticospinal neurons that replicate in vitro dynamics, including hyperpolarization-induced sag and realistic firing patterns. Models demonstrated resonance in response to synaptic stimulation, with resonance frequency increasing in apical dendrites with increasing distance from soma, matching the increasing oscillation frequencies spanning deep to superficial cortical layers. This gradient may enable specific corticospinal neuron dendrites to entrain to relevant oscillations in different cortical layers, contributing to appropriate motor output commands.
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Affiliation(s)
- Samuel A Neymotin
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Medical Center, Brooklyn, New York;
| | - Benjamin A Suter
- Department of Physiology, Northwestern University, Chicago, Illinois
| | - Salvador Dura-Bernal
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Medical Center, Brooklyn, New York
| | | | - Michele Migliore
- Institute of Biophysics, National Research Council, Palermo, Italy
| | - William W Lytton
- Department of Physiology and Pharmacology, State University of New York (SUNY) Downstate Medical Center, Brooklyn, New York.,Department of Neurology, SUNY Downstate Medical Center, Brooklyn, New York.,Department of Neurology, Kings County Hospital Center, Brooklyn, New York; and.,The Robert F. Furchgott Center for Neural and Behavioral Science, Brooklyn, New York
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10
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Using a Semi-Automated Strategy to Develop Multi-Compartment Models That Predict Biophysical Properties of Interneuron-Specific 3 (IS3) Cells in Hippocampus. eNeuro 2016; 3:eN-NWR-0087-16. [PMID: 27679813 PMCID: PMC5035096 DOI: 10.1523/eneuro.0087-16.2016] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2016] [Revised: 08/19/2016] [Accepted: 08/22/2016] [Indexed: 11/30/2022] Open
Abstract
Determining how intrinsic cellular properties govern and modulate neuronal input–output processing is a critical endeavor for understanding microcircuit functions in the brain. However, lack of cellular specifics and nonlinear interactions prevent experiments alone from achieving this. Building and using cellular models is essential in these efforts. We focus on uncovering the intrinsic properties of mus musculus hippocampal type 3 interneuron-specific (IS3) cells, a cell type that makes GABAergic synapses onto specific interneuron types, but not pyramidal cells. While IS3 cell morphology and synaptic output have been examined, their voltage-gated ion channel profile and distribution remain unknown. We combined whole-cell patch-clamp recordings and two-photon dendritic calcium imaging to examine IS3 cell membrane and dendritic properties. Using these data as a target reference, we developed a semi-automated strategy to obtain multi-compartment models for a cell type with unknown intrinsic properties. Our approach is based on generating populations of models to capture determined features of the experimental data, each of which possesses unique combinations of channel types and conductance values. From these populations, we chose models that most closely resembled the experimental data. We used these models to examine the impact of specific ion channel combinations on spike generation. Our models predict that fast delayed rectifier currents should be present in soma and proximal dendrites, and this is confirmed using immunohistochemistry. Further, without A-type potassium currents in the dendrites, spike generation is facilitated at more distal synaptic input locations. Our models will help to determine the functional role of IS3 cells in hippocampal microcircuits.
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11
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Mahmud M, Vassanelli S. Processing and Analysis of Multichannel Extracellular Neuronal Signals: State-of-the-Art and Challenges. Front Neurosci 2016; 10:248. [PMID: 27313507 PMCID: PMC4889584 DOI: 10.3389/fnins.2016.00248] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2016] [Accepted: 05/19/2016] [Indexed: 12/02/2022] Open
Abstract
In recent years multichannel neuronal signal acquisition systems have allowed scientists to focus on research questions which were otherwise impossible. They act as a powerful means to study brain (dys)functions in in-vivo and in in-vitro animal models. Typically, each session of electrophysiological experiments with multichannel data acquisition systems generate large amount of raw data. For example, a 128 channel signal acquisition system with 16 bits A/D conversion and 20 kHz sampling rate will generate approximately 17 GB data per hour (uncompressed). This poses an important and challenging problem of inferring conclusions from the large amounts of acquired data. Thus, automated signal processing and analysis tools are becoming a key component in neuroscience research, facilitating extraction of relevant information from neuronal recordings in a reasonable time. The purpose of this review is to introduce the reader to the current state-of-the-art of open-source packages for (semi)automated processing and analysis of multichannel extracellular neuronal signals (i.e., neuronal spikes, local field potentials, electroencephalogram, etc.), and the existing Neuroinformatics infrastructure for tool and data sharing. The review is concluded by pinpointing some major challenges that are being faced, which include the development of novel benchmarking techniques, cloud-based distributed processing and analysis tools, as well as defining novel means to share and standardize data.
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Affiliation(s)
- Mufti Mahmud
- NeuroChip Laboratory, Department of Biomedical Sciences, University of Padova Padova, Italy
| | - Stefano Vassanelli
- NeuroChip Laboratory, Department of Biomedical Sciences, University of Padova Padova, Italy
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12
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Stockton DB, Santamaria F. NeuroManager: a workflow analysis based simulation management engine for computational neuroscience. Front Neuroinform 2015; 9:24. [PMID: 26528175 PMCID: PMC4602303 DOI: 10.3389/fninf.2015.00024] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2015] [Accepted: 09/22/2015] [Indexed: 11/13/2022] Open
Abstract
We developed NeuroManager, an object-oriented simulation management software engine for computational neuroscience. NeuroManager automates the workflow of simulation job submissions when using heterogeneous computational resources, simulators, and simulation tasks. The object-oriented approach (1) provides flexibility to adapt to a variety of neuroscience simulators, (2) simplifies the use of heterogeneous computational resources, from desktops to super computer clusters, and (3) improves tracking of simulator/simulation evolution. We implemented NeuroManager in MATLAB, a widely used engineering and scientific language, for its signal and image processing tools, prevalence in electrophysiology analysis, and increasing use in college Biology education. To design and develop NeuroManager we analyzed the workflow of simulation submission for a variety of simulators, operating systems, and computational resources, including the handling of input parameters, data, models, results, and analyses. This resulted in 22 stages of simulation submission workflow. The software incorporates progress notification, automatic organization, labeling, and time-stamping of data and results, and integrated access to MATLAB's analysis and visualization tools. NeuroManager provides users with the tools to automate daily tasks, and assists principal investigators in tracking and recreating the evolution of research projects performed by multiple people. Overall, NeuroManager provides the infrastructure needed to improve workflow, manage multiple simultaneous simulations, and maintain provenance of the potentially large amounts of data produced during the course of a research project.
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Affiliation(s)
- David B. Stockton
- Biomedical Engineering Program, The University of Texas at San AntonioSan Antonio, TX, USA
| | - Fidel Santamaria
- UTSA Neurosciences Institute, The University of Texas at San AntonioSan Antonio, TX, USA
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13
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Sekulić V, Chen TC, Lawrence JJ, Skinner FK. Dendritic distributions of I h channels in experimentally-derived multi-compartment models of oriens-lacunosum/moleculare (O-LM) hippocampal interneurons. Front Synaptic Neurosci 2015; 7:2. [PMID: 25774132 PMCID: PMC4343010 DOI: 10.3389/fnsyn.2015.00002] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2014] [Accepted: 02/02/2015] [Indexed: 01/14/2023] Open
Abstract
The O-LM cell type mediates feedback inhibition onto hippocampal pyramidal cells and gates information flow in the CA1. Its functions depend on the presence of voltage-gated channels (VGCs), which affect its integrative properties and response to synaptic input. Given the challenges associated with determining densities and distributions of VGCs on interneuron dendrites, we take advantage of computational modeling to consider different possibilities. In this work, we focus on hyperpolarization-activated channels (h-channels) in O-LM cells. While h-channels are known to be present in O-LM cells, it is unknown whether they are present on their dendrites. In previous work, we used ensemble modeling techniques with experimental data to obtain insights into potentially important conductance balances. We found that the best O-LM models that included uniformly distributed h-channels in the dendrites could not fully capture the “sag” response. This led us to examine activation kinetics and non-uniform distributions of h-channels in the present work. In tuning our models, we found that different kinetics and non-uniform distributions could better reproduce experimental O-LM cell responses. In contrast to CA1 pyramidal cells where higher conductance densities of h-channels occur in more distal dendrites, decreasing conductance densities of h-channels away from the soma were observed in O-LM models. Via an illustrative scenario, we showed that having dendritic h-channels clearly speeds up back-propagating action potentials in O-LM cells, unlike when h-channels are present only in the soma. Although the present results were morphology-dependent, our work shows that it should be possible to determine the distributions and characteristics of O-LM cells with recordings and morphologies from the same cell. We hypothesize that h-channels are distributed in O-LM cell dendrites and endow them with particular synaptic integration properties that shape information flow in hippocampus.
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Affiliation(s)
- Vladislav Sekulić
- Department of Fundamental Neurobiology, Toronto Western Research Institute, University Health Network Toronto, ON, Canada ; Department of Physiology, University of Toronto Toronto, ON, Canada
| | - Tse-Chiang Chen
- Department of Fundamental Neurobiology, Toronto Western Research Institute, University Health Network Toronto, ON, Canada
| | - J Josh Lawrence
- Center for Structural and Functional Neuroscience, University of Montana Missoula, MT, USA ; Department of Biomedical and Pharmaceutical Sciences, University of Montana Missoula, MT, USA
| | - Frances K Skinner
- Department of Fundamental Neurobiology, Toronto Western Research Institute, University Health Network Toronto, ON, Canada ; Department of Physiology, University of Toronto Toronto, ON, Canada ; Department of Medicine (Neurology), University of Toronto Toronto, ON, Canada
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Sekulić V, Lawrence JJ, Skinner FK. Using multi-compartment ensemble modeling as an investigative tool of spatially distributed biophysical balances: application to hippocampal oriens-lacunosum/moleculare (O-LM) cells. PLoS One 2014; 9:e106567. [PMID: 25360752 PMCID: PMC4215854 DOI: 10.1371/journal.pone.0106567] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2014] [Accepted: 07/30/2014] [Indexed: 01/15/2023] Open
Abstract
Multi-compartmental models of neurons provide insight into the complex, integrative properties of dendrites. Because it is not feasible to experimentally determine the exact density and kinetics of each channel type in every neuronal compartment, an essential goal in developing models is to help characterize these properties. To address biological variability inherent in a given neuronal type, there has been a shift away from using hand-tuned models towards using ensembles or populations of models. In collectively capturing a neuron's output, ensemble modeling approaches uncover important conductance balances that control neuronal dynamics. However, conductances are never entirely known for a given neuron class in terms of its types, densities, kinetics and distributions. Thus, any multi-compartment model will always be incomplete. In this work, our main goal is to use ensemble modeling as an investigative tool of a neuron's biophysical balances, where the cycling between experiment and model is a design criterion from the start. We consider oriens-lacunosum/moleculare (O-LM) interneurons, a prominent interneuron subtype that plays an essential gating role of information flow in hippocampus. O-LM cells express the hyperpolarization-activated current (Ih). Although dendritic Ih could have a major influence on the integrative properties of O-LM cells, the compartmental distribution of Ih on O-LM dendrites is not known. Using a high-performance computing cluster, we generated a database of models that included those with or without dendritic Ih. A range of conductance values for nine different conductance types were used, and different morphologies explored. Models were quantified and ranked based on minimal error compared to a dataset of O-LM cell electrophysiological properties. Co-regulatory balances between conductances were revealed, two of which were dependent on the presence of dendritic Ih. These findings inform future experiments that differentiate between somatic and dendritic Ih, thereby continuing a cycle between model and experiment.
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Affiliation(s)
- Vladislav Sekulić
- Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
- * E-mail:
| | - J. Josh Lawrence
- NIH COBRE Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana, United States of America
- Department of Biomedical and Pharmaceutical Sciences, University of Montana, Missoula, Montana, United States of America
| | - Frances K. Skinner
- Toronto Western Research Institute, University Health Network, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine (Neurology), University of Toronto, Toronto, Ontario, Canada
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15
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Weaver AL. The effects of interactions between intrinsic properties and network parameters on bilateral phasing in a reduced leech heartbeat system. BMC Neurosci 2014. [PMCID: PMC4125019 DOI: 10.1186/1471-2202-15-s1-p13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
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High prevalence of multistability of rest states and bursting in a database of a model neuron. PLoS Comput Biol 2013; 9:e1002930. [PMID: 23505348 PMCID: PMC3591289 DOI: 10.1371/journal.pcbi.1002930] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2012] [Accepted: 01/07/2013] [Indexed: 12/26/2022] Open
Abstract
Flexibility in neuronal circuits has its roots in the dynamical richness of their neurons. Depending on their membrane properties single neurons can produce a plethora of activity regimes including silence, spiking and bursting. What is less appreciated is that these regimes can coexist with each other so that a transient stimulus can cause persistent change in the activity of a given neuron. Such multistability of the neuronal dynamics has been shown in a variety of neurons under different modulatory conditions. It can play either a functional role or present a substrate for dynamical diseases. We considered a database of an isolated leech heart interneuron model that can display silent, tonic spiking and bursting regimes. We analyzed only the cases of endogenous bursters producing functional half-center oscillators (HCOs). Using a one parameter (the leak conductance ()) bifurcation analysis, we extended the database to include silent regimes (stationary states) and systematically classified cases for the coexistence of silent and bursting regimes. We showed that different cases could exhibit two stable depolarized stationary states and two hyperpolarized stationary states in addition to various spiking and bursting regimes. We analyzed all cases of endogenous bursters and found that 18% of the cases were multistable, exhibiting coexistences of stationary states and bursting. Moreover, 91% of the cases exhibited multistability in some range of . We also explored HCOs built of multistable neuron cases with coexisting stationary states and a bursting regime. In 96% of cases analyzed, the HCOs resumed normal alternating bursting after one of the neurons was reset to a stationary state, proving themselves robust against this perturbation. It is often not appreciated that different activity regimes can coexist with each other in a given neuron so that a transient stimulus can cause a persistent change of activity. Such multistability of the neuronal dynamics has in fact been shown in a variety of neurons and can play either a functional role or present a substrate for neurological diseases. We explored the propensity for multistability in a database of a leech heart interneuron model, testing each case (parameter set) in a database for multistability. We found a large proportion of multistable cases, especially the coexistence of silent and bursting regimes. This was a surprising result, since these cells pace the heartbeat of the leech, and the coexistence of silence and bursting could disrupt the functional pattern, threatening the viability of the leech. Analysis of networks of mutually inhibitory multistable neurons, however, showed robustness in maintaining functional activity, suggesting that the mutually inhibitory coupling can act as a protective mechanism against failures induced by multistability.
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Ritter P, Schirner M, McIntosh AR, Jirsa VK. The virtual brain integrates computational modeling and multimodal neuroimaging. Brain Connect 2013; 3:121-45. [PMID: 23442172 PMCID: PMC3696923 DOI: 10.1089/brain.2012.0120] [Citation(s) in RCA: 143] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Brain function is thought to emerge from the interactions among neuronal populations. Apart from traditional efforts to reproduce brain dynamics from the micro- to macroscopic scales, complementary approaches develop phenomenological models of lower complexity. Such macroscopic models typically generate only a few selected-ideally functionally relevant-aspects of the brain dynamics. Importantly, they often allow an understanding of the underlying mechanisms beyond computational reproduction. Adding detail to these models will widen their ability to reproduce a broader range of dynamic features of the brain. For instance, such models allow for the exploration of consequences of focal and distributed pathological changes in the system, enabling us to identify and develop approaches to counteract those unfavorable processes. Toward this end, The Virtual Brain (TVB) ( www.thevirtualbrain.org ), a neuroinformatics platform with a brain simulator that incorporates a range of neuronal models and dynamics at its core, has been developed. This integrated framework allows the model-based simulation, analysis, and inference of neurophysiological mechanisms over several brain scales that underlie the generation of macroscopic neuroimaging signals. In this article, we describe how TVB works, and we present the first proof of concept.
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Affiliation(s)
- Petra Ritter
- Minerva Research Group Brain Modes, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.
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18
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Skinner FK. Cellular-based modeling of oscillatory dynamics in brain networks. Curr Opin Neurobiol 2012; 22:660-9. [DOI: 10.1016/j.conb.2012.02.001] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2011] [Revised: 01/23/2012] [Accepted: 02/05/2012] [Indexed: 11/27/2022]
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Sekulic V, Lawrence J, Skinner FK. Using model databases to determine dendritic distributions of Ih channels in oriens-lacunosum/moleculare hippocampal interneurons. BMC Neurosci 2012. [PMCID: PMC3403241 DOI: 10.1186/1471-2202-13-s1-p41] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Affiliation(s)
- Vladislav Sekulic
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada, M5S 1A8,Toronto, Western Research Institute, University Health Network, Toronto, Ontario, Canada, M5T 2S8
| | - Josh Lawrence
- Department of Biomedical and Pharmaceutical Sciences, University of Montana, Missoula, Montana 59812, USA,NIH COBRE Center for Structural and Functional Neuroscience, University of Montana, Missoula, Montana 59812, USA
| | - Frances K Skinner
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada, M5S 1A8,Toronto, Western Research Institute, University Health Network, Toronto, Ontario, Canada, M5T 2S8,Departments of Medicine (Neurology), Physiology, and IBBME, University of Toronto, Toronto, Ontario, Canada
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Mahmud M, Bertoldo A, Girardi S, Maschietto M, Vassanelli S. SigMate: a Matlab-based automated tool for extracellular neuronal signal processing and analysis. J Neurosci Methods 2012; 207:97-112. [PMID: 22513383 DOI: 10.1016/j.jneumeth.2012.03.009] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2011] [Revised: 03/20/2012] [Accepted: 03/21/2012] [Indexed: 11/19/2022]
Abstract
Rapid advances in neuronal probe technology for multisite recording of brain activity have posed a significant challenge to neuroscientists for processing and analyzing the recorded signals. To be able to infer meaningful conclusions quickly and accurately from large datasets, automated and sophisticated signal processing and analysis tools are required. This paper presents a Matlab-based novel tool, "SigMate", incorporating standard methods to analyze spikes and EEG signals, and in-house solutions for local field potentials (LFPs) analysis. Available modules at present are - 1. In-house developed algorithms for: data display (2D and 3D), file operations (file splitting, file concatenation, and file column rearranging), baseline correction, slow stimulus artifact removal, noise characterization and signal quality assessment, current source density (CSD) analysis, latency estimation from LFPs and CSDs, determination of cortical layer activation order using LFPs and CSDs, and single LFP clustering; 2. Existing modules: spike detection, sorting and spike train analysis, and EEG signal analysis. SigMate has the flexibility of analyzing multichannel signals as well as signals from multiple recording sources. The in-house developed tools for LFP analysis have been extensively tested with signals recorded using standard extracellular recording electrode, and planar and implantable multi transistor array (MTA) based neural probes. SigMate will be disseminated shortly to the neuroscience community under the open-source GNU-General Public License.
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Affiliation(s)
- Mufti Mahmud
- NeuroChip Laboratory, Department of Human Anatomy and Physiology, University of Padova, via f. Marzolo 3, 35131 Padova, Italy
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Abstract
Databases are, at their core, abstractions of data and their intentionally derived relationships. They serve as a central organizing metaphor and repository, supporting or augmenting nearly all bioinformatics. Behavioral domains provide a unique stage for contemporary databases, as research in this area spans diverse data types, locations, and data relationships. This chapter provides foundational information on the diversity and prevalence of databases, how data structures support the various needs of behavioral neuroscience analysis and interpretation. The focus is on the classes of databases, data curation, and advanced applications in bioinformatics using examples largely drawn from research efforts in behavioral neuroscience.
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Roffman RC, Norris BJ, Calabrese RL. Animal-to-animal variability of connection strength in the leech heartbeat central pattern generator. J Neurophysiol 2011; 107:1681-93. [PMID: 22190622 DOI: 10.1152/jn.00903.2011] [Citation(s) in RCA: 76] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
The heartbeat central pattern generator (CPG) in medicinal leeches controls blood flow within a closed circulatory by programming the constrictions of two parallel heart tubes. This circuit reliably produces a stereotyped fictive pattern of activity and has been extensively characterized. Here we determined, as quantitatively as possible, the strength of each inhibitory synapse and electrical junction within the core circuit of the heartbeat CPG. We also examined the animal-to-animal variability in strengths of these connections and, for some, determined the correlations between connections to the same postsynaptic target. The core CPG is composed of seven bilateral pairs of heart interneurons connected via both inhibitory chemical synapses and electrical junctions. Fifteen different connections within the core CPG were measured for strength using extracellular presynaptic recordings and postsynaptic voltage-clamp recordings across a minimum of seven individuals each, and the animal-to-animal variability was characterized. Connection strengths within the core network varied three to more than sevenfold among individuals (depending on the specific connection). The balance between two inputs onto various postsynaptic targets was explored by within-individual comparisons and correlation across individuals. Of the seven comparisons made within the core CPG, three showed a clear correlation of connection strengths, while the other four did not. We conclude that the leech heartbeat CPG can withstand wide variability in connection strengths and still produce stereotyped output. The network appears to preserve the relative strengths of some pairs of inputs, despite the animal-to-animal variability.
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Affiliation(s)
- Rebecca C Roffman
- Department of Biology, Emory University, Atlanta, Georgia 30322, USA
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Botta P, Simões de Souza FM, Sangrey T, De Schutter E, Valenzuela CF. Excitation of rat cerebellar Golgi cells by ethanol: further characterization of the mechanism. Alcohol Clin Exp Res 2011; 36:616-24. [PMID: 22004123 DOI: 10.1111/j.1530-0277.2011.01658.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
BACKGROUND Studies with rodents suggest that acute ethanol exposure impairs information flow through the cerebellar cortex, in part, by increasing GABAergic input to granule cells. Experiments suggest that an increase in the excitability of specialized GABAergic interneurons that regulate granule cell activity (i.e., Golgi cells [GoCs]) contributes to this effect. In GoCs, ethanol increases spontaneous action potential firing frequency, decreases the afterhyperpolarization amplitude, and depolarizes the membrane potential. Studies suggest that these effects could be mediated by inhibition of the Na(+)/K(+) ATPase. The purpose of this study was to characterize the potential role of other GoC conductances in the mechanism of action of ethanol. METHODS Computer modeling techniques and patch-clamp electrophysiological recordings with acute slices from rat cerebella were used for these studies. RESULTS Computer modeling suggested that modulation of subthreshold Na(+) channels, hyperpolarization-activated currents, and several K(+) conductances could explain some but not all actions of ethanol on GoCs. Electrophysiological studies did not find evidence consistent with a contribution of these conductances. Quinidine, a nonselective blocker of several types of channels (including several K(+) channels) that also antagonizes the Na(+)/K(+) ATPase, reduced the effect of ethanol on GoC firing. CONCLUSIONS These findings further support that ethanol increases GoC excitability via modulation of the Na(+)/K(+) ATPase and suggest that a quinidine-sensitive K(+) channel may also play a role in the mechanism of action of ethanol.
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Affiliation(s)
- Paolo Botta
- Department of Neurosciences, School of Medicine, University of New Mexico Health Sciences Center, Albuquerque, USA
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Doloc-Mihu A, Calabrese RL. A database of computational models of a half-center oscillator for analyzing how neuronal parameters influence network activity. J Biol Phys 2011; 37:263-83. [PMID: 22654177 PMCID: PMC3101324 DOI: 10.1007/s10867-011-9215-y] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2010] [Accepted: 01/06/2011] [Indexed: 11/30/2022] Open
Abstract
A half-center oscillator (HCO) is a common circuit building block of central pattern generator networks that produce rhythmic motor patterns in animals. Here we constructed an efficient relational database table with the resulting characteristics of the Hill et al.'s (J Comput Neurosci 10:281-302, 2001) HCO simple conductance-based model. The model consists of two reciprocally inhibitory neurons and replicates the electrical activity of the oscillator interneurons of the leech heartbeat central pattern generator under a variety of experimental conditions. Our long-range goal is to understand how this basic circuit building block produces functional activity under a variety of parameter regimes and how different parameter regimes influence stability and modulatability. By using the latest developments in computer technology, we simulated and stored large amounts of data (on the order of terabytes). We systematically explored the parameter space of the HCO and corresponding isolated neuron models using a brute-force approach. We varied a set of selected parameters (maximal conductance of intrinsic and synaptic currents) in all combinations, resulting in about 10 million simulations. We classified these HCO and isolated neuron model simulations by their activity characteristics into identifiable groups and quantified their prevalence. By querying the database, we compared the activity characteristics of the identified groups of our simulated HCO models with those of our simulated isolated neuron models and found that regularly bursting neurons compose only a small minority of functional HCO models; the vast majority was composed of spiking neurons.
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Affiliation(s)
- Anca Doloc-Mihu
- Department of Biology, Emory University, Atlanta, GA 30322 USA
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Günay C, Prinz AA. Model calcium sensors for network homeostasis: sensor and readout parameter analysis from a database of model neuronal networks. J Neurosci 2010; 30:1686-98. [PMID: 20130178 PMCID: PMC2851246 DOI: 10.1523/jneurosci.3098-09.2010] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2009] [Revised: 10/09/2009] [Accepted: 12/05/2009] [Indexed: 11/21/2022] Open
Abstract
In activity-dependent homeostatic regulation (ADHR) of neuronal and network properties, the intracellular Ca(2+) concentration is a good candidate for sensing activity levels because it is correlated with the electrical activity of the cell. Previous ADHR models, developed with abstract activity sensors for model pyloric neurons and networks of the crustacean stomatogastric ganglion, showed that functional activity can be maintained by a regulation mechanism that senses activity levels solely from Ca(2+). At the same time, several intracellular pathways have been discovered for Ca(2+)-dependent regulation of ion channels. To generate testable predictions for dynamics of these signaling pathways, we undertook a parameter study of model Ca(2+) sensors across thousands of model pyloric networks. We found that an optimal regulation signal can be generated for 86% of model networks with a sensing mechanism that activates with a time constant of 1 ms and that inactivates within 1 s. The sensor performed robustly around this optimal point and did not need to be specific to the role of the cell. When multiple sensors with different time constants were used, coverage extended to 88% of the networks. Without changing the sensors, it extended to 95% of the networks by letting the sensors affect the readout nonlinearly. Specific to this pyloric network model, the sensor of the follower pyloric constrictor cell was more informative than the pacemaker anterior burster cell for producing a regulatory signal. Conversely, a global signal indicating network activity that was generated by summing the sensors in individual cells was less informative for regulation.
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Affiliation(s)
- Cengiz Günay
- Department of Biology, Emory University, Atlanta, Georgia 30322, USA.
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