1
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Ren X, Bok I, Vareberg A, Hai A. Stimulation-mediated reverse engineering of silent neural networks. J Neurophysiol 2023; 129:1505-1514. [PMID: 37222450 PMCID: PMC10311990 DOI: 10.1152/jn.00100.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Revised: 05/16/2023] [Accepted: 05/23/2023] [Indexed: 05/25/2023] Open
Abstract
Reconstructing connectivity of neuronal networks from single-cell activity is essential to understanding brain function, but the challenge of deciphering connections from populations of silent neurons has been largely unmet. We demonstrate a protocol for deriving connectivity of simulated silent neuronal networks using stimulation combined with a supervised learning algorithm, which enables inferring connection weights with high fidelity and predicting spike trains at the single-spike and single-cell levels with high accuracy. We apply our method on rat cortical recordings fed through a circuit of heterogeneously connected leaky integrate-and-fire neurons firing at typical lognormal distributions and demonstrate improved performance during stimulation for multiple subpopulations. These testable predictions about the number and protocol of the required stimulations are expected to enhance future efforts for deriving neuronal connectivity and drive new experiments to better understand brain function.NEW & NOTEWORTHY We introduce a new concept for reverse engineering silent neuronal networks using a supervised learning algorithm combined with stimulation. We quantify the performance of the algorithm and the precision of deriving synaptic weights in inhibitory and excitatory subpopulations. We then show that stimulation enables deciphering connectivity of heterogeneous circuits fed with real electrode array recordings, which could extend in the future to deciphering connectivity in broad biological and artificial neural networks.
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Affiliation(s)
- Xiaoxuan Ren
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
- Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
| | - Ilhan Bok
- Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
| | - Adam Vareberg
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
| | - Aviad Hai
- Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
- Department of Electrical and Computer Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States
- Wisconsin Institute for Translational Neuroengineering (WITNe), Madison, Wisconsin, United States
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2
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Xue X, Buccino AP, Saseendran Kumar S, Hierlemann A, Bartram J. Inferring monosynaptic connections from paired dendritic spine Ca 2+imaging and large-scale recording of extracellular spiking. J Neural Eng 2022; 19. [PMID: 35931040 DOI: 10.1088/1741-2552/ac8765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 08/05/2022] [Indexed: 11/12/2022]
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 onin vitrorecordings. 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 asi) 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, andiii) 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.
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Affiliation(s)
- Xiaohan Xue
- D-BSSE, ETH Zürich, Mattenstrasse 26, Basel, 4058, SWITZERLAND
| | | | | | | | - Julian Bartram
- D-BSSE, ETH Zürich, Mattenstrasse 26, Basel, 4058, SWITZERLAND
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3
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Endo D, Kobayashi R, Bartolo R, Averbeck BB, Sugase-Miyamoto Y, Hayashi K, Kawano K, Richmond BJ, Shinomoto S. A convolutional neural network for estimating synaptic connectivity from spike trains. Sci Rep 2021; 11:12087. [PMID: 34103546 PMCID: PMC8187444 DOI: 10.1038/s41598-021-91244-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 05/21/2021] [Indexed: 02/05/2023] Open
Abstract
The recent increase in reliable, simultaneous high channel count extracellular recordings is exciting for physiologists and theoreticians because it offers the possibility of reconstructing the underlying neuronal circuits. We recently presented a method of inferring this circuit connectivity from neuronal spike trains by applying the generalized linear model to cross-correlograms. Although the algorithm can do a good job of circuit reconstruction, the parameters need to be carefully tuned for each individual dataset. Here we present another method using a Convolutional Neural Network for Estimating synaptic Connectivity from spike trains. After adaptation to huge amounts of simulated data, this method robustly captures the specific feature of monosynaptic impact in a noisy cross-correlogram. There are no user-adjustable parameters. With this new method, we have constructed diagrams of neuronal circuits recorded in several cortical areas of monkeys.
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Affiliation(s)
- Daisuke Endo
- Graduate School of Informatics, Kyoto University, Kyoto, 606-8501, Japan
| | - Ryota Kobayashi
- Mathematics and Informatics Center, The University of Tokyo, Tokyo, 113-8656, Japan
- Department of Complexity Science and Engineering, The University of Tokyo, Chiba, 277-8561, Japan
- JST, PRESTO, Saitama, 332-0012, Japan
| | - Ramon Bartolo
- Laboratory of Neuropsychology, NIMH/NIH/DHHS, Bethesda, MD, 20814, USA
| | - Bruno B Averbeck
- Laboratory of Neuropsychology, NIMH/NIH/DHHS, Bethesda, MD, 20814, USA
| | - Yasuko Sugase-Miyamoto
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, 305-8568, Japan
| | - Kazuko Hayashi
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, 305-8568, Japan
- Japan Society for the Promotion of Science, Tokyo, 102-0083, Japan
| | - Kenji Kawano
- Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba, 305-8568, Japan
| | - Barry J Richmond
- Laboratory of Neuropsychology, NIMH/NIH/DHHS, Bethesda, MD, 20814, USA
| | - Shigeru Shinomoto
- Graduate School of Informatics, Kyoto University, Kyoto, 606-8501, Japan.
- Brain Information Communication Research Laboratory Group, ATR Institute International, Kyoto, 619-0288, Japan.
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4
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Inhibitory neurons exhibit high controlling ability in the cortical microconnectome. PLoS Comput Biol 2021; 17:e1008846. [PMID: 33831009 PMCID: PMC8031186 DOI: 10.1371/journal.pcbi.1008846] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Accepted: 03/01/2021] [Indexed: 02/08/2023] Open
Abstract
The brain is a network system in which excitatory and inhibitory neurons keep activity balanced in the highly non-random connectivity pattern of the microconnectome. It is well known that the relative percentage of inhibitory neurons is much smaller than excitatory neurons in the cortex. So, in general, how inhibitory neurons can keep the balance with the surrounding excitatory neurons is an important question. There is much accumulated knowledge about this fundamental question. This study quantitatively evaluated the relatively higher functional contribution of inhibitory neurons in terms of not only properties of individual neurons, such as firing rate, but also in terms of topological mechanisms and controlling ability on other excitatory neurons. We combined simultaneous electrical recording (~2.5 hours) of ~1000 neurons in vitro, and quantitative evaluation of neuronal interactions including excitatory-inhibitory categorization. This study accurately defined recording brain anatomical targets, such as brain regions and cortical layers, by inter-referring MRI and immunostaining recordings. The interaction networks enabled us to quantify topological influence of individual neurons, in terms of controlling ability to other neurons. Especially, the result indicated that highly influential inhibitory neurons show higher controlling ability of other neurons than excitatory neurons, and are relatively often distributed in deeper layers of the cortex. Furthermore, the neurons having high controlling ability are more effectively limited in number than central nodes of k-cores, and these neurons also participate in more clustered motifs. In summary, this study suggested that the high controlling ability of inhibitory neurons is a key mechanism to keep balance with a large number of other excitatory neurons beyond simple higher firing rate. Application of the selection method of limited important neurons would be also applicable for the ability to effectively and selectively stimulate E/I imbalanced disease states. How small numbers of inhibitory neurons functionally keep balance with large numbers of excitatory neurons in the brain by controlling each other is a fundamental question. Especially, this study quantitatively evaluated a topological mechanism of interaction networks in terms of controlling abilities of individual cortical neurons to other neurons. Combination of simultaneous electrical recording of ~1000 neurons and a quantitative evaluation method of neuronal interactions including excitatory-inhibitory categories, enabled us to evaluate the influence of individual neurons not only about firing rate but also about their relative positions in the networks and controllable ability of other neurons. Especially, the result showed that inhibitory neurons have more controlling ability than excitatory neurons, and such neurons were more often observed in deep layers. Because the limited number of neurons in terms controlling ability were much smaller than neurons based on centrality measure and, of course, more directly selected neurons based on their ability to control other neurons, the selection method of important neurons will help not only to produce realistic computational models but also will help to stimulate brain to effectively treat imbalanced disease states.
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5
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Iwase M, Kitanishi T, Mizuseki K. Cell type, sub-region, and layer-specific speed representation in the hippocampal-entorhinal circuit. Sci Rep 2020; 10:1407. [PMID: 31996750 PMCID: PMC6989659 DOI: 10.1038/s41598-020-58194-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 01/13/2020] [Indexed: 12/15/2022] Open
Abstract
It has been hypothesised that speed information, encoded by ‘speed cells’, is important for updating spatial representation in the hippocampus and entorhinal cortex to reflect ongoing self-movement during locomotion. However, systematic characterisation of speed representation is still lacking. In this study, we compared the speed representation of distinct cell types across sub-regions/layers in the dorsal hippocampus and medial entorhinal cortex of rats during exploration. Our results indicate that the preferred theta phases of individual neurons are correlated with positive/negative speed modulation and a temporal shift of speed representation in a sub-region/layer and cell type-dependent manner. Most speed cells located in entorhinal cortex layer 2 represented speed prospectively, whereas those in the CA1 and entorhinal cortex layers 3 and 5 represented speed retrospectively. In entorhinal cortex layer 2, putative CA1-projecting pyramidal cells, but not putative dentate gyrus/CA3-projecting stellate cells, represented speed prospectively. Among the hippocampal interneurons, approximately one-third of putative dendrite-targeting (somatostatin-expressing) interneurons, but only a negligible fraction of putative soma-targeting (parvalbumin-expressing) interneurons, showed negative speed modulation. Putative parvalbumin-expressing CA1 interneurons and somatostatin-expressing CA3 interneurons represented speed more retrospectively than parvalbumin-expressing CA3 interneurons. These findings indicate that speed representation in the hippocampal-entorhinal circuit is cell-type, pathway, and theta-phase dependent.
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Affiliation(s)
- Motosada Iwase
- Department of Physiology, Osaka City University Graduate School of Medicine, Osaka, 545-8585, Japan
| | - Takuma Kitanishi
- Department of Physiology, Osaka City University Graduate School of Medicine, Osaka, 545-8585, Japan.,PRESTO, Japan Science and Technology Agency, Kawaguchi, Saitama, 332-0012, Japan
| | - Kenji Mizuseki
- Department of Physiology, Osaka City University Graduate School of Medicine, Osaka, 545-8585, Japan. .,Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, NJ, 07102, USA.
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6
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Kobayashi R, Kurita S, Kurth A, Kitano K, Mizuseki K, Diesmann M, Richmond BJ, Shinomoto S. Reconstructing neuronal circuitry from parallel spike trains. Nat Commun 2019; 10:4468. [PMID: 31578320 PMCID: PMC6775109 DOI: 10.1038/s41467-019-12225-2] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 08/27/2019] [Indexed: 11/23/2022] Open
Abstract
State-of-the-art techniques allow researchers to record large numbers of spike trains in parallel for many hours. With enough such data, we should be able to infer the connectivity among neurons. Here we develop a method for reconstructing neuronal circuitry by applying a generalized linear model (GLM) to spike cross-correlations. Our method estimates connections between neurons in units of postsynaptic potentials and the amount of spike recordings needed to verify connections. The performance of inference is optimized by counting the estimation errors using synthetic data. This method is superior to other established methods in correctly estimating connectivity. By applying our method to rat hippocampal data, we show that the types of estimated connections match the results inferred from other physiological cues. Thus our method provides the means to build a circuit diagram from recorded spike trains, thereby providing a basis for elucidating the differences in information processing in different brain regions. Current techniques have enabled the simultaneous collection of spike train data from large numbers of neurons. Here, the authors report a method to infer the underlying neural circuit connectivity diagram based on a generalized linear model applied to spike cross-correlations between neurons.
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Affiliation(s)
- Ryota Kobayashi
- National Institute of Informatics, Tokyo, 101-8430, Japan.,Department of Informatics, SOKENDAI (The Graduate University for Advanced Studies), Tokyo, 101-8430, Japan
| | - Shuhei Kurita
- Center for Advanced Intelligence Project, RIKEN, Tokyo, 103-0027, Japan
| | - Anno Kurth
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, 52425, Jülich, Germany.,Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany
| | - Katsunori Kitano
- Department of Information Science and Engineering, Ritsumeikan University, Kusatsu, 525-8577, Japan
| | - Kenji Mizuseki
- Department of Physiology, Osaka City University Graduate School of Medicine, Osaka, 545-8585, Japan
| | - Markus Diesmann
- Institute of Neuroscience and Medicine (INM-6) and Institute for Advanced Simulation (IAS-6) and JARA-Institute Brain Structure-Function Relationships (INM-10), Jülich Research Centre, 52425, Jülich, Germany.,Department of Physics, Faculty 1, RWTH Aachen University, Aachen, Germany.,Department of Psychiatry, Psychotherapy and Psychosomatics, School of Medicine, RWTH Aachen University, Aachen, Germany
| | - Barry J Richmond
- Laboratory of Neuropsychology, NIMH/NIH/DHHS, Bethesda, MD, 20814, USA
| | - Shigeru Shinomoto
- Department of Physics, Kyoto University, Kyoto, 606-8502, Japan. .,Brain Information Communication Research Laboratory Group, ATR Institute International, Kyoto, 619-0288, Japan.
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7
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Electrophysiological monitoring of inhibition in mammalian species, from rodents to humans. Neurobiol Dis 2019; 130:104500. [PMID: 31195126 DOI: 10.1016/j.nbd.2019.104500] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2018] [Revised: 05/31/2019] [Accepted: 06/06/2019] [Indexed: 01/20/2023] Open
Abstract
GABAergic interneurons constitute a highly diverse family of neurons that play a critical role in cortical functions. Due to their prominent role in cortical network dynamics, genetic, developmental, or other dysfunctions in GABAergic neurons have been linked to neurological disorders such as epilepsy. Thus, it is crucial to investigate the interaction of these various neurons and to develop methods to specifically and directly monitor inhibitory activity in vivo. While research in small mammals has benefited from a wealth of recent technological development, bridging the gap to large mammals and humans remains a challenge. This is of particular interest since single neuron monitoring with intracranial electrodes in epileptic patients is developing quickly, opening new avenues for understanding the role of different cell types in epilepsy. Here, we review currently available techniques that monitor inhibitory activity in the brain and the respective validations in rodents. Finally, we discuss the future developments of these techniques and how knowledge from animal research can be translated to the study of neuronal circuit dynamics in the human brain.
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8
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Senzai Y, Fernandez-Ruiz A, Buzsáki G. Layer-Specific Physiological Features and Interlaminar Interactions in the Primary Visual Cortex of the Mouse. Neuron 2019; 101:500-513.e5. [PMID: 30635232 PMCID: PMC6367010 DOI: 10.1016/j.neuron.2018.12.009] [Citation(s) in RCA: 134] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2018] [Revised: 11/27/2018] [Accepted: 12/04/2018] [Indexed: 12/01/2022]
Abstract
The relationship between mesoscopic local field potentials (LFPs) and single-neuron firing in the multi-layered neocortex is poorly understood. Simultaneous recordings from all layers in the primary visual cortex (V1) of the behaving mouse revealed functionally defined layers in V1. The depth of maximum spike power and sink-source distributions of LFPs provided consistent laminar landmarks across animals. Coherence of gamma oscillations (30-100 Hz) and spike-LFP coupling identified six physiological layers and further sublayers. Firing rates, burstiness, and other electrophysiological features of neurons displayed unique layer and brain state dependence. Spike transmission strength from layer 2/3 cells to layer 5 pyramidal cells and interneurons was stronger during waking compared with non-REM sleep but stronger during non-REM sleep among deep-layer excitatory neurons. A subset of deep-layer neurons was active exclusively in the DOWN state of non-REM sleep. These results bridge mesoscopic LFPs and single-neuron interactions with laminar structure in V1.
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Affiliation(s)
- Yuta Senzai
- Neuroscience Institute, New York University, Langone Medical Center, New York, NY 10016, USA
| | - Antonio Fernandez-Ruiz
- Neuroscience Institute, New York University, Langone Medical Center, New York, NY 10016, USA
| | - György Buzsáki
- Neuroscience Institute, New York University, Langone Medical Center, New York, NY 10016, USA; Department of Neurology, Langone Medical Center, New York University, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA.
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9
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Bermudez-Contreras E, Chekhov S, Sun J, Tarnowsky J, McNaughton BL, Mohajerani MH. High-performance, inexpensive setup for simultaneous multisite recording of electrophysiological signals and mesoscale voltage imaging in the mouse cortex. NEUROPHOTONICS 2018; 5:025005. [PMID: 29651448 PMCID: PMC5874445 DOI: 10.1117/1.nph.5.2.025005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/21/2017] [Accepted: 03/05/2018] [Indexed: 05/17/2023]
Abstract
Simultaneous recording of optical and electrophysiological signals from multiple cortical areas may provide crucial information to expand our understanding of cortical function. However, the insertion of multiple electrodes into the brain may compromise optical imaging by both restricting the field of view and interfering with the approaches used to stabilize the specimen. Existing methods that combine electrophysiological recording and optical imaging in vivo implement either multiple surface electrodes, silicon probes, or a single electrode for deeper recordings. To address such limitation, we built a microelectrode array (hyperdrive, patent US5928143 A) compatible with wide-field imaging that allows insertion of up to 12 probes into a large brain area (8 mm diameter). The hyperdrive is comprised of a circle of individual microdrives where probes are positioned at an angle leaving a large brain area unobstructed for wide-field imaging. Multiple tetrodes and voltage-sensitive dye imaging were used for acute simultaneous registration of spontaneous and evoked cortical activity in anesthetized mice. The electrophysiological signals were used to extract local field potential (LFP) traces, multiunit, and single-unit spiking activity. To demonstrate our approach, we compared LFP and VSD signals over multiple regions of the cortex and analyzed the relationship between single-unit and global cortical population activities. The study of the interactions between cortical activity at local and global scales, such as the one presented in this work, can help to expand our knowledge of brain function.
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Affiliation(s)
- Edgar Bermudez-Contreras
- University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, Lethbridge, Alberta, Canada
| | - Sergey Chekhov
- University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, Lethbridge, Alberta, Canada
| | - Jianjun Sun
- University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, Lethbridge, Alberta, Canada
| | - Jennifer Tarnowsky
- University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, Lethbridge, Alberta, Canada
| | - Bruce L. McNaughton
- University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, Lethbridge, Alberta, Canada
- University of California at Irvine, Center for the Neurobiology of Learning and Memory, Department of Neurobiology and Behavior, Irvine, California, United States
- Address all correspondence to: Bruce L. McNaughton, E-mail: ; Majid H. Mohajerani, E-mail:
| | - Majid H. Mohajerani
- University of Lethbridge, Canadian Centre for Behavioural Neuroscience, Department of Neuroscience, Lethbridge, Alberta, Canada
- Address all correspondence to: Bruce L. McNaughton, E-mail: ; Majid H. Mohajerani, E-mail:
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10
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Tavoni G, Ferrari U, Battaglia FP, Cocco S, Monasson R. Functional coupling networks inferred from prefrontal cortex activity show experience-related effective plasticity. Netw Neurosci 2017; 1:275-301. [PMID: 29855621 PMCID: PMC5874136 DOI: 10.1162/netn_a_00014] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 04/24/2017] [Indexed: 01/28/2023] Open
Abstract
Functional coupling networks are widely used to characterize collective patterns of activity in neural populations. Here, we ask whether functional couplings reflect the subtle changes, such as in physiological interactions, believed to take place during learning. We infer functional network models reproducing the spiking activity of simultaneously recorded neurons in prefrontal cortex (PFC) of rats, during the performance of a cross-modal rule shift task (task epoch), and during preceding and following sleep epochs. A large-scale study of the 96 recorded sessions allows us to detect, in about 20% of sessions, effective plasticity between the sleep epochs. These coupling modifications are correlated with the coupling values in the task epoch, and are supported by a small subset of the recorded neurons, which we identify by means of an automatized procedure. These potentiated groups increase their coativation frequency in the spiking data between the two sleep epochs, and, hence, participate to putative experience-related cell assemblies. Study of the reactivation dynamics of the potentiated groups suggests a possible connection with behavioral learning. Reactivation is largely driven by hippocampal ripple events when the rule is not yet learned, and may be much more autonomous, and presumably sustained by the potentiated PFC network, when learning is consolidated. Cell assemblies coding for memories are widely believed to emerge through synaptic modification resulting from learning, yet their identification from activity is very arduous. We propose a functional-connectivity-based approach to identify experience-related cell assemblies from multielectrode recordings in vivo, and apply it to the prefrontal cortex activity of rats recorded during a task epoch and the preceding and following sleep epochs. We infer functional couplings between the recorded cells in each epoch. Comparisons of the functional coupling networks across the epochs allow us to identify effective potentiation between the two sleep epochs. The neurons supporting these potentiated interactions strongly coactivate during the task and subsequent sleep epochs, but not in the preceding sleep, and, hence, presumably belong to an experience-related cell assembly. Study of the reactivation of this assembly in response to hippocampal ripple inputs suggests possible relations between the stage of behavorial learning and memory consolidation mechanisms.
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Affiliation(s)
- Gaia Tavoni
- Laboratoire de Physique Statistique, Ecole Normale Supérieure, PSL Research and CNRS - UMR 8550, Paris Sorbonne UPMC, Paris, France.,Laboratoire de Physique Théorique, Ecole Normale Supérieure, PSL Research and CNRS- UMR 8549, Paris Sorbonne UPMC, Paris, France
| | - Ulisse Ferrari
- Laboratoire de Physique Statistique, Ecole Normale Supérieure, PSL Research and CNRS - UMR 8550, Paris Sorbonne UPMC, Paris, France.,Laboratoire de Physique Théorique, Ecole Normale Supérieure, PSL Research and CNRS- UMR 8549, Paris Sorbonne UPMC, Paris, France
| | - Francesco P Battaglia
- Donders Institute for Brain, Cognition and Behaviour, Radboud Universiteit, Nijmegen, The Netherlands
| | - Simona Cocco
- Laboratoire de Physique Statistique, Ecole Normale Supérieure, PSL Research and CNRS - UMR 8550, Paris Sorbonne UPMC, Paris, France
| | - Rémi Monasson
- Laboratoire de Physique Théorique, Ecole Normale Supérieure, PSL Research and CNRS- UMR 8549, Paris Sorbonne UPMC, Paris, France
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11
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Neumann AR, Raedt R, Steenland HW, Sprengers M, Bzymek K, Navratilova Z, Mesina L, Xie J, Lapointe V, Kloosterman F, Vonck K, Boon PAJM, Soltesz I, McNaughton BL, Luczak A. Involvement of fast-spiking cells in ictal sequences during spontaneous seizures in rats with chronic temporal lobe epilepsy. Brain 2017; 140:2355-2369. [PMID: 29050390 PMCID: PMC6248724 DOI: 10.1093/brain/awx179] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2017] [Revised: 05/25/2017] [Accepted: 06/08/2017] [Indexed: 11/14/2022] Open
Abstract
See Lenck-Santini (doi:10.1093/awx205) for a scientific commentary on this article. Epileptic seizures represent altered neuronal network dynamics, but the temporal evolution and cellular substrates of the neuronal activity patterns associated with spontaneous seizures are not fully understood. We used simultaneous recordings from multiple neurons in the hippocampus and neocortex of rats with chronic temporal lobe epilepsy to demonstrate that subsets of cells discharge in a highly stereotypical sequential pattern during ictal events, and that these stereotypical patterns were reproducible across consecutive seizures. In contrast to the canonical view that principal cell discharges dominate ictal events, the ictal sequences were predominantly composed of fast-spiking, putative inhibitory neurons, which displayed unusually strong coupling to local field potential even before seizures. The temporal evolution of activity was characterized by unique dynamics where the most correlated neuronal pairs before seizure onset displayed the largest increases in correlation strength during the seizures. These results demonstrate the selective involvement of fast spiking interneurons in structured temporal sequences during spontaneous ictal events in hippocampal and neocortical circuits in experimental models of chronic temporal lobe epilepsy.
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Affiliation(s)
- Adam R Neumann
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
| | - Robrecht Raedt
- Department of Neurology, Ghent University, Gent, Belgium
| | - Hendrik W Steenland
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
| | | | - Katarzyna Bzymek
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
| | - Zaneta Navratilova
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
- Neuro-Electronics Research Flanders, Leuven, Belgium
| | - Lilia Mesina
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
| | - Jeanne Xie
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
| | - Valerie Lapointe
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
| | - Fabian Kloosterman
- Neuro-Electronics Research Flanders, Leuven, Belgium
- VIB, Leuven, Belgium
- Brain and Cognition Research unit, KU Leuven, Leuven, Belgium
| | - Kristl Vonck
- Department of Neurology, Ghent University, Gent, Belgium
| | | | - Ivan Soltesz
- Department of Neurosurgery, and Stanford Neurosciences Institute,
Stanford University, Stanford, CA, USA
| | - Bruce L McNaughton
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
- Department of Neurobiology and Behavior, University of California at
Irvine, Center for the Neurobiology of Learning and Memory, Irvine, CA, USA
| | - Artur Luczak
- Department of Neuroscience, Canadian Centre for Behavioural
Neuroscience, University of Lethbridge, 4401 University Dr W, Lethbridge, AB, T1K 3M4,
Canada
- Department of Neurosurgery, and Stanford Neurosciences Institute,
Stanford University, Stanford, CA, USA
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12
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Mizuseki K, Miyawaki H. Hippocampal information processing across sleep/wake cycles. Neurosci Res 2017; 118:30-47. [DOI: 10.1016/j.neures.2017.04.018] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2016] [Revised: 03/11/2017] [Accepted: 03/27/2017] [Indexed: 01/24/2023]
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13
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Sorensen J, Wiklendt L, Hibberd T, Costa M, Spencer NJ. Techniques to identify and temporally correlate calcium transients between multiple regions of interest in vertebrate neural circuits. J Neurophysiol 2016; 117:885-902. [PMID: 27903638 DOI: 10.1152/jn.00648.2016] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Accepted: 11/25/2016] [Indexed: 11/22/2022] Open
Abstract
Calcium imaging is commonly used to record dynamic changes in excitability from axons or cell bodies in the nervous system of vertebrates. These recordings often reveal discrete calcium transients that have variable amplitudes, durations, and rates of rise and decay, all of which can arise from an unstable or "noisy" baseline. This often leads to considerable ambiguity about how to discriminate and quantify calcium transients. We describe an analytical methodology that objectively identifies multiple calcium transients from multiple recording sites and quantifies the degree of temporal synchrony between each event. The methodology consists of multiple steps. The first step involves baselining, to either preserve the underlying shape of calcium transients or remove unwanted frequency components and transform the peaks of calcium transients into more easily detectable patterns. The second step is the application of at least one of two different spike detection algorithms, one based on a gradient estimate and the other on template matching. The third step is the quantification of synchrony between pairs of recordings using at least one of two time lag correlation measures. The fourth step is the identification of statistically significant coincident firing patterns. This allows discrimination of neuronal firing patterns between different sites that appear to occur simultaneously and that statistically could not be attributed to chance. The analytical methods we have demonstrated can be applied not only to calcium imaging but also to many other physiological recordings, where discrimination and temporal correlation of biological signals from multiple sites is required, particularly when arising from unstable baselines, with variable signal-to-noise ratios.NEW & NOTEWORTHY Dynamic imaging of intracellular calcium is commonly used to record changes in excitability in central and peripheral neurons. We describe a novel analytical methodology that objectively discriminates calcium transients from low signal-to-noise recordings from multiple sites and quantifies the degree of temporal synchrony between events. These new methods can be applied not only to calcium imaging but also to many other physiological recordings where discrimination and temporal correlation of biological signals from multiple sites is required.
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Affiliation(s)
- Julian Sorensen
- Discipline of Human Physiology and Centre for Neuroscience, School of Medicine, Flinders University of South Australia, Adelaide, Australia
| | - Lukasz Wiklendt
- Discipline of Human Physiology and Centre for Neuroscience, School of Medicine, Flinders University of South Australia, Adelaide, Australia
| | - Tim Hibberd
- Discipline of Human Physiology and Centre for Neuroscience, School of Medicine, Flinders University of South Australia, Adelaide, Australia
| | - Marcello Costa
- Discipline of Human Physiology and Centre for Neuroscience, School of Medicine, Flinders University of South Australia, Adelaide, Australia
| | - Nick J Spencer
- Discipline of Human Physiology and Centre for Neuroscience, School of Medicine, Flinders University of South Australia, Adelaide, Australia
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14
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Chanauria N, Bharmauria V, Bachatene L, Cattan S, Rouat J, Molotchnikoff S. Comparative effects of adaptation on layers II-III and V-VI neurons in cat V1. Eur J Neurosci 2016; 44:3094-3104. [PMID: 27740707 DOI: 10.1111/ejn.13439] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 10/04/2016] [Accepted: 10/06/2016] [Indexed: 12/23/2022]
Abstract
V1 is fundamentally grouped into columns that descend from layers II-III to V-VI. Neurons inherent to visual cortex are capable of adapting to changes in the incoming stimuli that drive the cortical plasticity. A principle feature called orientation selectivity can be altered by the presentation of non-optimal stimulus called 'adapter'. When triggered, LGN cells impinge upon layer IV and further relay the information to deeper layers via layers II-III. Using different adaptation protocols, neuronal plasticity can be investigated. Superficial neurons in area V1 are well acknowledged to exhibit attraction and repulsion by shifting their tuning peaks when challenged by a non-optimal stimulus called 'adapter'. Layers V-VI neurons in spite of partnering layers II-III neurons in cortical computation have not been explored simultaneously toward adaptation. We believe that adaptation not only affects cells specific to a layer but modifies the entire column. In this study, through simultaneous multiunit recordings in anesthetized cats using a multichannel depth electrode, we show for the first time how layers V-VI neurons (1000-1200 μm) along with layers II-III neurons (300-500 μm) exhibit plasticity in response to adaptation. Our results demonstrate that superficial and deeper layer neurons react synonymously toward adapter by exhibiting similar behavioral properties. The neurons displayed similar amplitude of shift and maintained equivalent sharpness of Gaussian tuning peaks before and the following adaptation. It appears that a similar mechanism, belonging to all layers, is responsible for the analog outcome of the neurons' experience with adapter.
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Affiliation(s)
- Nayan Chanauria
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
| | - Vishal Bharmauria
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada.,The Visuomotor Neuroscience Lab, Centre for Vision Research, Faculty of Health, York University, Toronto, ON, Canada
| | - Lyes Bachatene
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada.,Department of Nuclear Medicine and Radiobiology, Faculty of Medicine and Health Sciences (CHUS), SNAIL
- Sherbrooke Neuro Analysis and Imaging Lab, University of Sherbrooke, Sherbrooke, QC, Canada
| | - Sarah Cattan
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
| | - Jean Rouat
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada.,Département de Génie Électrique et Génie Informatique, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Stéphane Molotchnikoff
- Neurophysiology of Visual System, Département de Sciences Biologiques, Université de Montréal, CP 6128 Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
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15
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Okun M, Lak A, Carandini M, Harris KD. Long Term Recordings with Immobile Silicon Probes in the Mouse Cortex. PLoS One 2016; 11:e0151180. [PMID: 26959638 PMCID: PMC4784879 DOI: 10.1371/journal.pone.0151180] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2016] [Accepted: 02/24/2016] [Indexed: 12/31/2022] Open
Abstract
A key experimental approach in neuroscience involves measuring neuronal activity in behaving animals with extracellular chronic recordings. Such chronic recordings were initially made with single electrodes and tetrodes, and are now increasingly performed with high-density, high-count silicon probes. A common way to achieve long-term chronic recording is to attach the probes to microdrives that progressively advance them into the brain. Here we report, however, that such microdrives are not strictly necessary. Indeed, we obtained high-quality recordings in both head-fixed and freely moving mice for several months following the implantation of immobile chronic probes. Probes implanted into the primary visual cortex yielded well-isolated single units whose spike waveform and orientation tuning were highly reproducible over time. Although electrode drift was not completely absent, stable waveforms occurred in at least 70% of the neurons tested across consecutive days. Thus, immobile silicon probes represent a straightforward and reliable technique to obtain stable, long-term population recordings in mice, and to follow the activity of populations of well-isolated neurons over multiple days.
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Affiliation(s)
- Michael Okun
- UCL Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, United Kingdom
- UCL Institute of Ophthalmology, University College London, London EC1V 9EL, United Kingdom
- * E-mail:
| | - Armin Lak
- UCL Institute of Ophthalmology, University College London, London EC1V 9EL, United Kingdom
| | - Matteo Carandini
- UCL Institute of Ophthalmology, University College London, London EC1V 9EL, United Kingdom
| | - Kenneth D. Harris
- UCL Institute of Neurology, University College London, London WC1N 3BG, United Kingdom
- Department of Neuroscience, Physiology and Pharmacology, University College London, London WC1E 6DE, United Kingdom
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16
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Shafeghat N, Heidarinejad M, Murata N, Nakamura H, Inoue T. Optical detection of neuron connectivity by random access two-photon microscopy. J Neurosci Methods 2016; 263:48-56. [PMID: 26851307 DOI: 10.1016/j.jneumeth.2016.01.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2015] [Revised: 12/24/2015] [Accepted: 01/26/2016] [Indexed: 01/28/2023]
Abstract
BACKGROUND Knowledge about the distribution, strength, and direction of synaptic connections within neuronal networks are crucial for understanding brain function. Electrophysiology using multiple electrodes provides a very high temporal resolution, but does not yield sufficient spatial information for resolving neuronal connection topology. Optical recording techniques using single-cell resolution have provided promise for providing spatial information. Although calcium imaging from hundreds of neurons has provided a novel view of the neural connections within the network, the kinetics of calcium responses are not fast enough to resolve each action potential event with high fidelity. Therefore, it is not possible to detect the direction of neuronal connections. NEW METHOD We took advantage of the fast kinetics and large dynamic range of the DiO/DPA combination of voltage sensitive dye and the fast scan speed of a custom-made random-access two-photon microscope to resolve each action potential event from multiple neurons in culture. RESULTS Long-duration recording up to 100min from cultured hippocampal neurons yielded sufficient numbers of spike events for analyzing synaptic connections. Cross-correlation analysis of neuron pairs clearly distinguished synaptically connected neuron pairs with the connection direction. COMPARISON WITH EXISTING METHOD The long duration recording of action potentials with voltage-sensitive dye utilized in the present study is much longer than in previous studies. Simultaneous optical voltage and calcium measurements revealed that voltage-sensitive dye is able to detect firing events more reliably than calcium indicators. CONCLUSIONS This novel method reveals a new view of the functional structure of neuronal networks.
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Affiliation(s)
- Nasrin Shafeghat
- Department of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
| | - Morteza Heidarinejad
- Department of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
| | - Noboru Murata
- Department of Electrical Engineering and Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
| | - Hideki Nakamura
- Department of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan
| | - Takafumi Inoue
- Department of Life Science and Medical Bioscience, School of Advanced Science and Engineering, Waseda University, Tokyo, Japan.
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17
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Bharmauria V, Bachatene L, Cattan S, Brodeur S, Chanauria N, Rouat J, Molotchnikoff S. Network-selectivity and stimulus-discrimination in the primary visual cortex: cell-assembly dynamics. Eur J Neurosci 2015; 43:204-19. [DOI: 10.1111/ejn.13101] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2015] [Revised: 10/06/2015] [Accepted: 10/10/2015] [Indexed: 12/24/2022]
Affiliation(s)
- Vishal Bharmauria
- Neurophysiology of Visual System; Département de Sciences Biologiques; Université de Montréal; CP 6128 Succursale Centre-Ville Montréal QC Canada H3C 3J7
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
| | - Lyes Bachatene
- Neurophysiology of Visual System; Département de Sciences Biologiques; Université de Montréal; CP 6128 Succursale Centre-Ville Montréal QC Canada H3C 3J7
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
| | - Sarah Cattan
- Neurophysiology of Visual System; Département de Sciences Biologiques; Université de Montréal; CP 6128 Succursale Centre-Ville Montréal QC Canada H3C 3J7
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
| | - Simon Brodeur
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
- Département de Génie Électrique et Génie Informatique; Université de Sherbrooke; Sherbrooke QC Canada
| | - Nayan Chanauria
- Neurophysiology of Visual System; Département de Sciences Biologiques; Université de Montréal; CP 6128 Succursale Centre-Ville Montréal QC Canada H3C 3J7
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
| | - Jean Rouat
- Neurophysiology of Visual System; Département de Sciences Biologiques; Université de Montréal; CP 6128 Succursale Centre-Ville Montréal QC Canada H3C 3J7
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
- Département de Génie Électrique et Génie Informatique; Université de Sherbrooke; Sherbrooke QC Canada
| | - Stéphane Molotchnikoff
- Neurophysiology of Visual System; Département de Sciences Biologiques; Université de Montréal; CP 6128 Succursale Centre-Ville Montréal QC Canada H3C 3J7
- Neurosciences Computationnelles et Traitement Intelligent des Signaux (NECOTIS); Sherbrooke QC Canada
- Département de Génie Électrique et Génie Informatique; Université de Sherbrooke; Sherbrooke QC Canada
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18
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Feldman JL, Kam K. Facing the challenge of mammalian neural microcircuits: taking a few breaths may help. J Physiol 2015; 593:3-23. [PMID: 25556783 DOI: 10.1113/jphysiol.2014.277632] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2014] [Accepted: 11/01/2014] [Indexed: 12/27/2022] Open
Abstract
Breathing in mammals is a seemingly straightforward behaviour controlled by the brain. A brainstem nucleus called the preBötzinger Complex sits at the core of the neural circuit generating respiratory rhythm. Despite the discovery of this microcircuit almost 25 years ago, the mechanisms controlling breathing remain elusive. Given the apparent simplicity and well-defined nature of regulatory breathing behaviour, the identification of much of the circuitry, and the ability to study breathing in vitro as well as in vivo, many neuroscientists and physiologists are surprised that respiratory rhythm generation is still not well understood. Our view is that conventional rhythmogenic mechanisms involving pacemakers, inhibition or bursting are problematic and that simplifying assumptions commonly made for many vertebrate neural circuits ignore consequential detail. We propose that novel emergent mechanisms govern the generation of respiratory rhythm. That a mammalian function as basic as rhythm generation arises from complex and dynamic molecular, synaptic and neuronal interactions within a diverse neural microcircuit highlights the challenges in understanding neural control of mammalian behaviours, many (considerably) more elaborate than breathing. We suggest that the neural circuit controlling breathing is inimitably tractable and may inspire general strategies for elucidating other neural microcircuits.
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Affiliation(s)
- Jack L Feldman
- Systems Neurobiology Laboratory, Department of Neurobiology, David Geffen School of Medicine at the University of California Los Angeles, Los Angeles, CA, USA
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19
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Buzsáki G, Stark E, Berényi A, Khodagholy D, Kipke DR, Yoon E, Wise KD. Tools for probing local circuits: high-density silicon probes combined with optogenetics. Neuron 2015; 86:92-105. [PMID: 25856489 PMCID: PMC4392339 DOI: 10.1016/j.neuron.2015.01.028] [Citation(s) in RCA: 167] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
To understand how function arises from the interactions between neurons, it is necessary to use methods that allow the monitoring of brain activity at the single-neuron, single-spike level and the targeted manipulation of the diverse neuron types selectively in a closed-loop manner. Large-scale recordings of neuronal spiking combined with optogenetic perturbation of identified individual neurons has emerged as a suitable method for such tasks in behaving animals. To fully exploit the potential power of these methods, multiple steps of technical innovation are needed. We highlight the current state of the art in electrophysiological recording methods, combined with optogenetics, and discuss directions for progress. In addition, we point to areas where rapid development is in progress and discuss topics where near-term improvements are possible and needed.
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Affiliation(s)
- György Buzsáki
- The Neuroscience Institute, New York University, School of Medicine, New York, NY 10016, USA; Center for Neural Science, New York University, School of Medicine, New York, NY 10016, USA.
| | - Eran Stark
- The Neuroscience Institute, New York University, School of Medicine, New York, NY 10016, USA
| | - Antal Berényi
- The Neuroscience Institute, New York University, School of Medicine, New York, NY 10016, USA; MTA-SZTE "Lendület" Oscillatory Neural Networks Research Group, University of Szeged, Department of Physiology, Szeged H-6720, Hungary
| | - Dion Khodagholy
- The Neuroscience Institute, New York University, School of Medicine, New York, NY 10016, USA
| | - Daryl R Kipke
- NeuroNexus Technologies, Inc., Ann Arbor, MI 48108, USA
| | - Euisik Yoon
- Center for Wireless Integrated Microsensing and Systems, The University of Michigan, Ann Arbor, MI 48109-2122, USA
| | - Kensall D Wise
- Center for Wireless Integrated Microsensing and Systems, The University of Michigan, Ann Arbor, MI 48109-2122, USA
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