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Blum Moyse L, Berry H. A coupled neural field model for the standard consolidation theory. J Theor Biol 2024; 588:111818. [PMID: 38621583 DOI: 10.1016/j.jtbi.2024.111818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 03/29/2024] [Accepted: 04/03/2024] [Indexed: 04/17/2024]
Abstract
The standard consolidation theory states that short-term memories located in the hippocampus enable the consolidation of long-term memories in the neocortex. In other words, the neocortex slowly learns long-term memories with a transient support of the hippocampus that quickly learns unstable memories. However, it is not clear yet what could be the neurobiological mechanisms underlying these differences in learning rates and memory time-scales. Here, we propose a novel modeling approach of the standard consolidation theory, that focuses on its potential neurobiological mechanisms. In addition to synaptic plasticity and spike frequency adaptation, our model incorporates adult neurogenesis in the dentate gyrus as well as the difference in size between the neocortex and the hippocampus, that we associate with distance-dependent synaptic plasticity. We also take into account the interconnected spatial structure of the involved brain areas, by incorporating the above neurobiological mechanisms in a coupled neural field framework, where each area is represented by a separate neural field with intra- and inter-area connections. To our knowledge, this is the first attempt to apply neural fields to this process. Using numerical simulations and mathematical analysis, we explore the short-term and long-term dynamics of the model upon alternance of phases of hippocampal replay and retrieval cue of an external input. This external input is encodable as a memory pattern in the form of a multiple bump attractor pattern in the individual neural fields. In the model, hippocampal memory patterns become encoded first, before neocortical ones, because of the smaller distances between the bumps of the hippocampal memory patterns. As a result, retrieval of the input pattern in the neocortex at short time-scales necessitates the additional input delivered by the memory pattern of the hippocampus. Neocortical memory patterns progressively consolidate at longer times, up to a point where their retrieval does not need the support of the hippocampus anymore. At longer times, perturbation of the hippocampal neural fields by neurogenesis erases the hippocampus pattern, leading to a final state where the memory pattern is exclusively evoked in the neocortex. Therefore, the dynamics of our model successfully reproduces the main features of the standard consolidation theory. This suggests that neurogenesis in the hippocampus and distance-dependent synaptic plasticity coupled to synaptic depression and spike frequency adaptation, are indeed critical neurobiological processes in memory consolidation.
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Affiliation(s)
- Lisa Blum Moyse
- LIRIS, CNRS UMR 5205, Villeurbanne, F-69621, France; AIstroSight, Inria, Hospices Civils de Lyon, Universite Claude Bernard Lyon 1, Villeurbanne, F-69603, France.
| | - Hugues Berry
- AIstroSight, Inria, Hospices Civils de Lyon, Universite Claude Bernard Lyon 1, Villeurbanne, F-69603, France.
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2
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Feuerriegel D. Adaptation in the visual system: Networked fatigue or suppressed prediction error signalling? Cortex 2024; 177:302-320. [PMID: 38905873 DOI: 10.1016/j.cortex.2024.06.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Revised: 05/10/2024] [Accepted: 06/04/2024] [Indexed: 06/23/2024]
Abstract
Our brains are constantly adapting to changes in our visual environments. Neural adaptation exerts a persistent influence on the activity of sensory neurons and our perceptual experience, however there is a lack of consensus regarding how adaptation is implemented in the visual system. One account describes fatigue-based mechanisms embedded within local networks of stimulus-selective neurons (networked fatigue models). Another depicts adaptation as a product of stimulus expectations (predictive coding models). In this review, I evaluate neuroimaging and psychophysical evidence that poses fundamental problems for predictive coding models of neural adaptation. Specifically, I discuss observations of distinct repetition and expectation effects, as well as incorrect predictions of repulsive adaptation aftereffects made by predictive coding accounts. Based on this evidence, I argue that networked fatigue models provide a more parsimonious account of adaptation effects in the visual system. Although stimulus expectations can be formed based on recent stimulation history, any consequences of these expectations are likely to co-occur (or interact) with effects of fatigue-based adaptation. I conclude by proposing novel, testable hypotheses relating to interactions between fatigue-based adaptation and other predictive processes, focusing on stimulus feature extrapolation phenomena.
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Affiliation(s)
- Daniel Feuerriegel
- Melbourne School of Psychological Sciences, The University of Melbourne, Australia.
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3
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Brown ST, Medina-Pizarro M, Holla M, Vaaga CE, Raman IM. Simple spike patterns and synaptic mechanisms encoding sensory and motor signals in Purkinje cells and the cerebellar nuclei. Neuron 2024; 112:1848-1861.e4. [PMID: 38492575 PMCID: PMC11156563 DOI: 10.1016/j.neuron.2024.02.014] [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: 03/28/2022] [Revised: 01/04/2024] [Accepted: 02/15/2024] [Indexed: 03/18/2024]
Abstract
Whisker stimulation in awake mice evokes transient suppression of simple spike probability in crus I/II Purkinje cells. Here, we investigated how simple spike suppression arises synaptically, what it encodes, and how it affects cerebellar output. In vitro, monosynaptic parallel fiber (PF)-excitatory postsynaptic currents (EPSCs) facilitated strongly, whereas disynaptic inhibitory postsynaptic currents (IPSCs) remained stable, maximizing relative inhibitory strength at the onset of PF activity. Short-term plasticity thus favors the inhibition of Purkinje spikes before PFs facilitate. In vivo, whisker stimulation evoked a 2-6 ms synchronous spike suppression, just 6-8 ms (∼4 synaptic delays) after sensory onset, whereas active whisker movements elicited broadly timed spike rate increases that did not modulate sensory-evoked suppression. Firing in the cerebellar nuclei (CbN) inversely correlated with disinhibition from sensory-evoked simple spike suppressions but was decoupled from slow, non-synchronous movement-associated elevations of Purkinje firing rates. Synchrony thus allows the CbN to high-pass filter Purkinje inputs, facilitating sensory-evoked cerebellar outputs that can drive movements.
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Affiliation(s)
- Spencer T Brown
- Department of Neurobiology, Northwestern University, Evanston, IL, USA
| | - Mauricio Medina-Pizarro
- Department of Neurobiology, Northwestern University, Evanston, IL, USA; Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA
| | - Meghana Holla
- Department of Neurobiology, Northwestern University, Evanston, IL, USA; Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA
| | | | - Indira M Raman
- Department of Neurobiology, Northwestern University, Evanston, IL, USA; Northwestern University Interdepartmental Neuroscience Program, Northwestern University, Evanston, IL, USA.
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4
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Kim HH, Bonekamp KE, Gillie GR, Autio DM, Keller T, Crandall SR. Functional Dynamics and Selectivity of Two Parallel Corticocortical Pathways from Motor Cortex to Layer 5 Circuits in Somatosensory Cortex. eNeuro 2024; 11:ENEURO.0154-24.2024. [PMID: 38834298 DOI: 10.1523/eneuro.0154-24.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 05/20/2024] [Accepted: 05/28/2024] [Indexed: 06/06/2024] Open
Abstract
In the rodent whisker system, active sensing and sensorimotor integration are mediated in part by the dynamic interactions between the motor cortex (M1) and somatosensory cortex (S1). However, understanding these dynamic interactions requires knowledge about the synapses and how specific neurons respond to their input. Here, we combined optogenetics, retrograde labeling, and electrophysiology to characterize the synaptic connections between M1 and layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons in S1 of mice (both sexes). We found that M1 synapses onto IT cells displayed modest short-term depression, whereas synapses onto PT neurons showed robust short-term facilitation. Despite M1 inputs to IT cells depressing, their slower kinetics resulted in summation and a response that increased during short trains. In contrast, summation was minimal in PT neurons due to the fast time course of their M1 responses. The functional consequences of this reduced summation, however, were outweighed by the strong facilitation at these M1 synapses, resulting in larger response amplitudes in PT neurons than IT cells during repetitive stimulation. To understand the impact of facilitating M1 inputs on PT output, we paired trains of inputs with single backpropagating action potentials, finding that repetitive M1 activation increased the probability of bursts in PT cells without impacting the time dependence of this coupling. Thus, there are two parallel but dynamically distinct systems of M1 synaptic excitation in L5 of S1, each defined by the short-term dynamics of its synapses, the class of postsynaptic neurons, and how the neurons respond to those inputs.
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Affiliation(s)
- Hye-Hyun Kim
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
| | - Kelly E Bonekamp
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University, East Lansing, Michigan 48824
| | - Grant R Gillie
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University, East Lansing, Michigan 48824
| | - Dawn M Autio
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
| | - Tryton Keller
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
| | - Shane R Crandall
- Department of Physiology, Michigan State University, East Lansing, Michigan 48824
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University, East Lansing, Michigan 48824
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5
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Kim HH, Bonekamp KE, Gillie GR, Autio DM, Keller T, Crandall SR. Functional dynamics and selectivity of two parallel corticocortical pathways from motor cortex to layer 5 circuits in somatosensory cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.11.579810. [PMID: 38405888 PMCID: PMC10888929 DOI: 10.1101/2024.02.11.579810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
In the rodent whisker system, active sensing and sensorimotor integration are mediated in part by the dynamic interactions between the motor cortex (M1) and somatosensory cortex (S1). However, understanding these dynamic interactions requires knowledge about the synapses and how specific neurons respond to their input. Here, we combined optogenetics, retrograde labeling, and electrophysiology to characterize the synaptic connections between M1 and layer 5 (L5) intratelencephalic (IT) and pyramidal tract (PT) neurons in S1 of mice (both sexes). We found that M1 synapses onto IT cells displayed modest short-term depression, whereas synapses onto PT neurons showed robust short-term facilitation. Despite M1 inputs to IT cells depressing, their slower kinetics resulted in summation and a response that increased during short trains. In contrast, summation was minimal in PT neurons due to the fast time course of their M1 responses. The functional consequences of this reduced summation, however, were outweighed by the strong facilitation at these M1 synapses, resulting in larger response amplitudes in PT neurons than IT cells during repetitive stimulation. To understand the impact of facilitating M1 inputs on PT output, we paired trains of inputs with single backpropagating action potentials, finding that repetitive M1 activation increased the probability of bursts in PT cells without impacting the time-dependence of this coupling. Thus, there are two parallel but dynamically distinct systems of M1 synaptic excitation in L5 of S1, each defined by the short-term dynamics of its synapses, the class of postsynaptic neurons, and how the neurons respond to those inputs.
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Affiliation(s)
- Hye-Hyun Kim
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Kelly E. Bonekamp
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University East Lansing, MI 48824, USA
| | - Grant R. Gillie
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University East Lansing, MI 48824, USA
| | - Dawn M. Autio
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Tryton Keller
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
| | - Shane R. Crandall
- Department of Physiology, Michigan State University, East Lansing, MI 48824, USA
- Molecular, Cellular, and Integrative Physiology Program, Michigan State University East Lansing, MI 48824, USA
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6
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Bezerra TO, Roque AC, Salum C. A Computational Model for the Simulation of Prepulse Inhibition and Its Modulation by Cortical and Subcortical Units. Brain Sci 2024; 14:502. [PMID: 38790479 PMCID: PMC11118907 DOI: 10.3390/brainsci14050502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2024] [Revised: 05/10/2024] [Accepted: 05/11/2024] [Indexed: 05/26/2024] Open
Abstract
The sensorimotor gating is a nervous system function that modulates the acoustic startle response (ASR). Prepulse inhibition (PPI) phenomenon is an operational measure of sensorimotor gating, defined as the reduction of ASR when a high intensity sound (pulse) is preceded in milliseconds by a weaker stimulus (prepulse). Brainstem nuclei are associated with the mediation of ASR and PPI, whereas cortical and subcortical regions are associated with their modulation. However, it is still unclear how the modulatory units can influence PPI. In the present work, we developed a computational model of a neural circuit involved in the mediation (brainstem units) and modulation (cortical and subcortical units) of ASR and PPI. The activities of all units were modeled by the leaky-integrator formalism for neural population. The model reproduces basic features of PPI observed in experiments, such as the effects of changes in interstimulus interval, prepulse intensity, and habituation of ASR. The simulation of GABAergic and dopaminergic drugs impaired PPI by their effects over subcortical units activity. The results show that subcortical units constitute a central hub for PPI modulation. The presented computational model offers a valuable tool to investigate the neurobiology associated with disorder-related impairments in PPI.
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Affiliation(s)
- Thiago Ohno Bezerra
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, São Bernardo do Campo 09606-045, Brazil
| | - Antonio C. Roque
- Department of Physics, School of Philosophy, Sciences and Letters of Ribeirão Preto, University of São Paulo, Ribeirão Preto 14040-901, Brazil
| | - Cristiane Salum
- Center of Mathematics, Computation and Cognition, Universidade Federal do ABC, São Bernardo do Campo 09606-045, Brazil
- Interdisciplinary Applied Neuroscience Unit, Universidade Federal do ABC, São Bernardo do Campo 09606-045, Brazil
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7
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McFarlan AR, Guo C, Gomez I, Weinerman C, Liang TA, Sjöström PJ. The spike-timing-dependent plasticity of VIP interneurons in motor cortex. Front Cell Neurosci 2024; 18:1389094. [PMID: 38706517 PMCID: PMC11066220 DOI: 10.3389/fncel.2024.1389094] [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: 02/20/2024] [Accepted: 04/09/2024] [Indexed: 05/07/2024] Open
Abstract
The plasticity of inhibitory interneurons (INs) plays an important role in the organization and maintenance of cortical microcircuits. Given the many different IN types, there is an even greater diversity in synapse-type-specific plasticity learning rules at excitatory to excitatory (E→I), I→E, and I→I synapses. I→I synapses play a key disinhibitory role in cortical circuits. Because they typically target other INs, vasoactive intestinal peptide (VIP) INs are often featured in I→I→E disinhibition, which upregulates activity in nearby excitatory neurons. VIP IN dysregulation may thus lead to neuropathologies such as epilepsy. In spite of the important activity regulatory role of VIP INs, their long-term plasticity has not been described. Therefore, we characterized the phenomenology of spike-timing-dependent plasticity (STDP) at inputs and outputs of genetically defined VIP INs. Using a combination of whole-cell recording, 2-photon microscopy, and optogenetics, we explored I→I STDP at layer 2/3 (L2/3) VIP IN outputs onto L5 Martinotti cells (MCs) and basket cells (BCs). We found that VIP IN→MC synapses underwent causal long-term depression (LTD) that was presynaptically expressed. VIP IN→BC connections, however, did not undergo any detectable plasticity. Conversely, using extracellular stimulation, we explored E→I STDP at inputs to VIP INs which revealed long-term potentiation (LTP) for both causal and acausal timings. Taken together, our results demonstrate that VIP INs possess synapse-type-specific learning rules at their inputs and outputs. This suggests the possibility of harnessing VIP IN long-term plasticity to control activity-related neuropathologies such as epilepsy.
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Affiliation(s)
- Amanda R. McFarlan
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Connie Guo
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
| | - Isabella Gomez
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
| | - Chaim Weinerman
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
| | - Tasha A. Liang
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
| | - P. Jesper Sjöström
- Centre for Research in Neuroscience, BRaIN Program, Department of Neurology and Neurosurgery, Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, QC, Canada
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8
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Yonk AJ, Linares-García I, Pasternak L, Juliani SE, Gradwell MA, George AJ, Margolis DJ. Role of Posterior Medial Thalamus in the Modulation of Striatal Circuitry and Choice Behavior. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.21.586152. [PMID: 38585753 PMCID: PMC10996534 DOI: 10.1101/2024.03.21.586152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
The posterior medial (POm) thalamus is heavily interconnected with sensory and motor circuitry and is likely involved in behavioral modulation and sensorimotor integration. POm provides axonal projections to the dorsal striatum, a hotspot of sensorimotor processing, yet the role of POm-striatal projections has remained undetermined. Using optogenetics with slice electrophysiology, we found that POm provides robust synaptic input to direct and indirect pathway striatal spiny projection neurons (D1- and D2-SPNs, respectively) and parvalbumin-expressing fast spiking interneurons (PVs). During the performance of a whisker-based tactile discrimination task, POm-striatal projections displayed learning-related activation correlating with anticipatory, but not reward-related, pupil dilation. Inhibition of POm-striatal axons across learning caused slower reaction times and an increase in the number of training sessions for expert performance. Our data indicate that POm-striatal inputs provide a behaviorally relevant arousal-related signal, which may prime striatal circuitry for efficient integration of subsequent choice-related inputs.
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Affiliation(s)
- Alex J. Yonk
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
| | - Ivan Linares-García
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
| | - Logan Pasternak
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
| | - Sofia E. Juliani
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
| | - Mark A. Gradwell
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
| | - Arlene J. George
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
| | - David J. Margolis
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, 604 Allison Road, Piscataway, NJ, 08854, USA
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9
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Beninger J, Rossbroich J, Tóth K, Naud R. Functional subtypes of synaptic dynamics in mouse and human. Cell Rep 2024; 43:113785. [PMID: 38363673 DOI: 10.1016/j.celrep.2024.113785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 12/08/2023] [Accepted: 01/27/2024] [Indexed: 02/18/2024] Open
Abstract
Synapses preferentially respond to particular temporal patterns of activity with a large degree of heterogeneity that is informally or tacitly separated into classes. Yet, the precise number and properties of such classes are unclear. Do they exist on a continuum and, if so, when is it appropriate to divide that continuum into functional regions? In a large dataset of glutamatergic cortical connections, we perform model-based characterization to infer the number and characteristics of functionally distinct subtypes of synaptic dynamics. In rodent data, we find five clusters that partially converge with transgenic-associated subtypes. Strikingly, the application of the same clustering method in human data infers a highly similar number of clusters, supportive of stable clustering. This nuanced dictionary of functional subtypes shapes the heterogeneity of cortical synaptic dynamics and provides a lens into the basic motifs of information transmission in the brain.
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Affiliation(s)
- John Beninger
- Center for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, ON K1H 8M5, Canada; uOttawa Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Julian Rossbroich
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland; Faculty of Science, University of Basel, Basel, Switzerland
| | - Katalin Tóth
- Center for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, ON K1H 8M5, Canada; uOttawa Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada
| | - Richard Naud
- Center for Neural Dynamics and Artificial Intelligence, University of Ottawa, Ottawa, ON K1H 8M5, Canada; uOttawa Brain and Mind Research Institute, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, ON K1H 8M5, Canada; Department of Physics, University of Ottawa, Ottawa, ON K1H 8M5, Canada.
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10
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Chen X, Tang SJ. Neural Circuitry Polarization in the Spinal Dorsal Horn (SDH): A Novel Form of Dysregulated Circuitry Plasticity during Pain Pathogenesis. Cells 2024; 13:398. [PMID: 38474361 PMCID: PMC10930392 DOI: 10.3390/cells13050398] [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: 01/20/2024] [Revised: 02/20/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024] Open
Abstract
Pathological pain emerges from nociceptive system dysfunction, resulting in heightened pain circuit activity. Various forms of circuitry plasticity, such as central sensitization, synaptic plasticity, homeostatic plasticity, and excitation/inhibition balance, contribute to the malfunction of neural circuits during pain pathogenesis. Recently, a new form of plasticity in the spinal dorsal horn (SDH), named neural circuit polarization (NCP), was discovered in pain models induced by HIV-1 gp120 and chronic morphine administration. NCP manifests as an increase in excitatory postsynaptic currents (EPSCs) in excitatory neurons and a decrease in EPSCs in inhibitory neurons, presumably facilitating hyperactivation of pain circuits. The expression of NCP is associated with astrogliosis. Ablation of reactive astrocytes or suppression of astrogliosis blocks NCP and, concomitantly, the development of gp120- or morphine-induced pain. In this review, we aim to compare and integrate NCP with other forms of plasticity in pain circuits to improve the understanding of the pathogenic contribution of NCP and its cooperation with other forms of circuitry plasticity during the development of pathological pain.
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Affiliation(s)
| | - Shao-Jun Tang
- Stony Brook University Pain and Anesthesia Research Center (SPARC), Department of Anesthesiology, Stony Brook University, Stony Brook, NY 11794, USA;
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11
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Richardson MJE. Linear and nonlinear integrate-and-fire neurons driven by synaptic shot noise with reversal potentials. Phys Rev E 2024; 109:024407. [PMID: 38491664 DOI: 10.1103/physreve.109.024407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 12/18/2023] [Indexed: 03/18/2024]
Abstract
The steady-state firing rate and firing-rate response of the leaky and exponential integrate-and-fire models receiving synaptic shot noise with excitatory and inhibitory reversal potentials is examined. For the particular case where the underlying synaptic conductances are exponentially distributed, it is shown that the master equation for a population of such model neurons can be reduced from an integrodifferential form to a more tractable set of three differential equations. The system is nevertheless more challenging analytically than for current-based synapses: where possible, analytical results are provided with an efficient numerical scheme and code provided for other quantities. The increased tractability of the framework developed supports an ongoing critical comparison between models in which synapses are treated with and without reversal potentials, such as recently in the context of networks with balanced excitatory and inhibitory conductances.
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Affiliation(s)
- Magnus J E Richardson
- Warwick Mathematics Institute, University of Warwick, Coventry CV4 7AL, United Kingdom
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12
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Diehl GW, Redish AD. Measuring excitation-inhibition balance through spectral components of local field potentials. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.24.577086. [PMID: 38328057 PMCID: PMC10849740 DOI: 10.1101/2024.01.24.577086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
The balance between excitation and inhibition is critical to brain functioning, and dysregulation of this balance is a hallmark of numerous psychiatric conditions. Measuring this excitation-inhibition (E:I) balance in vivo has remained difficult, but theoretical models have proposed that characteristics of local field potentials (LFP) may provide an accurate proxy. To establish a conclusive link between LFP and E:I balance, we recorded single units and LFP from the prefrontal cortex (mPFC) of rats during decision making. Dynamic measures of synaptic coupling strength facilitated direct quantification of E:I balance and revealed a strong inverse relationship to broadband spectral power of LFP. These results provide a critical link between LFP and underlying network properties, opening the door for non-invasive recordings to measure E:I balance in clinical settings.
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Affiliation(s)
- Geoffrey W Diehl
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
| | - A David Redish
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, United States
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13
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Turner W, Sexton C, Hogendoorn H. Neural mechanisms of visual motion extrapolation. Neurosci Biobehav Rev 2024; 156:105484. [PMID: 38036162 DOI: 10.1016/j.neubiorev.2023.105484] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 11/21/2023] [Accepted: 11/25/2023] [Indexed: 12/02/2023]
Abstract
Because neural processing takes time, the brain only has delayed access to sensory information. When localising moving objects this is problematic, as an object will have moved on by the time its position has been determined. Here, we consider predictive motion extrapolation as a fundamental delay-compensation strategy. From a population-coding perspective, we outline how extrapolation can be achieved by a forwards shift in the population-level activity distribution. We identify general mechanisms underlying such shifts, involving various asymmetries which facilitate the targeted 'enhancement' and/or 'dampening' of population-level activity. We classify these on the basis of their potential implementation (intra- vs inter-regional processes) and consider specific examples in different visual regions. We consider how motion extrapolation can be achieved during inter-regional signaling, and how asymmetric connectivity patterns which support extrapolation can emerge spontaneously from local synaptic learning rules. Finally, we consider how more abstract 'model-based' predictive strategies might be implemented. Overall, we present an integrative framework for understanding how the brain determines the real-time position of moving objects, despite neural delays.
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Affiliation(s)
- William Turner
- Queensland University of Technology, Brisbane 4059, Australia; The University of Melbourne, Melbourne 3010, Australia.
| | | | - Hinze Hogendoorn
- Queensland University of Technology, Brisbane 4059, Australia; The University of Melbourne, Melbourne 3010, Australia
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14
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Barth-Maron A, D'Alessandro I, Wilson RI. Interactions between specialized gain control mechanisms in olfactory processing. Curr Biol 2023; 33:5109-5120.e7. [PMID: 37967554 DOI: 10.1016/j.cub.2023.10.041] [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: 04/07/2023] [Revised: 08/16/2023] [Accepted: 10/23/2023] [Indexed: 11/17/2023]
Abstract
Gain control is a process that adjusts a system's sensitivity when input levels change. Neural systems contain multiple mechanisms of gain control, but we do not understand why so many mechanisms are needed or how they interact. Here, we investigate these questions in the Drosophila antennal lobe, where we identify several types of inhibitory interneurons with specialized gain control functions. We find that some interneurons are nonspiking, with compartmentalized calcium signals, and they specialize in intra-glomerular gain control. Conversely, we find that other interneurons are recruited by strong and widespread network input; they specialize in global presynaptic gain control. Using computational modeling and optogenetic perturbations, we show how these mechanisms can work together to improve stimulus discrimination while also minimizing temporal distortions in network activity. Our results demonstrate how the robustness of neural network function can be increased by interactions among diverse and specialized mechanisms of gain control.
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Affiliation(s)
- Asa Barth-Maron
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Isabel D'Alessandro
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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15
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Zhang WH, Wu S, Josić K, Doiron B. Sampling-based Bayesian inference in recurrent circuits of stochastic spiking neurons. Nat Commun 2023; 14:7074. [PMID: 37925497 PMCID: PMC10625605 DOI: 10.1038/s41467-023-41743-3] [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: 01/31/2022] [Accepted: 09/15/2023] [Indexed: 11/06/2023] Open
Abstract
Two facts about cortex are widely accepted: neuronal responses show large spiking variability with near Poisson statistics and cortical circuits feature abundant recurrent connections between neurons. How these spiking and circuit properties combine to support sensory representation and information processing is not well understood. We build a theoretical framework showing that these two ubiquitous features of cortex combine to produce optimal sampling-based Bayesian inference. Recurrent connections store an internal model of the external world, and Poissonian variability of spike responses drives flexible sampling from the posterior stimulus distributions obtained by combining feedforward and recurrent neuronal inputs. We illustrate how this framework for sampling-based inference can be used by cortex to represent latent multivariate stimuli organized either hierarchically or in parallel. A neural signature of such network sampling are internally generated differential correlations whose amplitude is determined by the prior stored in the circuit, which provides an experimentally testable prediction for our framework.
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Affiliation(s)
- Wen-Hao Zhang
- Department of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Lyda Hill Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX, USA
| | - Si Wu
- School of Psychological and Cognitive Sciences, Peking University, Beijing, 100871, China
- IDG/McGovern Institute for Brain Research, Peking University, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Peking University, Beijing, 100871, China
- Center of Quantitative Biology, Peking University, Beijing, 100871, China
| | - Krešimir Josić
- Department of Mathematics, University of Houston, Houston, TX, USA.
- Department of Biology and Biochemistry, University of Houston, Houston, TX, USA.
| | - Brent Doiron
- Department of Neurobiology and Statistics, University of Chicago, Chicago, IL, USA.
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, USA.
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA.
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16
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Phillips RS, Baertsch NA. Interdependence of cellular and network properties in respiratory rhythmogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.30.564834. [PMID: 37961254 PMCID: PMC10634953 DOI: 10.1101/2023.10.30.564834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
How breathing is generated by the preBötzinger Complex (preBötC) remains divided between two ideological frameworks, and the persistent sodium current (INaP) lies at the heart of this debate. Although INaP is widely expressed, the pacemaker hypothesis considers it essential because it endows a small subset of neurons with intrinsic bursting or "pacemaker" activity. In contrast, burstlet theory considers INaP dispensable because rhythm emerges from "pre-inspiratory" spiking activity driven by feed-forward network interactions. Using computational modeling, we discover that changes in spike shape can dissociate INaP from intrinsic bursting. Consistent with many experimental benchmarks, conditional effects on spike shape during simulated changes in oxygenation, development, extracellular potassium, and temperature alter the prevalence of intrinsic bursting and pre-inspiratory spiking without altering the role of INaP. Our results support a unifying hypothesis where INaP and excitatory network interactions, but not intrinsic bursting or pre-inspiratory spiking, are critical interdependent features of preBötC rhythmogenesis.
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Affiliation(s)
- Ryan S Phillips
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle WA, USA
| | - Nathan A Baertsch
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle WA, USA
- Pulmonary, Critical Care and Sleep Medicine, Department of Pediatrics, University of Washington, Seattle WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle WA, USA
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17
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Andrei AR, Akil AE, Kharas N, Rosenbaum R, Josić K, Dragoi V. Rapid compensatory plasticity revealed by dynamic correlated activity in monkeys in vivo. Nat Neurosci 2023; 26:1960-1969. [PMID: 37828225 DOI: 10.1038/s41593-023-01446-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 09/01/2023] [Indexed: 10/14/2023]
Abstract
To produce adaptive behavior, neural networks must balance between plasticity and stability. Computational work has demonstrated that network stability requires plasticity mechanisms to be counterbalanced by rapid compensatory processes. However, such processes have yet to be experimentally observed. Here we demonstrate that repeated optogenetic activation of excitatory neurons in monkey visual cortex (area V1) induces a population-wide dynamic reduction in the strength of neuronal interactions over the timescale of minutes during the awake state, but not during rest. This new form of rapid plasticity was observed only in the correlation structure, with firing rates remaining stable across trials. A computational network model operating in the balanced regime confirmed experimental findings and revealed that inhibitory plasticity is responsible for the decrease in correlated activity in response to repeated light stimulation. These results provide the first experimental evidence for rapid homeostatic plasticity that primarily operates during wakefulness, which stabilizes neuronal interactions during strong network co-activation.
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Affiliation(s)
- Ariana R Andrei
- Department of Neurobiology and Anatomy, University of Texas, Houston, TX, USA.
| | - Alan E Akil
- Departments of Mathematics, Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - Natasha Kharas
- Department of Neurobiology and Anatomy, University of Texas, Houston, TX, USA
| | - Robert Rosenbaum
- Department of Applied and Computational Mathematics and Statistics, University of Notre Dame, Notre Dame, IN, USA
| | - Krešimir Josić
- Departments of Mathematics, Biology and Biochemistry, University of Houston, Houston, TX, USA
| | - Valentin Dragoi
- Department of Neurobiology and Anatomy, University of Texas, Houston, TX, USA.
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
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18
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Cheng X, Tang Y, Vidyadhara D, Li BZ, Zimmerman M, Pak A, Nareddula S, Edens PA, Chandra SS, Chubykin AA. Impaired pre-synaptic plasticity and visual responses in auxilin-knockout mice. iScience 2023; 26:107842. [PMID: 37766983 PMCID: PMC10520332 DOI: 10.1016/j.isci.2023.107842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 08/06/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023] Open
Abstract
Auxilin (DNAJC6/PARK19), an endocytic co-chaperone, is essential for maintaining homeostasis in the readily releasable pool (RRP) by aiding clathrin-mediated uncoating of synaptic vesicles. Its loss-of-function mutations, observed in familial Parkinson's disease (PD), lead to basal ganglia motor deficits and cortical dysfunction. We discovered that auxilin-knockout (Aux-KO) mice exhibited impaired pre-synaptic plasticity in layer 4 to layer 2/3 pyramidal cell synapses in the primary visual cortex (V1), including reduced short-term facilitation and depression. Computational modeling revealed increased RRP refilling during short repetitive stimulation, which diminished during prolonged stimulation. Silicon probe recordings in V1 of Aux-KO mice demonstrated disrupted visual cortical circuit responses, including reduced orientation selectivity, compromised visual mismatch negativity, and shorter visual familiarity-evoked theta oscillations. Pupillometry analysis revealed an impaired optokinetic response. Auxilin-dependent pre-synaptic endocytosis dysfunction was associated with deficits in pre-synaptic plasticity, visual cortical functions, and eye movement prodromally or at the early stage of motor symptoms.
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Affiliation(s)
- Xi Cheng
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Yu Tang
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - D.J. Vidyadhara
- Department of Neurology, Yale University, CT, USA
- Department of Neuroscience, Yale University, CT, USA
| | - Ben-Zheng Li
- Department of Physiology and Biophysics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Electrical Engineering, University of Colorado, Denver, Denver, CO, USA
| | - Michael Zimmerman
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
- Department of Biomedical Engineering, Purdue University, West Lafayette, IN 47907, USA
| | - Alexandr Pak
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Sanghamitra Nareddula
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Paige Alyssa Edens
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
| | - Sreeganga S. Chandra
- Department of Neurology, Yale University, CT, USA
- Department of Neuroscience, Yale University, CT, USA
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale University, CT, USA
| | - Alexander A. Chubykin
- Department of Biological Sciences, Purdue Institute for Integrative Neuroscience, Purdue Autism Research Center, Purdue University, West Lafayette, IN 47907, USA
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19
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Li JY, Glickfeld LL. Input-specific synaptic depression shapes temporal integration in mouse visual cortex. Neuron 2023; 111:3255-3269.e6. [PMID: 37543037 PMCID: PMC10592405 DOI: 10.1016/j.neuron.2023.07.003] [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: 01/23/2023] [Revised: 06/07/2023] [Accepted: 07/06/2023] [Indexed: 08/07/2023]
Abstract
Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, brief stimulus presentation engages a distinct adaptation mechanism from that previously reported in response to prolonged stimuli, enabling flexible control of sensory encoding across a wide range of timescales.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA.
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20
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Yiu YH, Leibold C. A theory of hippocampal theta correlations accounting for extrinsic and intrinsic sequences. eLife 2023; 12:RP86837. [PMID: 37792453 PMCID: PMC10550285 DOI: 10.7554/elife.86837] [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] [Indexed: 10/05/2023] Open
Abstract
Hippocampal place cell sequences have been hypothesized to serve as diverse purposes as the induction of synaptic plasticity, formation and consolidation of long-term memories, or navigation and planning. During spatial behaviors of rodents, sequential firing of place cells at the theta timescale (known as theta sequences) encodes running trajectories, which can be considered as one-dimensional behavioral sequences of traversed locations. In a two-dimensional space, however, each single location can be visited along arbitrary one-dimensional running trajectories. Thus, a place cell will generally take part in multiple different theta sequences, raising questions about how this two-dimensional topology can be reconciled with the idea of hippocampal sequences underlying memory of (one-dimensional) episodes. Here, we propose a computational model of cornu ammonis 3 (CA3) and dentate gyrus (DG), where sensorimotor input drives the direction-dependent (extrinsic) theta sequences within CA3 reflecting the two-dimensional spatial topology, whereas the intrahippocampal CA3-DG projections concurrently produce intrinsic sequences that are independent of the specific running trajectory. Consistent with experimental data, intrinsic theta sequences are less prominent, but can nevertheless be detected during theta activity, thereby serving as running-direction independent landmark cues. We hypothesize that the intrinsic sequences largely reflect replay and preplay activity during non-theta states.
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Affiliation(s)
- Yuk-Hoi Yiu
- Fakultät für Biologie & Bernstein Center Freiburg Albert-Ludwigs-Universität FreiburgFreiburgGermany
- Graduate School of Systemic Neurosciences, Ludwig-Maximilians-Universität MünchenMunichGermany
| | - Christian Leibold
- Fakultät für Biologie & Bernstein Center Freiburg Albert-Ludwigs-Universität FreiburgFreiburgGermany
- BrainLinks-BrainTools, Albert-Ludwigs-Universität FreiburgFreiburgGermany
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21
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Schmid D, Jarvers C, Neumann H. Canonical circuit computations for computer vision. BIOLOGICAL CYBERNETICS 2023; 117:299-329. [PMID: 37306782 PMCID: PMC10600314 DOI: 10.1007/s00422-023-00966-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 05/18/2023] [Indexed: 06/13/2023]
Abstract
Advanced computer vision mechanisms have been inspired by neuroscientific findings. However, with the focus on improving benchmark achievements, technical solutions have been shaped by application and engineering constraints. This includes the training of neural networks which led to the development of feature detectors optimally suited to the application domain. However, the limitations of such approaches motivate the need to identify computational principles, or motifs, in biological vision that can enable further foundational advances in machine vision. We propose to utilize structural and functional principles of neural systems that have been largely overlooked. They potentially provide new inspirations for computer vision mechanisms and models. Recurrent feedforward, lateral, and feedback interactions characterize general principles underlying processing in mammals. We derive a formal specification of core computational motifs that utilize these principles. These are combined to define model mechanisms for visual shape and motion processing. We demonstrate how such a framework can be adopted to run on neuromorphic brain-inspired hardware platforms and can be extended to automatically adapt to environment statistics. We argue that the identified principles and their formalization inspires sophisticated computational mechanisms with improved explanatory scope. These and other elaborated, biologically inspired models can be employed to design computer vision solutions for different tasks and they can be used to advance neural network architectures of learning.
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Affiliation(s)
- Daniel Schmid
- Institute for Neural Information Processing, Ulm University, James-Franck-Ring, Ulm, 89081 Germany
| | - Christian Jarvers
- Institute for Neural Information Processing, Ulm University, James-Franck-Ring, Ulm, 89081 Germany
| | - Heiko Neumann
- Institute for Neural Information Processing, Ulm University, James-Franck-Ring, Ulm, 89081 Germany
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22
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Zhou J, Chen A, Zhang Y, Pu D, Qiao B, Hu J, Li H, Zhong S, Zhao R, Xue F, Xu Y, Loh KP, Wang H, Yu B. 2D Ferroionics: Conductive Switching Mechanisms and Transition Boundaries in Van der Waals Layered Material CuInP 2 S 6. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2023; 35:e2302419. [PMID: 37352331 DOI: 10.1002/adma.202302419] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/30/2023] [Indexed: 06/25/2023]
Abstract
The recently unfolded ferroionic phenomena in 2D van der Waals (vdW) copper-indium-thiophosphate (CuInP2 S6 or CIPS) have received widespread interest as they allow for dynamic control of conductive switching properties, which are appealing in the paradigm-shift computing. The intricate couplings between ferroelectric polarization and ionic conduction in 2D vdW CIPS facilitate the manipulation and dynamic control of conductive behaviors. However, the complex interplays and underlying mechanisms are not yet fully explored and understood. Here, by investigating polarization switching and ionic conduction in the temperature and applied electric field domains, it is discovered that the conducting mechanisms of CIPS can be divided into four distinctive states (or modes) with transitional boundaries, depending on the dynamics of Cu ions in the material. Further, it demonstrates that dynamically-tunable synaptic responsive behavior can be well implemented by governing the working-state transition. This research provides an in-depth, quantitative understanding of the complex phenomena of conductive switching in 2D vdW CIPS with coexisting ferroelectric order and ionic disorder. The developed insights in this work lay the ground for implementing high-performance, function-enriched devices for information processing, data storage, and neuromorphic computing based on the 2D ferroionic material systems.
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Affiliation(s)
- Jiachao Zhou
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Anzhe Chen
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Yishu Zhang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Dong Pu
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
- Joint Institute of Zhejiang University and the University of Illinois at Urbana-Champaign, Zhejiang University, Haining, 314400, China
| | - Baoshi Qiao
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
- Joint Institute of Zhejiang University and the University of Illinois at Urbana-Champaign, Zhejiang University, Haining, 314400, China
| | - Jiayang Hu
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Hanxi Li
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Shuai Zhong
- Guangdong Institute of Intelligence Science and Technology, Hengqin, Zhuhai, 519031, China
- Center for Brain-Inspired Computing Research, Tsinghua University, Beijing, 100084, China
| | - Rong Zhao
- Center for Brain-Inspired Computing Research, Tsinghua University, Beijing, 100084, China
| | - Fei Xue
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Yang Xu
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
- Joint Institute of Zhejiang University and the University of Illinois at Urbana-Champaign, Zhejiang University, Haining, 314400, China
| | - Kian Ping Loh
- Department of Applied Physics, Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China
| | - Hua Wang
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
| | - Bin Yu
- School of Micro-Nano Electronics, Zhejiang University, Hangzhou, 310027, China
- ZJU-Hangzhou Global Scientific and Technological Innovation Center, Hangzhou, 310027, China
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23
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Asopa A, Bhalla US. A computational view of short-term plasticity and its implications for E-I balance. Curr Opin Neurobiol 2023; 81:102729. [PMID: 37245258 DOI: 10.1016/j.conb.2023.102729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 03/30/2023] [Accepted: 04/25/2023] [Indexed: 05/30/2023]
Abstract
Short-term plasticity (STP) and excitatory-inhibitory balance (EI balance) are both ubiquitous building blocks of brain circuits across the animal kingdom. The synapses involved in EI are also subject to short-term plasticity, and several experimental studies have shown that their effects overlap. Recent computational and theoretical work has begun to highlight the functional implications of the intersection of these motifs. The findings are nuanced: while there are general computational themes, such as pattern tuning, normalization, and gating, much of the richness of these interactions comes from region- and modality specific tuning of STP properties. Together these findings point towards the STP-EI balance combination as being a versatile and highly efficient neural building block for a wide range of pattern-specific responses.
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Affiliation(s)
- Aditya Asopa
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road, Bengaluru, 560065, India. https://twitter.com/adityaasopa
| | - Upinder S Bhalla
- National Centre for Biological Sciences, Tata Institute of Fundamental Research, Bellary Road, Bengaluru, 560065, India.
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24
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Petroccione MA, D'Brant LY, Affinnih N, Wehrle PH, Todd GC, Zahid S, Chesbro HE, Tschang IL, Scimemi A. Neuronal glutamate transporters control reciprocal inhibition and gain modulation in D1 medium spiny neurons. eLife 2023; 12:e81830. [PMID: 37435808 PMCID: PMC10411972 DOI: 10.7554/elife.81830] [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: 07/13/2022] [Accepted: 07/09/2023] [Indexed: 07/13/2023] Open
Abstract
Understanding the function of glutamate transporters has broad implications for explaining how neurons integrate information and relay it through complex neuronal circuits. Most of what is currently known about glutamate transporters, specifically their ability to maintain glutamate homeostasis and limit glutamate diffusion away from the synaptic cleft, is based on studies of glial glutamate transporters. By contrast, little is known about the functional implications of neuronal glutamate transporters. The neuronal glutamate transporter EAAC1 is widely expressed throughout the brain, particularly in the striatum, the primary input nucleus of the basal ganglia, a region implicated with movement execution and reward. Here, we show that EAAC1 limits synaptic excitation onto a population of striatal medium spiny neurons identified for their expression of D1 dopamine receptors (D1-MSNs). In these cells, EAAC1 also contributes to strengthen lateral inhibition from other D1-MSNs. Together, these effects contribute to reduce the gain of the input-output relationship and increase the offset at increasing levels of synaptic inhibition in D1-MSNs. By reducing the sensitivity and dynamic range of action potential firing in D1-MSNs, EAAC1 limits the propensity of mice to rapidly switch between behaviors associated with different reward probabilities. Together, these findings shed light on some important molecular and cellular mechanisms implicated with behavior flexibility in mice.
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Affiliation(s)
| | | | | | | | | | - Shergil Zahid
- SUNY Albany, Department of BiologyAlbanyUnited States
| | | | - Ian L Tschang
- SUNY Albany, Department of BiologyAlbanyUnited States
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25
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Sawicki J, Berner R, Loos SAM, Anvari M, Bader R, Barfuss W, Botta N, Brede N, Franović I, Gauthier DJ, Goldt S, Hajizadeh A, Hövel P, Karin O, Lorenz-Spreen P, Miehl C, Mölter J, Olmi S, Schöll E, Seif A, Tass PA, Volpe G, Yanchuk S, Kurths J. Perspectives on adaptive dynamical systems. CHAOS (WOODBURY, N.Y.) 2023; 33:071501. [PMID: 37486668 DOI: 10.1063/5.0147231] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 05/24/2023] [Indexed: 07/25/2023]
Abstract
Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems, such as the power grid, social, and neural networks, and they form the backbone of closed-loop control strategies and machine learning algorithms. In this article, we provide an interdisciplinary perspective on adaptive systems. We reflect on the notion and terminology of adaptivity in different disciplines and discuss which role adaptivity plays for various fields. We highlight common open challenges and give perspectives on future research directions, looking to inspire interdisciplinary approaches.
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Affiliation(s)
- Jakub Sawicki
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Rico Berner
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Sarah A M Loos
- DAMTP, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA, United Kingdom
| | - Mehrnaz Anvari
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Fraunhofer Institute for Algorithms and Scientific Computing, Schloss Birlinghoven, 53757 Sankt-Augustin, Germany
| | - Rolf Bader
- Institute of Systematic Musicology, University of Hamburg, Hamburg, Germany
| | - Wolfram Barfuss
- Transdisciplinary Research Area: Sustainable Futures, University of Bonn, 53113 Bonn, Germany
- Center for Development Research (ZEF), University of Bonn, 53113 Bonn, Germany
| | - Nicola Botta
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science and Engineering, Chalmers University of Technology, 412 96 Göteborg, Sweden
| | - Nuria Brede
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Computer Science, University of Potsdam, An der Bahn 2, 14476 Potsdam, Germany
| | - Igor Franović
- Scientific Computing Laboratory, Center for the Study of Complex Systems, Institute of Physics Belgrade, University of Belgrade, Pregrevica 118, 11080 Belgrade, Serbia
| | - Daniel J Gauthier
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Sebastian Goldt
- Department of Physics, International School of Advanced Studies (SISSA), Trieste, Italy
| | - Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Magdeburg, Germany
| | - Philipp Hövel
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
| | - Omer Karin
- Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
| | - Philipp Lorenz-Spreen
- Center for Adaptive Rationality, Max Planck Institute for Human Development, Lentzeallee 94, 14195 Berlin, Germany
| | - Christoph Miehl
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Jan Mölter
- Department of Mathematics, School of Computation, Information and Technology, Technical University of Munich, Boltzmannstraße 3, 85748 Garching bei München, Germany
| | - Simona Olmi
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Eckehard Schöll
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Akademie Basel, Fachhochschule Nordwestschweiz FHNW, Leonhardsstrasse 6, 4009 Basel, Switzerland
| | - Alireza Seif
- Pritzker School of Molecular Engineering, The University of Chicago, Chicago, Illinois 60637, USA
| | - Peter A Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, California 94304, USA
| | - Giovanni Volpe
- Department of Physics, University of Gothenburg, Gothenburg, Sweden
| | - Serhiy Yanchuk
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
| | - Jürgen Kurths
- Potsdam Institute for Climate Impact Research, Telegrafenberg, 14473 Potsdam, Germany
- Department of Physics, Humboldt-Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany
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26
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Li C, Zhang X, Chen P, Zhou K, Yu J, Wu G, Xiang D, Jiang H, Wang M, Liu Q. Short-term synaptic plasticity in emerging devices for neuromorphic computing. iScience 2023; 26:106315. [PMID: 36950108 PMCID: PMC10025973 DOI: 10.1016/j.isci.2023.106315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/06/2023] Open
Abstract
Neuromorphic computing is a promising computing paradigm toward building next-generation artificial intelligence machines, in which diverse types of synaptic plasticity play an active role in information processing. Compared to long-term plasticity (LTP) forming the foundation of learning and memory, short-term plasticity (STP) is essential for critical computational functions. So far, the practical applications of LTP have been widely investigated, whereas the implementation of STP in hardware is still elusive. Here, we review the development of STP by bridging the physics in emerging devices and biological behaviors. We explore the computational functions of various STP in biology and review their recent progress. Finally, we discuss the main challenges of introducing STP into synaptic devices and offer the potential approaches to utilize STP to enrich systems' capabilities. This review is expected to provide prospective ideas for implementing STP in emerging devices and may promote the construction of high-level neuromorphic machines.
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Affiliation(s)
- Chao Li
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Key Laboratory of Microelectronics Device & Integrated Technology, Institute of Microelectronics of Chinese Academy of Sciences, Beijing 100029, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xumeng Zhang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Pei Chen
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
| | - Keji Zhou
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Jie Yu
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
| | - Guangjian Wu
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Du Xiang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Hao Jiang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Ming Wang
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
| | - Qi Liu
- State Key Laboratory of Integrated Chip and System, Frontier Institute of Chip and System, Fudan University, Shanghai 200433, China
- Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 200433, China
- Shanghai Qi Zhi Institute, Shanghai 200232, China
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27
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Buchholz MO, Gastone Guilabert A, Ehret B, Schuhknecht GFP. How synaptic strength, short-term plasticity, and input synchrony contribute to neuronal spike output. PLoS Comput Biol 2023; 19:e1011046. [PMID: 37068099 PMCID: PMC10153727 DOI: 10.1371/journal.pcbi.1011046] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 05/02/2023] [Accepted: 03/24/2023] [Indexed: 04/18/2023] Open
Abstract
Neurons integrate from thousands of synapses whose strengths span an order of magnitude. Intriguingly, in mouse neocortex, the few 'strong' synapses are formed between similarly tuned cells, suggesting they determine spiking output. This raises the question of how other computational primitives, including 'background' activity from the many 'weak' synapses, short-term plasticity, and temporal factors contribute to spiking. We used paired recordings and extracellular stimulation experiments to map excitatory postsynaptic potential (EPSP) amplitudes and paired-pulse ratios of synaptic connections formed between pyramidal neurons in layer 2/3 (L2/3) of barrel cortex. While net short-term plasticity was weak, strong synaptic connections were exclusively depressing. Importantly, we found no evidence for clustering of synaptic properties on individual neurons. Instead, EPSPs and paired-pulse ratios of connections converging onto the same cells spanned the full range observed across L2/3, which critically constrains theoretical models of cortical filtering. To investigate how different computational primitives of synaptic information processing interact to shape spiking, we developed a computational model of a pyramidal neuron in the excitatory L2/3 circuitry, which was constrained by our experiments and published in vivo data. We found that strong synapses were substantially depressed during ongoing activation and their ability to evoke correlated spiking primarily depended on their high temporal synchrony and high firing rates observed in vivo. However, despite this depression, their larger EPSP amplitudes strongly amplified information transfer and responsiveness. Thus, our results contribute to a nuanced framework of how cortical neurons exploit synergies between temporal coding, synaptic properties, and noise to transform synaptic inputs into spikes.
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Affiliation(s)
- Moritz O Buchholz
- Institute of Neuroinformatics, University of Zürich and ETH Zürich Zürich, Switzerland
| | | | - Benjamin Ehret
- Institute of Neuroinformatics, University of Zürich and ETH Zürich Zürich, Switzerland
| | - Gregor F P Schuhknecht
- Institute of Neuroinformatics, University of Zürich and ETH Zürich Zürich, Switzerland
- Department of Molecular and Cellular Biology, Harvard University Cambridge, Massachusetts, United States of America
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28
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Liao J, Wen W, Wu J, Zhou Y, Hussain S, Hu H, Li J, Liaqat A, Zhu H, Jiao L, Zheng Q, Xie L. Van der Waals Ferroelectric Semiconductor Field Effect Transistor for In-Memory Computing. ACS NANO 2023; 17:6095-6102. [PMID: 36912657 DOI: 10.1021/acsnano.3c01198] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
In-memory computing is a highly efficient approach for breaking the bottleneck of von Neumann architectures, i.e., reducing redundant latency and energy consumption during the data transfer between the physically separated memory and processing units. Herein we have designed a in-memory computing device, a van der Waals ferroelectric semiconductor (InSe) based metal-oxide-ferroelectric semiconductor field-effect transistor (MOfeS-FET). This MOfeS-FET integrates memory and logic functions in the same material, in which the out-of-plane (OOP) ferroelectric polarization in InSe is used for data storage and the semiconducting property is used for the logic computation. The MOfeS-FET shows a long retention time with high on/off ratios (>106), high program/erase (P/E) ratios (103), and stable cyclic endurance. Moreover, inverter, programmable NAND, and NOR Boolean logic operations with nonvolatile storage of the results have all been demonstrated using our approach. These findings highlight the potential of van der Waals ferroelectric semiconductor-based MOfeS-FETs in the in-memory computing and their potential of achieving size scaling beyond Moore's law.
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Affiliation(s)
- Junyi Liao
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
- Department of Chemistry, Tsinghua University, Beijing 100084, P.R. China
- University of Chinese Academy of Sciences, Beijing 100049, P.R. China
| | - Wen Wen
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
| | - Juanxia Wu
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
| | - Yaming Zhou
- Department of Chemistry, Tsinghua University, Beijing 100084, P.R. China
| | - Sabir Hussain
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
| | - Haowen Hu
- School of Materials Science and Engineering, Tsinghua University, Beijing 100084, P.R. China
| | - Jiawei Li
- School of Materials Science and Engineering, Tsinghua University, Beijing 100084, P.R. China
| | - Adeel Liaqat
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
| | - Hongwei Zhu
- School of Materials Science and Engineering, Tsinghua University, Beijing 100084, P.R. China
| | - Liying Jiao
- Department of Chemistry, Tsinghua University, Beijing 100084, P.R. China
| | - Qiang Zheng
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
- University of Chinese Academy of Sciences, Beijing 100049, P.R. China
| | - Liming Xie
- CAS Key Laboratory of Standardization and Measurement for Nanotechnology, National Center for Nanoscience and Technology, Beijing 100190, P.R. China
- University of Chinese Academy of Sciences, Beijing 100049, P.R. China
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29
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Li JY, Glickfeld LL. Input-specific synaptic depression shapes temporal integration in mouse visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.30.526211. [PMID: 36778279 PMCID: PMC9915496 DOI: 10.1101/2023.01.30.526211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Efficient sensory processing requires the nervous system to adjust to ongoing features of the environment. In primary visual cortex (V1), neuronal activity strongly depends on recent stimulus history. Existing models can explain effects of prolonged stimulus presentation, but remain insufficient for explaining effects observed after shorter durations commonly encountered under natural conditions. We investigated the mechanisms driving adaptation in response to brief (100 ms) stimuli in L2/3 V1 neurons by performing in vivo whole-cell recordings to measure membrane potential and synaptic inputs. We find that rapid adaptation is generated by stimulus-specific suppression of excitatory and inhibitory synaptic inputs. Targeted optogenetic experiments reveal that these synaptic effects are due to input-specific short-term depression of transmission between layers 4 and 2/3. Thus, distinct mechanisms are engaged following brief and prolonged stimulus presentation and together enable flexible control of sensory encoding across a wide range of time scales.
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Affiliation(s)
- Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27701, USA
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30
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Barri A, Wiechert MT, Jazayeri M, DiGregorio DA. Synaptic basis of a sub-second representation of time in a neural circuit model. Nat Commun 2022; 13:7902. [PMID: 36550115 PMCID: PMC9780315 DOI: 10.1038/s41467-022-35395-y] [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: 03/31/2022] [Accepted: 11/29/2022] [Indexed: 12/24/2022] Open
Abstract
Temporal sequences of neural activity are essential for driving well-timed behaviors, but the underlying cellular and circuit mechanisms remain elusive. We leveraged the well-defined architecture of the cerebellum, a brain region known to support temporally precise actions, to explore theoretically whether the experimentally observed diversity of short-term synaptic plasticity (STP) at the input layer could generate neural dynamics sufficient for sub-second temporal learning. A cerebellar circuit model equipped with dynamic synapses produced a diverse set of transient granule cell firing patterns that provided a temporal basis set for learning precisely timed pauses in Purkinje cell activity during simulated delay eyelid conditioning and Bayesian interval estimation. The learning performance across time intervals was influenced by the temporal bandwidth of the temporal basis, which was determined by the input layer synaptic properties. The ubiquity of STP throughout the brain positions it as a general, tunable cellular mechanism for sculpting neural dynamics and fine-tuning behavior.
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Affiliation(s)
- A. Barri
- grid.508487.60000 0004 7885 7602Institut Pasteur, Université Paris Cité, Synapse and Circuit Dynamics Laboratory, CNRS UMR 3571 Paris, France
| | - M. T. Wiechert
- grid.508487.60000 0004 7885 7602Institut Pasteur, Université Paris Cité, Synapse and Circuit Dynamics Laboratory, CNRS UMR 3571 Paris, France
| | - M. Jazayeri
- grid.116068.80000 0001 2341 2786McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA USA ,grid.116068.80000 0001 2341 2786Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA USA
| | - D. A. DiGregorio
- grid.508487.60000 0004 7885 7602Institut Pasteur, Université Paris Cité, Synapse and Circuit Dynamics Laboratory, CNRS UMR 3571 Paris, France
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31
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Pietras B, Schmutz V, Schwalger T. Mesoscopic description of hippocampal replay and metastability in spiking neural networks with short-term plasticity. PLoS Comput Biol 2022; 18:e1010809. [PMID: 36548392 PMCID: PMC9822116 DOI: 10.1371/journal.pcbi.1010809] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 01/06/2023] [Accepted: 12/11/2022] [Indexed: 12/24/2022] Open
Abstract
Bottom-up models of functionally relevant patterns of neural activity provide an explicit link between neuronal dynamics and computation. A prime example of functional activity patterns are propagating bursts of place-cell activities called hippocampal replay, which is critical for memory consolidation. The sudden and repeated occurrences of these burst states during ongoing neural activity suggest metastable neural circuit dynamics. As metastability has been attributed to noise and/or slow fatigue mechanisms, we propose a concise mesoscopic model which accounts for both. Crucially, our model is bottom-up: it is analytically derived from the dynamics of finite-size networks of Linear-Nonlinear Poisson neurons with short-term synaptic depression. As such, noise is explicitly linked to stochastic spiking and network size, and fatigue is explicitly linked to synaptic dynamics. To derive the mesoscopic model, we first consider a homogeneous spiking neural network and follow the temporal coarse-graining approach of Gillespie to obtain a "chemical Langevin equation", which can be naturally interpreted as a stochastic neural mass model. The Langevin equation is computationally inexpensive to simulate and enables a thorough study of metastable dynamics in classical setups (population spikes and Up-Down-states dynamics) by means of phase-plane analysis. An extension of the Langevin equation for small network sizes is also presented. The stochastic neural mass model constitutes the basic component of our mesoscopic model for replay. We show that the mesoscopic model faithfully captures the statistical structure of individual replayed trajectories in microscopic simulations and in previously reported experimental data. Moreover, compared to the deterministic Romani-Tsodyks model of place-cell dynamics, it exhibits a higher level of variability regarding order, direction and timing of replayed trajectories, which seems biologically more plausible and could be functionally desirable. This variability is the product of a new dynamical regime where metastability emerges from a complex interplay between finite-size fluctuations and local fatigue.
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Affiliation(s)
- Bastian Pietras
- Institute for Mathematics, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
- Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Valentin Schmutz
- Brain Mind Institute, School of Computer and Communication Sciences and School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Tilo Schwalger
- Institute for Mathematics, Technische Universität Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
- * E-mail:
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32
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Marquis M, Wilson RI. Locomotor and olfactory responses in dopamine neurons of the Drosophila superior-lateral brain. Curr Biol 2022; 32:5406-5414.e5. [PMID: 36450284 DOI: 10.1016/j.cub.2022.11.008] [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: 06/24/2022] [Revised: 08/17/2022] [Accepted: 11/03/2022] [Indexed: 12/03/2022]
Abstract
The Drosophila brain contains about 50 distinct morphological types of dopamine neurons.1,2,3,4 Physiological studies of Drosophila dopamine neurons have been largely limited to one brain region, the mushroom body,5,6,7,8,9,10,11,12,13 where they are implicated in learning.14,15,16,17,18 By comparison, we know little about the physiology of other Drosophila dopamine neurons. Interestingly, a recent whole-brain imaging study found that dopamine neuron activity in several fly brain regions is correlated with locomotion.19 This is notable because many dopamine neurons in the rodent brain are also correlated with locomotion or other movements20,21,22,23,24,25,26,27,28,29,30; however, most rodent studies have focused on learned and rewarded behaviors, and few have investigated dopamine neuron activity during spontaneous (self-timed) movements. In this study, we monitored dopamine neurons in the Drosophila brain during self-timed locomotor movements, focusing on several previously uncharacterized cell types that arborize in the superior-lateral brain, specifically the lateral horn and superior-lateral protocerebrum. We found that activity of all of these dopamine neurons correlated with spontaneous fluctuations in walking speed, with different cell types showing different speed correlations. Some dopamine neurons also responded to odors, but these responses were suppressed by repeated odor encounters. Finally, we found that the same identifiable dopamine neuron can encode different combinations of locomotion and odor in different individuals. If these dopamine neurons promote synaptic plasticity-like the dopamine neurons of the mushroom body-then, their tuning profiles would imply that plasticity depends on a flexible integration of sensory signals, motor signals, and recent experience.
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Affiliation(s)
- Michael Marquis
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA
| | - Rachel I Wilson
- Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.
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33
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Mushtaq M, Marshall L, Bazhenov M, Mölle M, Martinetz T. Differential thalamocortical interactions in slow and fast spindle generation: A computational model. PLoS One 2022; 17:e0277772. [PMID: 36508417 PMCID: PMC9744318 DOI: 10.1371/journal.pone.0277772] [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: 04/28/2022] [Accepted: 11/02/2022] [Indexed: 12/14/2022] Open
Abstract
Cortical slow oscillations (SOs) and thalamocortical sleep spindles are two prominent EEG rhythms of slow wave sleep. These EEG rhythms play an essential role in memory consolidation. In humans, sleep spindles are categorized into slow spindles (8-12 Hz) and fast spindles (12-16 Hz), with different properties. Slow spindles that couple with the up-to-down phase of the SO require more experimental and computational investigation to disclose their origin, functional relevance and most importantly their relation with SOs regarding memory consolidation. To examine slow spindles, we propose a biophysical thalamocortical model with two independent thalamic networks (one for slow and the other for fast spindles). Our modeling results show that fast spindles lead to faster cortical cell firing, and subsequently increase the amplitude of the cortical local field potential (LFP) during the SO down-to-up phase. Slow spindles also facilitate cortical cell firing, but the response is slower, thereby increasing the cortical LFP amplitude later, at the SO up-to-down phase of the SO cycle. Neither the SO rhythm nor the duration of the SO down state is affected by slow spindle activity. Furthermore, at a more hyperpolarized membrane potential level of fast thalamic subnetwork cells, the activity of fast spindles decreases, while the slow spindles activity increases. Together, our model results suggest that slow spindles may facilitate the initiation of the following SO cycle, without however affecting expression of the SO Up and Down states.
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Affiliation(s)
| | - Lisa Marshall
- Institute of Experimental and Clinical Pharmacology, University of Lübeck, Lübeck, Germany
- Center for Brain, Behavior and Metabolism, Lübeck, Germany
- University Clinic Hospital Schleswig Holstein, Lübeck, Germany
| | - Maxim Bazhenov
- Department of Medicine, University of California, San Diego, La Jolla, California, United States of America
| | - Matthias Mölle
- Center for Brain, Behavior and Metabolism, Lübeck, Germany
| | - Thomas Martinetz
- Institute for Neuro- and Bioinformatics, Lübeck, Germany
- Center for Brain, Behavior and Metabolism, Lübeck, Germany
- * E-mail:
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34
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Cordella F, Ferrucci L, D’Antoni C, Ghirga S, Brighi C, Soloperto A, Gigante Y, Ragozzino D, Bezzi P, Di Angelantonio S. Human iPSC-Derived Cortical Neurons Display Homeostatic Plasticity. LIFE (BASEL, SWITZERLAND) 2022; 12:life12111884. [PMID: 36431019 PMCID: PMC9696876 DOI: 10.3390/life12111884] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 11/03/2022] [Accepted: 11/11/2022] [Indexed: 11/16/2022]
Abstract
Maintaining the excitability of neurons and circuits is fundamental for healthy brain functions. The global compensatory increase in excitatory synaptic strength, in response to decreased activity, is one of the main homeostatic mechanisms responsible for such regulation. This type of plasticity has been extensively characterized in rodents in vivo and in vitro, but few data exist on human neurons maturation. We have generated an in vitro cortical model system, based on differentiated human-induced pluripotent stem cells, chronically treated with tetrodotoxin, to investigate homeostatic plasticity at different developmental stages. Our findings highlight the presence of homeostatic plasticity in human cortical networks and show that the changes in synaptic strength are due to both pre- and post-synaptic mechanisms. Pre-synaptic plasticity involves the potentiation of neurotransmitter release machinery, associated to an increase in synaptic vesicle proteins expression. At the post-synaptic level, we report an increase in the expression of post-synaptic density proteins, involved in glutamatergic receptor anchoring. These results extend our understanding of neuronal homeostasis and reveal the developmental regulation of its expression in human cortical networks. Since induced pluripotent stem cell-derived neurons can be obtained from patients with neurodevelopmental and neurodegenerative diseases, our platform offers a versatile model for assessing human neural plasticity under physiological and pathological conditions.
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Affiliation(s)
- Federica Cordella
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Laura Ferrucci
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
| | - Chiara D’Antoni
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Silvia Ghirga
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Carlo Brighi
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- CrestOptics S.p.A., Via di Torre Rossa 66, 00165 Rome, Italy
| | - Alessandro Soloperto
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Ylenia Gigante
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- D-Tails s.r.l., Via di Torre Rossa 66, 00165 Rome, Italy
| | - Davide Ragozzino
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Santa Lucia Foundation, European Center for Brain Research, 00143 Rome, Italy
| | - Paola Bezzi
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Department of Fundamental Neurosciences, University of Lausanne, 1015 Lausanne, Switzerland
- Correspondence: or (P.B.); or (S.D.A.)
| | - Silvia Di Angelantonio
- Department of Physiology and Pharmacology, Sapienza University of Rome, 00185 Rome, Italy
- Center for Life Nano- & Neuro-Science of Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- D-Tails s.r.l., Via di Torre Rossa 66, 00165 Rome, Italy
- Correspondence: or (P.B.); or (S.D.A.)
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35
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Gansel KS. Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding. Front Integr Neurosci 2022; 16:900715. [PMID: 36262373 PMCID: PMC9574343 DOI: 10.3389/fnint.2022.900715] [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: 03/21/2022] [Accepted: 09/13/2022] [Indexed: 11/13/2022] Open
Abstract
Synchronization of neuronal discharges on the millisecond scale has long been recognized as a prevalent and functionally important attribute of neural activity. In this article, I review classical concepts and corresponding evidence of the mechanisms that govern the synchronization of distributed discharges in cortical networks and relate those mechanisms to their possible roles in coding and cognitive functions. To accommodate the need for a selective, directed synchronization of cells, I propose that synchronous firing of distributed neurons is a natural consequence of spike-timing-dependent plasticity (STDP) that associates cells repetitively receiving temporally coherent input: the “synchrony through synaptic plasticity” hypothesis. Neurons that are excited by a repeated sequence of synaptic inputs may learn to selectively respond to the onset of this sequence through synaptic plasticity. Multiple neurons receiving coherent input could thus actively synchronize their firing by learning to selectively respond at corresponding temporal positions. The hypothesis makes several predictions: first, the position of the cells in the network, as well as the source of their input signals, would be irrelevant as long as their input signals arrive simultaneously; second, repeating discharge patterns should get compressed until all or some part of the signals are synchronized; and third, this compression should be accompanied by a sparsening of signals. In this way, selective groups of cells could emerge that would respond to some recurring event with synchronous firing. Such a learned response pattern could further be modulated by synchronous network oscillations that provide a dynamic, flexible context for the synaptic integration of distributed signals. I conclude by suggesting experimental approaches to further test this new hypothesis.
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36
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Hajizadeh A, Matysiak A, Wolfrum M, May PJC, König R. Auditory cortex modelled as a dynamical network of oscillators: understanding event-related fields and their adaptation. BIOLOGICAL CYBERNETICS 2022; 116:475-499. [PMID: 35718809 PMCID: PMC9287241 DOI: 10.1007/s00422-022-00936-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 05/07/2022] [Indexed: 06/15/2023]
Abstract
Adaptation, the reduction of neuronal responses by repetitive stimulation, is a ubiquitous feature of auditory cortex (AC). It is not clear what causes adaptation, but short-term synaptic depression (STSD) is a potential candidate for the underlying mechanism. In such a case, adaptation can be directly linked with the way AC produces context-sensitive responses such as mismatch negativity and stimulus-specific adaptation observed on the single-unit level. We examined this hypothesis via a computational model based on AC anatomy, which includes serially connected core, belt, and parabelt areas. The model replicates the event-related field (ERF) of the magnetoencephalogram as well as ERF adaptation. The model dynamics are described by excitatory and inhibitory state variables of cell populations, with the excitatory connections modulated by STSD. We analysed the system dynamics by linearising the firing rates and solving the STSD equation using time-scale separation. This allows for characterisation of AC dynamics as a superposition of damped harmonic oscillators, so-called normal modes. We show that repetition suppression of the N1m is due to a mixture of causes, with stimulus repetition modifying both the amplitudes and the frequencies of the normal modes. In this view, adaptation results from a complete reorganisation of AC dynamics rather than a reduction of activity in discrete sources. Further, both the network structure and the balance between excitation and inhibition contribute significantly to the rate with which AC recovers from adaptation. This lifetime of adaptation is longer in the belt and parabelt than in the core area, despite the time constants of STSD being spatially homogeneous. Finally, we critically evaluate the use of a single exponential function to describe recovery from adaptation.
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Affiliation(s)
- Aida Hajizadeh
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Artur Matysiak
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
| | - Matthias Wolfrum
- Weierstrass Institute for Applied Analysis and Stochastics, Mohrenstraße 39, 10117 Berlin, Germany
| | - Patrick J. C. May
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
- Department of Psychology, Lancaster University, Lancaster, LA1 4YF UK
| | - Reinhard König
- Research Group Comparative Neuroscience, Leibniz Institute for Neurobiology, Brenneckestraße 6, 39118 Magdeburg, Germany
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37
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Whalen TC, Parker JE, Gittis AH, Rubin JE. Transmission of delta band (0.5-4 Hz) oscillations from the globus pallidus to the substantia nigra pars reticulata in dopamine depletion. J Comput Neurosci 2022; 51:361-380. [PMID: 37266768 PMCID: PMC10527635 DOI: 10.1007/s10827-023-00853-z] [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: 01/20/2023] [Revised: 01/20/2023] [Accepted: 04/28/2023] [Indexed: 06/03/2023]
Abstract
Parkinson's disease (PD) and animal models of PD feature enhanced oscillations in several frequency bands in the basal ganglia (BG). Past research has emphasized the enhancement of 13-30 Hz beta oscillations. Recently, however, oscillations in the delta band (0.5-4 Hz) have been identified as a robust predictor of dopamine loss and motor dysfunction in several BG regions in mouse models of PD. In particular, delta oscillations in the substantia nigra pars reticulata (SNr) were shown to lead oscillations in motor cortex (M1) and persist under M1 lesion, but it is not clear where these oscillations are initially generated. In this paper, we use a computational model to study how delta oscillations may arise in the SNr due to projections from the globus pallidus externa (GPe). We propose a network architecture that incorporates inhibition in SNr from oscillating GPe neurons and other SNr neurons. In our simulations, this configuration yields firing patterns in model SNr neurons that match those measured in vivo. In particular, we see the spontaneous emergence of near-antiphase active-predicting and inactive-predicting neural populations in the SNr, which persist under the inclusion of STN inputs based on experimental recordings. These results demonstrate how delta oscillations can propagate through BG nuclei despite imperfect oscillatory synchrony in the source site, narrowing down potential targets for the source of delta oscillations in PD models and giving new insight into the dynamics of SNr oscillations.
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Affiliation(s)
- Timothy C Whalen
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
- Design Interactive, Inc., Orlando, FL, United States
| | - John E Parker
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Aryn H Gittis
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, United States
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States
| | - Jonathan E Rubin
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, United States.
- Center for the Neural Basis of Cognition, Pittsburgh, PA, United States.
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38
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Mondal Y, Pena RFO, Rotstein HG. Temporal filters in response to presynaptic spike trains: interplay of cellular, synaptic and short-term plasticity time scales. J Comput Neurosci 2022; 50:395-429. [DOI: 10.1007/s10827-022-00822-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 05/06/2022] [Accepted: 05/25/2022] [Indexed: 10/16/2022]
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39
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Zhu Y, Zhang Y, Xie X, Huang T. An FPGA Accelerator for High-Speed Moving Objects Detection and Tracking With a Spike Camera. Neural Comput 2022; 34:1812-1839. [PMID: 35798326 DOI: 10.1162/neco_a_01507] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Accepted: 02/20/2022] [Indexed: 11/04/2022]
Abstract
Ultra-high-speed object detection and tracking are crucial in fields such as fault detection and scientific observation. Existing solutions to this task have deficiencies in processing speeds. To deal with this difficulty, we propose a neural-inspired ultra-high-speed moving object filtering, detection, and tracking scheme, as well as a corresponding accelerator based on a high-speed spike camera. We parallelize the filtering module and divide the detection module to accelerate the algorithm and balance latency among modules for the benefit of the task-level pipeline. To be specific, a block-based parallel computation model is proposed to accelerate the filtering module, and the detection module is accelerated by a parallel connected component labeling algorithm modeling spike sparsity and spatial connectivity of moving objects with a searching tree. The hardware optimizations include processing the LIF layer with a group of multiplexers to reduce ADD operations and replacing expensive exponential operations with multiplications of preprocessed fixed-point values to increase processing speed and minimize resource consumption. We design an accelerator with the above techniques, achieving 19 times acceleration over the serial version after 25-way parallelization. A processing system for the accelerator is also implemented on the Xilinx ZCU-102 board to validate its functionality and performance. Our accelerator can process more than 20,000 spike images with 250 × 400 resolution per second with 1.618 W dynamic power consumption.
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Affiliation(s)
- Yaoyu Zhu
- School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China
| | - Yu Zhang
- School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China.,Beijing Academy of Artificial Intelligence, Beijing 10084, China
| | - Xiaodong Xie
- School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China
| | - Tiejun Huang
- School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China
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40
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Chen L, Nagaraja C, Daniels S, Fisk ZA, Dvorak R, Meyerdirk L, Steiner JA, Escobar Galvis ML, Henderson MX, Rousseaux MWC, Brundin P, Chu HY. Synaptic location is a determinant of the detrimental effects of α-Synuclein pathology to glutamatergic transmission in the basolateral amygdala. eLife 2022; 11:78055. [PMID: 35775627 PMCID: PMC9286736 DOI: 10.7554/elife.78055] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2022] [Accepted: 06/27/2022] [Indexed: 11/22/2022] Open
Abstract
The presynaptic protein α-synuclein (αSyn) has been suggested to be involved in the pathogenesis of Parkinson’s disease (PD). In PD, the amygdala is prone to develop insoluble αSyn aggregates, and it has been suggested that circuit dysfunction involving the amygdala contributes to the psychiatric symptoms. Yet, how αSyn aggregates affect amygdala function is unknown. In this study, we examined αSyn in glutamatergic axon terminals and the impact of its aggregation on glutamatergic transmission in the basolateral amygdala (BLA). We found that αSyn is primarily present in the vesicular glutamate transporter 1-expressing (vGluT1+) terminals in the mouse BLA, which is consistent with higher levels of αSyn expression in vGluT1+ glutamatergic neurons in the cerebral cortex relative to the vGluT2+ glutamatergic neurons in the thalamus. We found that αSyn aggregation selectively decreased the cortico-BLA, but not the thalamo-BLA, transmission; and that cortico-BLA synapses displayed enhanced short-term depression upon repetitive stimulation. In addition, using confocal microscopy, we found that vGluT1+ axon terminals exhibited decreased levels of soluble αSyn, which suggests that lower levels of soluble αSyn might underlie the enhanced short-term depression of cortico-BLA synapses. In agreement with this idea, we found that cortico-BLA synaptic depression was also enhanced in αSyn knockout mice. In conclusion, both basal and dynamic cortico-BLA transmission were disrupted by abnormal aggregation of αSyn and these changes might be relevant to the perturbed cortical control of the amygdala that has been suggested to play a role in psychiatric symptoms in PD.
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Affiliation(s)
- Liqiang Chen
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
| | - Chetan Nagaraja
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
| | - Samuel Daniels
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
| | - Zoe A Fisk
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada
| | - Rachel Dvorak
- Department of Neurodegenerative Science, Van Andel Institute, GRand Rapids, United States
| | - Lindsay Meyerdirk
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
| | - Jennifer A Steiner
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
| | | | - Michael X Henderson
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
| | - Maxime W C Rousseaux
- Department of Cellular and Molecular Medicine, University of Ottawa, Ottawa, Canada
| | - Patrik Brundin
- Pharma Research and Early Development (pRED), F. Hoffmann-La Roche, Little Falls, United States
| | - Hong-Yuan Chu
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, United States
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A. Samara M, Oikonomou GD, Trompoukis G, Madarou G, Adamopoulou M, Papatheodoropoulos C. Septotemporal variation in modulation of synaptic transmission, paired-pulse ratio and frequency facilitation/depression by adenosine and GABA B receptors in the rat hippocampus. Brain Neurosci Adv 2022; 6:23982128221106315. [PMID: 35782711 PMCID: PMC9240614 DOI: 10.1177/23982128221106315] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Accepted: 05/19/2022] [Indexed: 11/26/2022] Open
Abstract
Short-term synaptic plasticity represents a fundamental mechanism in
neural information processing and is regulated by neuromodulators.
Here, using field recordings from the CA1 region of adult rat
hippocampal slices, we show that excitatory synaptic transmission is
suppressed by strong but not moderate activation of adenosine
A1 receptors by
2-Chloro-N6-cyclopentyladenosine (CCPA) more in the dorsal
than the ventral hippocampus; in contrast, both mild and strong
activation of GABAB receptors by baclofen (1 μM, 10 μM)
suppress synaptic transmission more in the ventral than the dorsal
hippocampus. Using a 10-pulse stimulation train of variable frequency,
we found that CCPA modulates short-term synaptic plasticity
independently of the suppression of synaptic transmission in both
segments of the hippocampus and at stimulation frequencies greater
than 10 Hz. However, specifically regarding the paired-pulse ratio
(PPR) and frequency facilitation/depression (FF/D) we found
significant drug action before but not after adjusting conditioning
responses to control levels. Activation of GABABRs by
baclofen suppressed synaptic transmission more in the ventral than the
dorsal hippocampus. Furthermore, relatively high (10 μM) but not low
(1 μM) baclofen concentration enhanced both PPR and FF in both
hippocampal segments at stimulation frequencies greater than 1 Hz,
independently of the suppression of synaptic transmission by baclofen.
These results show that A1Rs and GABABRs control
synaptic transmission more effectively in the dorsal and the ventral
hippocampus, respectively, and suggest that these receptors modulate
PPR and FF/D at different frequency bands of afferent input, in both
segments of the hippocampus.
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Affiliation(s)
- Maria A. Samara
- Laboratory of Neurophysiology, Department of Medicine, University of Patras, Rion, Greece
| | - George D. Oikonomou
- Laboratory of Neurophysiology, Department of Medicine, University of Patras, Rion, Greece
| | - George Trompoukis
- Laboratory of Neurophysiology, Department of Medicine, University of Patras, Rion, Greece
| | - Georgia Madarou
- Laboratory of Neurophysiology, Department of Medicine, University of Patras, Rion, Greece
| | - Maria Adamopoulou
- Laboratory of Neurophysiology, Department of Medicine, University of Patras, Rion, Greece
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42
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Mizusaki BEP, Li SSY, Costa RP, Sjöström PJ. Pre- and postsynaptically expressed spike-timing-dependent plasticity contribute differentially to neuronal learning. PLoS Comput Biol 2022; 18:e1009409. [PMID: 35700188 PMCID: PMC9236267 DOI: 10.1371/journal.pcbi.1009409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 06/27/2022] [Accepted: 05/11/2022] [Indexed: 11/18/2022] Open
Abstract
A plethora of experimental studies have shown that long-term synaptic plasticity can be expressed pre- or postsynaptically depending on a range of factors such as developmental stage, synapse type, and activity patterns. The functional consequences of this diversity are not clear, although it is understood that whereas postsynaptic expression of plasticity predominantly affects synaptic response amplitude, presynaptic expression alters both synaptic response amplitude and short-term dynamics. In most models of neuronal learning, long-term synaptic plasticity is implemented as changes in connective weights. The consideration of long-term plasticity as a fixed change in amplitude corresponds more closely to post- than to presynaptic expression, which means theoretical outcomes based on this choice of implementation may have a postsynaptic bias. To explore the functional implications of the diversity of expression of long-term synaptic plasticity, we adapted a model of long-term plasticity, more specifically spike-timing-dependent plasticity (STDP), such that it was expressed either independently pre- or postsynaptically, or in a mixture of both ways. We compared pair-based standard STDP models and a biologically tuned triplet STDP model, and investigated the outcomes in a minimal setting, using two different learning schemes: in the first, inputs were triggered at different latencies, and in the second a subset of inputs were temporally correlated. We found that presynaptic changes adjusted the speed of learning, while postsynaptic expression was more efficient at regulating spike timing and frequency. When combining both expression loci, postsynaptic changes amplified the response range, while presynaptic plasticity allowed control over postsynaptic firing rates, potentially providing a form of activity homeostasis. Our findings highlight how the seemingly innocuous choice of implementing synaptic plasticity by single weight modification may unwittingly introduce a postsynaptic bias in modelling outcomes. We conclude that pre- and postsynaptically expressed plasticity are not interchangeable, but enable complimentary functions. Differences between functional properties of pre- or postsynaptically expressed long-term plasticity have not yet been explored in much detail. In this paper, we used minimalist models of STDP with different expression loci, in search of fundamental functional consequences. Biologically, presynaptic expression acts mostly on neurotransmitter release, thereby altering short-term synaptic dynamics, whereas postsynaptic expression affects mainly synaptic gain. We compared models where plasticity was expressed only presynaptically or postsynaptically, or in both ways. We found that postsynaptic plasticity had a bigger impact over response times, while both pre- and postsynaptic plasticity were similarly capable of detecting correlated inputs. A model with biologically tuned expression of plasticity achieved the same outcome over a range of frequencies. Also, postsynaptic spiking frequency was not directly affected by presynaptic plasticity of short-term plasticity alone, however in combination with a postsynaptic component, it helped restrain positive feedback, contributing to activity homeostasis. In conclusion, expression locus may determine affinity for distinct coding schemes while also contributing to keep activity within bounds. Our findings highlight the importance of carefully implementing expression of plasticity in biological modelling, since the locus of expression may affect functional outcomes in simulations.
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Affiliation(s)
- Beatriz Eymi Pimentel Mizusaki
- Centre for Research in Neuroscience, Brain Repair and Integrative Neuroscience Programme, Departments of Medicine, Neurology and Neurosurgery, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, Quebec, Canada
- Instituto de Física, Universidade Federal do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil
- Computational Neuroscience Unit, Department of Computer Science, SCEEM, Faculty of Engineering, University of Bristol, Bristol, United Kingdom
| | - Sally Si Ying Li
- Centre for Research in Neuroscience, Brain Repair and Integrative Neuroscience Programme, Departments of Medicine, Neurology and Neurosurgery, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, Quebec, Canada
| | - Rui Ponte Costa
- Computational Neuroscience Unit, Department of Computer Science, SCEEM, Faculty of Engineering, University of Bristol, Bristol, United Kingdom
- Department of Physiology, University of Bern, Bern, Switzerland
- Centre for Neural Circuits and Behaviour, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, United Kingdom
| | - Per Jesper Sjöström
- Centre for Research in Neuroscience, Brain Repair and Integrative Neuroscience Programme, Departments of Medicine, Neurology and Neurosurgery, The Research Institute of the McGill University Health Centre, Montreal General Hospital, Montreal, Quebec, Canada
- * E-mail:
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43
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Jin L, Behabadi BF, Jadi MP, Ramachandra CA, Mel BW. Classical-Contextual Interactions in V1 May Rely on Dendritic Computations. Neuroscience 2022; 489:234-250. [PMID: 35272004 PMCID: PMC9049952 DOI: 10.1016/j.neuroscience.2022.02.033] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 02/14/2022] [Accepted: 02/27/2022] [Indexed: 12/20/2022]
Abstract
A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange "contextual" information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by "asking" natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The "answer" was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the "multiplicative" center-flanker interactions previously reported in V1 neurons (Kapadia et al., 1995, 2000; Polat et al., 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites - the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.
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Affiliation(s)
- Lei Jin
- USC Neuroscience Graduate Program, United States
| | | | | | | | - Bartlett W Mel
- USC Neuroscience Graduate Program, United States; Department of Biomedical Engineering, University of Southern California, United States.
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44
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Iliescu BF, Hansen B, Dragoi V. Learning by Exposure in the Visual System. Brain Sci 2022; 12:brainsci12040508. [PMID: 35448039 PMCID: PMC9027739 DOI: 10.3390/brainsci12040508] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 04/10/2022] [Accepted: 04/11/2022] [Indexed: 02/04/2023] Open
Abstract
It is increasingly being understood that perceptual learning involves different types of plasticity. Thus, whereas the practice-based improvement in the ability to perform specific tasks is believed to rely on top-down plasticity, the capacity of sensory systems to passively adapt to the stimuli they are exposed to is believed to rely on bottom-up plasticity. However, top-down and bottom-up plasticity have never been investigated concurrently, and hence their relationship is not well understood. To examine whether passive exposure influences perceptual performance, we asked subjects to test their orientation discrimination performance around and orthogonal to the exposed orientation axes, at an exposed and an unexposed location while oriented sine-wave gratings were presented in a fixed position. Here we report that repetitive passive exposure to oriented sequences that are not linked to a specific task induces a persistent, bottom-up form of learning that is stronger than top-down practice learning and generalizes across complex stimulus dimensions. Importantly, orientation-specific exposure learning led to a robust improvement in the discrimination of complex stimuli (shapes and natural scenes). Our results indicate that long-term sensory adaptation by passive exposure should be viewed as a form of perceptual learning that is complementary to practice learning in that it reduces constraints on speed and generalization.
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Affiliation(s)
- Bogdan F. Iliescu
- Neurosurgery Department, Gr T Popa University of medicine and Pharmacy, 700115 Iasi, Romania
- Correspondence:
| | - Bryan Hansen
- Neurobiology and Anatomy, University of Texas-Houston Medical School, Houston, TX 77030, USA; (B.H.); (V.D.)
| | - Valentin Dragoi
- Neurobiology and Anatomy, University of Texas-Houston Medical School, Houston, TX 77030, USA; (B.H.); (V.D.)
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45
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Phillips RS, Rubin JE. Putting the theory into 'burstlet theory' with a biophysical model of burstlets and bursts in the respiratory preBötzinger complex. eLife 2022; 11:75713. [PMID: 35380537 PMCID: PMC9023056 DOI: 10.7554/elife.75713] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2021] [Accepted: 04/04/2022] [Indexed: 11/17/2022] Open
Abstract
Inspiratory breathing rhythms arise from synchronized neuronal activity in a bilaterally distributed brainstem structure known as the preBötzinger complex (preBötC). In in vitro slice preparations containing the preBötC, extracellular potassium must be elevated above physiological levels (to 7–9 mM) to observe regular rhythmic respiratory motor output in the hypoglossal nerve to which the preBötC projects. Reexamination of how extracellular K+ affects preBötC neuronal activity has revealed that low-amplitude oscillations persist at physiological levels. These oscillatory events are subthreshold from the standpoint of transmission to motor output and are dubbed burstlets. Burstlets arise from synchronized neural activity in a rhythmogenic neuronal subpopulation within the preBötC that in some instances may fail to recruit the larger network events, or bursts, required to generate motor output. The fraction of subthreshold preBötC oscillatory events (burstlet fraction) decreases sigmoidally with increasing extracellular potassium. These observations underlie the burstlet theory of respiratory rhythm generation. Experimental and computational studies have suggested that recruitment of the non-rhythmogenic component of the preBötC population requires intracellular Ca2+ dynamics and activation of a calcium-activated nonselective cationic current. In this computational study, we show how intracellular calcium dynamics driven by synaptically triggered Ca2+ influx as well as Ca2+ release/uptake by the endoplasmic reticulum in conjunction with a calcium-activated nonselective cationic current can reproduce and offer an explanation for many of the key properties associated with the burstlet theory of respiratory rhythm generation. Altogether, our modeling work provides a mechanistic basis that can unify a wide range of experimental findings on rhythm generation and motor output recruitment in the preBötC.
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46
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Opposite forms of adaptation in mouse visual cortex are controlled by distinct inhibitory microcircuits. Nat Commun 2022; 13:1031. [PMID: 35210417 PMCID: PMC8873261 DOI: 10.1038/s41467-022-28635-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Accepted: 01/28/2022] [Indexed: 01/29/2023] Open
Abstract
Sensory processing in the cortex adapts to the history of stimulation but the mechanisms are not understood. Imaging the primary visual cortex of mice we find here that an increase in stimulus contrast is not followed by a simple decrease in gain of pyramidal cells; as many cells increase gain to improve detection of a subsequent decrease in contrast. Depressing and sensitizing forms of adaptation also occur in different types of interneurons (PV, SST and VIP) and the net effect within individual pyramidal cells reflects the balance of PV inputs, driving depression, and a subset of SST interneurons driving sensitization. Changes in internal state associated with locomotion increase gain across the population of pyramidal cells while maintaining the balance between these opposite forms of plasticity, consistent with activation of both VIP->SST and SST->PV disinhibitory pathways. These results reveal how different inhibitory microcircuits adjust the gain of pyramidal cells signalling changes in stimulus strength. The authors describe the role of inhibitory microcircuits in the visual cortex of mice in adaptation to contrast. They show how external stimuli and internal state interact to adjust processing in the visual cortex.
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47
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Abstract
The design of robots that interact autonomously with the environment and exhibit complex behaviours is an open challenge that can benefit from understanding what makes living beings fit to act in the world. Neuromorphic engineering studies neural computational principles to develop technologies that can provide a computing substrate for building compact and low-power processing systems. We discuss why endowing robots with neuromorphic technologies - from perception to motor control - represents a promising approach for the creation of robots which can seamlessly integrate in society. We present initial attempts in this direction, highlight open challenges, and propose actions required to overcome current limitations.
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Affiliation(s)
- Chiara Bartolozzi
- Event-Driven Perception for Robotics, Istituto Italiano di Tecnologia, via San Quirico 19D, 16163, Genova, Italy.
| | - Giacomo Indiveri
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Winterthurerstr. 190, 8057, Zurich, Switzerland
| | - Elisa Donati
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Winterthurerstr. 190, 8057, Zurich, Switzerland
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48
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Morabito A, Zerlaut Y, Serraz B, Sala R, Paoletti P, Rebola N. Activity-dependent modulation of NMDA receptors by endogenous zinc shapes dendritic function in cortical neurons. Cell Rep 2022; 38:110415. [PMID: 35196488 PMCID: PMC8889438 DOI: 10.1016/j.celrep.2022.110415] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 12/08/2021] [Accepted: 01/31/2022] [Indexed: 11/11/2022] Open
Abstract
NMDA receptors (NMDARs) have been proposed to control single-neuron computations in vivo. However, whether specific mechanisms regulate the function of such receptors and modulate input-output transformations performed by cortical neurons under in vivo-like conditions is understudied. Here, we report that in layer 2/3 pyramidal neurons (L2/3 PNs), repeated synaptic stimulation results in an activity-dependent decrease in NMDAR function by vesicular zinc. Such a mechanism shifts the threshold for dendritic non-linearities and strongly reduces LTP. Modulation of NMDARs is cell and pathway specific, being present selectively in L2/3-L2/3 connections but absent in inputs originating from L4 neurons. Numerical simulations highlight that activity-dependent modulation of NMDARs influences dendritic computations, endowing L2/3 PN dendrites with the ability to sustain non-linear integrations constant across different regimes of synaptic activity like those found in vivo. Our results unveil vesicular zinc as an important endogenous modulator of dendritic function in cortical PNs. Vesicular zinc release downregulates function of synaptic NMDARs in cortical neurons Zinc modulation of NMDARs is activity dependent, pathway and cell specific Endogenous zinc controls dendritic non-linearities and synaptic plasticity in L2/3 PNs Modulation of NMDARs normalizes dendritic function during ongoing synaptic activity
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Affiliation(s)
- Annunziato Morabito
- Sorbonne Université, Institut Du Cerveau-Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, 47 Boulevard de l'Hôpital, 75013 Paris, France
| | - Yann Zerlaut
- Sorbonne Université, Institut Du Cerveau-Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, 47 Boulevard de l'Hôpital, 75013 Paris, France
| | - Benjamin Serraz
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, Université PSL, CNRS, INSERM, 75005 Paris, France
| | - Romain Sala
- Sorbonne Université, Institut Du Cerveau-Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, 47 Boulevard de l'Hôpital, 75013 Paris, France
| | - Pierre Paoletti
- Institut de Biologie de l'Ecole Normale Supérieure (IBENS), Ecole Normale Supérieure, Université PSL, CNRS, INSERM, 75005 Paris, France
| | - Nelson Rebola
- Sorbonne Université, Institut Du Cerveau-Paris Brain Institute-ICM, Inserm U1127, CNRS UMR 7225, 47 Boulevard de l'Hôpital, 75013 Paris, France.
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Luo ZD, Zhang S, Liu Y, Zhang D, Gan X, Seidel J, Liu Y, Han G, Alexe M, Hao Y. Dual-Ferroelectric-Coupling-Engineered Two-Dimensional Transistors for Multifunctional In-Memory Computing. ACS NANO 2022; 16:3362-3372. [PMID: 35147405 DOI: 10.1021/acsnano.2c00079] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In-memory computing featuring a radical departure from the von Neumann architecture is promising to substantially reduce the energy and time consumption for data-intensive computation. With the increasing challenges facing silicon complementary metal-oxide-semiconductor (CMOS) technology, developing in-memory computing hardware would require a different platform to deliver significantly enhanced functionalities at the material and device level. Here, we explore a dual-gate two-dimensional ferroelectric field-effect transistor (2D FeFET) as a basic device to form both nonvolatile logic gates and artificial synapses, addressing in-memory computing simultaneously in digital and analog spaces. Through diversifying the electrostatic behaviors in 2D transistors with the dual-ferroelectric-coupling effect, rich logic functionalities including linear (AND, OR) and nonlinear (XNOR) gates were obtained in unipolar (MoS2) and ambipolar (MoTe2) FeFETs. Combining both types of 2D FeFETs in a heterogeneous platform, an important computation circuit, i.e., a half-adder, was successfully constructed with an area-efficient two-transistor structure. Furthermore, with the same device structure, several key synaptic functions are shown at the device level, and an artificial neural network is simulated at the system level, manifesting its potential for neuromorphic computing. These findings highlight the prospects of dual-gate 2D FeFETs for the development of multifunctional in-memory computing hardware capable of both digital and analog computation.
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Affiliation(s)
- Zheng-Dong Luo
- State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, P. R. China
| | - Siqing Zhang
- State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, P. R. China
| | - Yan Liu
- State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, P. R. China
| | - Dawei Zhang
- School of Materials Science and Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
| | - Xuetao Gan
- Key Laboratory of Light Field Manipulation and Information Acquisition, Ministry of Industry and Information Technology, and Shaanxi Key Laboratory of Optical Information Technology, School of Physical Science and Technology, Northwestern Polytechnical University, Xi'an 710129, China
| | - Jan Seidel
- School of Materials Science and Engineering, UNSW Sydney, Sydney, NSW 2052, Australia
- ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET), UNSW Sydney, Sydney, NSW 2052, Australia
| | - Yang Liu
- School of Materials Science and Engineering, State Key Laboratory of Material Processing and Die & Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, P. R. China
| | - Genquan Han
- State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, P. R. China
- Emerging Device and Chip Laboratory, Hangzhou Institute of Technology, Xidian University, Hangzhou 311220, P. R. China
| | - Marin Alexe
- Department of Physics, The University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Yue Hao
- State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology, School of Microelectronics, Xidian University, Xi'an 710071, P. R. China
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50
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Input rate encoding and gain control in dendrites of neocortical pyramidal neurons. Cell Rep 2022; 38:110382. [PMID: 35172157 PMCID: PMC8967317 DOI: 10.1016/j.celrep.2022.110382] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 11/15/2021] [Accepted: 01/23/2022] [Indexed: 01/06/2023] Open
Abstract
Elucidating how neurons encode network activity is essential to understanding how the brain processes information. Neocortical pyramidal cells receive excitatory input onto spines distributed along dendritic branches. Local dendritic branch nonlinearities can boost the response to spatially clustered and synchronous input, but how this translates into the integration of patterns of ongoing activity remains unclear. To examine dendritic integration under naturalistic stimulus regimes, we use two-photon glutamate uncaging to repeatedly activate multiple dendritic spines at random intervals. In the proximal dendrites of two populations of layer 5 pyramidal neurons in the mouse motor cortex, spatially restricted synchrony is not a prerequisite for dendritic boosting. Branches encode afferent inputs with distinct rate sensitivities depending upon cell and branch type. Thus, inputs distributed along a dendritic branch can recruit supralinear boosting and the window of this nonlinearity may provide a mechanism by which dendrites can preferentially amplify slow-frequency network oscillations.
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