1
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Horton S, Mastrolia V, Jackson RE, Kemlo S, Pereira Machado PM, Carbajal MA, Hindges R, Fleck RA, Aguiar P, Neves G, Burrone J. Excitatory and inhibitory synapses show a tight subcellular correlation that weakens over development. Cell Rep 2024; 43:114361. [PMID: 38900634 DOI: 10.1016/j.celrep.2024.114361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 04/24/2024] [Accepted: 05/30/2024] [Indexed: 06/22/2024] Open
Abstract
Neurons receive correlated levels of excitation and inhibition, a feature that is important for proper brain function. However, how this relationship between excitatory and inhibitory inputs is established during the dynamic period of circuit wiring remains unexplored. Using multiple techniques, including in utero electroporation, electron microscopy, and electrophysiology, we reveal a tight correlation in the distribution of excitatory and inhibitory synapses along the dendrites of developing CA1 hippocampal neurons. This correlation was present within short dendritic stretches (<20 μm) and, surprisingly, was most pronounced during early development, sharply declining with maturity. The tight matching between excitation and inhibition was unexpected, as inhibitory synapses lacked an active zone when formed and exhibited compromised evoked release. We propose that inhibitory synapses form as a stabilizing scaffold to counterbalance growing excitation levels. This relationship diminishes over time, suggesting a critical role for a subcellular balance in early neuronal function and circuit formation.
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Affiliation(s)
- Sally Horton
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Vincenzo Mastrolia
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Rachel E Jackson
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Sarah Kemlo
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Pedro M Pereira Machado
- Centre for Ultrastructural Imaging (CUI), Kings College London, New Hunts House, Guys Hospital Campus, London SE1 1UL, UK
| | - Maria Alejandra Carbajal
- Centre for Ultrastructural Imaging (CUI), Kings College London, New Hunts House, Guys Hospital Campus, London SE1 1UL, UK
| | - Robert Hindges
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK
| | - Roland A Fleck
- Centre for Ultrastructural Imaging (CUI), Kings College London, New Hunts House, Guys Hospital Campus, London SE1 1UL, UK
| | - Paulo Aguiar
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
| | - Guilherme Neves
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK.
| | - Juan Burrone
- MRC Centre for Neurodevelopmental Disorders, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK; Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE1 1UL, UK.
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2
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Agnes EJ, Vogels TP. Co-dependent excitatory and inhibitory plasticity accounts for quick, stable and long-lasting memories in biological networks. Nat Neurosci 2024; 27:964-974. [PMID: 38509348 PMCID: PMC11089004 DOI: 10.1038/s41593-024-01597-4] [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: 06/29/2022] [Accepted: 02/08/2024] [Indexed: 03/22/2024]
Abstract
The brain's functionality is developed and maintained through synaptic plasticity. As synapses undergo plasticity, they also affect each other. The nature of such 'co-dependency' is difficult to disentangle experimentally, because multiple synapses must be monitored simultaneously. To help understand the experimentally observed phenomena, we introduce a framework that formalizes synaptic co-dependency between different connection types. The resulting model explains how inhibition can gate excitatory plasticity while neighboring excitatory-excitatory interactions determine the strength of long-term potentiation. Furthermore, we show how the interplay between excitatory and inhibitory synapses can account for the quick rise and long-term stability of a variety of synaptic weight profiles, such as orientation tuning and dendritic clustering of co-active synapses. In recurrent neuronal networks, co-dependent plasticity produces rich and stable motor cortex-like dynamics with high input sensitivity. Our results suggest an essential role for the neighborly synaptic interaction during learning, connecting micro-level physiology with network-wide phenomena.
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Affiliation(s)
- Everton J Agnes
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK.
- Biozentrum, University of Basel, Basel, Switzerland.
| | - Tim P Vogels
- Centre for Neural Circuits and Behaviour, University of Oxford, Oxford, UK
- Institute of Science and Technology Austria, Klosterneuburg, Austria
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3
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Piette C, Gervasi N, Venance L. Synaptic plasticity through a naturalistic lens. Front Synaptic Neurosci 2023; 15:1250753. [PMID: 38145207 PMCID: PMC10744866 DOI: 10.3389/fnsyn.2023.1250753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 11/20/2023] [Indexed: 12/26/2023] Open
Abstract
From the myriad of studies on neuronal plasticity, investigating its underlying molecular mechanisms up to its behavioral relevance, a very complex landscape has emerged. Recent efforts have been achieved toward more naturalistic investigations as an attempt to better capture the synaptic plasticity underpinning of learning and memory, which has been fostered by the development of in vivo electrophysiological and imaging tools. In this review, we examine these naturalistic investigations, by devoting a first part to synaptic plasticity rules issued from naturalistic in vivo-like activity patterns. We next give an overview of the novel tools, which enable an increased spatio-temporal specificity for detecting and manipulating plasticity expressed at individual spines up to neuronal circuit level during behavior. Finally, we put particular emphasis on works considering brain-body communication loops and macroscale contributors to synaptic plasticity, such as body internal states and brain energy metabolism.
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Affiliation(s)
- Charlotte Piette
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France
| | | | - Laurent Venance
- Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS, INSERM, Université PSL, Paris, France
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4
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Jędrzejewska-Szmek J, Dorman DB, Blackwell KT. Making time and space for calcium control of neuron activity. Curr Opin Neurobiol 2023; 83:102804. [PMID: 37913687 PMCID: PMC10842147 DOI: 10.1016/j.conb.2023.102804] [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: 02/02/2023] [Revised: 10/02/2023] [Accepted: 10/03/2023] [Indexed: 11/03/2023]
Abstract
Calcium directly controls or indirectly regulates numerous functions that are critical for neuronal network activity. Intracellular calcium concentration is tightly regulated by numerous molecular mechanisms because spatial domains and temporal dynamics (not just peak amplitude) are critical for calcium control of synaptic plasticity and ion channel activation, which in turn determine neuron spiking activity. The computational models investigating calcium control are valuable because experiments achieving high spatial and temporal resolution simultaneously are technically unfeasible. Simulations of calcium nanodomains reveal that specific calcium sources can couple to specific calcium targets, providing a mechanism to determine the direction of synaptic plasticity. Cooperativity of calcium domains opposes specificity, suggesting that the dendritic branch might be the preferred computational unit of the neuron.
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Affiliation(s)
- Joanna Jędrzejewska-Szmek
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Science, 3 Pasteur Street, Warsaw, 02-093, Poland.
| | - Daniel B Dorman
- Department of Biomedical Engineering, Johns Hopkins University, 3400 N. Charles St., Baltimore, 21218, MD, USA
| | - Kim T Blackwell
- Bioengineering Department and Interdisciplinary Program in Neuroscience, George Mason University, 4400 University Drive, Fairfax, 22031, VA, USA
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5
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Miehl C, Gjorgjieva J. Stability and learning in excitatory synapses by nonlinear inhibitory plasticity. PLoS Comput Biol 2022; 18:e1010682. [PMID: 36459503 PMCID: PMC9718420 DOI: 10.1371/journal.pcbi.1010682] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Accepted: 10/25/2022] [Indexed: 12/03/2022] Open
Abstract
Synaptic changes are hypothesized to underlie learning and memory formation in the brain. But Hebbian synaptic plasticity of excitatory synapses on its own is unstable, leading to either unlimited growth of synaptic strengths or silencing of neuronal activity without additional homeostatic mechanisms. To control excitatory synaptic strengths, we propose a novel form of synaptic plasticity at inhibitory synapses. Using computational modeling, we suggest two key features of inhibitory plasticity, dominance of inhibition over excitation and a nonlinear dependence on the firing rate of postsynaptic excitatory neurons whereby inhibitory synaptic strengths change with the same sign (potentiate or depress) as excitatory synaptic strengths. We demonstrate that the stable synaptic strengths realized by this novel inhibitory plasticity model affects excitatory/inhibitory weight ratios in agreement with experimental results. Applying a disinhibitory signal can gate plasticity and lead to the generation of receptive fields and strong bidirectional connectivity in a recurrent network. Hence, a novel form of nonlinear inhibitory plasticity can simultaneously stabilize excitatory synaptic strengths and enable learning upon disinhibition.
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Affiliation(s)
- Christoph Miehl
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- School of Life Sciences, Technical University of Munich, Freising, Germany
- * E-mail: (CM); (JG)
| | - Julijana Gjorgjieva
- Max Planck Institute for Brain Research, Frankfurt am Main, Germany
- School of Life Sciences, Technical University of Munich, Freising, Germany
- * E-mail: (CM); (JG)
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6
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Wu YK, Miehl C, Gjorgjieva J. Regulation of circuit organization and function through inhibitory synaptic plasticity. Trends Neurosci 2022; 45:884-898. [PMID: 36404455 DOI: 10.1016/j.tins.2022.10.006] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Revised: 10/02/2022] [Accepted: 10/04/2022] [Indexed: 11/15/2022]
Abstract
Diverse inhibitory neurons in the mammalian brain shape circuit connectivity and dynamics through mechanisms of synaptic plasticity. Inhibitory plasticity can establish excitation/inhibition (E/I) balance, control neuronal firing, and affect local calcium concentration, hence regulating neuronal activity at the network, single neuron, and dendritic level. Computational models can synthesize multiple experimental results and provide insight into how inhibitory plasticity controls circuit dynamics and sculpts connectivity by identifying phenomenological learning rules amenable to mathematical analysis. We highlight recent studies on the role of inhibitory plasticity in modulating excitatory plasticity, forming structured networks underlying memory formation and recall, and implementing adaptive phenomena and novelty detection. We conclude with experimental and modeling progress on the role of interneuron-specific plasticity in circuit computation and context-dependent learning.
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Affiliation(s)
- Yue Kris Wu
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Christoph Miehl
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of Munich, Freising, Germany; Max Planck Institute for Brain Research, Frankfurt, Germany.
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7
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Differential Hebbian learning with time-continuous signals for active noise reduction. PLoS One 2022; 17:e0266679. [PMID: 35617161 PMCID: PMC9135254 DOI: 10.1371/journal.pone.0266679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 05/09/2022] [Indexed: 11/19/2022] Open
Abstract
Spike timing-dependent plasticity, related to differential Hebb-rules, has become a leading paradigm in neuronal learning, because weights can grow or shrink depending on the timing of pre- and post-synaptic signals. Here we use this paradigm to reduce unwanted (acoustic) noise. Our system relies on heterosynaptic differential Hebbian learning and we show that it can efficiently eliminate noise by up to -140 dB in multi-microphone setups under various conditions. The system quickly learns, most often within a few seconds, and it is robust with respect to different geometrical microphone configurations, too. Hence, this theoretical study demonstrates that it is possible to successfully transfer differential Hebbian learning, derived from the neurosciences, into a technical domain.
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8
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Moore JJ, Robert V, Rashid SK, Basu J. Assessing Local and Branch-specific Activity in Dendrites. Neuroscience 2022; 489:143-164. [PMID: 34756987 PMCID: PMC9125998 DOI: 10.1016/j.neuroscience.2021.10.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 10/09/2021] [Accepted: 10/21/2021] [Indexed: 01/12/2023]
Abstract
Dendrites are elaborate neural processes which integrate inputs from various sources in space and time. While decades of work have suggested an independent role for dendrites in driving nonlinear computations for the cell, only recently have technological advances enabled us to capture the variety of activity in dendrites and their coupling dynamics with the soma. Under certain circumstances, activity generated in a given dendritic branch remains isolated, such that the soma or even sister dendrites are not privy to these localized signals. Such branch-specific activity could radically increase the capacity and flexibility of coding for the cell as a whole. Here, we discuss these forms of localized and branch-specific activity, their functional relevance in plasticity and behavior, and their supporting biophysical and circuit-level mechanisms. We conclude by showcasing electrical and optical approaches in hippocampal area CA3, using original experimental data to discuss experimental and analytical methodology and key considerations to take when investigating the functional relevance of independent dendritic activity.
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Affiliation(s)
- Jason J Moore
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Vincent Robert
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Shannon K Rashid
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Jayeeta Basu
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA; Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA.
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9
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Kirchner JH, Gjorgjieva J. Emergence of synaptic organization and computation in dendrites. NEUROFORUM 2022; 28:21-30. [PMID: 35881644 PMCID: PMC8887907 DOI: 10.1515/nf-2021-0031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Single neurons in the brain exhibit astounding computational capabilities, which gradually emerge throughout development and enable them to become integrated into complex neural circuits. These capabilities derive in part from the precise arrangement of synaptic inputs on the neurons' dendrites. While the full computational benefits of this arrangement are still unknown, a picture emerges in which synapses organize according to their functional properties across multiple spatial scales. In particular, on the local scale (tens of microns), excitatory synaptic inputs tend to form clusters according to their functional similarity, whereas on the scale of individual dendrites or the entire tree, synaptic inputs exhibit dendritic maps where excitatory synapse function varies smoothly with location on the tree. The development of this organization is supported by inhibitory synapses, which are carefully interleaved with excitatory synapses and can flexibly modulate activity and plasticity of excitatory synapses. Here, we summarize recent experimental and theoretical research on the developmental emergence of this synaptic organization and its impact on neural computations.
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Affiliation(s)
- Jan H. Kirchner
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Max-von-Laue-Str. 4, 60438Frankfurt, Germany
- Technical University of Munich, School of Life Sciences, 85354Freising, Germany
| | - Julijana Gjorgjieva
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, Max-von-Laue-Str. 4, 60438Frankfurt, Germany
- Technical University of Munich, School of Life Sciences, 85354Freising, Germany
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10
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Santos-Mayo A, Moratti S, de Echegaray J, Susi G. A Model of the Early Visual System Based on Parallel Spike-Sequence Detection, Showing Orientation Selectivity. BIOLOGY 2021; 10:biology10080801. [PMID: 34440033 PMCID: PMC8389551 DOI: 10.3390/biology10080801] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/08/2021] [Revised: 08/12/2021] [Accepted: 08/16/2021] [Indexed: 12/22/2022]
Abstract
Simple Summary A computational model of primates’ early visual processing, showing orientation selectivity, is presented. The system importantly integrates two key elements: (1) a neuromorphic spike-decoding structure that considerably resembles the circuitry between layers IV and II/III of the primary visual cortex, both in topology and operation; (2) the plasticity of intrinsic excitability, to embed recent findings about the operation of the same area. The model is proposed as a tool for the analysis and reproduction of the orientation selectivity phenomenon, whose underlying neuronal-level computational mechanisms are today the subject of intense scrutiny. In response to rotated Gabor patches the model is able to exhibit realistic orientation tuning curves and to reproduce responses similar to those found in neurophysiological recordings from the primary visual cortex obtained under the same task, considering different stages of the network. This demonstrates its aptness to capture the mechanisms underlying the evoked response in the primary visual cortex. Our tool is available online, and can be expanded to other experiments using a dedicated software library developed by the authors, to elucidate the computational mechanisms underlying orientation selectivity. Abstract Since the first half of the twentieth century, numerous studies have been conducted on how the visual cortex encodes basic image features. One of the hallmarks of basic feature extraction is the phenomenon of orientation selectivity, of which the underlying neuronal-level computational mechanisms remain partially unclear despite being intensively investigated. In this work we present a reduced visual system model (RVSM) of the first level of scene analysis, involving the retina, the lateral geniculate nucleus and the primary visual cortex (V1), showing orientation selectivity. The detection core of the RVSM is the neuromorphic spike-decoding structure MNSD, which is able to learn and recognize parallel spike sequences and considerably resembles the neuronal microcircuits of V1 in both topology and operation. This structure is equipped with plasticity of intrinsic excitability to embed recent findings about V1 operation. The RVSM, which embeds 81 groups of MNSD arranged in 4 oriented columns, is tested using sets of rotated Gabor patches as input. Finally, synthetic visual evoked activity generated by the RVSM is compared with real neurophysiological signal from V1 area: (1) postsynaptic activity of human subjects obtained by magnetoencephalography and (2) spiking activity of macaques obtained by multi-tetrode arrays. The system is implemented using the NEST simulator. The results attest to a good level of resemblance between the model response and real neurophysiological recordings. As the RVSM is available online, and the model parameters can be customized by the user, we propose it as a tool to elucidate the computational mechanisms underlying orientation selectivity.
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Affiliation(s)
- Alejandro Santos-Mayo
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain; (A.S.-M.); (S.M.); (J.d.E.)
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid, 28040 Madrid, Spain
| | - Stephan Moratti
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain; (A.S.-M.); (S.M.); (J.d.E.)
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid, 28040 Madrid, Spain
- Laboratory of Clinical Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain
| | - Javier de Echegaray
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain; (A.S.-M.); (S.M.); (J.d.E.)
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid, 28040 Madrid, Spain
| | - Gianluca Susi
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, 28040 Madrid, Spain; (A.S.-M.); (S.M.); (J.d.E.)
- Department of Experimental Psychology, Faculty of Psychology, Complutense University of Madrid, 28040 Madrid, Spain
- Department of Civil Engineering and Computer Science, University of Rome “Tor Vergata”, 00133 Rome, Italy
- Correspondence: ; Tel.: +34-(61)-86893399-79317
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11
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Marks WD, Paris JJ, Barbour AJ, Moon J, Carpenter VJ, McLane VD, Lark ARS, Nass SR, Zhang J, Yarotskyy V, McQuiston AR, Knapp PE, Hauser KF. HIV-1 Tat and Morphine Differentially Disrupt Pyramidal Cell Structure and Function and Spatial Learning in Hippocampal Area CA1: Continuous versus Interrupted Morphine Exposure. eNeuro 2021; 8:ENEURO.0547-20.2021. [PMID: 33782102 PMCID: PMC8146490 DOI: 10.1523/eneuro.0547-20.2021] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Revised: 02/27/2021] [Accepted: 03/10/2021] [Indexed: 02/06/2023] Open
Abstract
About half the people infected with human immunodeficiency virus (HIV) have neurocognitive deficits that often include memory impairment and hippocampal deficits, which can be exacerbated by opioid abuse. To explore the effects of opioids and HIV on hippocampal CA1 pyramidal neuron structure and function, we induced HIV-1 transactivator of transcription (Tat) expression in transgenic mice for 14 d and co-administered time-release morphine or vehicle subcutaneous implants during the final 5 d (days 9-14) to establish steady-state morphine levels. Morphine was withheld from some ex vivo slices during recordings to begin to assess the initial pharmacokinetic consequences of opioid withdrawal. Tat expression reduced hippocampal CA1 pyramidal neuronal excitability at lower stimulating currents. Pyramidal cell firing rates were unaffected by continuous morphine exposure. Behaviorally, exposure to Tat or high dosages of morphine impaired spatial memory Exposure to Tat and steady-state levels of morphine appeared to have largely independent effects on pyramidal neuron structure and function, a response that is distinct from other vulnerable brain regions such as the striatum. By contrast, acutely withholding morphine (from morphine-tolerant ex vivo slices) revealed unique and selective neuroadaptive shifts in CA1 pyramidal neuronal excitability and dendritic plasticity, including some interactions with Tat. Collectively, the results show that opioid-HIV interactions in hippocampal area CA1 are more nuanced than previously assumed, and appear to vary depending on the outcome assessed and on the pharmacokinetics of morphine exposure.
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Affiliation(s)
- William D Marks
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Jason J Paris
- Department of BioMolecular Sciences, University of Mississippi, School of Pharmacy, University, MS 38677-1848
| | - Aaron J Barbour
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA 23298-0709
| | - Jean Moon
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Valerie J Carpenter
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Virginia D McLane
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Arianna R S Lark
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Sara R Nass
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Jingli Zhang
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - Viktor Yarotskyy
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
| | - A Rory McQuiston
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA 23298-0709
| | - Pamela E Knapp
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA 23298-0709
- Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, VA 23298-0709
| | - Kurt F Hauser
- Department of Pharmacology and Toxicology, Virginia Commonwealth University, School of Medicine, Richmond, VA 23298-0613
- Department of Anatomy and Neurobiology, Virginia Commonwealth University, Richmond, VA 23298-0709
- Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, VA 23298-0709
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12
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Herstel LJ, Wierenga CJ. Network control through coordinated inhibition. Curr Opin Neurobiol 2020; 67:34-41. [PMID: 32853970 DOI: 10.1016/j.conb.2020.08.001] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 07/29/2020] [Accepted: 08/01/2020] [Indexed: 12/29/2022]
Abstract
Coordinated excitatory and inhibitory activity is required for proper brain functioning. Recent computational and experimental studies have demonstrated that activity patterns in recurrent cortical networks are dominated by inhibition. Whereas previous studies have suggested that inhibitory plasticity is important for homeostatic control, this new framework puts inhibition in the driver's seat. Complex neuronal networks in the brain comprise many configurations in parallel, controlled by external and internal 'switches'. Context-dependent modulation and plasticity of inhibitory connections play a key role in memory and learning. It is therefore important to realize that synaptic plasticity is often multisynaptic and that a proper balance between excitation and inhibition is not fixed, but depends on context and activity level.
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Affiliation(s)
- Lotte J Herstel
- Cell Biology, Neurobiology and Biophysics, Biology Department, Faculty of Science, Utrecht University, The Netherlands
| | - Corette J Wierenga
- Cell Biology, Neurobiology and Biophysics, Biology Department, Faculty of Science, Utrecht University, The Netherlands.
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13
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Field RE, D'amour JA, Tremblay R, Miehl C, Rudy B, Gjorgjieva J, Froemke RC. Heterosynaptic Plasticity Determines the Set Point for Cortical Excitatory-Inhibitory Balance. Neuron 2020; 106:842-854.e4. [PMID: 32213321 DOI: 10.1016/j.neuron.2020.03.002] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Revised: 12/27/2019] [Accepted: 03/03/2020] [Indexed: 01/24/2023]
Abstract
Excitation in neural circuits must be carefully controlled by inhibition to regulate information processing and network excitability. During development, cortical inhibitory and excitatory inputs are initially mismatched but become co-tuned or balanced with experience. However, little is known about how excitatory-inhibitory balance is defined at most synapses or about the mechanisms for establishing or maintaining this balance at specific set points. Here we show how coordinated long-term plasticity calibrates populations of excitatory-inhibitory inputs onto mouse auditory cortical pyramidal neurons. Pairing pre- and postsynaptic activity induced plasticity at paired inputs and different forms of heterosynaptic plasticity at the strongest unpaired synapses, which required minutes of activity and dendritic Ca2+ signaling to be computed. Theoretical analyses demonstrated how the relative rate of heterosynaptic plasticity could normalize and stabilize synaptic strengths to achieve any possible excitatory-inhibitory correlation. Thus, excitatory-inhibitory balance is dynamic and cell specific, determined by distinct plasticity rules across multiple excitatory and inhibitory synapses.
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Affiliation(s)
- Rachel E Field
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY 10016, USA; Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA; Department of Otolaryngology, New York University School of Medicine, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY 10016, USA
| | - James A D'amour
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY 10016, USA; Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA; Department of Otolaryngology, New York University School of Medicine, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY 10016, USA
| | - Robin Tremblay
- Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY 10016, USA; Department of Anesthesiology, New York University School of Medicine, New York, NY 10016, USA
| | - Christoph Miehl
- Max Planck Institute for Brain Research, 60438 Frankfurt, Germany; School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Bernardo Rudy
- Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY 10016, USA; Department of Anesthesiology, New York University School of Medicine, New York, NY 10016, USA
| | - Julijana Gjorgjieva
- Max Planck Institute for Brain Research, 60438 Frankfurt, Germany; School of Life Sciences, Technical University of Munich, 85354 Freising, Germany
| | - Robert C Froemke
- Skirball Institute for Biomolecular Medicine, New York University School of Medicine, New York, NY 10016, USA; Neuroscience Institute, New York University School of Medicine, New York, NY 10016, USA; Department of Otolaryngology, New York University School of Medicine, New York, NY 10016, USA; Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY 10016, USA; Center for Neural Science, New York University, New York, NY 10003, USA.
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14
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Mendes A, Vignoud G, Perez S, Perrin E, Touboul J, Venance L. Concurrent Thalamostriatal and Corticostriatal Spike-Timing-Dependent Plasticity and Heterosynaptic Interactions Shape Striatal Plasticity Map. Cereb Cortex 2020; 30:4381-4401. [DOI: 10.1093/cercor/bhaa024] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
Abstract
Abstract
The striatum integrates inputs from the cortex and thalamus, which display concomitant or sequential activity. The striatum assists in forming memory, with acquisition of the behavioral repertoire being associated with corticostriatal (CS) plasticity. The literature has mainly focused on that CS plasticity, and little remains known about thalamostriatal (TS) plasticity rules or CS and TS plasticity interactions. We undertook here the study of these plasticity rules. We found bidirectional Hebbian and anti-Hebbian spike-timing-dependent plasticity (STDP) at the thalamic and cortical inputs, respectively, which were driving concurrent changes at the striatal synapses. Moreover, TS- and CS-STDP induced heterosynaptic plasticity. We developed a calcium-based mathematical model of the coupled TS and CS plasticity, and simulations predict complex changes in the CS and TS plasticity maps depending on the precise cortex–thalamus–striatum engram. These predictions were experimentally validated using triplet-based STDP stimulations, which revealed the significant remodeling of the CS-STDP map upon TS activity, which is notably the induction of the LTD areas in the CS-STDP for specific timing regimes. TS-STDP exerts a greater influence on CS plasticity than CS-STDP on TS plasticity. These findings highlight the major impact of precise timing in cortical and thalamic activity for the memory engram of striatal synapses.
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Affiliation(s)
- Alexandre Mendes
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS UMR7241, INSERM U1050, PSL Research University, Paris, 75005, France
| | - Gaetan Vignoud
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS UMR7241, INSERM U1050, PSL Research University, Paris, 75005, France
- Department of Mathematics, Volen National Center for Complex Systems, Brandeis University, Waltham, MA 2454-9110, USA
| | - Sylvie Perez
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS UMR7241, INSERM U1050, PSL Research University, Paris, 75005, France
| | - Elodie Perrin
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS UMR7241, INSERM U1050, PSL Research University, Paris, 75005, France
| | - Jonathan Touboul
- Department of Mathematics, Volen National Center for Complex Systems, Brandeis University, Waltham, MA 2454-9110, USA
| | - Laurent Venance
- Dynamics and Pathophysiology of Neuronal Networks Team, Center for Interdisciplinary Research in Biology (CIRB), College de France, CNRS UMR7241, INSERM U1050, PSL Research University, Paris, 75005, France
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15
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McDevitt DS, Jonik B, Graziane NM. Morphine Differentially Alters the Synaptic and Intrinsic Properties of D1R- and D2R-Expressing Medium Spiny Neurons in the Nucleus Accumbens. Front Synaptic Neurosci 2019; 11:35. [PMID: 31920618 PMCID: PMC6932971 DOI: 10.3389/fnsyn.2019.00035] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2019] [Accepted: 12/06/2019] [Indexed: 12/31/2022] Open
Abstract
Exposure to opioids reshapes future reward and motivated behaviors partially by altering the functional output of medium spiny neurons (MSNs) in the nucleus accumbens shell. Here, we investigated how morphine, a highly addictive opioid, alters synaptic transmission and intrinsic excitability on dopamine D1-receptor (D1R) expressing and dopamine D2-receptor (D2R) expressing MSNs, the two main output neurons in the nucleus accumbens shell. Using whole-cell electrophysiology recordings, we show, that 24 h abstinence following repeated non-contingent administration of morphine (10 mg/kg, i.p.) in mice reduces the miniature excitatory postsynaptic current (mEPSC) frequency and miniature inhibitory postsynaptic current (mIPSC) frequency on D2R-MSNs, with concomitant increases in D2R-MSN intrinsic membrane excitability. We did not observe any changes in synaptic or intrinsic changes on D1R-MSNs. Last, in an attempt to determine the integrated effect of the synaptic and intrinsic alterations on the overall functional output of D2R-MSNs, we measured the input-output efficacy by measuring synaptically-driven action potential firing. We found that both D1R-MSN and D2R-MSN output was unchanged following morphine treatment.
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Affiliation(s)
- Dillon S McDevitt
- Departments of Anesthesiology and Perioperative Medicine, and Pharmacology, Penn State College of Medicine, Hershey, PA, United States.,Neuroscience Graduate Program, Penn State College of Medicine, Hershey, PA, United States
| | - Benjamin Jonik
- Medical Student Research Program, Penn State College of Medicine, Hershey, PA, United States
| | - Nicholas M Graziane
- Departments of Anesthesiology and Perioperative Medicine, and Pharmacology, Penn State College of Medicine, Hershey, PA, United States
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16
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Susi G, Antón Toro L, Canuet L, López ME, Maestú F, Mirasso CR, Pereda E. A Neuro-Inspired System for Online Learning and Recognition of Parallel Spike Trains, Based on Spike Latency, and Heterosynaptic STDP. Front Neurosci 2018; 12:780. [PMID: 30429767 PMCID: PMC6220070 DOI: 10.3389/fnins.2018.00780] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2018] [Accepted: 10/09/2018] [Indexed: 11/17/2022] Open
Abstract
Humans perform remarkably well in many cognitive tasks including pattern recognition. However, the neuronal mechanisms underlying this process are not well understood. Nevertheless, artificial neural networks, inspired in brain circuits, have been designed and used to tackle spatio-temporal pattern recognition tasks. In this paper we present a multi-neuronal spike pattern detection structure able to autonomously implement online learning and recognition of parallel spike sequences (i.e., sequences of pulses belonging to different neurons/neural ensembles). The operating principle of this structure is based on two spiking/synaptic neurocomputational characteristics: spike latency, which enables neurons to fire spikes with a certain delay and heterosynaptic plasticity, which allows the own regulation of synaptic weights. From the perspective of the information representation, the structure allows mapping a spatio-temporal stimulus into a multi-dimensional, temporal, feature space. In this space, the parameter coordinate and the time at which a neuron fires represent one specific feature. In this sense, each feature can be considered to span a single temporal axis. We applied our proposed scheme to experimental data obtained from a motor-inhibitory cognitive task. The results show that out method exhibits similar performance compared with other classification methods, indicating the effectiveness of our approach. In addition, its simplicity and low computational cost suggest a large scale implementation for real time recognition applications in several areas, such as brain computer interface, personal biometrics authentication, or early detection of diseases.
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Affiliation(s)
- Gianluca Susi
- UCM-UPM Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Dipartimento di Ingegneria Civile e Ingegneria Informatica, Università di Roma 'Tor Vergata', Rome, Italy
| | - Luis Antón Toro
- UCM-UPM Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Departamento de Psicología Experimental, Procesos Cognitivos y Logopedia, Facultad de Psicología, Universidad Complutense de Madrid, Madrid, Spain
| | - Leonides Canuet
- UCM-UPM Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Departamento de Psicología Clinica, Psicobiología y Metodología, Universidad de La Laguna, La Laguna, Spain
| | - Maria Eugenia López
- UCM-UPM Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Departamento de Psicología Experimental, Procesos Cognitivos y Logopedia, Facultad de Psicología, Universidad Complutense de Madrid, Madrid, Spain
| | - Fernando Maestú
- UCM-UPM Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Departamento de Psicología Experimental, Procesos Cognitivos y Logopedia, Facultad de Psicología, Universidad Complutense de Madrid, Madrid, Spain
| | - Claudio R Mirasso
- Instituto de Fisica Interdisciplinar y Sistemas Complejos, CSIC-UIB, Campus Universitat de les Illes Balears, Palma de Mallorca, Spain
| | - Ernesto Pereda
- UCM-UPM Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Technical University of Madrid, Madrid, Spain.,Departamento de Ingeniería Industrial, Escuela Superior de Ingeniería y Tecnología & IUNE, Universidad de La Laguna, La Laguna, Spain
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17
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Beyond STDP-towards diverse and functionally relevant plasticity rules. Curr Opin Neurobiol 2018; 54:12-19. [PMID: 30056261 DOI: 10.1016/j.conb.2018.06.011] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 06/06/2018] [Accepted: 06/18/2018] [Indexed: 01/08/2023]
Abstract
Synaptic plasticity, induced by the close temporal association of two neural signals, supports associative forms of learning. However, the millisecond timescales for association often do not match the much longer delays for behaviorally relevant signals that supervise learning. In particular, information about the behavioral outcome of neural activity can be delayed, leading to a problem of temporal credit assignment. Recent studies suggest that synaptic plasticity can have temporal rules that not only accommodate the delays relevant to the circuit, but also be precisely tuned to the behavior the circuit supports. These discoveries highlight the diversity of plasticity rules, whose temporal requirements may depend on circuit delays and the contingencies of behavior.
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18
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Foncelle A, Mendes A, Jędrzejewska-Szmek J, Valtcheva S, Berry H, Blackwell KT, Venance L. Modulation of Spike-Timing Dependent Plasticity: Towards the Inclusion of a Third Factor in Computational Models. Front Comput Neurosci 2018; 12:49. [PMID: 30018546 PMCID: PMC6037788 DOI: 10.3389/fncom.2018.00049] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2018] [Accepted: 06/06/2018] [Indexed: 11/13/2022] Open
Abstract
In spike-timing dependent plasticity (STDP) change in synaptic strength depends on the timing of pre- vs. postsynaptic spiking activity. Since STDP is in compliance with Hebb's postulate, it is considered one of the major mechanisms of memory storage and recall. STDP comprises a system of two coincidence detectors with N-methyl-D-aspartate receptor (NMDAR) activation often posited as one of the main components. Numerous studies have unveiled a third component of this coincidence detection system, namely neuromodulation and glia activity shaping STDP. Even though dopaminergic control of STDP has most often been reported, acetylcholine, noradrenaline, nitric oxide (NO), brain-derived neurotrophic factor (BDNF) or gamma-aminobutyric acid (GABA) also has been shown to effectively modulate STDP. Furthermore, it has been demonstrated that astrocytes, via the release or uptake of glutamate, gate STDP expression. At the most fundamental level, the timing properties of STDP are expected to depend on the spatiotemporal dynamics of the underlying signaling pathways. However in most cases, due to technical limitations experiments grant only indirect access to these pathways. Computational models carefully constrained by experiments, allow for a better qualitative understanding of the molecular basis of STDP and its regulation by neuromodulators. Recently, computational models of calcium dynamics and signaling pathway molecules have started to explore STDP emergence in ex and in vivo-like conditions. These models are expected to reproduce better at least part of the complex modulation of STDP as an emergent property of the underlying molecular pathways. Elucidation of the mechanisms underlying STDP modulation and its consequences on network dynamics is of critical importance and will allow better understanding of the major mechanisms of memory storage and recall both in health and disease.
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Affiliation(s)
- Alexandre Foncelle
- INRIA, Villeurbanne, France
- LIRIS UMR 5205 CNRS-INSA, University of Lyon, Villeurbanne, France
| | - Alexandre Mendes
- Dynamic and Pathophysiology of Neuronal Networks, Center for Interdisciplinary Research in Biology (CIRB), College de France, INSERM U1050, CNRS UMR7241, Labex Memolife, Paris, France
- University Pierre et Marie Curie, ED 158, Paris, France
| | | | - Silvana Valtcheva
- Dynamic and Pathophysiology of Neuronal Networks, Center for Interdisciplinary Research in Biology (CIRB), College de France, INSERM U1050, CNRS UMR7241, Labex Memolife, Paris, France
- University Pierre et Marie Curie, ED 158, Paris, France
| | - Hugues Berry
- INRIA, Villeurbanne, France
- LIRIS UMR 5205 CNRS-INSA, University of Lyon, Villeurbanne, France
| | - Kim T. Blackwell
- The Krasnow Institute for Advanced Studies, George Mason University, Fairfax, VA, United States
| | - Laurent Venance
- Dynamic and Pathophysiology of Neuronal Networks, Center for Interdisciplinary Research in Biology (CIRB), College de France, INSERM U1050, CNRS UMR7241, Labex Memolife, Paris, France
- University Pierre et Marie Curie, ED 158, Paris, France
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