1
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Garcia N, Reitz S, Handy G. Extending Mathematical Frameworks to Investigate Neuronal Dynamics in the Presence of Microglial Ensheathment. Bull Math Biol 2025; 87:63. [PMID: 40183855 PMCID: PMC11971063 DOI: 10.1007/s11538-025-01438-w] [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: 09/21/2024] [Accepted: 03/05/2025] [Indexed: 04/05/2025]
Abstract
Recent experimental evidence has shown that glial cells, including microglia and astrocytes, can ensheathe specific synapses, positioning them to disrupt neurotransmitter flow between pre- and post-synaptic terminals. This study, as part of the special issue "Problems, Progress and Perspectives in Mathematical and Computational Biology," expands micro- and network-scale theoretical frameworks to incorporate these new experimental observations that introduce substantial heterogeneities into the system. Specifically, we aim to explore how varying degrees of synaptic ensheathment affect synaptic communication and network dynamics. Consistent with previous studies, our microscale model shows that ensheathment accelerates synaptic transmission while reducing its strength and reliability, with the potential to effectively switch off synaptic connections. Building on these findings, we integrate an "effective" glial cell model into a large-scale neuronal network. Specifically, we analyze a network with highly heterogeneous synaptic strengths and time constants, where glial proximity parametrizes synaptic properties. This parametrization results in a multimodal distribution of synaptic parameters across the network, introducing significantly greater variability compared to previous modeling efforts that assumed a normal distribution. This framework is applied to large networks of exponential integrate-and-fire neurons, extending linear response theory to analyze not only firing rate distributions but also noise correlations across the network. Despite the significant heterogeneity in the system, a mean-field approximation accurately captures network statistics. We demonstrate the utility of our model by reproducing experimental findings, showing that microglial ensheathment leads to post-anesthesia hyperactivity in excitatory neurons of mice. Furthermore, we explore how glial ensheathment may be used in the visual cortex to target specific neuronal subclasses, tuning higher-order network statistics.
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Affiliation(s)
- Nellie Garcia
- School of Mathematics, University of Minnesota, 127 Vincent Hall 206 Church St. SE, Minneapolis, MN, 55455, USA
| | - Silvie Reitz
- School of Mathematics, University of Minnesota, 127 Vincent Hall 206 Church St. SE, Minneapolis, MN, 55455, USA
| | - Gregory Handy
- School of Mathematics, University of Minnesota, 127 Vincent Hall 206 Church St. SE, Minneapolis, MN, 55455, USA.
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2
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Arkhipov A, da Costa N, de Vries S, Bakken T, Bennett C, Bernard A, Berg J, Buice M, Collman F, Daigle T, Garrett M, Gouwens N, Groblewski PA, Harris J, Hawrylycz M, Hodge R, Jarsky T, Kalmbach B, Lecoq J, Lee B, Lein E, Levi B, Mihalas S, Ng L, Olsen S, Reid C, Siegle JH, Sorensen S, Tasic B, Thompson C, Ting JT, van Velthoven C, Yao S, Yao Z, Koch C, Zeng H. Integrating multimodal data to understand cortical circuit architecture and function. Nat Neurosci 2025; 28:717-730. [PMID: 40128391 DOI: 10.1038/s41593-025-01904-7] [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: 12/19/2023] [Accepted: 01/21/2025] [Indexed: 03/26/2025]
Abstract
In recent years there has been a tremendous growth in new technologies that allow large-scale investigation of different characteristics of the nervous system at an unprecedented level of detail. There is a growing trend to use combinations of these new techniques to determine direct links between different modalities. In this Perspective, we focus on the mouse visual cortex, as this is one of the model systems in which much progress has been made in the integration of multimodal data to advance understanding. We review several approaches that allow integration of data regarding various properties of cortical cell types, connectivity at the level of brain areas, cell types and individual cells, and functional neural activity in vivo. The increasingly crucial contributions of computation and theory in analyzing and systematically modeling data are also highlighted. Together with open sharing of data, tools and models, integrative approaches are essential tools in modern neuroscience for improving our understanding of the brain architecture, mechanisms and function.
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Affiliation(s)
| | | | | | | | | | | | - Jim Berg
- Allen Institute, Seattle, WA, USA
| | | | | | | | | | | | | | - Julie Harris
- Allen Institute, Seattle, WA, USA
- Cure Alzheimer's Fund, Wellesley Hills, MA, USA
| | | | | | | | | | | | | | - Ed Lein
- Allen Institute, Seattle, WA, USA
| | | | | | - Lydia Ng
- Allen Institute, Seattle, WA, USA
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3
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Balla E, Nabbefeld G, Wiesbrock C, Linde J, Graff S, Musall S, Kampa BM. Broadband visual stimuli improve neuronal representation and sensory perception. Nat Commun 2025; 16:2957. [PMID: 40140355 PMCID: PMC11947450 DOI: 10.1038/s41467-025-58003-1] [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: 05/14/2023] [Accepted: 03/07/2025] [Indexed: 03/28/2025] Open
Abstract
Natural scenes consist of complex feature distributions that shape neural responses and perception. However, in contrast to single features like stimulus orientations, the impact of broadband feature distributions remains unclear. We, therefore, presented visual stimuli with parametrically-controlled bandwidths of orientations and spatial frequencies to awake mice while recording neural activity in their primary visual cortex (V1). Increasing orientation but not spatial frequency bandwidth strongly increased the number and response amplitude of V1 neurons. This effect was not explained by single-cell orientation tuning but rather a broadband-specific relief from center-surround suppression. Moreover, neurons in deeper V1 and the superior colliculus responded much stronger to broadband stimuli, especially when mixing orientations and spatial frequencies. Lastly, broadband stimuli increased the separability of neural responses and improved the performance of mice in a visual discrimination task. Our results show that surround modulation increases neural responses to complex natural feature distributions to enhance sensory perception.
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Affiliation(s)
- Elisabeta Balla
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany
- JARA BRAIN Institute of Neuroscience and Medicine (INM-10), Forschungszentrum Jülich, Jülich, Germany
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany
| | - Gerion Nabbefeld
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany
| | - Christopher Wiesbrock
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany
| | - Jenice Linde
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany
| | - Severin Graff
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany
- Institute of Biological Information Processing, Department for Bioelectronics, Forschungszentrum Jülich, Jülich, Germany
| | - Simon Musall
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany.
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany.
- Institute of Biological Information Processing, Department for Bioelectronics, Forschungszentrum Jülich, Jülich, Germany.
- Faculty of Medicine, Institute of Experimental Epileptology and Cognition Research, University of Bonn, Bonn, Germany.
| | - Björn M Kampa
- Systems Neurophysiology, Department of Neurobiology, RWTH Aachen University, Aachen, Germany.
- JARA BRAIN Institute of Neuroscience and Medicine (INM-10), Forschungszentrum Jülich, Jülich, Germany.
- Research Training Group 2416 MultiSenses - MultiScales, RWTH Aachen University, Aachen, Germany.
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4
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Rachel J, Möck M, Daigle TL, Tasic B, Witte M, Staiger JF. VIP-to-SST Cell Circuit Motif Shows Differential Short-Term Plasticity across Sensory Areas of Mouse Cortex. J Neurosci 2025; 45:e0949242025. [PMID: 39919833 PMCID: PMC11949481 DOI: 10.1523/jneurosci.0949-24.2025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2024] [Revised: 09/30/2024] [Accepted: 01/06/2025] [Indexed: 02/09/2025] Open
Abstract
Inhibition of GABAergic interneurons has been found to critically fine-tune the excitation-inhibition balance of the cortex. Inhibition is mediated by many connectivity motifs formed by GABAergic neurons. One such motif is the inhibition of somatostatin (SST)-expressing neurons by vasoactive intestinal polypeptide (VIP)-expressing neurons. We studied the synaptic properties of layer (L) 2/3 VIP cells onto L4 SST cells in somatosensory (S1) and visual (V1) cortices of mice of either sex using paired whole-cell patch-clamp recordings, followed by morphological reconstructions. We identified strong differences in the morphological features of L4 SST cells, wherein cells in S1 fell into the non-Martinotti cell (nMC) subclass, while in V1 presented with Martinotti cell (MC)-like features. Approximately 40-45% of tested SST cells were inhibited by VIP cells in both cortices. While unitary connectivity properties of the VIP-to-nMC and VIP-to-MC motifs were comparable, we observed stark differences in short-term plasticity. During high-frequency stimulation of both motifs, some connections showed short-term facilitation while others showed a stable response, with a fraction of VIP-to-nMC connections showing short-term depression. We thus provide evidence that VIP cells target morphological subclasses of SST cells differentially, forming cell-type-specific inhibitory motifs.
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Affiliation(s)
- Jenifer Rachel
- Institute for Neuroanatomy, Universitätsmedizin Göttingen, Georg-August-Universität, Göttingen 37075, Germany
| | - Martin Möck
- Institute for Neuroanatomy, Universitätsmedizin Göttingen, Georg-August-Universität, Göttingen 37075, Germany
| | - Tanya L Daigle
- Allen Institute for Brain Science, Seattle 98109, Washington
| | - Bosiljka Tasic
- Allen Institute for Brain Science, Seattle 98109, Washington
| | - Mirko Witte
- Institute for Neuroanatomy, Universitätsmedizin Göttingen, Georg-August-Universität, Göttingen 37075, Germany
| | - Jochen F Staiger
- Institute for Neuroanatomy, Universitätsmedizin Göttingen, Georg-August-Universität, Göttingen 37075, Germany
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5
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Onorato I, Tzanou A, Schneider M, Uran C, Broggini AC, Vinck M. Distinct roles of PV and Sst interneurons in visually induced gamma oscillations. Cell Rep 2025; 44:115385. [PMID: 40048428 DOI: 10.1016/j.celrep.2025.115385] [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: 06/16/2024] [Revised: 11/26/2024] [Accepted: 02/11/2025] [Indexed: 03/29/2025] Open
Abstract
Gamma-frequency oscillations are a hallmark of active information processing and are generated by interactions between excitatory and inhibitory neurons. To examine the contribution of distinct inhibitory interneurons to visually induced gamma oscillations, we recorded from optogenetically identified PV+ (parvalbumin) and Sst+ (somatostatin) interneurons in mouse primary visual cortex (V1). PV and Sst inhibitory interneurons exhibited distinct correlations to gamma oscillations. PV cells were strongly phase locked, while Sst cells were weakly phase locked, except for narrow-waveform Sst cells. PV cells fired at a substantially earlier phase in the gamma cycle (≈6 ms) than Sst cells. PV cells fired shortly after the onset of tightly synchronized burst events in excitatory cells, while Sst interneurons fired after subsequent burst spikes or single spikes. These findings indicate a main role of PV interneurons in synchronizing network activity and suggest that PV and Sst interneurons control the excitability of somatic and dendritic neural compartments with precise time delays coordinated by gamma oscillations.
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Affiliation(s)
- Irene Onorato
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany; Neuroscience Research Center, Charité-Universitätsmedizin Berlin, 10117 Berlin, Germany.
| | - Athanasia Tzanou
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Marius Schneider
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neurophysics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands; Max Planck Institute for Brain Research, 60438 Frankfurt, Germany
| | - Ana Clara Broggini
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neurophysics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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6
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Chen C, Xu S, Wang Y, Wang X. Location-specific neural facilitation in marmoset auditory cortex. Nat Commun 2025; 16:2773. [PMID: 40113772 PMCID: PMC11926104 DOI: 10.1038/s41467-025-58034-8] [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: 01/21/2024] [Accepted: 03/06/2025] [Indexed: 03/22/2025] Open
Abstract
A large body of literature has shown that sensory neurons typically exhibit adaptation to repetitive stimulation. However, adaptation alone does not account for the ability of sensory systems to remain vigilant to the environment in spite of repetitive sensory stimulation. Here, we investigated single neuron responses to sequences of sounds repeatedly delivered from a particular spatial location. Instead of inducing adaptation, repetitive stimulation evoked long-lasting and location-specific facilitation (LSF) in firing rate of nearly 90% of recorded neurons. The LSF decreased with decreasing presentation probability and diminished when sounds were randomly delivered from multiple spatial locations. Intracellular recordings showed that repetitive sound stimulation evoked sustained membrane potential depolarization. Computational modeling showed that increased arousal, not decreased inhibition, underlies the LSF. Our findings reveal a novel form of contextual modulation in the marmoset auditory cortex that may play a role in tasks such as auditory streaming and the cocktail party effect.
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Affiliation(s)
- Chenggang Chen
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Sheng Xu
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Yunyan Wang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xiaoqin Wang
- Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
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7
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Zhang X, Mukherjee A, Halassa MM, Chen ZS. Mediodorsal thalamus regulates task uncertainty to enable cognitive flexibility. Nat Commun 2025; 16:2640. [PMID: 40097445 PMCID: PMC11914509 DOI: 10.1038/s41467-025-58011-1] [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: 10/23/2023] [Accepted: 03/07/2025] [Indexed: 03/19/2025] Open
Abstract
The mediodorsal (MD) thalamus is a critical partner for the prefrontal cortex (PFC) in cognitive control. Accumulating evidence has shown that the MD regulates task uncertainty in decision making and enhance cognitive flexibility. However, the computational mechanism of this cognitive process remains unclear. Here we trained biologically-constrained computational models to delineate the mechanistic role of MD in context-dependent decision making. We show that the addition of a feedforward MD structure to the recurrent PFC increases robustness to low cueing signal-to-noise ratio, enhances working memory, and enables rapid context switching. Incorporating genetically identified thalamocortical connectivity and interneuron cell types into the model replicates key neurophysiological findings in task-performing animals. Our model reveals computational mechanisms and geometric interpretations of MD in regulating cue uncertainty and context switching to enable cognitive flexibility. Our model makes experimentally testable predictions linking cognitive deficits with disrupted thalamocortical connectivity, prefrontal excitation-inhibition imbalance and dysfunctional inhibitory cell types.
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Affiliation(s)
- Xiaohan Zhang
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA
| | - Arghya Mukherjee
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA, USA
| | - Michael M Halassa
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA, USA
| | - Zhe Sage Chen
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, USA.
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY, USA.
- Neuroscience Institute, New York University Grossman School of Medicine, New York, NY, USA.
- Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA.
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8
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Bogaj K, Urban‐Ciecko J. Inhibition of BK channels by GABAb receptors enhances intrinsic excitability of layer 2/3 vasoactive intestinal polypeptide-expressing interneurons in mouse neocortex. J Physiol 2025; 603:1171-1196. [PMID: 39901494 PMCID: PMC11870045 DOI: 10.1113/jp286439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Accepted: 01/16/2025] [Indexed: 02/05/2025] Open
Abstract
GABAb receptors (GABAbRs) affect many signalling pathways, and hence the net effect of the activity of these receptors depends upon the specific ion channels that they are linked to, leading to different effects on specific neuronal populations. Typically, GABAbRs suppress neuronal activity in the cerebral cortex. Previously, we found that neocortical parvalbumin-expressing cells are strongly inhibited through GABAbRs, whereas somatostatin interneurons are immune to this modulation. Here, we employed in vitro whole-cell patch-clamp recordings to study whether GABAbRs modulate the activity of vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) in layer (L) 2/3 of the mouse primary somatosensory cortex. Utilizing machine learning algorithms (hierarchical clustering and principal component analysis), we revealed that one VIP-IN cluster (about 68% of all VIP-INs) was sensitive to GABAbR activation. Paradoxically, when recordings were performed in standard conditions with high extracellular Ca2+ level, GABAbRs indirectly inhibited the activity of large conductance voltage- and calcium-activated potassium (BK) channels and reduced GABAaR-mediated inhibition, leading to an increase in intrinsic excitability of these interneurons. However, a classical inhibitory effect of GABAbRs on L2/3 VIP-INs was observed in modified artificial cerebrospinal fluid with physiological (low) Ca2+ concentration. Our results are essential for a deeper understanding of mechanisms underlying the modulation of cortical networks. KEY POINTS: Layer 2/3 vasoactive intestinal polypeptide-expressing interneurons (VIP-INs) in the mouse somatosensory cortex cluster into three electrophysiological types differentially sensitive to GABAb receptors (GABAbRs). The majority of VIP-INs (type 1, about 68% of all VIP-INs) are regulated through pre- and postsynaptic GABAbRs, while a subset of these interneurons (types 2 and 3) is controlled only presynaptically. The net effect of GABAbR activation on VIP-IN excitability depends on [Ca2+] in artificial cerebrospinal fluid. When [Ca2+] is high (2.5 mM), GABAbRs indirectly inhibit BK channels and reduce GABAaR inhibition leading to increased intrinsic excitability of type 1 VIP-INs. When [Ca2+] is low (1 mM), which is more physiological, BK channels do not regulate the intrinsic excitability of VIP-INs and thus postsynaptic GABAbRs canonically decrease the intrinsic excitability of type 1 VIP-INs.
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Affiliation(s)
- Karolina Bogaj
- Laboratory of Electrophysiology, Nencki Institute of Experimental BiologyPolish Academy of SciencesWarsawPoland
| | - Joanna Urban‐Ciecko
- Laboratory of Electrophysiology, Nencki Institute of Experimental BiologyPolish Academy of SciencesWarsawPoland
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9
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Meier AM, D'Souza RD, Ji W, Han EB, Burkhalter A. Interdigitating Modules for Visual Processing During Locomotion and Rest in Mouse V1. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.02.21.639505. [PMID: 40060542 PMCID: PMC11888233 DOI: 10.1101/2025.02.21.639505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 03/20/2025]
Abstract
Layer 1 of V1 has been shown to receive locomotion-related signals from the dorsal lateral geniculate (dLGN) and lateral posterior (LP) thalamic nuclei (Roth et al., 2016). Inputs from the dLGN terminate in M2+ patches while inputs from LP target M2- interpatches (D'Souza et al., 2019) suggesting that motion related signals are processed in distinct networks. Here, we investigated by calcium imaging in head-fixed awake mice whether L2/3 neurons underneath L1 M2+ and M2- modules are differentially activated by locomotion, and whether distinct networks of feedback connections from higher cortical areas to L1 may contribute to these differences. We found that strongly locomotion-modulated cell clusters during visual stimulation were aligned with M2- interpatches, while weakly modulated cells clustered under M2+ patches. Unlike M2+ patch cells, pairs of M2- interpatch cells showed increased correlated variability of calcium transients when the sites in the visuotopic map were far apart, suggesting that activity is integrated across large parts of the visual field. Pathway tracing further suggests that strong locomotion modulation in L2/3 M2- interpatch cells of V1 relies on looped, like-to-like networks between apical dendrites of MOs-, PM- and RSP-projecting neurons and feedback input from these areas to L1. M2- interpatches receive strong inputs from SST neurons, suggesting that during locomotion these interneurons influence the firing of specific subnetworks by controlling the excitability of apical dendrites in M2- interpatches.
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Affiliation(s)
- A M Meier
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110; USA
| | - R D D'Souza
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110; USA
| | - W Ji
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110; USA
| | - E B Han
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110; USA
| | - A Burkhalter
- Department of Neuroscience, Washington University School of Medicine, St. Louis, MO 63110; USA
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10
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Najafi F, Russo S, Lecoq J. Unexpected events trigger task-independent signaling in VIP and excitatory neurons of mouse visual cortex. iScience 2025; 28:111728. [PMID: 39898018 PMCID: PMC11787536 DOI: 10.1016/j.isci.2024.111728] [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] [Revised: 10/21/2024] [Accepted: 12/30/2024] [Indexed: 02/04/2025] Open
Abstract
The visual cortex predicts incoming sensory stimuli through internal models that are updated following unexpected events. Cortical inhibitory neurons, particularly vasoactive intestinal polypeptide (VIP) interneurons, play a critical role in representing unexpected stimuli. Notably, this response is stimulus non-specific, raising the question of what information it conveys. Given their unique connectivity, we hypothesized that during unexpected stimuli, VIP neurons encode broad context signals, referred to here as task-independent information. To test this hypothesis, we analyzed the Allen Institute Visual Behavior dataset, in which mice viewed repeated familiar images and unexpected omissions of these images, while two-photon calcium imaging was performed from distinct cell types across primary and higher-order visual areas. Using dimensionality reduction methods, we found that, in contrast to image presentations, unexpected omissions trigger task-independent signaling in VIP and excitatory neurons. This signaling may facilitate the integration of contextual and sensory information, enabling updated predictions.
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Affiliation(s)
- Farzaneh Najafi
- Georgia Institute of Technology, Biological Sciences, Atlanta, GA, USA
- Allen Institute for Brain Science, Mindscope Program, Seattle, WA, USA
| | - Simone Russo
- Allen Institute for Brain Science, Brain and Consciousness Program, Seattle, WA, USA
- Georgia Institute of Technology, Wallace H Coulter Department of Biomedical Engineering, Atlanta, GA, USA
- Department of Biomedical and Clinical Sciences, Università degli Studi di Milano, 20157 Milan, Italy
| | - Jérôme Lecoq
- Allen Institute for Brain Science, Neural Dynamics Program, Seattle, WA, USA
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11
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Di Santo S, Dipoppa M, Keller A, Roth M, Scanziani M, Miller KD. Contextual modulation emerges by integrating feedforward and feedback processing in mouse visual cortex. Cell Rep 2025; 44:115088. [PMID: 39709599 DOI: 10.1016/j.celrep.2024.115088] [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: 05/19/2024] [Revised: 09/27/2024] [Accepted: 11/27/2024] [Indexed: 12/24/2024] Open
Abstract
Sensory systems use context to infer meaning. Accordingly, context profoundly influences neural responses to sensory stimuli. However, a cohesive understanding of the circuit mechanisms governing contextual effects across different stimulus conditions is still lacking. Here we present a unified circuit model of mouse visual cortex that accounts for the main standard forms of contextual modulation. This data-driven and biologically realistic circuit, including three primary inhibitory cell types, sheds light on how bottom-up, top-down, and recurrent inputs are integrated across retinotopic space to generate contextual effects in layer 2/3. We establish causal relationships between neural responses, geometrical features of the inputs, and the connectivity patterns. The model not only reveals how a single canonical cortical circuit differently modulates sensory response depending on context but also generates multiple testable predictions, offering insights that apply to broader neural circuitry.
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Affiliation(s)
- Serena Di Santo
- Center for Theoretical Neuroscience and Mortimer B Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA; Departamento de Electromagnetismo y Física de la Materia and Instituto Carlos I de Física Teórica y Computacional, Universidad de Granada, 18071 Granada, Spain.
| | - Mario Dipoppa
- Center for Theoretical Neuroscience and Mortimer B Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA; Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Andreas Keller
- Department of Biomedicine, University of Basel, 4056 Basel, Switzerland; Department of Physiology, University of California, San Francisco, San Francisco, CA 94143, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Morgane Roth
- Department of Biomedicine, University of Basel, 4056 Basel, Switzerland; Department of Physiology, University of California, San Francisco, San Francisco, CA 94143, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Massimo Scanziani
- Department of Physiology, University of California, San Francisco, San Francisco, CA 94143, USA; Howard Hughes Medical Institute, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Kenneth D Miller
- Center for Theoretical Neuroscience and Mortimer B Zuckerman Mind Brain Behavior Institute, Columbia University, New York City, NY 10027, USA; Department 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 City, NY 10027, USA
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12
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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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13
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Milicevic KD, Ivanova VO, Brazil TN, Varillas CA, Zhu YMD, Andjus PR, Antic SD. The Impact of Optical Undersampling on the Ca 2+ Signal Resolution in Ca 2+ Imaging of Spontaneous Neuronal Activity. J Integr Neurosci 2025; 24:26242. [PMID: 39862012 DOI: 10.31083/jin26242] [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: 08/23/2024] [Revised: 10/03/2024] [Accepted: 10/24/2024] [Indexed: 01/30/2025] Open
Abstract
BACKGROUND In neuroscience, Ca2+ imaging is a prevalent technique used to infer neuronal electrical activity, often relying on optical signals recorded at low sampling rates (3 to 30 Hz) across multiple neurons simultaneously. This study investigated whether increasing the sampling rate preserves critical information that may be missed at slower acquisition speeds. METHODS Primary neuronal cultures were prepared from the cortex of newborn pups. Neurons were loaded with Oregon Green BAPTA-1 AM (OGB1-AM) fluorescent indicator. Spontaneous neuronal activity was recorded at low (14 Hz) and high (500 Hz) sampling rates, and the same neurons (n = 269) were analyzed under both conditions. We compared optical signal amplitude, duration, and frequency. RESULTS Although recurring Ca2+ transients appeared visually similar at 14 Hz and 500 Hz, quantitative analysis revealed significantly faster rise times and shorter durations (half-widths) at the higher sampling rate. Small-amplitude Ca2+ transients, undetectable at 14 Hz, became evident at 500 Hz, particularly in the neuropil (putative dendrites and axons), but not in nearby cell bodies. Large Ca2+ transients exhibited greater amplitudes and faster temporal dynamics in dendrites compared with somas, potentially due to the higher surface-to-volume ratio of dendrites. In neurons bulk-loaded with OGB1-AM, cell nucleus-mediated signal distortions were observed in every neuron examined (n = 57). Specifically, two regions of interest (ROIs) on different segments of the same cell body displayed significantly different signal amplitudes and durations due to dye accumulation in the nucleus. CONCLUSIONS Our findings reveal that Ca2+ signal undersampling leads to three types of information loss: (1) distortion of rise times and durations for large-amplitude transients, (2) failure to detect small-amplitude transients in cell bodies, and (3) omission of small-amplitude transients in the neuropil.
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Affiliation(s)
- Katarina D Milicevic
- Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA
- Center for Laser Microscopy, Institute of Physiology and Biochemistry 'Jean Giaja' , Faculty of Biology, University of Belgrade, 11000 Belgrade, Serbia
| | - Violetta O Ivanova
- Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA
| | - Tina N Brazil
- Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA
| | - Cesar A Varillas
- Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA
| | - Yan M D Zhu
- Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA
| | - Pavle R Andjus
- Center for Laser Microscopy, Institute of Physiology and Biochemistry 'Jean Giaja' , Faculty of Biology, University of Belgrade, 11000 Belgrade, Serbia
| | - Srdjan D Antic
- Neuroscience Department, University of Connecticut Health, School of Medicine, Institute for Systems Genomics, Farmington, CT 06030, USA
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14
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Klein SD, Teich CD, Pokorny VJ, Rawls E, Olman CA, Sponheim SR. Altered Use of Context During Visual Perception in Psychotic Psychopathology: A Neurophysiological Investigation of Tuned and Untuned Suppression During Contrast Perception. Schizophr Bull 2024; 51:170-185. [PMID: 39148463 PMCID: PMC11661954 DOI: 10.1093/schbul/sbae103] [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] [Indexed: 08/17/2024]
Abstract
BACKGROUND AND HYPOTHESIS The human visual system streamlines visual processing by suppressing responses to textures that are similar to their surrounding context. Surround suppression is weaker in individuals with schizophrenia (ISZ); this altered use of visuospatial context may relate to the characteristic visual distortions they experience. STUDY DESIGN To understand atypical surround suppression in psychotic psychopathology, we investigated neurophysiological responses in ISZ, healthy controls (HC), individuals with bipolar disorder (IBP), and first-degree relatives (ISZR/IBPR). Participants performed a contrast judgment task on a circular target with annular surrounds, with concurrent electroencephalography. Orientation-independent (untuned) suppression was estimated from responses to central targets with orthogonal surrounds; the orientation-dependence of suppression was estimated by fitting an exponential function to the increase in suppression as surrounds became more aligned with the center. RESULTS ISZ exhibited weakened untuned suppression coupled with enhanced orientation-dependence of suppression. The N1 visual evoked potential was associated with the orientation-dependence of suppression, with ISZ and ISZR (but not IBP or IBPR) showing enhanced orientation-dependence of the N1. Collapsed across orientation conditions, the N1 for ISZ lacked asymmetry toward the right hemisphere; this reduction in N1 asymmetry was associated with reduced untuned suppression, real-world perceptual anomalies, and psychotic psychopathology. The overall amplitude of the N1 was reduced in ISZ and IBP. CONCLUSIONS Key measures of symptomatology for ISZ are associated with reductions in untuned suppression. Increased sensitivity for ISZ to the relative orientation of suppressive surrounds is reflected in the N1 VEP, which is commonly associated with higher-level visual functions such as allocation of spatial attention or scene segmentation.
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Affiliation(s)
- Samuel D Klein
- Department of Psychology, University of Minnesota-Twin Cities, Minneapolis, MN, USA
| | - Collin D Teich
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Victor J Pokorny
- Department of Psychology, University of Minnesota-Twin Cities, Minneapolis, MN, USA
| | - Eric Rawls
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA
| | - Cheryl A Olman
- Department of Psychology, University of Minnesota-Twin Cities, Minneapolis, MN, USA
| | - Scott R Sponheim
- Minneapolis Veterans Affairs Health Care System, Minneapolis, MN, USA
- Department of Psychiatry, University of Minnesota Medical School, Minneapolis, MN, USA
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15
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Li J, Bauer R, Rentzeperis I, van Leeuwen C. Adaptive rewiring: a general principle for neural network development. FRONTIERS IN NETWORK PHYSIOLOGY 2024; 4:1410092. [PMID: 39534101 PMCID: PMC11554485 DOI: 10.3389/fnetp.2024.1410092] [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: 03/31/2024] [Accepted: 10/15/2024] [Indexed: 11/16/2024]
Abstract
The nervous system, especially the human brain, is characterized by its highly complex network topology. The neurodevelopment of some of its features has been described in terms of dynamic optimization rules. We discuss the principle of adaptive rewiring, i.e., the dynamic reorganization of a network according to the intensity of internal signal communication as measured by synchronization or diffusion, and its recent generalization for applications in directed networks. These have extended the principle of adaptive rewiring from highly oversimplified networks to more neurally plausible ones. Adaptive rewiring captures all the key features of the complex brain topology: it transforms initially random or regular networks into networks with a modular small-world structure and a rich-club core. This effect is specific in the sense that it can be tailored to computational needs, robust in the sense that it does not depend on a critical regime, and flexible in the sense that parametric variation generates a range of variant network configurations. Extreme variant networks can be associated at macroscopic level with disorders such as schizophrenia, autism, and dyslexia, and suggest a relationship between dyslexia and creativity. Adaptive rewiring cooperates with network growth and interacts constructively with spatial organization principles in the formation of topographically distinct modules and structures such as ganglia and chains. At the mesoscopic level, adaptive rewiring enables the development of functional architectures, such as convergent-divergent units, and sheds light on the early development of divergence and convergence in, for example, the visual system. Finally, we discuss future prospects for the principle of adaptive rewiring.
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Affiliation(s)
- Jia Li
- Brain and Cognition, KU Leuven, Leuven, Belgium
- Cognitive Science, RPTU Kaiserslautern, Kaiserslautern, Germany
| | - Roman Bauer
- NICE Research Group, Computer Science Research Centre, University of Surrey, Guildford, United Kingdom
| | - Ilias Rentzeperis
- Institute of Optics, Spanish National Research Council (CSIC), Madrid, Spain
| | - Cees van Leeuwen
- Brain and Cognition, KU Leuven, Leuven, Belgium
- Cognitive Science, RPTU Kaiserslautern, Kaiserslautern, Germany
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16
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Cammarata CM, Pei Y, Shields BC, Lim SSX, Hawley T, Li JY, St Amand D, Brunel N, Tadross MR, Glickfeld LL. Behavioral state and stimulus strength regulate the role of somatostatin interneurons in stabilizing network activity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.09.612138. [PMID: 39314375 PMCID: PMC11419099 DOI: 10.1101/2024.09.09.612138] [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: 09/25/2024]
Abstract
Inhibition stabilization enables cortical circuits to encode sensory signals across diverse contexts. Somatostatin-expressing (SST) interneurons are well-suited for this role through their strong recurrent connectivity with excitatory pyramidal cells. We developed a cortical circuit model predicting that SST cells become increasingly important for stabilization as sensory input strengthens. We tested this prediction in mouse primary visual cortex by manipulating excitatory input to SST cells, a key parameter for inhibition stabilization, with a novel cell-type specific pharmacological method to selectively block glutamatergic receptors on SST cells. Consistent with our model predictions, we find antagonizing glutamatergic receptors drives a paradoxical facilitation of SST cells with increasing stimulus contrast. In addition, we find even stronger engagement of SST-dependent stabilization when the mice are aroused. Thus, we reveal that the role of SST cells in cortical processing gradually switches as a function of both input strength and behavioral state.
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Affiliation(s)
- Celine M Cammarata
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
| | - Yingming Pei
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
| | - Brenda C Shields
- Department of Biomedical Engineering, Duke University, Durham, NC 27701 USA
| | - Shaun S X Lim
- Department of Biomedical Engineering, Duke University, Durham, NC 27701 USA
| | - Tammy Hawley
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
| | - Jennifer Y Li
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
| | - David St Amand
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
| | - Nicolas Brunel
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
- Department of Physics, Duke University, Durham, NC 27710, USA
- Department of Computing Sciences, Bocconi University, Milan 20136, Italy
- These authors contributed equally
| | - Michael R Tadross
- Department of Biomedical Engineering, Duke University, Durham, NC 27701 USA
- These authors contributed equally
| | - Lindsey L Glickfeld
- Department of Neurobiology, Duke University Medical Center, Durham, NC 27710 USA
- Lead Contact: Lindsey Glickfeld, Department of Neurobiology, Duke University Medical Center, 311 Research Drive, BRB 401F, Durham, NC 27710
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17
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Edwards MM, Rubin JE, Huang C. State modulation in spatial networks with three interneuron subtypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.23.609417. [PMID: 39229194 PMCID: PMC11370595 DOI: 10.1101/2024.08.23.609417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Several inhibitory interneuron subtypes have been identified as critical in regulating sensory responses. However, the specific contribution of each interneuron subtype remains uncertain. In this work, we explore the contributions of cell-type specific activity and synaptic connections to dynamics of a spatially organized spiking neuron network. We find that the firing rates of the somatostatin (SOM) interneurons align closely with the level of network synchrony irrespective of the target of modulatory input. Further analysis reveals that inhibition from SOM to parvalbumin (PV) interneurons must be limited to allow gradual transitions from asynchrony to synchrony and that the strength of recurrent excitation onto SOM neurons determines the level of synchrony achievable in the network. Our results are consistent with recent experimental findings on cell-type specific manipulations. Overall, our results highlight common dynamic regimes achieved across modulations of different cell populations and identify SOM cells as the main driver of network synchrony.
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Affiliation(s)
- Madeline M. Edwards
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan E. Rubin
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Chengcheng Huang
- Center for the Neural Basis of Cognition, Pittsburgh, PA, USA
- Department of Neuroscience, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, USA
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18
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Miyashita Y. Cortical Layer-Dependent Signaling in Cognition: Three Computational Modes of the Canonical Circuit. Annu Rev Neurosci 2024; 47:211-234. [PMID: 39115926 DOI: 10.1146/annurev-neuro-081623-091311] [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] [Indexed: 08/10/2024]
Abstract
The cerebral cortex performs computations via numerous six-layer modules. The operational dynamics of these modules were studied primarily in early sensory cortices using bottom-up computation for response selectivity as a model, which has been recently revolutionized by genetic approaches in mice. However, cognitive processes such as recall and imagery require top-down generative computation. The question of whether the layered module operates similarly in top-down generative processing as in bottom-up sensory processing has become testable by advances in the layer identification of recorded neurons in behaving monkeys. This review examines recent advances in laminar signaling in these two computations, using predictive coding computation as a common reference, and shows that each of these computations recruits distinct laminar circuits, particularly in layer 5, depending on the cognitive demands. These findings highlight many open questions, including how different interareal feedback pathways, originating from and terminating at different layers, convey distinct functional signals.
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Affiliation(s)
- Yasushi Miyashita
- Department of Physiology, The University of Tokyo School of Medicine, Tokyo, Japan;
- Juntendo University Graduate School of Medicine, Tokyo, Japan
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19
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Liu Y, Wang XJ. Flexible gating between subspaces in a neural network model of internally guided task switching. Nat Commun 2024; 15:6497. [PMID: 39090084 PMCID: PMC11294624 DOI: 10.1038/s41467-024-50501-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 07/10/2024] [Indexed: 08/04/2024] Open
Abstract
Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks' dynamical trajectories for different rules resided in separate subspaces of population activity; the subspaces collapsed and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, illustrating how a phenomenological description of representational subspaces is explained by a specific circuit mechanism.
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Affiliation(s)
- Yue Liu
- Center for Neural Science, New York University, New York, NY, 10003, USA
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY, 10003, USA.
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20
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Yang H, Han F, Wang Q. A large-scale neuronal network modelling study: Stimulus size modulates gamma oscillations in the primary visual cortex by long-range connections. Eur J Neurosci 2024; 60:4224-4243. [PMID: 38812400 DOI: 10.1111/ejn.16429] [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: 10/06/2023] [Revised: 05/04/2024] [Accepted: 05/13/2024] [Indexed: 05/31/2024]
Abstract
Stimulus size modulation of neuronal firing activity is a fundamental property of the primary visual cortex. Numerous biological experiments have shown that stimulus size modulation is affected by multiple factors at different spatiotemporal scales, but the exact pathways and mechanisms remain incompletely understood. In this paper, we establish a large-scale neuronal network model of primary visual cortex with layer 2/3 to study how gamma oscillation properties are modulated by stimulus size and especially how long-range connections affect the modulation as realistic neuronal properties and spatial distributions of synaptic connections are considered. It is shown that long-range horizontal synaptic connections are sufficient to produce dimensional modulation of firing rates and gamma oscillations. In particular, with increasing grating stimulus size, the firing rate increases and then decreases, the peak frequency of gamma oscillations decreases and the spectral power increases. These are consistent with biological experimental observations. Furthermore, we explain in detail how the number and spatial distribution of long-range connections affect the size modulation of gamma oscillations by using the analysis of neuronal firing activity and synaptic current fluctuations. Our results provide a mechanism explanation for size modulation of gamma oscillations in the primary visual cortex and reveal the important and unique role played by long-range connections, which contributes to a deeper understanding of the cognitive function of gamma oscillations in visual cortex.
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Affiliation(s)
- Hao Yang
- College of Information Science and Technology, Donghua University, Shanghai, China
| | - Fang Han
- College of Information Science and Technology, Donghua University, Shanghai, China
| | - Qingyun Wang
- Department of Dynamics and Control, Beihang University, Beijing, China
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21
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Horrocks EAB, Rodrigues FR, Saleem AB. Flexible neural population dynamics govern the speed and stability of sensory encoding in mouse visual cortex. Nat Commun 2024; 15:6415. [PMID: 39080254 PMCID: PMC11289260 DOI: 10.1038/s41467-024-50563-y] [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: 12/11/2023] [Accepted: 07/15/2024] [Indexed: 08/02/2024] Open
Abstract
Time courses of neural responses underlie real-time sensory processing and perception. How these temporal dynamics change may be fundamental to how sensory systems adapt to different perceptual demands. By simultaneously recording from hundreds of neurons in mouse primary visual cortex, we examined neural population responses to visual stimuli at sub-second timescales, during different behavioural states. We discovered that during active behavioural states characterised by locomotion, single-neurons shift from transient to sustained response modes, facilitating rapid emergence of visual stimulus tuning. Differences in single-neuron response dynamics were associated with changes in temporal dynamics of neural correlations, including faster stabilisation of stimulus-evoked changes in the structure of correlations during locomotion. Using Factor Analysis, we examined temporal dynamics of latent population responses and discovered that trajectories of population activity make more direct transitions between baseline and stimulus-encoding neural states during locomotion. This could be partly explained by dampening of oscillatory dynamics present during stationary behavioural states. Functionally, changes in temporal response dynamics collectively enabled faster, more stable and more efficient encoding of new visual information during locomotion. These findings reveal a principle of how sensory systems adapt to perceptual demands, where flexible neural population dynamics govern the speed and stability of sensory encoding.
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Affiliation(s)
- Edward A B Horrocks
- Institute of Behavioural Neuroscience, University College London, London, WC1V 0AP, UK.
| | - Fabio R Rodrigues
- Institute of Behavioural Neuroscience, University College London, London, WC1V 0AP, UK
| | - Aman B Saleem
- Institute of Behavioural Neuroscience, University College London, London, WC1V 0AP, UK.
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22
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Liu Y, Wang XJ. Flexible gating between subspaces in a neural network model of internally guided task switching. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.08.15.553375. [PMID: 37645801 PMCID: PMC10462002 DOI: 10.1101/2023.08.15.553375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Behavioral flexibility relies on the brain's ability to switch rapidly between multiple tasks, even when the task rule is not explicitly cued but must be inferred through trial and error. The underlying neural circuit mechanism remains poorly understood. We investigated recurrent neural networks (RNNs) trained to perform an analog of the classic Wisconsin Card Sorting Test. The networks consist of two modules responsible for rule representation and sensorimotor mapping, respectively, where each module is comprised of a circuit with excitatory neurons and three major types of inhibitory neurons. We found that rule representation by self-sustained persistent activity across trials, error monitoring and gated sensorimotor mapping emerged from training. Systematic dissection of trained RNNs revealed a detailed circuit mechanism that is consistent across networks trained with different hyperparameters. The networks' dynamical trajectories for different rules resided in separate subspaces of population activity; the subspaces collapsed and performance was reduced to chance level when dendrite-targeting somatostatin-expressing interneurons were silenced, illustrating how a phenomenological description of representational subspaces is explained by a specific circuit mechanism.
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23
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Piet A, Ponvert N, Ollerenshaw D, Garrett M, Groblewski PA, Olsen S, Koch C, Arkhipov A. Behavioral strategy shapes activation of the Vip-Sst disinhibitory circuit in visual cortex. Neuron 2024; 112:1876-1890.e4. [PMID: 38447579 PMCID: PMC11156560 DOI: 10.1016/j.neuron.2024.02.008] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 11/17/2023] [Accepted: 02/08/2024] [Indexed: 03/08/2024]
Abstract
In complex environments, animals can adopt diverse strategies to find rewards. How distinct strategies differentially engage brain circuits is not well understood. Here, we investigate this question, focusing on the cortical Vip-Sst disinhibitory circuit between vasoactive intestinal peptide-postive (Vip) interneurons and somatostatin-positive (Sst) interneurons. We characterize the behavioral strategies used by mice during a visual change detection task. Using a dynamic logistic regression model, we find that individual mice use mixtures of a visual comparison strategy and a statistical timing strategy. Separately, mice also have periods of task engagement and disengagement. Two-photon calcium imaging shows large strategy-dependent differences in neural activity in excitatory, Sst inhibitory, and Vip inhibitory cells in response to both image changes and image omissions. In contrast, task engagement has limited effects on neural population activity. We find that the diversity of neural correlates of strategy can be understood parsimoniously as the increased activation of the Vip-Sst disinhibitory circuit during the visual comparison strategy, which facilitates task-appropriate responses.
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Affiliation(s)
- Alex Piet
- Allen Institute, Mindscope Program, Seattle, WA, USA.
| | - Nick Ponvert
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | | | | | | | - Shawn Olsen
- Allen Institute, Mindscope Program, Seattle, WA, USA
| | - Christof Koch
- Allen Institute, Mindscope Program, Seattle, WA, USA
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24
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Djambazovska S, Zafer A, Ramezanpour H, Kreiman G, Kar K. The Impact of Scene Context on Visual Object Recognition: Comparing Humans, Monkeys, and Computational Models. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.27.596127. [PMID: 38854011 PMCID: PMC11160639 DOI: 10.1101/2024.05.27.596127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
During natural vision, we rarely see objects in isolation but rather embedded in rich and complex contexts. Understanding how the brain recognizes objects in natural scenes by integrating contextual information remains a key challenge. To elucidate neural mechanisms compatible with human visual processing, we need an animal model that behaves similarly to humans, so that inferred neural mechanisms can provide hypotheses relevant to the human brain. Here we assessed whether rhesus macaques could model human context-driven object recognition by quantifying visual object identification abilities across variations in the amount, quality, and congruency of contextual cues. Behavioral metrics revealed strikingly similar context-dependent patterns between humans and monkeys. However, neural responses in the inferior temporal (IT) cortex of monkeys that were never explicitly trained to discriminate objects in context, as well as current artificial neural network models, could only partially explain this cross-species correspondence. The shared behavioral variance unexplained by context-naive neural data or computational models highlights fundamental knowledge gaps. Our findings demonstrate an intriguing alignment of human and monkey visual object processing that defies full explanation by either brain activity in a key visual region or state-of-the-art models.
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Affiliation(s)
- Sara Djambazovska
- York University, Department of Biology and Centre for Vision Research, Toronto, Canada
- Children’s Hospital, Harvard Medical School, MA, USA
| | - Anaa Zafer
- York University, Department of Biology and Centre for Vision Research, Toronto, Canada
| | - Hamidreza Ramezanpour
- York University, Department of Biology and Centre for Vision Research, Toronto, Canada
| | | | - Kohitij Kar
- York University, Department of Biology and Centre for Vision Research, Toronto, Canada
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25
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Aitken K, Campagnola L, Garrett ME, Olsen SR, Mihalas S. Simple synaptic modulations implement diverse novelty computations. Cell Rep 2024; 43:114188. [PMID: 38713584 PMCID: PMC12054332 DOI: 10.1016/j.celrep.2024.114188] [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: 11/06/2023] [Revised: 02/09/2024] [Accepted: 04/17/2024] [Indexed: 05/09/2024] Open
Abstract
Detecting novelty is ethologically useful for an organism's survival. Recent experiments characterize how different types of novelty over timescales from seconds to weeks are reflected in the activity of excitatory and inhibitory neuron types. Here, we introduce a learning mechanism, familiarity-modulated synapses (FMSs), consisting of multiplicative modulations dependent on presynaptic or pre/postsynaptic neuron activity. With FMSs, network responses that encode novelty emerge under unsupervised continual learning and minimal connectivity constraints. Implementing FMSs within an experimentally constrained model of a visual cortical circuit, we demonstrate the generalizability of FMSs by simultaneously fitting absolute, contextual, and omission novelty effects. Our model also reproduces functional diversity within cell subpopulations, leading to experimentally testable predictions about connectivity and synaptic dynamics that can produce both population-level novelty responses and heterogeneous individual neuron signals. Altogether, our findings demonstrate how simple plasticity mechanisms within a cortical circuit structure can produce qualitatively distinct and complex novelty responses.
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Affiliation(s)
- Kyle Aitken
- Center for Data-Driven Discovery for Biology, Allen Institute, Seattle, WA 98109, USA.
| | | | | | - Shawn R Olsen
- Allen Institute for Neural Dynamics, Seattle, WA 98109, USA
| | - Stefan Mihalas
- Center for Data-Driven Discovery for Biology, Allen Institute, Seattle, WA 98109, USA; Applied Mathematics, University of Washington, Seattle, WA 98195, USA
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26
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Beiran M, Litwin-Kumar A. Prediction of neural activity in connectome-constrained recurrent networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.22.581667. [PMID: 38854115 PMCID: PMC11160579 DOI: 10.1101/2024.02.22.581667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
We develop a theory of connectome-constrained neural networks in which a "student" network is trained to reproduce the activity of a ground-truth "teacher," representing a neural system for which a connectome is available. Unlike standard paradigms with unconstrained connectivity, here the two networks have the same connectivity but different biophysical parameters, reflecting uncertainty in neuronal and synaptic properties. We find that a connectome is often insufficient to constrain the dynamics of networks that perform a specific task, illustrating the difficulty of inferring function from connectivity alone. However, recordings from a small subset of neurons can remove this degeneracy, producing dynamics in the student that agree with the teacher. Our theory can also prioritize which neurons to record from to most efficiently predict unmeasured network activity. Our analysis shows that the solution spaces of connectome-constrained and unconstrained models are qualitatively different and provides a framework to determine when such models yield consistent dynamics.
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Affiliation(s)
- Manuel Beiran
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Ashok Litwin-Kumar
- Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
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27
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Fu J, Shrinivasan S, Baroni L, Ding Z, Fahey PG, Pierzchlewicz P, Ponder K, Froebe R, Ntanavara L, Muhammad T, Willeke KF, Wang E, Ding Z, Tran DT, Papadopoulos S, Patel S, Reimer J, Ecker AS, Pitkow X, Antolik J, Sinz FH, Haefner RM, Tolias AS, Franke K. Pattern completion and disruption characterize contextual modulation in the visual cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.03.13.532473. [PMID: 36993321 PMCID: PMC10054952 DOI: 10.1101/2023.03.13.532473] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/20/2023]
Abstract
Vision is fundamentally context-dependent, with neuronal responses influenced not just by local features but also by surrounding contextual information. In the visual cortex, studies using simple grating stimuli indicate that congruent stimuli - where the center and surround share the same orientation - are more inhibitory than when orientations are orthogonal, potentially serving redundancy reduction and predictive coding. Understanding these center-surround interactions in relation to natural image statistics is challenging due to the high dimensionality of the stimulus space, yet crucial for deciphering the neuronal code of real-world sensory processing. Utilizing large-scale recordings from mouse V1, we trained convolutional neural networks (CNNs) to predict and synthesize surround patterns that either optimally suppressed or enhanced responses to center stimuli, confirmed by in vivo experiments. Contrary to the notion that congruent stimuli are suppressive, we found that surrounds that completed patterns based on natural image statistics were facilitatory, while disruptive surrounds were suppressive. Applying our CNN image synthesis method in macaque V1, we discovered that pattern completion within the near surround occurred more frequently with excitatory than with inhibitory surrounds, suggesting that our results in mice are conserved in macaques. Further, experiments and model analyses confirmed previous studies reporting the opposite effect with grating stimuli in both species. Using the MICrONS functional connectomics dataset, we observed that neurons with similar feature selectivity formed excitatory connections regardless of their receptive field overlap, aligning with the pattern completion phenomenon observed for excitatory surrounds. Finally, our empirical results emerged in a normative model of perception implementing Bayesian inference, where neuronal responses are modulated by prior knowledge of natural scene statistics. In summary, our findings identify a novel relationship between contextual information and natural scene statistics and provide evidence for a role of contextual modulation in hierarchical inference.
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28
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Waitzmann F, Wu YK, Gjorgjieva J. Top-down modulation in canonical cortical circuits with short-term plasticity. Proc Natl Acad Sci U S A 2024; 121:e2311040121. [PMID: 38593083 PMCID: PMC11032497 DOI: 10.1073/pnas.2311040121] [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: 06/30/2023] [Accepted: 02/14/2024] [Indexed: 04/11/2024] Open
Abstract
Cortical dynamics and computations are strongly influenced by diverse GABAergic interneurons, including those expressing parvalbumin (PV), somatostatin (SST), and vasoactive intestinal peptide (VIP). Together with excitatory (E) neurons, they form a canonical microcircuit and exhibit counterintuitive nonlinear phenomena. One instance of such phenomena is response reversal, whereby SST neurons show opposite responses to top-down modulation via VIP depending on the presence of bottom-up sensory input, indicating that the network may function in different regimes under different stimulation conditions. Combining analytical and computational approaches, we demonstrate that model networks with multiple interneuron subtypes and experimentally identified short-term plasticity mechanisms can implement response reversal. Surprisingly, despite not directly affecting SST and VIP activity, PV-to-E short-term depression has a decisive impact on SST response reversal. We show how response reversal relates to inhibition stabilization and the paradoxical effect in the presence of several short-term plasticity mechanisms demonstrating that response reversal coincides with a change in the indispensability of SST for network stabilization. In summary, our work suggests a role of short-term plasticity mechanisms in generating nonlinear phenomena in networks with multiple interneuron subtypes and makes several experimentally testable predictions.
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Affiliation(s)
- Felix Waitzmann
- School of Life Sciences, Technical University of Munich, 85354Freising, Germany
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438Frankfurt, Germany
| | - Yue Kris Wu
- School of Life Sciences, Technical University of Munich, 85354Freising, Germany
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438Frankfurt, Germany
| | - Julijana Gjorgjieva
- School of Life Sciences, Technical University of Munich, 85354Freising, Germany
- Computation in Neural Circuits Group, Max Planck Institute for Brain Research, 60438Frankfurt, Germany
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29
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Goris RLT, Coen-Cagli R, Miller KD, Priebe NJ, Lengyel M. Response sub-additivity and variability quenching in visual cortex. Nat Rev Neurosci 2024; 25:237-252. [PMID: 38374462 PMCID: PMC11444047 DOI: 10.1038/s41583-024-00795-0] [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] [Accepted: 01/24/2024] [Indexed: 02/21/2024]
Abstract
Sub-additivity and variability are ubiquitous response motifs in the primary visual cortex (V1). Response sub-additivity enables the construction of useful interpretations of the visual environment, whereas response variability indicates the factors that limit the precision with which the brain can do this. There is increasing evidence that experimental manipulations that elicit response sub-additivity often also quench response variability. Here, we provide an overview of these phenomena and suggest that they may have common origins. We discuss empirical findings and recent model-based insights into the functional operations, computational objectives and circuit mechanisms underlying V1 activity. These different modelling approaches all predict that response sub-additivity and variability quenching often co-occur. The phenomenology of these two response motifs, as well as many of the insights obtained about them in V1, generalize to other cortical areas. Thus, the connection between response sub-additivity and variability quenching may be a canonical motif across the cortex.
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Affiliation(s)
- Robbe L T Goris
- Center for Perceptual Systems, University of Texas at Austin, Austin, TX, USA.
| | - Ruben Coen-Cagli
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY, USA
- Department of Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, Columbia University, New York, NY, USA
- Kavli Institute for Brain Science, Columbia University, New York, NY, USA
- Dept. of Neuroscience, College of Physicians and Surgeons, Columbia University, New York, NY, USA
- Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY, USA
- Swartz Program in Theoretical Neuroscience, Columbia University, New York, NY, USA
| | - Nicholas J Priebe
- Center for Learning and Memory, University of Texas at Austin, Austin, TX, USA
| | - Máté Lengyel
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK
- Center for Cognitive Computation, Department of Cognitive Science, Central European University, Budapest, Hungary
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30
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Almeida VN. Somatostatin and the pathophysiology of Alzheimer's disease. Ageing Res Rev 2024; 96:102270. [PMID: 38484981 DOI: 10.1016/j.arr.2024.102270] [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: 07/18/2023] [Revised: 03/09/2024] [Accepted: 03/09/2024] [Indexed: 03/28/2024]
Abstract
Among the central features of Alzheimer's disease (AD) progression are altered levels of the neuropeptide somatostatin (SST), and the colocalisation of SST-positive interneurons (SST-INs) with amyloid-β plaques, leading to cell death. In this theoretical review, I propose a molecular model for the pathogenesis of AD based on SST-IN hypofunction and hyperactivity. Namely, hypofunctional and hyperactive SST-INs struggle to control hyperactivity in medial regions in early stages, leading to axonal Aβ production through excessive presynaptic GABAB inhibition, GABAB1a/APP complex downregulation and internalisation. Concomitantly, excessive SST-14 release accumulates near SST-INs in the form of amyloids, which bind to Aβ to form toxic mixed oligomers. This leads to differential SST-IN death through excitotoxicity, further disinhibition, SST deficits, and increased Aβ release, fibrillation and plaque formation. Aβ plaques, hyperactive networks and SST-IN distributions thereby tightly overlap in the brain. Conversely, chronic stimulation of postsynaptic SST2/4 on gulutamatergic neurons by hyperactive SST-INs promotes intense Mitogen-Activated Protein Kinase (MAPK) p38 activity, leading to somatodendritic p-tau staining and apoptosis/neurodegeneration - in agreement with a near complete overlap between p38 and neurofibrillary tangles. This model is suitable to explain some of the principal risk factors and markers of AD progression, including mitochondrial dysfunction, APOE4 genotype, sex-dependent vulnerability, overactive glial cells, dystrophic neurites, synaptic/spine losses, inter alia. Finally, the model can also shed light on qualitative aspects of AD neuropsychology, especially within the domains of spatial and declarative (episodic, semantic) memory, under an overlying pattern of contextual indiscrimination, ensemble instability, interference and generalisation.
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Affiliation(s)
- Victor N Almeida
- Institute of Psychiatry, Faculty of Medicine, University of São Paulo (USP), Brazil; Faculty of Languages, Federal University of Minas Gerais (UFMG), Brazil.
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31
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Wang A, Ferguson KA, Gupta J, Higley MJ, Cardin JA. Developmental trajectory of cortical somatostatin interneuron function. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.05.583539. [PMID: 38496673 PMCID: PMC10942364 DOI: 10.1101/2024.03.05.583539] [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
GABAergic inhibition is critical to the proper development of neocortical circuits. However, GABAergic interneurons are highly diverse and the developmental roles of distinct inhibitory subpopulations remain largely unclear. Dendrite-targeting, somatostatin-expressing interneurons (SST-INs) in the mature cortex regulate synaptic integration and plasticity in excitatory pyramidal neurons (PNs) and exhibit unique feature selectivity. Relatively little is known about early postnatal SST-IN activity or impact on surrounding local circuits. We examined juvenile SST-INs and PNs in mouse primary visual cortex. PNs exhibited stable visual responses and feature selectivity from eye opening onwards. In contrast, SST-INs developed visual responses and feature selectivity during the third postnatal week in parallel with a rapid increase in excitatory synaptic innervation. SST-INs largely exerted a multiplicative effect on nearby PN visual responses at all ages, but this impact increased over time. Our results identify a developmental window for the emergence of an inhibitory circuit mechanism for normalization.
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Affiliation(s)
| | | | - Jyoti Gupta
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Michael J. Higley
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jessica A. Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
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32
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Myers-Joseph D, Wilmes KA, Fernandez-Otero M, Clopath C, Khan AG. Disinhibition by VIP interneurons is orthogonal to cross-modal attentional modulation in primary visual cortex. Neuron 2024; 112:628-645.e7. [PMID: 38070500 DOI: 10.1016/j.neuron.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/24/2023] [Accepted: 11/08/2023] [Indexed: 02/24/2024]
Abstract
Attentional modulation of sensory processing is a key feature of cognition; however, its neural circuit basis is poorly understood. A candidate mechanism is the disinhibition of pyramidal cells through vasoactive intestinal peptide (VIP) and somatostatin (SOM)-positive interneurons. However, the interaction of attentional modulation and VIP-SOM disinhibition has never been directly tested. We used all-optical methods to bi-directionally manipulate VIP interneuron activity as mice performed a cross-modal attention-switching task. We measured the activities of VIP, SOM, and parvalbumin (PV)-positive interneurons and pyramidal neurons identified in the same tissue and found that although activity in all cell classes was modulated by both attention and VIP manipulation, their effects were orthogonal. Attention and VIP-SOM disinhibition relied on distinct patterns of changes in activity and reorganization of interactions between inhibitory and excitatory cells. Circuit modeling revealed a precise network architecture consistent with multiplexing strong yet non-interacting modulations in the same neural population.
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Affiliation(s)
- Dylan Myers-Joseph
- Centre for Developmental Neurobiology, King's College London, London SE1 1UL, UK
| | | | | | - Claudia Clopath
- Department of Bioengineering, Imperial College, London SW7 2AZ, UK
| | - Adil G Khan
- Centre for Developmental Neurobiology, King's College London, London SE1 1UL, UK.
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33
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De Filippo R, Schmitz D. Synthetic surprise as the foundation of the psychedelic experience. Neurosci Biobehav Rev 2024; 157:105538. [PMID: 38220035 PMCID: PMC10839673 DOI: 10.1016/j.neubiorev.2024.105538] [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: 09/18/2023] [Revised: 01/03/2024] [Accepted: 01/05/2024] [Indexed: 01/16/2024]
Abstract
Psychedelic agents, such as LSD and psilocybin, induce marked alterations in consciousness via activation of the 5-HT2A receptor (5-HT2ARs). We hypothesize that psychedelics enforce a state of synthetic surprise through the biased activation of the 5-HTRs system. This idea is informed by recent insights into the role of 5-HT in signaling surprise. The effects on consciousness, explained by the cognitive penetrability of perception, can be described within the predictive coding framework where surprise corresponds to prediction error, the mismatch between predictions and actual sensory input. Crucially, the precision afforded to the prediction error determines its effect on priors, enabling a dynamic interaction between top-down expectations and incoming sensory data. By integrating recent findings on predictive coding circuitry and 5-HT2ARs transcriptomic data, we propose a biological implementation with emphasis on the role of inhibitory interneurons. Implications arise for the clinical use of psychedelics, which may rely primarily on their inherent capacity to induce surprise in order to disrupt maladaptive patterns.
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Affiliation(s)
- Roberto De Filippo
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Neuroscience Research Center, 10117 Berlin, Germany.
| | - Dietmar Schmitz
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Neuroscience Research Center, 10117 Berlin, Germany; German Center for Neurodegenerative Diseases (DZNE) Berlin, 10117 Berlin, Germany; Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, Einstein Center for Neuroscience, 10117 Berlin, Germany; Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität Berlin, and Berlin Institute of Health, NeuroCure Cluster of Excellence, 10117 Berlin, Germany; Humboldt-Universität zu Berlin, Bernstein Center for Computational Neuroscience, Philippstr. 13, 10115 Berlin, Germany
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34
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Seignette K, Jamann N, Papale P, Terra H, Porneso RO, de Kraker L, van der Togt C, van der Aa M, Neering P, Ruimschotel E, Roelfsema PR, Montijn JS, Self MW, Kole MHP, Levelt CN. Experience shapes chandelier cell function and structure in the visual cortex. eLife 2024; 12:RP91153. [PMID: 38192196 PMCID: PMC10963032 DOI: 10.7554/elife.91153] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2024] Open
Abstract
Detailed characterization of interneuron types in primary visual cortex (V1) has greatly contributed to understanding visual perception, yet the role of chandelier cells (ChCs) in visual processing remains poorly characterized. Using viral tracing we found that V1 ChCs predominantly receive monosynaptic input from local layer 5 pyramidal cells and higher-order cortical regions. Two-photon calcium imaging and convolutional neural network modeling revealed that ChCs are visually responsive but weakly selective for stimulus content. In mice running in a virtual tunnel, ChCs respond strongly to events known to elicit arousal, including locomotion and visuomotor mismatch. Repeated exposure of the mice to the virtual tunnel was accompanied by reduced visual responses of ChCs and structural plasticity of ChC boutons and axon initial segment length. Finally, ChCs only weakly inhibited pyramidal cells. These findings suggest that ChCs provide an arousal-related signal to layer 2/3 pyramidal cells that may modulate their activity and/or gate plasticity of their axon initial segments during behaviorally relevant events.
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Affiliation(s)
- Koen Seignette
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Nora Jamann
- Department of Axonal Signaling, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Biology Cell Biology, Neurobiology and Biophysics, Faculty of Science, Utrecht UniversityUtrechtNetherlands
| | - Paolo Papale
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Huub Terra
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Ralph O Porneso
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Leander de Kraker
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Chris van der Togt
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Maaike van der Aa
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Paul Neering
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Emma Ruimschotel
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Pieter R Roelfsema
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Laboratory of Visual Brain Therapy, Sorbonne Université, Institut National de la Santé et de la Recherche Médicale, Centre National de la Recherche Scientifique, Institut de la VisionParisFrance
- Department of Integrative Neurophysiology, Centre for Neurogenomics and Cognitive Research, VU UniversityAmsterdamNetherlands
- Department of Psychiatry, Academic Medical Center, University of AmsterdamAmsterdamNetherlands
| | - Jorrit S Montijn
- Department of Cortical Structure & Function, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Matthew W Self
- Department of Vision & Cognition, Netherlands Institute for NeuroscienceAmsterdamNetherlands
| | - Maarten HP Kole
- Department of Axonal Signaling, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Biology Cell Biology, Neurobiology and Biophysics, Faculty of Science, Utrecht UniversityUtrechtNetherlands
| | - Christiaan N Levelt
- Department of Molecular Visual Plasticity, Netherlands Institute for NeuroscienceAmsterdamNetherlands
- Department of Molecular and Cellular Neurobiology, Center for Neurogenomics and Cognitive Research, VU University AmsterdamAmsterdamNetherlands
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35
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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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36
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Soo WWM, Goudar V, Wang XJ. Training biologically plausible recurrent neural networks on cognitive tasks with long-term dependencies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.10.561588. [PMID: 37873445 PMCID: PMC10592728 DOI: 10.1101/2023.10.10.561588] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Training recurrent neural networks (RNNs) has become a go-to approach for generating and evaluating mechanistic neural hypotheses for cognition. The ease and efficiency of training RNNs with backpropagation through time and the availability of robustly supported deep learning libraries has made RNN modeling more approachable and accessible to neuroscience. Yet, a major technical hindrance remains. Cognitive processes such as working memory and decision making involve neural population dynamics over a long period of time within a behavioral trial and across trials. It is difficult to train RNNs to accomplish tasks where neural representations and dynamics have long temporal dependencies without gating mechanisms such as LSTMs or GRUs which currently lack experimental support and prohibit direct comparison between RNNs and biological neural circuits. We tackled this problem based on the idea of specialized skip-connections through time to support the emergence of task-relevant dynamics, and subsequently reinstitute biological plausibility by reverting to the original architecture. We show that this approach enables RNNs to successfully learn cognitive tasks that prove impractical if not impossible to learn using conventional methods. Over numerous tasks considered here, we achieve less training steps and shorter wall-clock times, particularly in tasks that require learning long-term dependencies via temporal integration over long timescales or maintaining a memory of past events in hidden-states. Our methods expand the range of experimental tasks that biologically plausible RNN models can learn, thereby supporting the development of theory for the emergent neural mechanisms of computations involving long-term dependencies.
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37
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Ferguson KA, Salameh J, Alba C, Selwyn H, Barnes C, Lohani S, Cardin JA. VIP interneurons regulate cortical size tuning and visual perception. Cell Rep 2023; 42:113088. [PMID: 37682710 PMCID: PMC10618959 DOI: 10.1016/j.celrep.2023.113088] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 07/12/2023] [Accepted: 08/17/2023] [Indexed: 09/10/2023] Open
Abstract
Cortical circuit function is regulated by extensively interconnected, diverse populations of GABAergic interneurons that may play key roles in shaping circuit operation according to behavioral context. A specialized population of interneurons that co-express vasoactive intestinal peptides (VIP-INs) are activated during arousal and innervate other INs and pyramidal neurons (PNs). Although state-dependent modulation of VIP-INs has been extensively studied, their role in regulating sensory processing is less well understood. We examined the impact of VIP-INs in the primary visual cortex of awake behaving mice. Loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing INs (SST-INs) but not PNs. In contrast, reduced VIP-IN activity globally disrupts visual feature selectivity for stimulus size. Moreover, the impact of VIP-INs on perceptual behavior varies with context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical activity and sensory context-dependent perceptual performance.
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Affiliation(s)
- Katie A Ferguson
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jenna Salameh
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Christopher Alba
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Hannah Selwyn
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Clayton Barnes
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510, USA.
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38
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Bastos G, Holmes JT, Ross JM, Rader AM, Gallimore CG, Wargo JA, Peterka DS, Hamm JP. Top-down input modulates visual context processing through an interneuron-specific circuit. Cell Rep 2023; 42:113133. [PMID: 37708021 PMCID: PMC10591868 DOI: 10.1016/j.celrep.2023.113133] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/17/2023] [Accepted: 08/30/2023] [Indexed: 09/16/2023] Open
Abstract
Visual stimuli that deviate from the current context elicit augmented responses in the primary visual cortex (V1). These heightened responses, known as "deviance detection," require local inhibition in the V1 and top-down input from the anterior cingulate area (ACa). Here, we investigated the mechanisms by which the ACa and V1 interact to support deviance detection. Local field potential recordings in mice during an oddball paradigm showed that ACa-V1 synchrony peaks in the theta/alpha band (≈10 Hz). Two-photon imaging in the V1 revealed that mainly pyramidal neurons exhibited deviance detection, while contextually redundant stimuli increased vasoactive intestinal peptide (VIP)-positive interneuron (VIP) activity and decreased somatostatin-positive interneuron (SST) activity. Optogenetic drive of ACa-V1 inputs at 10 Hz activated V1-VIPs but inhibited V1-SSTs, mirroring the dynamics present during the oddball paradigm. Chemogenetic inhibition of V1-VIPs disrupted Aca-V1 synchrony and deviance detection in the V1. These results outline temporal and interneuron-specific mechanisms of top-down modulation that support visual context processing.
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Affiliation(s)
- Georgia Bastos
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Jacob T Holmes
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Jordan M Ross
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Anna M Rader
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Connor G Gallimore
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Joseph A Wargo
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA
| | - Darcy S Peterka
- Mortimer B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, NY 10027, USA
| | - Jordan P Hamm
- Neuroscience Institute, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Neuroinflammation and Cardiometabolic Diseases, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA; Center for Behavioral Neuroscience, Georgia State University, Petit Science Center, 100 Piedmont Ave, Atlanta, GA 30303, USA.
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39
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Machold R, Dellal S, Valero M, Zurita H, Kruglikov I, Meng JH, Hanson JL, Hashikawa Y, Schuman B, Buzsáki G, Rudy B. Id2 GABAergic interneurons comprise a neglected fourth major group of cortical inhibitory cells. eLife 2023; 12:e85893. [PMID: 37665123 PMCID: PMC10581691 DOI: 10.7554/elife.85893] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 08/21/2023] [Indexed: 09/05/2023] Open
Abstract
Cortical GABAergic interneurons (INs) represent a diverse population of mainly locally projecting cells that provide specialized forms of inhibition to pyramidal neurons and other INs. Most recent work on INs has focused on subtypes distinguished by expression of Parvalbumin (PV), Somatostatin (SST), or Vasoactive Intestinal Peptide (VIP). However, a fourth group that includes neurogliaform cells (NGFCs) has been less well characterized due to a lack of genetic tools. Here, we show that these INs can be accessed experimentally using intersectional genetics with the gene Id2. We find that outside of layer 1 (L1), the majority of Id2 INs are NGFCs that express high levels of neuropeptide Y (NPY) and exhibit a late-spiking firing pattern, with extensive local connectivity. While much sparser, non-NGFC Id2 INs had more variable properties, with most cells corresponding to a diverse group of INs that strongly expresses the neuropeptide CCK. In vivo, using silicon probe recordings, we observed several distinguishing aspects of NGFC activity, including a strong rebound in activity immediately following the cortical down state during NREM sleep. Our study provides insights into IN diversity and NGFC distribution and properties, and outlines an intersectional genetics approach for further study of this underappreciated group of INs.
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Affiliation(s)
- Robert Machold
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - Shlomo Dellal
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - Manuel Valero
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - Hector Zurita
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - Ilya Kruglikov
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - John Hongyu Meng
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Jessica L Hanson
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - Yoshiko Hashikawa
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - Benjamin Schuman
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
| | - György Buzsáki
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
- Department of Neuroscience and Physiology, New York University Grossman School of MedicineNew YorkUnited States
| | - Bernardo Rudy
- Neuroscience Institute, New York University Grossman School of MedicineNew YorkUnited States
- Department of Neuroscience and Physiology, New York University Grossman School of MedicineNew YorkUnited States
- Department of Anesthesiology, Perioperative Care and Pain Medicine, New York University Grossman School of MedicineNew YorkUnited States
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40
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Pan X, DeForge A, Schwartz O. Generalizing biological surround suppression based on center surround similarity via deep neural network models. PLoS Comput Biol 2023; 19:e1011486. [PMID: 37738258 PMCID: PMC10550176 DOI: 10.1371/journal.pcbi.1011486] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 10/04/2023] [Accepted: 09/04/2023] [Indexed: 09/24/2023] Open
Abstract
Sensory perception is dramatically influenced by the context. Models of contextual neural surround effects in vision have mostly accounted for Primary Visual Cortex (V1) data, via nonlinear computations such as divisive normalization. However, surround effects are not well understood within a hierarchy, for neurons with more complex stimulus selectivity beyond V1. We utilized feedforward deep convolutional neural networks and developed a gradient-based technique to visualize the most suppressive and excitatory surround. We found that deep neural networks exhibited a key signature of surround effects in V1, highlighting center stimuli that visually stand out from the surround and suppressing responses when the surround stimulus is similar to the center. We found that in some neurons, especially in late layers, when the center stimulus was altered, the most suppressive surround surprisingly can follow the change. Through the visualization approach, we generalized previous understanding of surround effects to more complex stimuli, in ways that have not been revealed in visual cortices. In contrast, the suppression based on center surround similarity was not observed in an untrained network. We identified further successes and mismatches of the feedforward CNNs to the biology. Our results provide a testable hypothesis of surround effects in higher visual cortices, and the visualization approach could be adopted in future biological experimental designs.
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Affiliation(s)
- Xu Pan
- Department of Computer Science, University of Miami, Coral Gables, FL, United States of America
| | - Annie DeForge
- School of Information, University of California, Berkeley, CA, United States of America
- Bentley University, Waltham, MA, United States of America
| | - Odelia Schwartz
- Department of Computer Science, University of Miami, Coral Gables, FL, United States of America
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41
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Guo L, Kumar A. Role of interneuron subtypes in controlling trial-by-trial output variability in the neocortex. Commun Biol 2023; 6:874. [PMID: 37620550 PMCID: PMC10449833 DOI: 10.1038/s42003-023-05231-0] [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: 12/13/2022] [Accepted: 08/08/2023] [Indexed: 08/26/2023] Open
Abstract
Trial-by-trial variability is a ubiquitous property of neuronal activity in vivo which shapes the stimulus response. Computational models have revealed how local network structure and feedforward inputs shape the trial-by-trial variability. However, the role of input statistics and different interneuron subtypes in this process is less understood. To address this, we investigate the dynamics of stimulus response in a cortical microcircuit model with one excitatory and three inhibitory interneuron populations (PV, SST, VIP). Our findings demonstrate that the balance of inputs to different neuron populations and input covariances are the primary determinants of output trial-by-trial variability. The effect of input covariances is contingent on the input balances. In general, the network exhibits smaller output trial-by-trial variability in a PV-dominated regime than in an SST-dominated regime. Importantly, our work reveals mechanisms by which output trial-by-trial variability can be controlled in a context, state, and task-dependent manner.
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Affiliation(s)
- Lihao Guo
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology Stockholm, Stockholm, Sweden.
- Scilife Lab, Stockholm, Sweden.
| | - Arvind Kumar
- Division of Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology Stockholm, Stockholm, Sweden.
- Scilife Lab, Stockholm, Sweden.
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42
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Bernáez Timón L, Ekelmans P, Kraynyukova N, Rose T, Busse L, Tchumatchenko T. How to incorporate biological insights into network models and why it matters. J Physiol 2023; 601:3037-3053. [PMID: 36069408 DOI: 10.1113/jp282755] [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: 04/22/2022] [Accepted: 08/24/2022] [Indexed: 11/08/2022] Open
Abstract
Due to the staggering complexity of the brain and its neural circuitry, neuroscientists rely on the analysis of mathematical models to elucidate its function. From Hodgkin and Huxley's detailed description of the action potential in 1952 to today, new theories and increasing computational power have opened up novel avenues to study how neural circuits implement the computations that underlie behaviour. Computational neuroscientists have developed many models of neural circuits that differ in complexity, biological realism or emergent network properties. With recent advances in experimental techniques for detailed anatomical reconstructions or large-scale activity recordings, rich biological data have become more available. The challenge when building network models is to reflect experimental results, either through a high level of detail or by finding an appropriate level of abstraction. Meanwhile, machine learning has facilitated the development of artificial neural networks, which are trained to perform specific tasks. While they have proven successful at achieving task-oriented behaviour, they are often abstract constructs that differ in many features from the physiology of brain circuits. Thus, it is unclear whether the mechanisms underlying computation in biological circuits can be investigated by analysing artificial networks that accomplish the same function but differ in their mechanisms. Here, we argue that building biologically realistic network models is crucial to establishing causal relationships between neurons, synapses, circuits and behaviour. More specifically, we advocate for network models that consider the connectivity structure and the recorded activity dynamics while evaluating task performance.
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Affiliation(s)
- Laura Bernáez Timón
- Institute for Physiological Chemistry, University of Mainz Medical Center, Mainz, Germany
| | - Pierre Ekelmans
- Frankfurt Institute for Advanced Studies, Frankfurt, Germany
| | - Nataliya Kraynyukova
- Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Tobias Rose
- Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
| | - Laura Busse
- Division of Neurobiology, Faculty of Biology, LMU Munich, Munich, Germany
- Bernstein Center for Computational Neuroscience, Munich, Germany
| | - Tatjana Tchumatchenko
- Institute for Physiological Chemistry, University of Mainz Medical Center, Mainz, Germany
- Institute of Experimental Epileptology and Cognition Research, University of Bonn Medical Center, Bonn, Germany
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43
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Li J, Rentzeperis I, van Leeuwen C. Functional and spatial rewiring principles jointly regulate context-sensitive computation. PLoS Comput Biol 2023; 19:e1011325. [PMID: 37566628 PMCID: PMC10446201 DOI: 10.1371/journal.pcbi.1011325] [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: 10/19/2022] [Revised: 08/23/2023] [Accepted: 07/03/2023] [Indexed: 08/13/2023] Open
Abstract
Adaptive rewiring provides a basic principle of self-organizing connectivity in evolving neural network topology. By selectively adding connections to regions with intense signal flow and deleting underutilized connections, adaptive rewiring generates optimized brain-like, i.e. modular, small-world, and rich club connectivity structures. Besides topology, neural self-organization also follows spatial optimization principles, such as minimizing the neural wiring distance and topographic alignment of neural pathways. We simulated the interplay of these spatial principles and adaptive rewiring in evolving neural networks with weighted and directed connections. The neural traffic flow within the network is represented by the equivalent of diffusion dynamics for directed edges: consensus and advection. We observe a constructive synergy between adaptive and spatial rewiring, which contributes to network connectedness. In particular, wiring distance minimization facilitates adaptive rewiring in creating convergent-divergent units. These units support the flow of neural information and enable context-sensitive information processing in the sensory cortex and elsewhere. Convergent-divergent units consist of convergent hub nodes, which collect inputs from pools of nodes and project these signals via a densely interconnected set of intermediate nodes onto divergent hub nodes, which broadcast their output back to the network. Convergent-divergent units vary in the degree to which their intermediate nodes are isolated from the rest of the network. This degree, and hence the context-sensitivity of the network's processing style, is parametrically determined in the evolving network model by the relative prominence of spatial versus adaptive rewiring.
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Affiliation(s)
- Jia Li
- Brain and Cognition unit, Faculty of psychology and educational sciences, KU Leuven, Leuven, Belgium
| | - Ilias Rentzeperis
- Brain and Cognition unit, Faculty of psychology and educational sciences, KU Leuven, Leuven, Belgium
| | - Cees van Leeuwen
- Brain and Cognition unit, Faculty of psychology and educational sciences, KU Leuven, Leuven, Belgium
- Cognitive and developmental psychology unit, Faculty of social science, University of Kaiserslautern, Kaiserslautern, Germany
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44
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Kumar M, Handy G, Kouvaros S, Zhao Y, Brinson LL, Wei E, Bizup B, Doiron B, Tzounopoulos T. Cell-type-specific plasticity of inhibitory interneurons in the rehabilitation of auditory cortex after peripheral damage. Nat Commun 2023; 14:4170. [PMID: 37443148 PMCID: PMC10345144 DOI: 10.1038/s41467-023-39732-7] [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: 09/23/2022] [Accepted: 06/21/2023] [Indexed: 07/15/2023] Open
Abstract
Peripheral sensory organ damage leads to compensatory cortical plasticity that is associated with a remarkable recovery of cortical responses to sound. The precise mechanisms that explain how this plasticity is implemented and distributed over a diverse collection of excitatory and inhibitory cortical neurons remain unknown. After noise trauma and persistent peripheral deficits, we found recovered sound-evoked activity in mouse A1 excitatory principal neurons (PNs), parvalbumin- and vasoactive intestinal peptide-expressing neurons (PVs and VIPs), but reduced activity in somatostatin-expressing neurons (SOMs). This cell-type-specific recovery was also associated with cell-type-specific intrinsic plasticity. These findings, along with our computational modelling results, are consistent with the notion that PV plasticity contributes to PN stability, SOM plasticity allows for increased PN and PV activity, and VIP plasticity enables PN and PV recovery by inhibiting SOMs.
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Affiliation(s)
- Manoj Kumar
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
| | - Gregory Handy
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Stylianos Kouvaros
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Yanjun Zhao
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Lovisa Ljungqvist Brinson
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Eric Wei
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Brandon Bizup
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Brent Doiron
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA
| | - Thanos Tzounopoulos
- Pittsburgh Hearing Research Center, Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA, 15261, USA.
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45
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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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46
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Shine JM. Neuromodulatory control of complex adaptive dynamics in the brain. Interface Focus 2023; 13:20220079. [PMID: 37065268 PMCID: PMC10102735 DOI: 10.1098/rsfs.2022.0079] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/23/2023] [Indexed: 04/18/2023] Open
Abstract
How is the massive dimensionality and complexity of the microscopic constituents of the nervous system brought under sufficiently tight control so as to coordinate adaptive behaviour? A powerful means for striking this balance is to poise neurons close to the critical point of a phase transition, at which a small change in neuronal excitability can manifest a nonlinear augmentation in neuronal activity. How the brain could mediate this critical transition is a key open question in neuroscience. Here, I propose that the different arms of the ascending arousal system provide the brain with a diverse set of heterogeneous control parameters that can be used to modulate the excitability and receptivity of target neurons-in other words, to act as control parameters for mediating critical neuronal order. Through a series of worked examples, I demonstrate how the neuromodulatory arousal system can interact with the inherent topological complexity of neuronal subsystems in the brain to mediate complex adaptive behaviour.
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Affiliation(s)
- James M. Shine
- Brain and Mind Center, The University of Sydney, Sydney, Australia
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47
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Daumail L, Carlson BM, Mitchell BA, Cox MA, Westerberg JA, Johnson C, Martin PR, Tong F, Maier A, Dougherty K. Rapid adaptation of primate LGN neurons to drifting grating stimulation. J Neurophysiol 2023; 129:1447-1467. [PMID: 37162181 PMCID: PMC10259864 DOI: 10.1152/jn.00058.2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 04/18/2023] [Accepted: 05/08/2023] [Indexed: 05/11/2023] Open
Abstract
The visual system needs to dynamically adapt to changing environments. Much is known about the adaptive effects of constant stimulation over prolonged periods. However, there are open questions regarding adaptation to stimuli that are changing over time, interrupted, or repeated. Feature-specific adaptation to repeating stimuli has been shown to occur as early as primary visual cortex (V1), but there is also evidence for more generalized, fatigue-like adaptation that might occur at an earlier stage of processing. Here, we show adaptation in the lateral geniculate nucleus (LGN) of awake, fixating monkeys following brief (1 s) exposure to repeated cycles of a 4-Hz drifting grating. We examined the relative change of each neuron's response across successive (repeated) grating cycles. We found that neurons from all cell classes (parvocellular, magnocellular, and koniocellular) showed significant adaptation. However, only magnocellular neurons showed adaptation when responses were averaged to a population response. In contrast to firing rates, response variability was largely unaffected. Finally, adaptation was comparable between monocular and binocular stimulation, suggesting that rapid LGN adaptation is monocular in nature.NEW & NOTEWORTHY Neural adaptation can be defined as reduction of spiking responses following repeated or prolonged stimulation. Adaptation helps adjust neural responsiveness to avoid saturation and has been suggested to improve perceptual selectivity, information transmission, and predictive coding. Here, we report rapid adaptation to repeated cycles of gratings drifting over the receptive field of neurons at the earliest site of postretinal processing, the lateral geniculate nucleus of the thalamus.
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Affiliation(s)
- Loïc Daumail
- Department of Psychology, College of Arts and Science, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, Tennessee, United States
| | - Brock M Carlson
- Department of Psychology, College of Arts and Science, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, Tennessee, United States
| | - Blake A Mitchell
- Department of Psychology, College of Arts and Science, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, Tennessee, United States
| | - Michele A Cox
- Department of Brain and Cognitive Sciences, University of Rochester, Rochester, New York, United States
| | - Jacob A Westerberg
- Department of Psychology, College of Arts and Science, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, Tennessee, United States
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Cortez Johnson
- Kaiser Permanente Bernard J. Tyson School of Medicine in Pasadena, Pasadena, California, United States
| | - Paul R Martin
- Save Sight Institute and Australian Research Council Centre of Excellence for Integrative Brain Function, The University of Sydney, Sydney, New South Wales, Australia
| | - Frank Tong
- Department of Psychology, College of Arts and Science, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, Tennessee, United States
| | - Alexander Maier
- Department of Psychology, College of Arts and Science, Vanderbilt Vision Research Center, Vanderbilt University, Nashville, Tennessee, United States
| | - Kacie Dougherty
- Princeton Neuroscience Institute, Princeton University, Princeton, New Jersey, United States
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48
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Ferguson KA, Salameh J, Alba C, Selwyn H, Barnes C, Lohani S, Cardin JA. VIP interneurons regulate cortical size tuning and visual perception. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.14.532664. [PMID: 37162871 PMCID: PMC10168200 DOI: 10.1101/2023.03.14.532664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
Local cortical circuit function is regulated by diverse populations of GABAergic interneurons with distinct properties and extensive interconnectivity. Inhibitory-to-inhibitory interactions between interneuron populations may play key roles in shaping circuit operation according to behavioral context. A specialized population of GABAergic interneurons that co-express vasoactive intestinal peptide (VIP-INs) are activated during arousal and locomotion and innervate other local interneurons and pyramidal neurons. Although modulation of VIP-IN activity by behavioral state has been extensively studied, their role in regulating information processing and selectivity is less well understood. Using a combination of cellular imaging, short and long-term manipulation, and perceptual behavior, we examined the impact of VIP-INs on their synaptic target populations in the primary visual cortex of awake behaving mice. We find that loss of VIP-IN activity alters the behavioral state-dependent modulation of somatostatin-expressing interneurons (SST-INs) but not pyramidal neurons (PNs). In contrast, reduced VIP-IN activity disrupts visual feature selectivity for stimulus size in both populations. Inhibitory-to inhibitory interactions thus directly shape the selectivity of GABAergic interneurons for sensory stimuli. Moreover, the impact of VIP-IN activity on perceptual behavior varies with visual context and is more acute for small than large visual cues. VIP-INs thus contribute to both state-dependent modulation of cortical circuit activity and sensory context-dependent perceptual performance.
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Affiliation(s)
- Katie A Ferguson
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jenna Salameh
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Christopher Alba
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Hannah Selwyn
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Clayton Barnes
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Sweyta Lohani
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
| | - Jessica A Cardin
- Department of Neuroscience, Kavli Institute for Neuroscience, Wu Tsai Institute, Yale University School of Medicine, New Haven, CT 06510 USA
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Ding W, Fischer L, Chen Q, Li Z, Yang L, You Z, Hu K, Wu X, Zhou X, Chao W, Hu P, Dagnew TM, Dubreuil DM, Wang S, Xia S, Bao C, Zhu S, Chen L, Wang C, Wainger B, Jin P, Mao J, Feng G, Harnett MT, Shen S. Highly synchronized cortical circuit dynamics mediate spontaneous pain in mice. J Clin Invest 2023; 133:e166408. [PMID: 36602876 PMCID: PMC9974100 DOI: 10.1172/jci166408] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 12/22/2022] [Indexed: 01/06/2023] Open
Abstract
Cortical neural dynamics mediate information processing for the cerebral cortex, which is implicated in fundamental biological processes such as vision and olfaction, in addition to neurological and psychiatric diseases. Spontaneous pain is a key feature of human neuropathic pain. Whether spontaneous pain pushes the cortical network into an aberrant state and, if so, whether it can be brought back to a "normal" operating range to ameliorate pain are unknown. Using a clinically relevant mouse model of neuropathic pain with spontaneous pain-like behavior, we report that orofacial spontaneous pain activated a specific area within the primary somatosensory cortex (S1), displaying synchronized neural dynamics revealed by intravital two-photon calcium imaging. This synchronization was underpinned by local GABAergic interneuron hypoactivity. Pain-induced cortical synchronization could be attenuated by manipulating local S1 networks or clinically effective pain therapies. Specifically, both chemogenetic inhibition of pain-related c-Fos-expressing neurons and selective activation of GABAergic interneurons significantly attenuated S1 synchronization. Clinically effective pain therapies including carbamazepine and nerve root decompression could also dampen S1 synchronization. More important, restoring a "normal" range of neural dynamics through attenuation of pain-induced S1 synchronization alleviated pain-like behavior. These results suggest that spontaneous pain pushed the S1 regional network into a synchronized state, whereas reversal of this synchronization alleviated pain.
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Affiliation(s)
- Weihua Ding
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Lukas Fischer
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Qian Chen
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Ziyi Li
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Liuyue Yang
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Zerong You
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Kun Hu
- Department of Pathology, Tufts University School of Medicine, Medford, Massachusetts, USA
| | - Xinbo Wu
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Xue Zhou
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Wei Chao
- Department of Anesthesiology, Center for Shock, Trauma and Anesthesiology Research, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Peter Hu
- Department of Anesthesiology, Center for Shock, Trauma and Anesthesiology Research, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Tewodros Mulugeta Dagnew
- MGH/HST Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Daniel M. Dubreuil
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Shiyu Wang
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Suyun Xia
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Caroline Bao
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Shengmei Zhu
- Department of Anesthesiology, the First Affiliate Hospital of Zhejiang University, Hangzhou, China
| | - Lucy Chen
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Changning Wang
- MGH/HST Martinos Center for Biomedical Imaging, Department of Radiology, MGH, Harvard Medical School, Boston, Massachusetts, USA
| | - Brian Wainger
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Peng Jin
- Department of Human Genetics, Emory University, Atlanta, Georgia, USA
| | - Jianren Mao
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
| | - Guoping Feng
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Mark T. Harnett
- McGovern Institute for Brain Research and Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Shiqian Shen
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital (MGH), Harvard Medical School, Boston, Massachusetts, USA
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Musall S, Sun XR, Mohan H, An X, Gluf S, Li SJ, Drewes R, Cravo E, Lenzi I, Yin C, Kampa BM, Churchland AK. Pyramidal cell types drive functionally distinct cortical activity patterns during decision-making. Nat Neurosci 2023; 26:495-505. [PMID: 36690900 PMCID: PMC9991922 DOI: 10.1038/s41593-022-01245-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 12/06/2022] [Indexed: 01/25/2023]
Abstract
Understanding how cortical circuits generate complex behavior requires investigating the cell types that comprise them. Functional differences across pyramidal neuron (PyN) types have been observed within cortical areas, but it is not known whether these local differences extend throughout the cortex, nor whether additional differences emerge when larger-scale dynamics are considered. We used genetic and retrograde labeling to target pyramidal tract, intratelencephalic and corticostriatal projection neurons and measured their cortex-wide activity. Each PyN type drove unique neural dynamics, both at the local and cortex-wide scales. Cortical activity and optogenetic inactivation during an auditory decision task revealed distinct functional roles. All PyNs in parietal cortex were recruited during perception of the auditory stimulus, but, surprisingly, pyramidal tract neurons had the largest causal role. In frontal cortex, all PyNs were required for accurate choices but showed distinct choice tuning. Our results reveal that rich, cell-type-specific cortical dynamics shape perceptual decisions.
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Affiliation(s)
- Simon Musall
- Institute of Biological Information Processing (IBI-3), Forschungszentrum Jülich, Jülich, Germany.
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany.
| | - Xiaonan R Sun
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
- Department of Neurosurgery, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Hemanth Mohan
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Xu An
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Steven Gluf
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
| | - Shu-Jing Li
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
| | - Rhonda Drewes
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA
| | - Emma Cravo
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
| | - Irene Lenzi
- Institute of Biological Information Processing (IBI-3), Forschungszentrum Jülich, Jülich, Germany
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
| | - Chaoqun Yin
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Björn M Kampa
- Department of Systems Neurophysiology, Institute for Zoology, RWTH Aachen University, Aachen, Germany
- JARA Brain, Institute for Neuroscience and Medicine (INM-10), Forschungszentrum Jülich, Jülich, Germany
| | - Anne K Churchland
- Cold Spring Harbor Laboratory, Neuroscience, Cold Spring Harbor, New York, NY, USA.
- Department of Neurobiology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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