1
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Bergoin R, Torcini A, Deco G, Quoy M, Zamora-López G. Emergence and maintenance of modularity in neural networks with Hebbian and anti-Hebbian inhibitory STDP. PLoS Comput Biol 2025; 21:e1012973. [PMID: 40262082 PMCID: PMC12054933 DOI: 10.1371/journal.pcbi.1012973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Revised: 05/06/2025] [Accepted: 03/19/2025] [Indexed: 04/24/2025] Open
Abstract
The modular and hierarchical organization of the brain is believed to support the coexistence of segregated (specialization) and integrated (binding) information processes. A relevant question is yet to understand how such architecture naturally emerges and is sustained over time, given the plastic nature of the brain's wiring. Following evidences that the sensory cortices organize into assemblies under selective stimuli, it has been shown that stable neuronal assemblies can emerge due to targeted stimulation, embedding various forms of synaptic plasticity in presence of homeostatic and/or control mechanisms. Here, we show that simple spike-timing-dependent plasticity (STDP) rules, based only on pre- and post-synaptic spike times, can also lead to the stable encoding of memories in the absence of any control mechanism. We develop a model of spiking neurons, trained by stimuli targeting different sub-populations. The model satisfies some biologically plausible features: (i) it contains excitatory and inhibitory neurons with Hebbian and anti-Hebbian STDP; (ii) neither the neuronal activity nor the synaptic weights are frozen after the learning phase. Instead, the neurons are allowed to fire spontaneously while synaptic plasticity remains active. We find that only the combination of two inhibitory STDP sub-populations allows for the formation of stable modules in the network, with each sub-population playing a distinctive role. The Hebbian sub-population controls for the firing activity, while the anti-Hebbian neurons promote pattern selectivity. After the learning phase, the network settles into an asynchronous irregular resting-state. This post-learning activity is associated with spontaneous memory recalls which turn out to be fundamental for the long-term consolidation of the learned memories. Due to its simplicity, the introduced model can represent a test-bed for further investigations on the role played by STDP on memory storing and maintenance.
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Affiliation(s)
- Raphaël Bergoin
- ETIS, UMR 8051, ENSEA, CY Cergy Paris Université, CNRS, Cergy-Pontoise, France
- Center for Brain and Cognition, Pompeu Fabra University, Barcelona, Spain
- Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
- Institute of Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Alessandro Torcini
- Laboratoire de Physique Théorique et Modélisation, UMR 8089, CY Cergy Paris Université, CNRS, Cergy-Pontoise, France
| | - Gustavo Deco
- Center for Brain and Cognition, Pompeu Fabra University, Barcelona, Spain
- Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
- Instituciò Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Mathias Quoy
- ETIS, UMR 8051, ENSEA, CY Cergy Paris Université, CNRS, Cergy-Pontoise, France
- IPAL, CNRS, Singapore, Singapore
| | - Gorka Zamora-López
- Center for Brain and Cognition, Pompeu Fabra University, Barcelona, Spain
- Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
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2
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Huang JY, Hess M, Bajpai A, Li X, Hobson LN, Xu AJ, Barton SJ, Lu HC. From initial formation to developmental refinement: GABAergic inputs shape neuronal subnetworks in the primary somatosensory cortex. iScience 2025; 28:112104. [PMID: 40129704 PMCID: PMC11930745 DOI: 10.1016/j.isci.2025.112104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2024] [Revised: 01/07/2025] [Accepted: 02/21/2025] [Indexed: 03/26/2025] Open
Abstract
Neuronal subnetworks, also known as ensembles, are functional units formed by interconnected neurons for information processing and encoding in the adult brain. Our study investigates the establishment of neuronal subnetworks in the mouse primary somatosensory (S1) cortex from postnatal days (P)11 to P21 using in vivo two-photon calcium imaging. We found that at P11, neuronal activity was highly synchronized but became sparser by P21. Clustering analyses revealed that while the number of subnetworks remained constant, their activity patterns became more distinct, with increased coherence, independent of cortical layer or sex. Furthermore, the coherence of neuronal activity within individual subnetworks significantly increased when synchrony frequencies were reduced by augmenting gamma-aminobutyric acid (GABA)ergic activity at P15/16, a period when the neuronal subnetworks were still maturing. Together, these findings indicate the early formation of subnetworks and underscore the pivotal roles of GABAergic inputs in modulating S1 neuronal subnetworks.
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Affiliation(s)
- Jui-Yen Huang
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA
| | - Michael Hess
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
| | - Abhinav Bajpai
- Research Technologies, Indiana University, Bloomington, IN 47408, USA
| | - Xuan Li
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Liam N. Hobson
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Ashley J. Xu
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA
| | - Scott J. Barton
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
| | - Hui-Chen Lu
- The Gill Institute for Neuroscience, Indiana University, Bloomington, IN 47405, USA
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA
- Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA
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3
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Thibeault KC, Leonard MZ, Kondev V, Emerson SD, Bethi R, Lopez AJ, Sens JP, Nabit BP, Elam HB, Winder DG, Patel S, Kiraly DD, Grueter BA, Calipari ES. A Cocaine-Activated Ensemble Exerts Increased Control Over Behavior While Decreasing in Size. Biol Psychiatry 2025; 97:590-601. [PMID: 38901723 PMCID: PMC11995305 DOI: 10.1016/j.biopsych.2024.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 06/06/2024] [Accepted: 06/11/2024] [Indexed: 06/22/2024]
Abstract
BACKGROUND Substance use disorder is characterized by long-lasting changes in reward-related brain regions, such as the nucleus accumbens. Previous work has shown that cocaine exposure induces plasticity in broad, genetically defined cell types in the nucleus accumbens; however, in response to a stimulus, only a small percentage of neurons are transcriptionally active-termed an ensemble. Here, we identify an Arc-expressing neuronal ensemble that has a unique trajectory of recruitment and causally controls drug self-administration after repeated, but not acute, cocaine exposure. METHODS Using Arc-CreERT2 transgenic mice, we expressed transgenes in Arc+ ensembles activated by cocaine exposure (either acute [1 × 10 mg/kg intraperitoneally] or repeated [10 × 10 mg/kg intraperitoneally]). Using genetic, optical, and physiological recording and manipulation strategies, we assessed the contribution of these ensembles to behaviors associated with substance use disorder. RESULTS Repeated cocaine exposure reduced the size of the ensemble while simultaneously increasing its control over behavior. Neurons within the repeated cocaine ensemble were hyperexcitable, and their optogenetic excitation was sufficient for reinforcement. Finally, lesioning the repeated cocaine, but not the acute cocaine, ensemble blunted cocaine self-administration. Thus, repeated cocaine exposure reduced the size of the ensemble while simultaneously increasing its contributions to drug reinforcement. CONCLUSIONS We showed that repeated, but not acute, cocaine exposure induced a physiologically distinct ensemble characterized by the expression of the immediate early gene Arc, which was uniquely capable of modulating reinforcement behavior.
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Affiliation(s)
- Kimberly C Thibeault
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee
| | - Michael Z Leonard
- Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee
| | - Veronika Kondev
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee
| | - Soren D Emerson
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee
| | - Rishik Bethi
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee
| | - Alberto J Lopez
- Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee
| | - Jonathon P Sens
- Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Brett P Nabit
- Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee
| | - Hannah B Elam
- Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee
| | - Danny G Winder
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Vanderbilt JF Kennedy Center, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Sachin Patel
- Department of Psychiatry, Northwestern University, Chicago, Illinois
| | - Drew D Kiraly
- Department of Physiology and Pharmacology, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Brad A Grueter
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Department of Anesthesiology, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Erin S Calipari
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee; Vanderbilt Center for Addiction Research, Vanderbilt University, Nashville, Tennessee; Department of Pharmacology, Vanderbilt University, Nashville, Tennessee; Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee; Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, Tennessee; Vanderbilt JF Kennedy Center, Vanderbilt University School of Medicine, Nashville, Tennessee.
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4
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Murakami T. Spatial dynamics of spontaneous activity in the developing and adult cortices. Neurosci Res 2025; 212:1-10. [PMID: 39653148 DOI: 10.1016/j.neures.2024.12.002] [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: 03/29/2024] [Revised: 11/29/2024] [Accepted: 12/02/2024] [Indexed: 12/16/2024]
Abstract
Even in the absence of external stimuli, the brain remains remarkably active, with neurons continuously firing and communicating with each other. It is not merely random firing of individual neurons but rather orchestrated patterns of activity that propagate throughout the intricate network. Over two decades, advancements in neuroscience observation tools for hemodynamics, membrane potential, and neural calcium signals, have allowed researchers to analyze the dynamics of spontaneous activity across different spatial scales, from individual neurons to macroscale brain networks. One of the remarkable findings from these studies is that the spatial patterns of spontaneous activity in the developing brain are vastly different from those in the mature adult brain. Spatial patterns of spontaneous activity during development are essential for connection refinement between brain regions, whereas the functional role in the adult brain is still controversial. In this paper, I review the differences in spatial dynamics of spontaneous activity between developing and adult cortices. Then, I delve into the cellular mechanisms underlying spontaneous activity, especially its generation and propagation manner, to contribute to a deeper understanding of brain function and its development.
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Affiliation(s)
- Tomonari Murakami
- Department of Physiology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan; Institute for AI and Beyond, The University of Tokyo, Tokyo, Japan.
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5
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Pouget C, Morier F, Treiber N, García PF, Mazza N, Zhang R, Reeves I, Winston S, Brimble MA, Kim CK, Vetere G. Deconstruction of a Memory Engram Reveals Distinct Ensembles Recruited at Learning. RESEARCH SQUARE 2025:rs.3.rs-5633532. [PMID: 39975896 PMCID: PMC11838775 DOI: 10.21203/rs.3.rs-5633532/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
How are associative memories formed? Which cells represent a memory, and when are they engaged? By visualizing and tagging cells based on their calcium influx with unparalleled temporal precision, we identified non-overlapping dorsal CA1 neuronal ensembles that are differentially active during associative fear memory acquisition. We dissected the acquisition experience into periods during which salient stimuli were presented or certain mouse behaviors occurred and found that cells associated with specific acquisition periods are sufficient alone to drive memory expression and contribute to fear engram formation. This study delineated the different identities of the cell ensembles active during learning, and revealed, for the first time, which ones form the core engram and are essential for memory formation and recall.
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Affiliation(s)
- Clément Pouget
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Flora Morier
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Nadja Treiber
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Pablo Fernández García
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Nina Mazza
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Run Zhang
- Biomedical Engineering Graduate Group, University of California, Davis; Davis, CA, 95618, USA
| | - Isaiah Reeves
- Dept of Surgery, St Jude Children’s Research Hospital; Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital; Memphis, TN, 38105, USA
| | - Stephen Winston
- Dept of Surgery, St Jude Children’s Research Hospital; Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital; Memphis, TN, 38105, USA
| | - Mark A. Brimble
- Dept of Host-Microbe Interactions, St Jude Children’s Research Hospital; Memphis, TN, 38105, USA
| | - Christina K. Kim
- Center for Neuroscience, University of California, Davis; Davis, CA, 95618, USA
- Dept of Neurology, School of Medicine, University of California, Davis; Sacramento, CA, 95817, USA
| | - Gisella Vetere
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
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6
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Judák L, Dobos G, Ócsai K, Báthory E, Szebik H, Tarján B, Maák P, Szadai Z, Takács I, Chiovini B, Lőrincz T, Szepesi Á, Roska B, Szalay G, Rózsa B. Moculus: an immersive virtual reality system for mice incorporating stereo vision. Nat Methods 2025; 22:386-398. [PMID: 39668210 PMCID: PMC11810792 DOI: 10.1038/s41592-024-02554-6] [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: 09/13/2023] [Accepted: 10/29/2024] [Indexed: 12/14/2024]
Abstract
Due to technical roadblocks, it is unclear how visual circuits represent multiple features or how behaviorally relevant representations are selected for long-term memory. Here we developed Moculus, a head-mounted virtual reality platform for mice that covers the entire visual field, and allows binocular depth perception and full visual immersion. This controllable environment, with three-dimensional (3D) corridors and 3D objects, in combination with 3D acousto-optical imaging, affords rapid visual learning and the uncovering of circuit substrates in one measurement session. Both the control and reinforcement-associated visual cue coding neuronal assemblies are transiently expanded by reinforcement feedback to near-saturation levels. This increases computational capability and allows competition among assemblies that encode behaviorally relevant information. The coding assemblies form partially orthogonal and overlapping clusters centered around hub cells with higher and earlier ramp-like responses, as well as locally increased functional connectivity.
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Grants
- ERC 682426 (VISONby3DSTIM), 2018-1.3.1-VKE-00032, 2018-1.1.2-KFI-00097, PM/20453-15/2020, 712821-NEURAM, 2020-1.1.5-GYORSÍTÓSÁV-2021-00004, GINOP-1.2.15-21-2021-00061. 2020-2.1.1-ED-2021-00190, 2020-2.1.1-ED-2022-00208, 2022-1.1.1-KK- 2022-00005, 2022-2.1.1-NL-2022-00012, 2021-1.1.4-GYORSÍTÓSÁV-2022-00064, NUMBER 871277 — AMPLITUDE, GINOP_PLUSZ-2.1.1-21-2022-00143,NKFIH/143650
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Affiliation(s)
- Linda Judák
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - Gergely Dobos
- Bay Zoltán Nonprofit for Applied Research, Budapest, Hungary
| | - Katalin Ócsai
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
- Department of Algebra and Geometry, Institute of Mathematics, Budapest University of Technology and Economics, Budapest, Hungary
| | - Eszter Báthory
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - Huba Szebik
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - Balázs Tarján
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
- Doctoral School, Semmelweis University, Budapest, Hungary
| | - Pál Maák
- Department of Atomic Physics, Budapest University of Technology and Economics, Budapest, Hungary
| | - Zoltán Szadai
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - István Takács
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
| | - Balázs Chiovini
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Tibor Lőrincz
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - Áron Szepesi
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - Botond Roska
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
- Department of Ophthalmology, University of Basel, Basel, Switzerland
- Institute of Molecular and Clinical Ophthalmology Basel, Basel, Switzerland
| | - Gergely Szalay
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary
| | - Balázs Rózsa
- Laboratory of 3D Functional Network and Dendritic Imaging, Institute of Experimental Medicine, Budapest, Hungary.
- BrainVisionCenter Research Institute and Competence Center, Budapest, Hungary.
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary.
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7
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Chau HY, Miller KD, Palmigiano A. Exact linear theory of perturbation response in a space- and feature-dependent cortical circuit model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.12.27.630558. [PMID: 39896520 PMCID: PMC11785077 DOI: 10.1101/2024.12.27.630558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/04/2025]
Abstract
What are the principles that govern the responses of cortical networks to their inputs and the emergence of these responses from recurrent connectivity? Recent experiments have probed these questions by measuring cortical responses to two-photon optogenetic perturbations of single cells in the mouse primary visual cortex. A robust theoretical framework is needed to determine the implications of these responses for cortical recurrence. Here we propose a novel analytical approach: a formulation of the dependence of cell-type-specific connectivity on spatial distance that yields an exact solution for the linear perturbation response of a model with multiple cell types and space- and feature-dependent connectivity. Importantly and unlike previous approaches, the solution is valid in regimes of strong as well as weak intra-cortical coupling. Analysis reveals the structure of connectivity implied by various features of single-cell perturbation responses, such as the surprisingly narrow spatial radius of nearby excitation beyond which inhibition dominates, the number of transitions between mean excitation and inhibition thereafter, and the dependence of these responses on feature preferences. Comparison of these results to existing optogenetic perturbation data yields constraints on cell-type-specific connection strengths and their tuning dependence. Finally, we provide experimental predictions regarding the response of inhibitory neurons to single-cell perturbations and the modulation of perturbation response by neuronal gain; the latter can explain observed differences in the feature-tuning of perturbation responses in the presence vs. absence of visual stimuli.
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Affiliation(s)
- Ho Yin Chau
- Center for Theoretical Neuroscience, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
| | - Kenneth D. Miller
- Center for Theoretical Neuroscience, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
- Dept. of Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York
| | - Agostina Palmigiano
- Center for Theoretical Neuroscience, College of Physicians and Surgeons and Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY
- Gatsby Computational Neuroscience Unit, University College London
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8
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Kato DD, Bruno RM. Stability of cross-sensory input to primary somatosensory cortex across experience. Neuron 2025; 113:291-306.e7. [PMID: 39561767 PMCID: PMC11757082 DOI: 10.1016/j.neuron.2024.10.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 08/03/2024] [Accepted: 10/22/2024] [Indexed: 11/21/2024]
Abstract
Merging information across sensory modalities is key to forming robust percepts, yet how the brain achieves this feat remains unclear. Recent studies report cross-modal influences in the primary sensory cortex, suggesting possible multisensory integration in the early stages of cortical processing. We test several hypotheses about the function of auditory influences on mouse primary somatosensory cortex (S1) using in vivo two-photon calcium imaging. We found sound-evoked spiking activity in an extremely small fraction of cells, and this sparse activity did not encode auditory stimulus identity. Moreover, S1 did not encode information about specific audio-tactile feature conjunctions. Auditory and audio-tactile stimulus encoding remained unchanged after both passive experience and reinforcement. These results suggest that while primary sensory cortex is plastic within its own modality, the influence of other modalities is remarkably stable and stimulus nonspecific.
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Affiliation(s)
- Daniel D Kato
- Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Randy M Bruno
- Department of Neuroscience, Columbia University, New York, NY 10027, USA; Department of Physiology, Anatomy, & Genetics, University of Oxford, Oxford OX1 3PT, UK.
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9
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Khan HF, Dutta S, Scott AN, Xiao S, Yadav S, Chen X, Aryal UK, Kinzer-Ursem TL, Rochet JC, Jayant K. Site-specific seeding of Lewy pathology induces distinct pre-motor cellular and dendritic vulnerabilities in the cortex. Nat Commun 2024; 15:10775. [PMID: 39737978 PMCID: PMC11685769 DOI: 10.1038/s41467-024-54945-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 11/26/2024] [Indexed: 01/01/2025] Open
Abstract
Circuit-based biomarkers distinguishing the gradual progression of Lewy pathology across synucleinopathies remain unknown. Here, we show that seeding of α-synuclein preformed fibrils in mouse dorsal striatum and motor cortex leads to distinct prodromal-phase cortical dysfunction across months. Our findings reveal that while both seeding sites had increased cortical pathology and hyperexcitability, distinct differences in electrophysiological and cellular ensemble patterns were crucial in distinguishing pathology spread between the two seeding sites. Notably, while beta-band spike-field-coherence reflected a significant increase beginning in Layer-5 and then spreading to Layer-2/3, the rate of entrainment and the propensity of stochastic beta-burst dynamics was markedly seeding location-specific. This beta dysfunction was accompanied by gradual superficial excitatory ensemble instability following cortical, but not striatal, preformed fibrils injection. We reveal a link between Layer-5 dendritic vulnerabilities and translaminar beta event dysfunction, which could be used to differentiate symptomatically similar synucleinopathies.
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Affiliation(s)
- Hammad F Khan
- Weldon School of Biomedical Engineering, West Lafayette, Indiana, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
| | - Sayan Dutta
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
- Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA
| | - Alicia N Scott
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
- Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA
| | - Shulan Xiao
- Weldon School of Biomedical Engineering, West Lafayette, Indiana, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
| | - Saumitra Yadav
- Weldon School of Biomedical Engineering, West Lafayette, Indiana, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
| | - Xiaoling Chen
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
- Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA
| | - Uma K Aryal
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN, USA
- Purdue Proteomics Facility, Bindley Bioscience Center, Purdue University, West Lafayette, IN, USA
| | - Tamara L Kinzer-Ursem
- Weldon School of Biomedical Engineering, West Lafayette, Indiana, IN, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA
| | - Jean-Christophe Rochet
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA.
- Borch Department of Medicinal Chemistry and Molecular Pharmacology, Purdue University, West Lafayette, IN, USA.
| | - Krishna Jayant
- Weldon School of Biomedical Engineering, West Lafayette, Indiana, IN, USA.
- Purdue Institute for Integrative Neuroscience, Purdue University, West Lafayette, IN, USA.
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10
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Pouget C, Morier F, Treiber N, García PF, Mazza N, Zhang R, Reeves I, Winston S, Brimble MA, Kim CK, Vetere G. Deconstruction of a memory engram reveals distinct ensembles recruited at learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.11.627894. [PMID: 39713328 PMCID: PMC11661170 DOI: 10.1101/2024.12.11.627894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/24/2024]
Abstract
How are associative memories formed? Which cells represent a memory, and when are they engaged? By visualizing and tagging cells based on their calcium influx with unparalleled temporal precision, we identified non-overlapping dorsal CA1 neuronal ensembles that are differentially active during associative fear memory acquisition. We dissected the acquisition experience into periods during which salient stimuli were presented or certain mouse behaviors occurred and found that cells associated with specific acquisition periods are sufficient alone to drive memory expression and contribute to fear engram formation. This study delineated the different identities of the cell ensembles active during learning, and revealed, for the first time, which ones form the core engram and are essential for memory formation and recall.
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Affiliation(s)
- Clément Pouget
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Flora Morier
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Nadja Treiber
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Pablo Fernández García
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Nina Mazza
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
| | - Run Zhang
- Biomedical Engineering Graduate Group, University of California, Davis; Davis, CA, 95618, USA
| | - Isaiah Reeves
- Dept of Surgery, St Jude Children’s Research Hospital; Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital; Memphis, TN, 38105, USA
| | - Stephen Winston
- Dept of Surgery, St Jude Children’s Research Hospital; Memphis, TN, 38105, USA
- Graduate School of Biomedical Sciences, St. Jude Children’s Research Hospital; Memphis, TN, 38105, USA
| | - Mark A. Brimble
- Dept of Host-Microbe Interactions, St Jude Children’s Research Hospital; Memphis, TN, 38105, USA
| | - Christina K. Kim
- Center for Neuroscience, University of California, Davis; Davis, CA, 95618, USA
- Dept of Neurology, School of Medicine, University of California, Davis; Sacramento, CA, 95817, USA
| | - Gisella Vetere
- Cerebral Codes and Circuits Connectivity team, Brain Plasticity Unit, CNRS, ESPCI Paris, PSL Research University; Paris, France
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11
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Arroyo B, Hernandez-Lemus E, Gutierrez R. The flow of reward information through neuronal ensembles in the accumbens. Cell Rep 2024; 43:114838. [PMID: 39395166 DOI: 10.1016/j.celrep.2024.114838] [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: 02/27/2024] [Revised: 07/05/2024] [Accepted: 09/20/2024] [Indexed: 10/14/2024] Open
Abstract
The nucleus accumbens shell (NAcSh) integrates reward information through diverse and specialized neuronal ensembles, influencing decision-making. By training rats in a probabilistic choice task and recording NAcSh neuronal activity, we found that rats adapt their choices based solely on the presence or absence of a sucrose reward, suggesting they build an internal representation of reward likelihood. We further demonstrate that NAcSh ensembles dynamically process different aspects of reward-guided behavior, with changes in composition and functional connections observed throughout the reinforcement learning process. The NAcSh forms a highly connected network characterized by a heavy-tailed distribution and the presence of neuronal hubs, facilitating efficient information flow. Reward delivery enhances mutual information, indicating increased communication between ensembles and network synchronization, whereas reward omission decreases it. Our findings reveal how reward information flows through dynamic NAcSh ensembles, whose flexible membership adapts as the rat learns to obtain rewards (energy) in an ever-changing environment.
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Affiliation(s)
- Benjamin Arroyo
- Laboratory Neurobiology of Appetite, Department of Pharmacology, CINVESTAV, Mexico City 07360, Mexico; Laboratory Neurobiology of Appetite, Center for Research on Aging (CIE), Cinvestav Sede Sur, Mexico City 14330, Mexico
| | - Enrique Hernandez-Lemus
- Computational Genomics Division, National Institute of Genomic Medicine (INMEGEN), Mexico City 14610, Mexico; Center for Complexity Sciences, Universidad Nacional Autónoma de México (UNAM), Mexico City 04510, Mexico
| | - Ranier Gutierrez
- Laboratory Neurobiology of Appetite, Department of Pharmacology, CINVESTAV, Mexico City 07360, Mexico; Laboratory Neurobiology of Appetite, Center for Research on Aging (CIE), Cinvestav Sede Sur, Mexico City 14330, Mexico.
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12
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Vinograd A, Nair A, Kim JH, Linderman SW, Anderson DJ. Causal evidence of a line attractor encoding an affective state. Nature 2024; 634:910-918. [PMID: 39142337 PMCID: PMC11499281 DOI: 10.1038/s41586-024-07915-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Accepted: 08/06/2024] [Indexed: 08/16/2024]
Abstract
Continuous attractors are an emergent property of neural population dynamics that have been hypothesized to encode continuous variables such as head direction and eye position1-4. In mammals, direct evidence of neural implementation of a continuous attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles2,3. Dynamical systems modelling has revealed that neurons in the hypothalamus exhibit approximate line-attractor dynamics in male mice during aggressive encounters5. We have previously hypothesized that these dynamics may encode the variable intensity and persistence of an aggressive internal state. Here we report that these neurons also showed line-attractor dynamics in head-fixed mice observing aggression6. This allowed us to identify and manipulate line-attractor-contributing neurons using two-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations yielded integration of optogenetic stimulation pulses and persistent activity that drove the system along the line attractor, while transient off-manifold perturbations were followed by rapid relaxation back into the attractor. Furthermore, single-cell stimulation and imaging revealed selective functional connectivity among attractor-contributing neurons. Notably, individual differences among mice in line-attractor stability were correlated with the degree of functional connectivity among attractor-contributing neurons. Mechanistic recurrent neural network modelling indicated that dense subnetwork connectivity and slow neurotransmission7 best recapitulate our empirical findings. Our work bridges circuit and manifold levels3, providing causal evidence of continuous attractor dynamics encoding an affective internal state in the mammalian hypothalamus.
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Affiliation(s)
- Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Joseph H Kim
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA
| | - Scott W Linderman
- Department of Statistics, Stanford University, Stanford, CA, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA, USA
| | - David J Anderson
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech, Pasadena, CA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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13
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Ravichandran N, Lansner A, Herman P. Spiking representation learning for associative memories. Front Neurosci 2024; 18:1439414. [PMID: 39371606 PMCID: PMC11450452 DOI: 10.3389/fnins.2024.1439414] [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: 05/27/2024] [Accepted: 08/29/2024] [Indexed: 10/08/2024] Open
Abstract
Networks of interconnected neurons communicating through spiking signals offer the bedrock of neural computations. Our brain's spiking neural networks have the computational capacity to achieve complex pattern recognition and cognitive functions effortlessly. However, solving real-world problems with artificial spiking neural networks (SNNs) has proved to be difficult for a variety of reasons. Crucially, scaling SNNs to large networks and processing large-scale real-world datasets have been challenging, especially when compared to their non-spiking deep learning counterparts. The critical operation that is needed of SNNs is the ability to learn distributed representations from data and use these representations for perceptual, cognitive and memory operations. In this work, we introduce a novel SNN that performs unsupervised representation learning and associative memory operations leveraging Hebbian synaptic and activity-dependent structural plasticity coupled with neuron-units modelled as Poisson spike generators with sparse firing (~1 Hz mean and ~100 Hz maximum firing rate). Crucially, the architecture of our model derives from the neocortical columnar organization and combines feedforward projections for learning hidden representations and recurrent projections for forming associative memories. We evaluated the model on properties relevant for attractor-based associative memories such as pattern completion, perceptual rivalry, distortion resistance, and prototype extraction.
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Affiliation(s)
- Naresh Ravichandran
- Computational Cognitive Brain Science Group, Department of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Anders Lansner
- Computational Cognitive Brain Science Group, Department of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
- Department of Mathematics, Stockholm University, Stockholm, Sweden
| | - Pawel Herman
- Computational Cognitive Brain Science Group, Department of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
- Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden
- Swedish e-Science Research Centre (SeRC), Stockholm, Sweden
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14
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Kato DD, Bruno RM. Stability of cross-sensory input to primary somatosensory cortex across experience. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.07.607026. [PMID: 39149350 PMCID: PMC11326227 DOI: 10.1101/2024.08.07.607026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Merging information from across sensory modalities is key to forming robust, disambiguated percepts of the world, yet how the brain achieves this feat remains unclear. Recent observations of cross-modal influences in primary sensory cortical areas have suggested that multisensory integration may occur in the earliest stages of cortical processing, but the role of these responses is still poorly understood. We address these questions by testing several hypotheses about the possible functions served by auditory influences on the barrel field of mouse primary somatosensory cortex (S1) using in vivo 2-photon calcium imaging. We observed sound-evoked spiking activity in a small fraction of cells overall, and moreover that this sparse activity was insufficient to encode auditory stimulus identity; few cells responded preferentially to one sound or another, and a linear classifier trained to decode auditory stimuli from population activity performed barely above chance. Moreover S1 did not encode information about specific audio-tactile feature conjunctions that we tested. Our ability to decode auditory audio-tactile stimuli from neural activity remained unchanged after both passive experience and reinforcement. Collectively, these results suggest that while a primary sensory cortex is highly plastic with regard to its own modality, the influence of other modalities are remarkably stable and play a largely stimulus-non-specific role.
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Affiliation(s)
- Daniel D Kato
- Department of Neuroscience, Columbia University, New York, NY 10027, USA
| | - Randy M Bruno
- Department of Neuroscience, Columbia University, New York, NY 10027, USA
- Department of Physiology, Anatomy, & Genetics, University of Oxford, Oxford OX1 3PT, United Kingdom
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15
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Hansel C, Yuste R. Neural ensembles: role of intrinsic excitability and its plasticity. Front Cell Neurosci 2024; 18:1440588. [PMID: 39144154 PMCID: PMC11322048 DOI: 10.3389/fncel.2024.1440588] [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: 05/29/2024] [Accepted: 07/18/2024] [Indexed: 08/16/2024] Open
Abstract
Synaptic connectivity defines groups of neurons that engage in correlated activity during specific functional tasks. These co-active groups of neurons form ensembles, the operational units involved in, for example, sensory perception, motor coordination and memory (then called an engram). Traditionally, ensemble formation has been thought to occur via strengthening of synaptic connections via long-term potentiation (LTP) as a plasticity mechanism. This synaptic theory of memory arises from the learning rules formulated by Hebb and is consistent with many experimental observations. Here, we propose, as an alternative, that the intrinsic excitability of neurons and its plasticity constitute a second, non-synaptic mechanism that could be important for the initial formation of ensembles. Indeed, enhanced neural excitability is widely observed in multiple brain areas subsequent to behavioral learning. In cortical structures and the amygdala, excitability changes are often reported as transient, even though they can last tens of minutes to a few days. Perhaps it is for this reason that they have been traditionally considered as modulatory, merely supporting ensemble formation by facilitating LTP induction, without further involvement in memory function (memory allocation hypothesis). We here suggest-based on two lines of evidence-that beyond modulating LTP allocation, enhanced excitability plays a more fundamental role in learning. First, enhanced excitability constitutes a signature of active ensembles and, due to it, subthreshold synaptic connections become suprathreshold in the absence of synaptic plasticity (iceberg model). Second, enhanced excitability promotes the propagation of dendritic potentials toward the soma and allows for enhanced coupling of EPSP amplitude (LTP) to the spike output (and thus ensemble participation). This permissive gate model describes a need for permanently increased excitability, which seems at odds with its traditional consideration as a short-lived mechanism. We propose that longer modifications in excitability are made possible by a low threshold for intrinsic plasticity induction, suggesting that excitability might be on/off-modulated at short intervals. Consistent with this, in cerebellar Purkinje cells, excitability lasts days to weeks, which shows that in some circuits the duration of the phenomenon is not a limiting factor in the first place. In our model, synaptic plasticity defines the information content received by neurons through the connectivity network that they are embedded in. However, the plasticity of cell-autonomous excitability could dynamically regulate the ensemble participation of individual neurons as well as the overall activity state of an ensemble.
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Affiliation(s)
- Christian Hansel
- Department of Neurobiology and Neuroscience Institute, University of Chicago, Chicago, IL, United States
| | - Rafael Yuste
- NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, NY, United States
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16
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Gauld OM, Packer AM, Russell LE, Dalgleish HWP, Iuga M, Sacadura F, Roth A, Clark BA, Häusser M. A latent pool of neurons silenced by sensory-evoked inhibition can be recruited to enhance perception. Neuron 2024; 112:2386-2403.e6. [PMID: 38729150 PMCID: PMC7616379 DOI: 10.1016/j.neuron.2024.04.015] [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: 07/31/2023] [Revised: 02/12/2024] [Accepted: 04/12/2024] [Indexed: 05/12/2024]
Abstract
To investigate which activity patterns in sensory cortex are relevant for perceptual decision-making, we combined two-photon calcium imaging and targeted two-photon optogenetics to interrogate barrel cortex activity during perceptual discrimination. We trained mice to discriminate bilateral whisker deflections and report decisions by licking left or right. Two-photon calcium imaging revealed sparse coding of contralateral and ipsilateral whisker input in layer 2/3, with most neurons remaining silent during the task. Activating pyramidal neurons using two-photon holographic photostimulation evoked a perceptual bias that scaled with the number of neurons photostimulated. This effect was dominated by optogenetic activation of non-coding neurons, which did not show sensory or motor-related activity during task performance. Photostimulation also revealed potent recruitment of cortical inhibition during sensory processing, which strongly and preferentially suppressed non-coding neurons. Our results suggest that a pool of non-coding neurons, selectively suppressed by network inhibition during sensory processing, can be recruited to enhance perception.
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Affiliation(s)
- Oliver M Gauld
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK; Sainsbury Wellcome Centre, University College London, London W1T 4JG, UK.
| | - Adam M Packer
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK; Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford OX1 3PT, UK
| | - Lloyd E Russell
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK
| | - Henry W P Dalgleish
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK
| | - Maya Iuga
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK
| | - Francisco Sacadura
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK
| | - Arnd Roth
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK
| | - Beverley A Clark
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK
| | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London WC1E 6BT, UK.
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17
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Gimenez-Gomez P, Le T, Zinter M, M'Angale P, Duran-Laforet V, Freels TG, Pavchinskiy R, Molas S, Schafer DP, Tapper AR, Thomson T, Martin GE. An orbitocortical-thalamic circuit suppresses binge alcohol-drinking. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.03.601895. [PMID: 39005328 PMCID: PMC11245026 DOI: 10.1101/2024.07.03.601895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/16/2024]
Abstract
Alcohol consumption remains a significant global health challenge, causing millions of direct and indirect deaths annually. Intriguingly, recent work has highlighted the prefrontal cortex, a major brain area that regulates inhibitory control of behaviors, whose activity becomes dysregulated upon alcohol abuse. However, whether an endogenous mechanism exists within this brain area that limits alcohol consumption is unknown. Here we identify a discrete GABAergic neuronal ensemble in the medial orbitofrontal cortex (mOFC) that is selectively recruited during binge alcohol-drinking and intoxication. Upon alcohol intoxication, this neuronal ensemble suppresses binge drinking behavior. Optogenetically silencing of this population, or its ablation, results in uncontrolled binge alcohol consumption. We find that this neuronal ensemble is specific to alcohol and is not recruited by other rewarding substances. We further show, using brain-wide analysis, that this neuronal ensemble projects widely, and that its projections specifically to the mediodorsal thalamus are responsible for regulating binge alcohol drinking. Together, these results identify a brain circuit in the mOFC that serves to protect against binge drinking by halting alcohol intake. These results provide valuable insights into the complex nature of alcohol abuse and offers potential avenues for the development of mOFC neuronal ensemble-targeted interventions.
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Affiliation(s)
- P Gimenez-Gomez
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - T Le
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - M Zinter
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - P M'Angale
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - V Duran-Laforet
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - T G Freels
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - R Pavchinskiy
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - S Molas
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO 80303, USA
- Department of Psychology and Neuroscience, University of Colorado, Boulder, CO 80309, USA
| | - D P Schafer
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - A R Tapper
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - T Thomson
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - G E Martin
- Brudnick Neuropsychiatric Research Institute, Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Department of Neurobiology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
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18
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Abatis M, Perin R, Niu R, van den Burg E, Hegoburu C, Kim R, Okamura M, Bito H, Markram H, Stoop R. Fear learning induces synaptic potentiation between engram neurons in the rat lateral amygdala. Nat Neurosci 2024; 27:1309-1317. [PMID: 38871992 PMCID: PMC11239494 DOI: 10.1038/s41593-024-01676-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 05/07/2024] [Indexed: 06/15/2024]
Abstract
The lateral amygdala (LA) encodes fear memories by potentiating sensory inputs associated with threats and, in the process, recruits 10-30% of its neurons per fear memory engram. However, how the local network within the LA processes this information and whether it also plays a role in storing it are still largely unknown. Here, using ex vivo 12-patch-clamp and in vivo 32-electrode electrophysiological recordings in the LA of fear-conditioned rats, in combination with activity-dependent fluorescent and optogenetic tagging and recall, we identified a sparsely connected network between principal LA neurons that is organized in clusters. Fear conditioning specifically causes potentiation of synaptic connections between learning-recruited neurons. These findings of synaptic plasticity in an autoassociative excitatory network of the LA may suggest a basic principle through which a small number of pyramidal neurons could encode a large number of memories.
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Affiliation(s)
- Marios Abatis
- Department of Psychiatry, Center for Psychiatric Neuroscience, University Hospital of Lausanne, Prilly-Lausanne, Switzerland
| | - Rodrigo Perin
- Brain-Mind Institute, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ruifang Niu
- Department of Psychiatry, Center for Psychiatric Neuroscience, University Hospital of Lausanne, Prilly-Lausanne, Switzerland
| | - Erwin van den Burg
- Department of Psychiatry, Center for Psychiatric Neuroscience, University Hospital of Lausanne, Prilly-Lausanne, Switzerland
| | - Chloe Hegoburu
- Department of Psychiatry, Center for Psychiatric Neuroscience, University Hospital of Lausanne, Prilly-Lausanne, Switzerland
| | - Ryang Kim
- Department of Neurochemistry, The University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Michiko Okamura
- Department of Neurochemistry, The University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Haruhiko Bito
- Department of Neurochemistry, The University of Tokyo Graduate School of Medicine, Tokyo, Japan
| | - Henry Markram
- Brain-Mind Institute, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ron Stoop
- Department of Psychiatry, Center for Psychiatric Neuroscience, University Hospital of Lausanne, Prilly-Lausanne, Switzerland.
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19
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Hira R. Closed-loop experiments and brain machine interfaces with multiphoton microscopy. NEUROPHOTONICS 2024; 11:033405. [PMID: 38375331 PMCID: PMC10876015 DOI: 10.1117/1.nph.11.3.033405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 01/22/2024] [Accepted: 01/29/2024] [Indexed: 02/21/2024]
Abstract
In the field of neuroscience, the importance of constructing closed-loop experimental systems has increased in conjunction with technological advances in measuring and controlling neural activity in live animals. We provide an overview of recent technological advances in the field, focusing on closed-loop experimental systems where multiphoton microscopy-the only method capable of recording and controlling targeted population activity of neurons at a single-cell resolution in vivo-works through real-time feedback. Specifically, we present some examples of brain machine interfaces (BMIs) using in vivo two-photon calcium imaging and discuss applications of two-photon optogenetic stimulation and adaptive optics to real-time BMIs. We also consider conditions for realizing future optical BMIs at the synaptic level, and their possible roles in understanding the computational principles of the brain.
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Affiliation(s)
- Riichiro Hira
- Tokyo Medical and Dental University, Graduate School of Medical and Dental Sciences, Department of Physiology and Cell Biology, Tokyo, Japan
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20
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Correa A, Ponzi A, Calderón VM, Migliore R. Pathological cell assembly dynamics in a striatal MSN network model. Front Comput Neurosci 2024; 18:1410335. [PMID: 38903730 PMCID: PMC11188713 DOI: 10.3389/fncom.2024.1410335] [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: 04/01/2024] [Accepted: 05/15/2024] [Indexed: 06/22/2024] Open
Abstract
Under normal conditions the principal cells of the striatum, medium spiny neurons (MSNs), show structured cell assembly activity patterns which alternate sequentially over exceedingly long timescales of many minutes. It is important to understand this activity since it is characteristically disrupted in multiple pathologies, such as Parkinson's disease and dyskinesia, and thought to be caused by alterations in the MSN to MSN lateral inhibitory connections and in the strength and distribution of cortical excitation to MSNs. To understand how these long timescales arise we extended a previous network model of MSN cells to include synapses with short-term plasticity, with parameters taken from a recent detailed striatal connectome study. We first confirmed the presence of sequentially switching cell clusters using the non-linear dimensionality reduction technique, Uniform Manifold Approximation and Projection (UMAP). We found that the network could generate non-stationary activity patterns varying extremely slowly on the order of minutes under biologically realistic conditions. Next we used Simulation Based Inference (SBI) to train a deep net to map features of the MSN network generated cell assembly activity to MSN network parameters. We used the trained SBI model to estimate MSN network parameters from ex-vivo brain slice calcium imaging data. We found that best fit network parameters were very close to their physiologically observed values. On the other hand network parameters estimated from Parkinsonian, decorticated and dyskinetic ex-vivo slice preparations were different. Our work may provide a pipeline for diagnosis of basal ganglia pathology from spiking data as well as for the design pharmacological treatments.
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Affiliation(s)
- Astrid Correa
- Institute of Biophysics, National Research Council, Palermo, Italy
| | - Adam Ponzi
- Institute of Biophysics, National Research Council, Palermo, Italy
- Center for Human Nature, Artificial Intelligence, and Neuroscience, Hokkaido University, Sapporo, Japan
| | - Vladimir M. Calderón
- Department of Developmental Neurobiology and Neurophysiology, Neurobiology Institute, National Autonomous University of Mexico, Querétaro, Mexico
| | - Rosanna Migliore
- Institute of Biophysics, National Research Council, Palermo, Italy
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21
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Vinograd A, Nair A, Linderman SW, Anderson DJ. Intrinsic Dynamics and Neural Implementation of a Hypothalamic Line Attractor Encoding an Internal Behavioral State. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.21.595051. [PMID: 38826298 PMCID: PMC11142118 DOI: 10.1101/2024.05.21.595051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Line attractors are emergent population dynamics hypothesized to encode continuous variables such as head direction and internal states. In mammals, direct evidence of neural implementation of a line attractor has been hindered by the challenge of targeting perturbations to specific neurons within contributing ensembles. Estrogen receptor type 1 (Esr1)-expressing neurons in the ventrolateral subdivision of the ventromedial hypothalamus (VMHvl) show line attractor dynamics in male mice during fighting. We hypothesized that these dynamics may encode continuous variation in the intensity of an internal aggressive state. Here, we report that these neurons also show line attractor dynamics in head-fixed mice observing aggression. We exploit this finding to identify and perturb line attractor-contributing neurons using 2-photon calcium imaging and holographic optogenetic perturbations. On-manifold perturbations demonstrate that integration and persistent activity are intrinsic properties of these neurons which drive the system along the line attractor, while transient off-manifold perturbations reveal rapid relaxation back into the attractor. Furthermore, stimulation and imaging reveal selective functional connectivity among attractor-contributing neurons. Intriguingly, individual differences among mice in line attractor stability were correlated with the degree of functional connectivity among contributing neurons. Mechanistic modelling indicates that dense subnetwork connectivity and slow neurotransmission are required to explain our empirical findings. Our work bridges circuit and manifold paradigms, shedding light on the intrinsic and operational dynamics of a behaviorally relevant mammalian line attractor.
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Affiliation(s)
- Amit Vinograd
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
| | - Aditya Nair
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
| | - Scott W. Linderman
- Department of Statistics, Stanford University, Stanford, USA
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, USA
| | - David J. Anderson
- Division of Biology and Biological Engineering, California Institute of Technology; Pasadena, USA
- Tianqiao and Chrissy Chen Institute for Neuroscience Caltech; Pasadena, USA
- Howard Hughes Medical Institute; Chevy Chase, USA
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22
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Chockanathan U, Padmanabhan K. Differential disruptions in population coding along the dorsal-ventral axis of CA1 in the APP/PS1 mouse model of Aβ pathology. PLoS Comput Biol 2024; 20:e1012085. [PMID: 38709845 PMCID: PMC11098488 DOI: 10.1371/journal.pcbi.1012085] [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: 02/04/2023] [Revised: 05/16/2024] [Accepted: 04/17/2024] [Indexed: 05/08/2024] Open
Abstract
Alzheimer's Disease (AD) is characterized by a range of behavioral alterations, including memory loss and psychiatric symptoms. While there is evidence that molecular pathologies, such as amyloid beta (Aβ), contribute to AD, it remains unclear how this histopathology gives rise to such disparate behavioral deficits. One hypothesis is that Aβ exerts differential effects on neuronal circuits across brain regions, depending on the neurophysiology and connectivity of different areas. To test this, we recorded from large neuronal populations in dorsal CA1 (dCA1) and ventral CA1 (vCA1), two hippocampal areas known to be structurally and functionally diverse, in the APP/PS1 mouse model of amyloidosis. Despite similar levels of Aβ pathology, dCA1 and vCA1 showed distinct disruptions in neuronal population activity as animals navigated a virtual reality environment. In dCA1, pairwise correlations and entropy, a measure of the diversity of activity patterns, were decreased in APP/PS1 mice relative to age-matched C57BL/6 controls. However, in vCA1, APP/PS1 mice had increased pair-wise correlations and entropy as compared to age matched controls. Finally, using maximum entropy models, we connected the microscopic features of population activity (correlations) to the macroscopic features of the population code (entropy). We found that the models' performance increased in predicting dCA1 activity, but decreased in predicting vCA1 activity, in APP/PS1 mice relative to the controls. Taken together, we found that Aβ exerts distinct effects across different hippocampal regions, suggesting that the various behavioral deficits of AD may reflect underlying heterogeneities in neuronal circuits and the different disruptions that Aβ pathology causes in those circuits.
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Affiliation(s)
- Udaysankar Chockanathan
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Neuroscience Graduate Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Medical Scientist Training Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
| | - Krishnan Padmanabhan
- Department of Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Neuroscience Graduate Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Medical Scientist Training Program, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Center for Visual Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
- Intellectual and Developmental Disabilities Research Center, University of Rochester School of Medicine and Dentistry, Rochester, New York, United States of America
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23
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Papadopouli M, Smyrnakis I, Koniotakis E, Savaglio MA, Brozi C, Psilou E, Palagina G, Smirnakis SM. Brain orchestra under spontaneous conditions: Identifying communication modules from the functional architecture of area V1. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.29.582364. [PMID: 38496414 PMCID: PMC10942267 DOI: 10.1101/2024.02.29.582364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
We used two-photon imaging to record from granular and supragranular layers in mouse primary visual cortex (V1) under spontaneous conditions and applied an extension of the spike time tiling coefficient (STTC; introduced by Cutts and Eglen) to map functional connectivity architecture within and across layers. We made several observations: Approximately, 19-34% of neuronal pairs within 300 μm of each other exhibit statistically significant functional connections, compared to ~10% at distances of 1mm or more. As expected, neuronal pairs with similar tuning functions exhibit a significant, though relatively small, increase in the fraction of functional inter-neuronal correlations. In contrast, internal state as reflected by pupillary diameter or aggregate neuronal activity appears to play a much stronger role in determining inter-neuronal correlation distributions and topography. Overall, inter-neuronal correlations appear to be slightly more prominent in L4. The first-order functionally connected (i.e., direct) neighbors of neurons determine the hub structure of the V1 microcircuit. L4 exhibits a nearly flat degree of connectivity distribution, extending to higher values than seen in supragranular layers, whose distribution drops exponentially. In all layers, functional connectivity exhibits small-world characteristics and network robustness. The probability of firing of L2/3 pyramidal neurons can be predicted as a function of the aggregate activity in their first-order functionally connected partners within L4, which represent their putative input group. The functional form of this prediction conforms well to a ReLU function, reaching up to firing probability one in some neurons. Interestingly, the properties of L2/3 pyramidal neurons differ based on the size of their L4 functional connectivity group. Specifically, L2/3 neurons with small layer-4 degrees of connectivity appear to be more sensitive to the firing of their L4 functional connectivity partners, suggesting they may be more effective at transmitting synchronous activity downstream from L4. They also appear to fire largely independently from each other, compared to neurons with high layer-4 degrees of connectivity, and are less modulated by changes in pupil size and aggregate population dynamics. Information transmission is best viewed as occurring from neuronal ensembles in L4 to neuronal ensembles in L2/3. Under spontaneous conditions, we were able to identify such candidate neuronal ensembles, which exhibit high sensitivity, precision, and specificity for L4 to L2/3 information transmission. In sum, functional connectivity analysis under spontaneous activity conditions reveals a modular neuronal ensemble architecture within and across granular and supragranular layers of mouse primary visual cortex. Furthermore, modules with different degrees of connectivity appear to obey different rules of engagement and communication across the V1 columnar circuit.
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Affiliation(s)
- Maria Papadopouli
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | | | - Emmanouil Koniotakis
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Mario-Alexios Savaglio
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Christina Brozi
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Eleftheria Psilou
- Department of Computer Science, University of Crete, Heraklion, Greece
- Institute of Computer Science, Foundation for Research & Technology-Hellas, Heraklion, Greece
| | - Ganna Palagina
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, USA
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24
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Yuste R, Cossart R, Yaksi E. Neuronal ensembles: Building blocks of neural circuits. Neuron 2024; 112:875-892. [PMID: 38262413 PMCID: PMC10957317 DOI: 10.1016/j.neuron.2023.12.008] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 06/07/2023] [Accepted: 12/13/2023] [Indexed: 01/25/2024]
Abstract
Neuronal ensembles, defined as groups of neurons displaying recurring patterns of coordinated activity, represent an intermediate functional level between individual neurons and brain areas. Novel methods to measure and optically manipulate the activity of neuronal populations have provided evidence of ensembles in the neocortex and hippocampus. Ensembles can be activated intrinsically or in response to sensory stimuli and play a causal role in perception and behavior. Here we review ensemble phenomenology, developmental origin, biophysical and synaptic mechanisms, and potential functional roles across different brain areas and species, including humans. As modular units of neural circuits, ensembles could provide a mechanistic underpinning of fundamental brain processes, including neural coding, motor planning, decision-making, learning, and adaptability.
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Affiliation(s)
- Rafael Yuste
- NeuroTechnology Center, Department of Biological Sciences, Columbia University, New York, NY, USA.
| | - Rosa Cossart
- Inserm, INMED, Turing Center for Living Systems Aix-Marseille University, Marseille, France.
| | - Emre Yaksi
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway; Koç University Research Center for Translational Medicine, Koç University School of Medicine, Istanbul, Turkey.
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25
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Russell LE, Fişek M, Yang Z, Tan LP, Packer AM, Dalgleish HWP, Chettih SN, Harvey CD, Häusser M. The influence of cortical activity on perception depends on behavioral state and sensory context. Nat Commun 2024; 15:2456. [PMID: 38503769 PMCID: PMC10951313 DOI: 10.1038/s41467-024-46484-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 02/28/2024] [Indexed: 03/21/2024] Open
Abstract
The mechanistic link between neural circuit activity and behavior remains unclear. While manipulating cortical activity can bias certain behaviors and elicit artificial percepts, some tasks can still be solved when cortex is silenced or removed. Here, mice were trained to perform a visual detection task during which we selectively targeted groups of visually responsive and co-tuned neurons in L2/3 of primary visual cortex (V1) for two-photon photostimulation. The influence of photostimulation was conditional on two key factors: the behavioral state of the animal and the contrast of the visual stimulus. The detection of low-contrast stimuli was enhanced by photostimulation, while the detection of high-contrast stimuli was suppressed, but crucially, only when mice were highly engaged in the task. When mice were less engaged, our manipulations of cortical activity had no effect on behavior. The behavioral changes were linked to specific changes in neuronal activity. The responses of non-photostimulated neurons in the local network were also conditional on two factors: their functional similarity to the photostimulated neurons and the contrast of the visual stimulus. Functionally similar neurons were increasingly suppressed by photostimulation with increasing visual stimulus contrast, correlating with the change in behavior. Our results show that the influence of cortical activity on perception is not fixed, but dynamically and contextually modulated by behavioral state, ongoing activity and the routing of information through specific circuits.
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Affiliation(s)
- Lloyd E Russell
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Mehmet Fişek
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Zidan Yang
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Lynn Pei Tan
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Adam M Packer
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | - Henry W P Dalgleish
- Wolfson Institute for Biomedical Research, University College London, London, UK
| | | | | | - Michael Häusser
- Wolfson Institute for Biomedical Research, University College London, London, UK.
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26
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Matteucci G, Piasini E, Zoccolan D. Unsupervised learning of mid-level visual representations. Curr Opin Neurobiol 2024; 84:102834. [PMID: 38154417 DOI: 10.1016/j.conb.2023.102834] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 12/03/2023] [Accepted: 12/05/2023] [Indexed: 12/30/2023]
Abstract
Recently, a confluence between trends in neuroscience and machine learning has brought a renewed focus on unsupervised learning, where sensory processing systems learn to exploit the statistical structure of their inputs in the absence of explicit training targets or rewards. Sophisticated experimental approaches have enabled the investigation of the influence of sensory experience on neural self-organization and its synaptic bases. Meanwhile, novel algorithms for unsupervised and self-supervised learning have become increasingly popular both as inspiration for theories of the brain, particularly for the function of intermediate visual cortical areas, and as building blocks of real-world learning machines. Here we review some of these recent developments, placing them in historical context and highlighting some research lines that promise exciting breakthroughs in the near future.
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Affiliation(s)
- Giulio Matteucci
- Department of Basic Neurosciences, University of Geneva, Geneva, 1206, Switzerland. https://twitter.com/giulio_matt
| | - Eugenio Piasini
- International School for Advanced Studies (SISSA), Trieste, 34136, Italy
| | - Davide Zoccolan
- International School for Advanced Studies (SISSA), Trieste, 34136, Italy.
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27
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de Brito CSN, Gerstner W. Learning what matters: Synaptic plasticity with invariance to second-order input correlations. PLoS Comput Biol 2024; 20:e1011844. [PMID: 38346073 PMCID: PMC10890752 DOI: 10.1371/journal.pcbi.1011844] [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: 12/01/2022] [Revised: 02/23/2024] [Accepted: 01/18/2024] [Indexed: 02/25/2024] Open
Abstract
Cortical populations of neurons develop sparse representations adapted to the statistics of the environment. To learn efficient population codes, synaptic plasticity mechanisms must differentiate relevant latent features from spurious input correlations, which are omnipresent in cortical networks. Here, we develop a theory for sparse coding and synaptic plasticity that is invariant to second-order correlations in the input. Going beyond classical Hebbian learning, our learning objective explains the functional form of observed excitatory plasticity mechanisms, showing how Hebbian long-term depression (LTD) cancels the sensitivity to second-order correlations so that receptive fields become aligned with features hidden in higher-order statistics. Invariance to second-order correlations enhances the versatility of biologically realistic learning models, supporting optimal decoding from noisy inputs and sparse population coding from spatially correlated stimuli. In a spiking model with triplet spike-timing-dependent plasticity (STDP), we show that individual neurons can learn localized oriented receptive fields, circumventing the need for input preprocessing, such as whitening, or population-level lateral inhibition. The theory advances our understanding of local unsupervised learning in cortical circuits, offers new interpretations of the Bienenstock-Cooper-Munro and triplet STDP models, and assigns a specific functional role to synaptic LTD mechanisms in pyramidal neurons.
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Affiliation(s)
- Carlos Stein Naves de Brito
- École Polytechnique Fédérale de Lausanne, EPFL, Lusanne, Switzerland
- Champalimaud Research, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Wulfram Gerstner
- École Polytechnique Fédérale de Lausanne, EPFL, Lusanne, Switzerland
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28
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Oldenburg IA, Hendricks WD, Handy G, Shamardani K, Bounds HA, Doiron B, Adesnik H. The logic of recurrent circuits in the primary visual cortex. Nat Neurosci 2024; 27:137-147. [PMID: 38172437 PMCID: PMC10774145 DOI: 10.1038/s41593-023-01510-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 10/27/2023] [Indexed: 01/05/2024]
Abstract
Recurrent cortical activity sculpts visual perception by refining, amplifying or suppressing visual input. However, the rules that govern the influence of recurrent activity remain enigmatic. We used ensemble-specific two-photon optogenetics in the mouse visual cortex to isolate the impact of recurrent activity from external visual input. We found that the spatial arrangement and the visual feature preference of the stimulated ensemble and the neighboring neurons jointly determine the net effect of recurrent activity. Photoactivation of these ensembles drives suppression in all cells beyond 30 µm but uniformly drives activation in closer similarly tuned cells. In nonsimilarly tuned cells, compact, cotuned ensembles drive net suppression, while diffuse, cotuned ensembles drive activation. Computational modeling suggests that highly local recurrent excitatory connectivity and selective convergence onto inhibitory neurons explain these effects. Our findings reveal a straightforward logic in which space and feature preference of cortical ensembles determine their impact on local recurrent activity.
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Affiliation(s)
- Ian Antón Oldenburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, and Center for Advanced Biotechnology and Medicine, Rutgers University, Piscataway, NJ, USA.
| | - William D Hendricks
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Gregory Handy
- 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 Minnesota, Minneapolis, MN, USA.
| | - Kiarash Shamardani
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Hayley A Bounds
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, 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
| | - Hillel Adesnik
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
- The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA.
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29
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Dragoi G. The generative grammar of the brain: a critique of internally generated representations. Nat Rev Neurosci 2024; 25:60-75. [PMID: 38036709 PMCID: PMC11878217 DOI: 10.1038/s41583-023-00763-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/18/2023] [Indexed: 12/02/2023]
Abstract
The past decade of progress in neurobiology has uncovered important organizational principles for network preconfiguration and neuronal selection that suggest a generative grammar exists in the brain. In this Perspective, I discuss the competence of the hippocampal neural network to generically express temporally compressed sequences of neuronal firing that represent novel experiences, which is envisioned as a form of generative neural syntax supporting a neurobiological perspective on brain function. I compare this neural competence with the hippocampal network performance that represents specific experiences with higher fidelity after new learning during replay, which is envisioned as a form of neural semantic that supports a complementary neuropsychological perspective. I also demonstrate how the syntax of network competence emerges a priori during early postnatal life and is followed by the later development of network performance that enables rapid encoding and memory consolidation. Thus, I propose that this generative grammar of the brain is essential for internally generated representations, which are crucial for the cognitive processes underlying learning and memory, prospection, and inference, which ultimately underlie our reason and representation of the world.
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Affiliation(s)
- George Dragoi
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA.
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
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30
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Nguyen ND, Lutas A, Amsalem O, Fernando J, Ahn AYE, Hakim R, Vergara J, McMahon J, Dimidschstein J, Sabatini BL, Andermann ML. Cortical reactivations predict future sensory responses. Nature 2024; 625:110-118. [PMID: 38093002 PMCID: PMC11014741 DOI: 10.1038/s41586-023-06810-1] [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: 10/10/2022] [Accepted: 10/31/2023] [Indexed: 01/05/2024]
Abstract
Many theories of offline memory consolidation posit that the pattern of neurons activated during a salient sensory experience will be faithfully reactivated, thereby stabilizing the pattern1,2. However, sensory-evoked patterns are not stable but, instead, drift across repeated experiences3-6. Here, to investigate the relationship between reactivations and the drift of sensory representations, we imaged the calcium activity of thousands of excitatory neurons in the mouse lateral visual cortex. During the minute after a visual stimulus, we observed transient, stimulus-specific reactivations, often coupled with hippocampal sharp-wave ripples. Stimulus-specific reactivations were abolished by local cortical silencing during the preceding stimulus. Reactivations early in a session systematically differed from the pattern evoked by the previous stimulus-they were more similar to future stimulus response patterns, thereby predicting both within-day and across-day representational drift. In particular, neurons that participated proportionally more or less in early stimulus reactivations than in stimulus response patterns gradually increased or decreased their future stimulus responses, respectively. Indeed, we could accurately predict future changes in stimulus responses and the separation of responses to distinct stimuli using only the rate and content of reactivations. Thus, reactivations may contribute to a gradual drift and separation in sensory cortical response patterns, thereby enhancing sensory discrimination7.
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Affiliation(s)
- Nghia D Nguyen
- Program in Neuroscience, Harvard University, Boston, MA, USA
| | - Andrew Lutas
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Diabetes, Endocrinology and Obesity Branch, National Institutes of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | - Oren Amsalem
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Jesseba Fernando
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Andy Young-Eon Ahn
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Richard Hakim
- Program in Neuroscience, Harvard University, Boston, MA, USA
- Howard Hughes Medical Institute, Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Josselyn Vergara
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Justin McMahon
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Jordane Dimidschstein
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Bernardo L Sabatini
- Program in Neuroscience, Harvard University, Boston, MA, USA
- Howard Hughes Medical Institute, Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Mark L Andermann
- Program in Neuroscience, Harvard University, Boston, MA, USA.
- Division of Endocrinology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA.
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31
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Lees RM, Pichler B, Packer AM. Contribution of optical resolution to the spatial precision of two-photon optogenetic photostimulation in vivo. NEUROPHOTONICS 2024; 11:015006. [PMID: 38322022 PMCID: PMC10846536 DOI: 10.1117/1.nph.11.1.015006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 01/04/2024] [Accepted: 01/05/2024] [Indexed: 02/08/2024]
Abstract
Significance Two-photon optogenetics combines nonlinear excitation with noninvasive activation of neurons to enable the manipulation of neural circuits with a high degree of spatial precision. Combined with two-photon population calcium imaging, these approaches comprise a flexible platform for all-optical interrogation of neural circuits. However, a multitude of optical and biological factors dictate the exact precision of this approach in vivo, where it is most usefully applied. Aim We aimed to assess how the optical point spread function (OPSF) contributes to the spatial precision of two-photon photostimulation in neurobiology. Approach We altered the axial spread of the OPSF of the photostimulation beam using a spatial light modulator. Subsequently, calcium imaging was used to monitor the axial spatial precision of two-photon photostimulation of layer 2 neurons in the mouse neocortex. Results We found that optical resolution is not always the limiting factor of the spatial precision of two-photon optogenetic photostimulation and, by doing so, reveal the key factors that must be improved to achieve maximal precision. Conclusions Our results enable future work to focus on the optimal factors by providing key insight from controlled experiments in a manner not previously reported. This research can be applied to advance the state-of-the-art of all-optical interrogation, extending the toolkit for neuroscience research to achieve spatiotemporal precision at the crucial levels in which neural circuits operate.
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Affiliation(s)
- Robert M. Lees
- Science and Technology Facilities Council, Octopus Imaging Facility, Oxfordshire, United Kingdom
- University of Oxford, Department of Physiology, Anatomy, and Genetics, Oxford, United Kingdom
| | - Bruno Pichler
- Independent NeuroScience Services INSS Ltd., East Sussex, United Kingdom
| | - Adam M. Packer
- University of Oxford, Department of Physiology, Anatomy, and Genetics, Oxford, United Kingdom
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32
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Davidson CJ, Mascarin AT, Yahya MA, Rubio FJ, Gheidi A. Approaches and considerations of studying neuronal ensembles: a brief review. Front Cell Neurosci 2023; 17:1310724. [PMID: 38155864 PMCID: PMC10752959 DOI: 10.3389/fncel.2023.1310724] [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: 10/09/2023] [Accepted: 11/27/2023] [Indexed: 12/30/2023] Open
Abstract
First theorized by Hebb, neuronal ensembles have provided a framework for understanding how the mammalian brain operates, especially regarding learning and memory. Neuronal ensembles are discrete, sparsely distributed groups of neurons that become activated in response to a specific stimulus and are thought to provide an internal representation of the world. Beyond the study of region-wide or projection-wide activation, the study of ensembles offers increased specificity and resolution to identify and target specific memories or associations. Neuroscientists interested in the neurobiology of learning, memory, and motivated behavior have used electrophysiological-, calcium-, and protein-based proxies of neuronal activity in preclinical models to better understand the neurobiology of learned and motivated behaviors. Although these three approaches may be used to pursue the same general goal of studying neuronal ensembles, technical differences lead to inconsistencies in the output and interpretation of data. This mini-review highlights some of the methodologies used in electrophysiological-, calcium-, and protein-based studies of neuronal ensembles and discusses their strengths and weaknesses.
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Affiliation(s)
- Cameron J. Davidson
- William Beaumont School of Medicine, Oakland University, Rochester, MI, United States
| | - Alixandria T. Mascarin
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - Majd A. Yahya
- Department of Psychiatry and Behavioral Neurosciences, Wayne State University School of Medicine, Detroit, MI, United States
| | - F. Javier Rubio
- Neuronal Ensembles in Addiction Section, Behavioral Neuroscience Research Branch, Intramural Research Program/National Institute on Drug Abuse/National Institutes of Health, Bethesda, MD, United States
| | - Ali Gheidi
- Department of Biomedical Sciences, Mercer University, Macon, GA, United States
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33
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Frost NA, Donohue KC, Sohal V. Context-invariant socioemotional encoding by prefrontal ensembles. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.19.563015. [PMID: 37961143 PMCID: PMC10634670 DOI: 10.1101/2023.10.19.563015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The prefrontal cortex plays a key role in social interactions, anxiety-related avoidance, and flexible context- dependent behaviors, raising the question: how do prefrontal neurons represent socioemotional information across different environments? Are contextual and socioemotional representations segregated or intermixed, and does this cause socioemotional encoding to remap or generalize across environments? To address this, we imaged neuronal activity in the medial prefrontal cortex of mice engaged in social interactions or anxiety-related avoidance within different environments. Neuronal ensembles representing context and social interaction overlapped more than expected while remaining orthogonal. Anxiety-related representations similarly generalized across environments while remaining orthogonal to contextual information. This shows how prefrontal cortex multiplexes parallel information streams using the same neurons, rather than distinct subcircuits, achieving context-invariant encoding despite context-specific reorganization of population-level activity.
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34
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Tong L, Han S, Xue Y, Chen M, Chen F, Ke W, Shu Y, Ding N, Bewersdorf J, Zhou ZJ, Yuan P, Grutzendler J. Single cell in vivo optogenetic stimulation by two-photon excitation fluorescence transfer. iScience 2023; 26:107857. [PMID: 37752954 PMCID: PMC10518705 DOI: 10.1016/j.isci.2023.107857] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Revised: 06/01/2023] [Accepted: 09/06/2023] [Indexed: 09/28/2023] Open
Abstract
Optogenetic manipulation with single-cell resolution can be achieved by two-photon excitation. However, this frequently requires relatively high laser powers. Here, we developed a novel strategy that can improve the efficiency of current two-photon stimulation technologies by positioning fluorescent proteins or small fluorescent molecules with high two-photon cross-sections in the vicinity of opsins. This generates a highly localized source of endogenous single-photon illumination that can be tailored to match the optimal opsin absorbance. Through neuronal and vascular stimulation in the live mouse brain, we demonstrate the utility of this technique to achieve efficient opsin stimulation, without loss of cellular resolution. We also provide a theoretical framework for understanding the potential advantages and constrains of this methodology, with directions for future improvements. Altogether, this fluorescence transfer illumination method opens new possibilities for experiments difficult to implement in the live brain such as all-optical neural interrogation and control of regional cerebral blood flow.
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Affiliation(s)
- Lei Tong
- Department of Neurology, Yale School of Medicine, New Haven, CT 06511, USA
| | - Shanshan Han
- Department of Rehabilitation Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Institute for Translational Brain Research, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Yao Xue
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT 06511, USA
| | - Minggang Chen
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT 06511, USA
| | - Fuyi Chen
- Department of Neurology, Yale School of Medicine, New Haven, CT 06511, USA
| | - Wei Ke
- Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Institute for Translational Brain Research, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Yousheng Shu
- Department of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Institute for Translational Brain Research, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Ning Ding
- Department of Rehabilitation Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Institute for Translational Brain Research, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Joerg Bewersdorf
- Department of Cell Biology, Yale School of Medicine, New Haven, CT 06511, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA
| | - Z. Jimmy Zhou
- Department of Ophthalmology and Visual Science, Yale School of Medicine, New Haven, CT 06511, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06511, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06511, USA
| | - Peng Yuan
- Department of Neurology, Yale School of Medicine, New Haven, CT 06511, USA
- Department of Rehabilitation Medicine, Huashan Hospital, State Key Laboratory of Medical Neurobiology, Institute for Translational Brain Research, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Jaime Grutzendler
- Department of Neurology, Yale School of Medicine, New Haven, CT 06511, USA
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06511, USA
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35
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Navarro P, Oweiss K. Compressive sensing of functional connectivity maps from patterned optogenetic stimulation of neuronal ensembles. PATTERNS (NEW YORK, N.Y.) 2023; 4:100845. [PMID: 37876895 PMCID: PMC10591201 DOI: 10.1016/j.patter.2023.100845] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Revised: 04/04/2023] [Accepted: 08/25/2023] [Indexed: 10/26/2023]
Abstract
Mapping functional connectivity between neurons is an essential step toward probing the neural computations mediating behavior. Accurately determining synaptic connectivity maps in populations of neurons is challenging in terms of yield, accuracy, and experimental time. Here, we developed a compressive sensing approach to reconstruct synaptic connectivity maps based on random two-photon cell-targeted optogenetic stimulation and membrane voltage readout of many putative postsynaptic neurons. Using a biophysical network model of interconnected populations of excitatory and inhibitory neurons, we characterized mapping recall and precision as a function of network observability, sparsity, number of neurons stimulated, off-target stimulation, synaptic reliability, propagation latency, and network topology. We found that mapping can be achieved with far fewer measurements than the standard pairwise sequential approach, with network sparsity and synaptic reliability serving as primary determinants of the performance. Our results suggest a rapid and efficient method to reconstruct functional connectivity of sparsely connected neuronal networks.
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Affiliation(s)
- Phillip Navarro
- Electrical and Computer Engineering Department, University of Florida, Gainesville, FL 32611, USA
| | - Karim Oweiss
- Electrical and Computer Engineering Department, University of Florida, Gainesville, FL 32611, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, FL 32611, USA
- Department of Neurology, University of Florida, Gainesville, FL 32611, USA
- Department of Neuroscience, McKnight Brain Institute, University of Florida, Gainesville, FL 32611, USA
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36
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Kimura R. Flexible information representation to stabilize sensory perception despite minor external input variations. Neurosci Res 2023; 195:1-8. [PMID: 37236268 DOI: 10.1016/j.neures.2023.05.002] [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: 02/06/2023] [Revised: 05/14/2023] [Accepted: 05/18/2023] [Indexed: 05/28/2023]
Abstract
Sensory information about the environment constantly changes or varies depending on circumstances. However, once we repeatedly experience objects, our brain can perceive and recognize them as identical, even if they are slightly altered or include some diversity. We can stably perceive things without interference from minor external changes or variety. Our recent study focusing on visual perception showed that repeatedly viewing the same oriented grating stimuli enables information representation for low-contrast (or weak-intensity) orientations in the primary visual cortex. We observed low contrast-preferring neurons, whose firing rates increased by reducing the luminance contrast. The number of such neurons increased after the experience, and the neuronal population, including such neurons, can represent even low-contrast orientations. This study indicated that experience leads to flexible information representations that continuously respond to inputs of various strengths at the neuronal population level in the primary sensory cortex. In this perspective article, in addition to the above mechanism, I would discuss alternative mechanisms for perceptual stabilization. The primary sensory cortex represents external information faithfully without alterations, as well as in a state distorted by experience. Both sensory representations may cooperatively and dynamically affect hierarchical downstream, resulting in stable perception.
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Affiliation(s)
- Rie Kimura
- International Research Center for Neurointelligence, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan.
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37
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O'Neil DA, Akrouh A, Yuste R. Mapping neuronal ensembles and pattern-completion neurons through graphical models. STAR Protoc 2023; 4:102543. [PMID: 37659084 PMCID: PMC10491856 DOI: 10.1016/j.xpro.2023.102543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/25/2023] [Accepted: 08/07/2023] [Indexed: 09/04/2023] Open
Abstract
Neuronal ensembles are coordinated groups of neurons that serve as functional building blocks of neural circuits. Here, we present PatMap, a computational toolbox for identifying pattern-completion neurons, key trigger cells capable of reactivating entire neuronal ensembles. We describe a protocol for modeling neural circuits as probabilistic graphical models, linking behavior with specific neuronal ensembles, and identifying their pattern-completion neurons. By linking the cellular and circuit level, PatMap provides a springboard for targeted manipulation and control of neural circuits. For complete details on the use and execution of this protocol, please refer to Carrillo-Reid et al. (2021).1.
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Affiliation(s)
- Darik A O'Neil
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York City, NY 10027, USA.
| | - Alejandro Akrouh
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York City, NY 10027, USA
| | - Rafael Yuste
- Neurotechnology Center, Department of Biological Sciences, Columbia University, New York City, NY 10027, USA
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38
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Bounds HA, Sadahiro M, Hendricks WD, Gajowa M, Gopakumar K, Quintana D, Tasic B, Daigle TL, Zeng H, Oldenburg IA, Adesnik H. All-optical recreation of naturalistic neural activity with a multifunctional transgenic reporter mouse. Cell Rep 2023; 42:112909. [PMID: 37542722 PMCID: PMC10755854 DOI: 10.1016/j.celrep.2023.112909] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/23/2023] [Accepted: 07/14/2023] [Indexed: 08/07/2023] Open
Abstract
Determining which features of the neural code drive behavior requires the ability to simultaneously read out and write in neural activity patterns with high precision across many neurons. All-optical systems that combine two-photon calcium imaging and targeted photostimulation enable the activation of specific, functionally defined groups of neurons. However, these techniques are unable to test how patterns of activity across a population contribute to computation because of an inability to both read and write cell-specific firing rates. To overcome this challenge, we make two advances: first, we introduce a genetic line of mice for Cre-dependent co-expression of a calcium indicator and a potent soma-targeted microbial opsin. Second, using this line, we develop a method for read-out and write-in of precise population vectors of neural activity by calibrating the photostimulation to each cell. These advances offer a powerful and convenient platform for investigating the neural codes of computation and behavior.
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Affiliation(s)
- Hayley A Bounds
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Masato Sadahiro
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - William D Hendricks
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Marta Gajowa
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Karthika Gopakumar
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | - Daniel Quintana
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA
| | | | | | - Hongkui Zeng
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Ian Antón Oldenburg
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA.
| | - Hillel Adesnik
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA, USA; The Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA; Chan Zuckerberg Biohub, San Francisco, CA 94158, USA.
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39
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Maes A, Barahona M, Clopath C. Long- and short-term history effects in a spiking network model of statistical learning. Sci Rep 2023; 13:12939. [PMID: 37558704 PMCID: PMC10412617 DOI: 10.1038/s41598-023-39108-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 07/20/2023] [Indexed: 08/11/2023] Open
Abstract
The statistical structure of the environment is often important when making decisions. There are multiple theories of how the brain represents statistical structure. One such theory states that neural activity spontaneously samples from probability distributions. In other words, the network spends more time in states which encode high-probability stimuli. Starting from the neural assembly, increasingly thought of to be the building block for computation in the brain, we focus on how arbitrary prior knowledge about the external world can both be learned and spontaneously recollected. We present a model based upon learning the inverse of the cumulative distribution function. Learning is entirely unsupervised using biophysical neurons and biologically plausible learning rules. We show how this prior knowledge can then be accessed to compute expectations and signal surprise in downstream networks. Sensory history effects emerge from the model as a consequence of ongoing learning.
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Affiliation(s)
- Amadeus Maes
- Department of Neuroscience, Feinberg School of Medicine, Northwestern University, Chicago, USA.
- Department of Bioengineering, Imperial College London, London, UK.
| | | | - Claudia Clopath
- Department of Bioengineering, Imperial College London, London, UK
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40
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Guskjolen A, Cembrowski MS. Engram neurons: Encoding, consolidation, retrieval, and forgetting of memory. Mol Psychiatry 2023; 28:3207-3219. [PMID: 37369721 PMCID: PMC10618102 DOI: 10.1038/s41380-023-02137-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 06/02/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023]
Abstract
Tremendous strides have been made in our understanding of the neurobiological substrates of memory - the so-called memory "engram". Here, we integrate recent progress in the engram field to illustrate how engram neurons transform across the "lifespan" of a memory - from initial memory encoding, to consolidation and retrieval, and ultimately to forgetting. To do so, we first describe how cell-intrinsic properties shape the initial emergence of the engram at memory encoding. Second, we highlight how these encoding neurons preferentially participate in synaptic- and systems-level consolidation of memory. Third, we describe how these changes during encoding and consolidation guide neural reactivation during retrieval, and facilitate memory recall. Fourth, we describe neurobiological mechanisms of forgetting, and how these mechanisms can counteract engram properties established during memory encoding, consolidation, and retrieval. Motivated by recent experimental results across these four sections, we conclude by proposing some conceptual extensions to the traditional view of the engram, including broadening the view of cell-type participation within engrams and across memory stages. In collection, our review synthesizes general principles of the engram across memory stages, and describes future avenues to further understand the dynamic engram.
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Affiliation(s)
- Axel Guskjolen
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada.
| | - Mark S Cembrowski
- Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada.
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada.
- School of Biomedical Engineering, University of British Columbia, Vancouver, BC, Canada.
- Department of Mathematics, University of British Columbia, Vancouver, BC, Canada.
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41
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Pancholi R, Ryan L, Peron S. Learning in a sensory cortical microstimulation task is associated with elevated representational stability. Nat Commun 2023; 14:3860. [PMID: 37385989 PMCID: PMC10310840 DOI: 10.1038/s41467-023-39542-x] [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: 08/27/2022] [Accepted: 06/16/2023] [Indexed: 07/01/2023] Open
Abstract
Sensory cortical representations can be highly dynamic, raising the question of how representational stability impacts learning. We train mice to discriminate the number of photostimulation pulses delivered to opsin-expressing pyramidal neurons in layer 2/3 of primary vibrissal somatosensory cortex. We simultaneously track evoked neural activity across learning using volumetric two-photon calcium imaging. In well-trained animals, trial-to-trial fluctuations in the amount of photostimulus-evoked activity predicted animal choice. Population activity levels declined rapidly across training, with the most active neurons showing the largest declines in responsiveness. Mice learned at varied rates, with some failing to learn the task in the time provided. The photoresponsive population showed greater instability both within and across behavioral sessions among animals that failed to learn. Animals that failed to learn also exhibited a faster deterioration in stimulus decoding. Thus, greater stability in the stimulus response is associated with learning in a sensory cortical microstimulation task.
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Affiliation(s)
- Ravi Pancholi
- Center for Neural Science, New York University, 4 Washington Place Rm. 621, New York, NY, 10003, USA
| | - Lauren Ryan
- Center for Neural Science, New York University, 4 Washington Place Rm. 621, New York, NY, 10003, USA
| | - Simon Peron
- Center for Neural Science, New York University, 4 Washington Place Rm. 621, New York, NY, 10003, USA.
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42
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Baker CM, Gong Y. Identifying properties of pattern completion neurons in a computational model of the visual cortex. PLoS Comput Biol 2023; 19:e1011167. [PMID: 37279242 DOI: 10.1371/journal.pcbi.1011167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Accepted: 05/09/2023] [Indexed: 06/08/2023] Open
Abstract
Neural ensembles are found throughout the brain and are believed to underlie diverse cognitive functions including memory and perception. Methods to activate ensembles precisely, reliably, and quickly are needed to further study the ensembles' role in cognitive processes. Previous work has found that ensembles in layer 2/3 of the visual cortex (V1) exhibited pattern completion properties: ensembles containing tens of neurons were activated by stimulation of just two neurons. However, methods that identify pattern completion neurons are underdeveloped. In this study, we optimized the selection of pattern completion neurons in simulated ensembles. We developed a computational model that replicated the connectivity patterns and electrophysiological properties of layer 2/3 of mouse V1. We identified ensembles of excitatory model neurons using K-means clustering. We then stimulated pairs of neurons in identified ensembles while tracking the activity of the entire ensemble. Our analysis of ensemble activity quantified a neuron pair's power to activate an ensemble using a novel metric called pattern completion capability (PCC) based on the mean pre-stimulation voltage across the ensemble. We found that PCC was directly correlated with multiple graph theory parameters, such as degree and closeness centrality. To improve selection of pattern completion neurons in vivo, we computed a novel latency metric that was correlated with PCC and could potentially be estimated from modern physiological recordings. Lastly, we found that stimulation of five neurons could reliably activate ensembles. These findings can help researchers identify pattern completion neurons to stimulate in vivo during behavioral studies to control ensemble activation.
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Affiliation(s)
- Casey M Baker
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America
| | - Yiyang Gong
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, United States of America
- Department of Neurobiology, Duke University, Durham, North Carolina, United States of America
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43
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Rindner DJ, Lur G. Practical considerations in an era of multicolor optogenetics. Front Cell Neurosci 2023; 17:1160245. [PMID: 37293628 PMCID: PMC10244638 DOI: 10.3389/fncel.2023.1160245] [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: 02/06/2023] [Accepted: 05/05/2023] [Indexed: 06/10/2023] Open
Abstract
The ability to control synaptic communication is indispensable to modern neuroscience. Until recently, only single-pathway manipulations were possible due to limited availability of opsins activated by distinct wavelengths. However, extensive protein engineering and screening efforts have drastically expanded the optogenetic toolkit, ushering in an era of multicolor approaches for studying neural circuits. Nonetheless, opsins with truly discrete spectra are scarce. Experimenters must therefore take care to avoid unintended cross-activation of optogenetic tools (crosstalk). Here, we demonstrate the multidimensional nature of crosstalk in a single model synaptic pathway, testing stimulus wavelength, irradiance, duration, and opsin choice. We then propose a "lookup table" method for maximizing the dynamic range of opsin responses on an experiment-by-experiment basis.
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Affiliation(s)
| | - Gyorgy Lur
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, United States
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44
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Pancholi R, Sun-Yan A, Peron S. Microstimulation of sensory cortex engages natural sensory representations. Curr Biol 2023; 33:1765-1777.e5. [PMID: 37130521 PMCID: PMC10246453 DOI: 10.1016/j.cub.2023.03.085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Revised: 03/03/2023] [Accepted: 03/30/2023] [Indexed: 05/04/2023]
Abstract
Cortical activity patterns occupy a small subset of possible network states. If this is due to intrinsic network properties, microstimulation of sensory cortex should evoke activity patterns resembling those observed during natural sensory input. Here, we use optical microstimulation of virally transfected layer 2/3 pyramidal neurons in the mouse primary vibrissal somatosensory cortex to compare artificially evoked activity with natural activity evoked by whisker touch and movement ("whisking"). We find that photostimulation engages touch- but not whisking-responsive neurons more than expected by chance. Neurons that respond to photostimulation and touch or to touch alone exhibit higher spontaneous pairwise correlations than purely photoresponsive neurons. Exposure to several days of simultaneous touch and optogenetic stimulation raises both overlap and spontaneous activity correlations among touch and photoresponsive neurons. We thus find that cortical microstimulation engages existing cortical representations and that repeated co-presentation of natural and artificial stimulation enhances this effect.
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Affiliation(s)
- Ravi Pancholi
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003, USA
| | - Andrew Sun-Yan
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003, USA
| | - Simon Peron
- Center for Neural Science, New York University, 4 Washington Pl., Rm. 621, New York, NY 10003, USA.
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45
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Fişek M, Herrmann D, Egea-Weiss A, Cloves M, Bauer L, Lee TY, Russell LE, Häusser M. Cortico-cortical feedback engages active dendrites in visual cortex. Nature 2023; 617:769-776. [PMID: 37138089 DOI: 10.1038/s41586-023-06007-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Accepted: 03/23/2023] [Indexed: 05/05/2023]
Abstract
Sensory processing in the neocortex requires both feedforward and feedback information flow between cortical areas1. In feedback processing, higher-level representations provide contextual information to lower levels, and facilitate perceptual functions such as contour integration and figure-ground segmentation2,3. However, we have limited understanding of the circuit and cellular mechanisms that mediate feedback influence. Here we use long-range all-optical connectivity mapping in mice to show that feedback influence from the lateromedial higher visual area (LM) to the primary visual cortex (V1) is spatially organized. When the source and target of feedback represent the same area of visual space, feedback is relatively suppressive. By contrast, when the source is offset from the target in visual space, feedback is relatively facilitating. Two-photon calcium imaging data show that this facilitating feedback is nonlinearly integrated in the apical tuft dendrites of V1 pyramidal neurons: retinotopically offset (surround) visual stimuli drive local dendritic calcium signals indicative of regenerative events, and two-photon optogenetic activation of LM neurons projecting to identified feedback-recipient spines in V1 can drive similar branch-specific local calcium signals. Our results show how neocortical feedback connectivity and nonlinear dendritic integration can together form a substrate to support both predictive and cooperative contextual interactions.
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Affiliation(s)
- Mehmet Fişek
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
| | - Dustin Herrmann
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Alexander Egea-Weiss
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Matilda Cloves
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lisa Bauer
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Tai-Ying Lee
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Lloyd E Russell
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK
| | - Michael Häusser
- Wolfson Institute for Biomedical Research and Department of Neuroscience, Physiology and Pharmacology, University College London, London, UK.
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46
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Li XW, Ren Y, Shi DQ, Qi L, Xu F, Xiao Y, Lau PM, Bi GQ. Biphasic Cholinergic Modulation of Reverberatory Activity in Neuronal Networks. Neurosci Bull 2023; 39:731-744. [PMID: 36670292 PMCID: PMC10170002 DOI: 10.1007/s12264-022-01012-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 09/04/2022] [Indexed: 01/22/2023] Open
Abstract
Acetylcholine (ACh) is an important neuromodulator in various cognitive functions. However, it is unclear how ACh influences neural circuit dynamics by altering cellular properties. Here, we investigated how ACh influences reverberatory activity in cultured neuronal networks. We found that ACh suppressed the occurrence of evoked reverberation at low to moderate doses, but to a much lesser extent at high doses. Moreover, high doses of ACh caused a longer duration of evoked reverberation, and a higher occurrence of spontaneous activity. With whole-cell recording from single neurons, we found that ACh inhibited excitatory postsynaptic currents (EPSCs) while elevating neuronal firing in a dose-dependent manner. Furthermore, all ACh-induced cellular and network changes were blocked by muscarinic, but not nicotinic receptor antagonists. With computational modeling, we found that simulated changes in EPSCs and the excitability of single cells mimicking the effects of ACh indeed modulated the evoked network reverberation similar to experimental observations. Thus, ACh modulates network dynamics in a biphasic fashion, probably by inhibiting excitatory synaptic transmission and facilitating neuronal excitability through muscarinic signaling pathways.
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Affiliation(s)
- Xiao-Wei Li
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Yi Ren
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Dong-Qing Shi
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Lei Qi
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
| | - Fang Xu
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
| | - Yanyang Xiao
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
| | - Pak-Ming Lau
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China.
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China.
| | - Guo-Qiang Bi
- CAS Key Laboratory of Brain Function and Disease, School of Life Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230027, China
- CAS Key Laboratory of Brain Connectome and Manipulation, Interdisciplinary Center for Brain Information, the Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences; Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, 518055, China
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47
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Abdeladim L, Shin H, Jagadisan UK, Ogando MB, Adesnik H. Probing inter-areal computations with a cellular resolution two-photon holographic mesoscope. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.02.530875. [PMID: 37090604 PMCID: PMC10120651 DOI: 10.1101/2023.03.02.530875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Brain computation depends on intricately connected yet highly distributed neural networks. Due to the absence of the requisite technologies, causally testing fundamental hypotheses on the nature of inter-areal processing have remained largely out-of-each. Here we developed the first two photon holographic mesoscope, a system capable of simultaneously reading and writing neural activity patterns with single cell resolution across large regions of the brain. We demonstrate the precise photo-activation of spatial and temporal sequences of neurons in one brain area while reading out the downstream effect in several other regions. Investigators can use this new platform to understand feed-forward and feed-back processing in distributed neural circuits with single cell precision for the first time.
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48
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Chen S, Yang Q, Lim S. Efficient inference of synaptic plasticity rule with Gaussian process regression. iScience 2023; 26:106182. [PMID: 36879810 PMCID: PMC9985048 DOI: 10.1016/j.isci.2023.106182] [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: 07/22/2022] [Revised: 01/24/2023] [Accepted: 02/07/2023] [Indexed: 02/16/2023] Open
Abstract
Finding the form of synaptic plasticity is critical to understanding its functions underlying learning and memory. We investigated an efficient method to infer synaptic plasticity rules in various experimental settings. We considered biologically plausible models fitting a wide range of in-vitro studies and examined the recovery of their firing-rate dependence from sparse and noisy data. Among the methods assuming low-rankness or smoothness of plasticity rules, Gaussian process regression (GPR), a nonparametric Bayesian approach, performs the best. Under the conditions measuring changes in synaptic weights directly or measuring changes in neural activities as indirect observables of synaptic plasticity, which leads to different inference problems, GPR performs well. Also, GPR could simultaneously recover multiple plasticity rules and robustly perform under various plasticity rules and noise levels. Such flexibility and efficiency, particularly at the low sampling regime, make GPR suitable for recent experimental developments and inferring a broader class of plasticity models.
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Affiliation(s)
- Shirui Chen
- Department of Applied Mathematics, University of Washington, Lewis Hall 201, Box 353925, Seattle, WA 98195-3925, USA
- Neural Science, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
| | - Qixin Yang
- The Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, The Suzanne and Charles Goodman Brain Sciences Building, Edmond J. Safra Campus, Jerusalem, 9190401, Israel
- Neural Science, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
| | - Sukbin Lim
- Neural Science, New York University Shanghai, 1555 Century Avenue, Shanghai, 200122, China
- NYU-ECNU Institute of Brain and Cognitive Science at NYU Shanghai, 3663 Zhongshan Road North, Shanghai, 200062, China
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49
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Boyce R, Dard RF, Cossart R. Cortical neuronal assemblies coordinate with EEG microstate dynamics during resting wakefulness. Cell Rep 2023; 42:112053. [PMID: 36716148 PMCID: PMC9989822 DOI: 10.1016/j.celrep.2023.112053] [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: 06/13/2022] [Revised: 09/26/2022] [Accepted: 01/17/2023] [Indexed: 01/30/2023] Open
Abstract
The disruption of cortical assembly activity has been associated with anesthesia-induced loss of consciousness. However, the relationship between cortical assembly activity and the variations in consciousness associated with natural vigilance states remains unclear. Here, we address this by performing vigilance state-specific clustering analysis on 2-photon calcium imaging data from the sensorimotor cortex in combination with global electroencephalogram (EEG) microstate analysis derived from multi-EEG signals obtained over widespread cortical locations. We report no difference in the structure of assembly activity during quiet wakefulness (QW), non-rapid eye movement sleep (NREMs), or REMs, despite the latter two vigilance states being associated with significantly reduced levels of consciousness relative to QW. However, we describe a significant coordination between global EEG microstate dynamics and general local cortical assembly activity during periods of QW, but not sleep. These results suggest that the coordination of cortical assembly activity with global brain dynamics could be a key factor of sustained conscious experience.
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Affiliation(s)
- Richard Boyce
- INMED, INSERM, Aix Marseille University, 13273 Marseille, France.
| | - Robin F Dard
- INMED, INSERM, Aix Marseille University, 13273 Marseille, France
| | - Rosa Cossart
- INMED, INSERM, Aix Marseille University, 13273 Marseille, France
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50
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Accanto N, Blot FGC, Lorca-Cámara A, Zampini V, Bui F, Tourain C, Badt N, Katz O, Emiliani V. A flexible two-photon fiberscope for fast activity imaging and precise optogenetic photostimulation of neurons in freely moving mice. Neuron 2023; 111:176-189.e6. [PMID: 36395773 DOI: 10.1016/j.neuron.2022.10.030] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 07/28/2022] [Accepted: 10/19/2022] [Indexed: 11/17/2022]
Abstract
We developed a flexible two-photon microendoscope (2P-FENDO) capable of all-optical brain investigation at near cellular resolution in freely moving mice. The system performs fast two-photon (2P) functional imaging and 2P holographic photostimulation of single and multiple cells using axially confined extended spots. Proof-of-principle experiments were performed in freely moving mice co-expressing jGCaMP7s and the opsin ChRmine in the visual or barrel cortex. On a field of view of 250 μm in diameter, we demonstrated functional imaging at a frame rate of up to 50 Hz and precise photostimulation of selected groups of cells. With the capability to simultaneously image and control defined neuronal networks in freely moving animals, 2P-FENDO will enable a precise investigation of neuronal functions in the brain during naturalistic behaviors.
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Affiliation(s)
- Nicolò Accanto
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France.
| | - François G C Blot
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | | | - Valeria Zampini
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | - Florence Bui
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | - Christophe Tourain
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France
| | - Noam Badt
- Department of Applied Physics, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Ori Katz
- Department of Applied Physics, Hebrew University of Jerusalem, Jerusalem 9190401, Israel
| | - Valentina Emiliani
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, F-75012 Paris, France.
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