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Boroujeni KB, Helfrich RF, Fiebelkorn IC, Bentley N, Lin JJ, Knight RT, Kastner S. Attentional Information Routing in The Human Brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.11.612548. [PMID: 39314423 PMCID: PMC11419049 DOI: 10.1101/2024.09.11.612548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/25/2024]
Abstract
Brain-wide communication supports behaviors that require coordination between sensory and associative regions. However, how large-scale brain networks route sensory information at fast timescales to guide upcoming actions remains unclear. Using spiking neural networks and human intracranial electrophysiology during spatial attention tasks, where participants detected a target at cued locations, we show that high-frequency activity bursts (HFAb) serve as information-carrying events, facilitating fast and long-range communications. HFAbs emerged as bouts of neural population spiking and were coordinated brain-wide through low-frequency rhythms. At the network-level, HFAb coordination identified distinct cue- and target-activated subnetworks. HFAbs following the cue onset in cue-subnetworks predicted successful target detection and preceded the information in target-subnetworks following target onset. Our findings suggest HFAbs as a neural mechanism for fast brain-wide information routing that supports attentional performance.
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2
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Cho S, Han HB, Jung D, Kim J, Choi JH. Mouse Escape Behaviors and mPFC-BLA Activity Dataset: Understanding Flexible Defensive Strategies Under Threat. Sci Data 2024; 11:861. [PMID: 39127738 DOI: 10.1038/s41597-024-03688-0] [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] [Received: 03/05/2024] [Accepted: 07/26/2024] [Indexed: 08/12/2024] Open
Abstract
Responding to threats in the real world demands a sophisticated orchestration of freeze and flight behaviors dynamically modulated by the neural activity. While the medial prefrontal cortex-basolateral amygdala (mPFC-BLA) network is known to play a pivotal role in coordinating these responses, the mechanisms underlying its population dynamics remain vague. As traditional Pavlovian fear conditioning models fall short in encapsulating the breadth of natural escape behaviors, we introduce a novel dataset to bridge this gap, capturing the defensive strategies of mice against a spider robot in a natural-like environment. The adaptive escape behaviors and concurrent mPFC-BLA activity in eight mice were monitored using wireless local field potential (LFP) and video recordings, both individually and in groups. Our data offers a unique avenue to explore the neural dynamics that govern fear- and vigilance-induced threat responses in isolated and social contexts. Supplemented by detailed methodologies and validation, the dataset allows for the analysis of the transient neural oscillatory dynamics, with prospective implications for the fields of neuroscience, robotics, and artificial intelligence.
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Affiliation(s)
- SungJun Cho
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, OX3 7JX, UK
| | - Hio-Been Han
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- The Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, 43 Vassar Street, Cambridge, MA, 02139, USA
- School of Convergence, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea
| | - DaYoung Jung
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Biotechnology, Korea University, Seoul, 02841, Republic of Korea
| | - Jisoo Kim
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea
- Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, CB2 3EG, UK
| | - Jee Hyun Choi
- Computational Cognitive & Systems Neuroscience Laboratory, Brain Science Institute, Korea Institute of Science and Technology, Seoul, 02792, Republic of Korea.
- Division of Bio-Medical Science & Technology, Korea University of Science and Technology, Daejeon, 34113, Republic of Korea.
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3
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Spyropoulos G, Schneider M, van Kempen J, Gieselmann MA, Thiele A, Vinck M. Distinct feedforward and feedback pathways for cell-type specific attention effects. Neuron 2024; 112:2423-2434.e7. [PMID: 38759641 DOI: 10.1016/j.neuron.2024.04.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 02/12/2024] [Accepted: 04/17/2024] [Indexed: 05/19/2024]
Abstract
Selective attention is thought to depend on enhanced firing activity in extrastriate areas. Theories suggest that this enhancement depends on selective inter-areal communication via gamma (30-80 Hz) phase-locking. To test this, we simultaneously recorded from different cell types and cortical layers of macaque V1 and V4. We find that while V1-V4 gamma phase-locking between local field potentials increases with attention, the V1 gamma rhythm does not engage V4 excitatory-neurons, but only fast-spiking interneurons in L4 of V4. By contrast, attention enhances V4 spike-rates in both excitatory and inhibitory cells, most strongly in L2/3. The rate increase in L2/3 of V4 precedes V1 in time. These findings suggest enhanced signal transmission with attention does not depend on inter-areal gamma phase-locking and show that the endogenous gamma rhythm has cell-type- and layer-specific effects on downstream target areas. Similar findings were made in the mouse visual system, based on opto-tagging of identified interneurons.
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Affiliation(s)
- Georgios Spyropoulos
- 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; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands
| | - Jochem van Kempen
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | | | - Alexander Thiele
- Biosciences Institute, Newcastle University, Newcastle upon Tyne NE1 7RU, UK
| | - 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 Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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4
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Fukushima M, Leibnitz K. Effects of packetization on communication dynamics in brain networks. Netw Neurosci 2024; 8:418-436. [PMID: 38952819 PMCID: PMC11142457 DOI: 10.1162/netn_a_00360] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 01/18/2024] [Indexed: 07/03/2024] Open
Abstract
Computational studies in network neuroscience build models of communication dynamics in the connectome that help us understand the structure-function relationships of the brain. In these models, the dynamics of cortical signal transmission in brain networks are approximated with simple propagation strategies such as random walks and shortest path routing. Furthermore, the signal transmission dynamics in brain networks can be associated with the switching architectures of engineered communication systems (e.g., message switching and packet switching). However, it has been unclear how propagation strategies and switching architectures are related in models of brain network communication. Here, we investigate the effects of the difference between packet switching and message switching (i.e., whether signals are packetized or not) on the transmission completion time of propagation strategies when simulating signal propagation in mammalian brain networks. The results show that packetization in the connectome with hubs increases the time of the random walk strategy and does not change that of the shortest path strategy, but decreases that of more plausible strategies for brain networks that balance between communication speed and information requirements. This finding suggests an advantage of packet-switched communication in the connectome and provides new insights into modeling the communication dynamics in brain networks.
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Affiliation(s)
- Makoto Fukushima
- Graduate School of Advanced Science and Engineering, Hiroshima University, Hiroshima, Japan
| | - Kenji Leibnitz
- Center for Information and Neural Networks, National Institute of Information and Communications Technology, Osaka, Japan
- Graduate School of Information Science and Technology, Osaka University, Osaka, Japan
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5
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Lundqvist M, Miller EK, Nordmark J, Liljefors J, Herman P. Beta: bursts of cognition. Trends Cogn Sci 2024; 28:662-676. [PMID: 38658218 DOI: 10.1016/j.tics.2024.03.010] [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: 09/11/2023] [Revised: 03/11/2024] [Accepted: 03/20/2024] [Indexed: 04/26/2024]
Abstract
Beta oscillations are linked to the control of goal-directed processing of sensory information and the timing of motor output. Recent evidence demonstrates they are not sustained but organized into intermittent high-power bursts mediating timely functional inhibition. This implies there is a considerable moment-to-moment variation in the neural dynamics supporting cognition. Beta bursts thus offer new opportunities for studying how sensory inputs are selectively processed, reshaped by inhibitory cognitive operations and ultimately result in motor actions. Recent method advances reveal diversity in beta bursts that provide deeper insights into their function and the underlying neural circuit activity motifs. We propose that brain-wide, spatiotemporal patterns of beta bursting reflect various cognitive operations and that their dynamics reveal nonlinear aspects of cortical processing.
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Affiliation(s)
- Mikael Lundqvist
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden; The Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Earl K Miller
- The Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jonatan Nordmark
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
| | - Johan Liljefors
- Division of Psychology, Department of Clinical Neuroscience, Karolinska Institutet, Solna, Sweden
| | - Pawel Herman
- School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden; Digital Futures, KTH Royal Institute of Technology, Stockholm, Sweden
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6
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Combrisson E, Basanisi R, Gueguen MCM, Rheims S, Kahane P, Bastin J, Brovelli A. Neural interactions in the human frontal cortex dissociate reward and punishment learning. eLife 2024; 12:RP92938. [PMID: 38941238 PMCID: PMC11213568 DOI: 10.7554/elife.92938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/30/2024] Open
Abstract
How human prefrontal and insular regions interact while maximizing rewards and minimizing punishments is unknown. Capitalizing on human intracranial recordings, we demonstrate that the functional specificity toward reward or punishment learning is better disentangled by interactions compared to local representations. Prefrontal and insular cortices display non-selective neural populations to rewards and punishments. Non-selective responses, however, give rise to context-specific interareal interactions. We identify a reward subsystem with redundant interactions between the orbitofrontal and ventromedial prefrontal cortices, with a driving role of the latter. In addition, we find a punishment subsystem with redundant interactions between the insular and dorsolateral cortices, with a driving role of the insula. Finally, switching between reward and punishment learning is mediated by synergistic interactions between the two subsystems. These results provide a unifying explanation of distributed cortical representations and interactions supporting reward and punishment learning.
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Affiliation(s)
- Etienne Combrisson
- Institut de Neurosciences de la Timone, Aix Marseille UniversitéMarseilleFrance
| | - Ruggero Basanisi
- Institut de Neurosciences de la Timone, Aix Marseille UniversitéMarseilleFrance
| | - Maelle CM Gueguen
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut NeurosciencesGrenobleFrance
| | - Sylvain Rheims
- Department of Functional Neurology and Epileptology, Hospices Civils de Lyon and University of LyonLyonFrance
| | - Philippe Kahane
- Univ. Grenoble Alpes, Inserm, U1216, CHU Grenoble Alpes, Grenoble Institut NeurosciencesGrenobleFrance
| | - Julien Bastin
- Univ. Grenoble Alpes, Inserm, U1216, Grenoble Institut NeurosciencesGrenobleFrance
| | - Andrea Brovelli
- Institut de Neurosciences de la Timone, Aix Marseille UniversitéMarseilleFrance
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7
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Holt CJ, Miller KD, Ahmadian Y. The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations. PLoS Comput Biol 2024; 20:e1012190. [PMID: 38935792 PMCID: PMC11236182 DOI: 10.1371/journal.pcbi.1012190] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 07/10/2024] [Accepted: 05/23/2024] [Indexed: 06/29/2024] Open
Abstract
When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.
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Affiliation(s)
- Caleb J Holt
- Department of Physics, Institute of Neuroscience, University of Oregon, Eugene, Oregon, United States of America
| | - Kenneth D Miller
- Deptartment of Neuroscience, Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, College of Physicians and Surgeons, and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, New York, New York, United States of America
| | - Yashar Ahmadian
- Department of Engineering, Computational and Biological Learning Lab, University of Cambridge, Cambridge, United Kingdom
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8
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Ni S, Harris B, Gong P. Distributed and dynamical communication: a mechanism for flexible cortico-cortical interactions and its functional roles in visual attention. Commun Biol 2024; 7:550. [PMID: 38719883 PMCID: PMC11078951 DOI: 10.1038/s42003-024-06228-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 04/22/2024] [Indexed: 05/12/2024] Open
Abstract
Perceptual and cognitive processing relies on flexible communication among cortical areas; however, the underlying neural mechanism remains unclear. Here we report a mechanism based on the realistic spatiotemporal dynamics of propagating wave patterns in neural population activity. Using a biophysically plausible, multiarea spiking neural circuit model, we demonstrate that these wave patterns, characterized by their rich and complex dynamics, can account for a wide variety of empirically observed neural processes. The coordinated interactions of these wave patterns give rise to distributed and dynamic communication (DDC) that enables flexible and rapid routing of neural activity across cortical areas. We elucidate how DDC unifies the previously proposed oscillation synchronization-based and subspace-based views of interareal communication, offering experimentally testable predictions that we validate through the analysis of Allen Institute Neuropixels data. Furthermore, we demonstrate that DDC can be effectively modulated during attention tasks through the interplay of neuromodulators and cortical feedback loops. This modulation process explains many neural effects of attention, underscoring the fundamental functional role of DDC in cognition.
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Affiliation(s)
- Shencong Ni
- School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Brendan Harris
- School of Physics, University of Sydney, Sydney, NSW, Australia
| | - Pulin Gong
- School of Physics, University of Sydney, Sydney, NSW, Australia.
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9
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Rhamidda SL, Girardi-Schappo M, Kinouchi O. Optimal input reverberation and homeostatic self-organization toward the edge of synchronization. CHAOS (WOODBURY, N.Y.) 2024; 34:053127. [PMID: 38767461 DOI: 10.1063/5.0202743] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 04/25/2024] [Indexed: 05/22/2024]
Abstract
Transient or partial synchronization can be used to do computations, although a fully synchronized network is sometimes related to the onset of epileptic seizures. Here, we propose a homeostatic mechanism that is capable of maintaining a neuronal network at the edge of a synchronization transition, thereby avoiding the harmful consequences of a fully synchronized network. We model neurons by maps since they are dynamically richer than integrate-and-fire models and more computationally efficient than conductance-based approaches. We first describe the synchronization phase transition of a dense network of neurons with different tonic spiking frequencies coupled by gap junctions. We show that at the transition critical point, inputs optimally reverberate through the network activity through transient synchronization. Then, we introduce a local homeostatic dynamic in the synaptic coupling and show that it produces a robust self-organization toward the edge of this phase transition. We discuss the potential biological consequences of this self-organization process, such as its relation to the Brain Criticality hypothesis, its input processing capacity, and how its malfunction could lead to pathological synchronization and the onset of seizure-like activity.
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Affiliation(s)
- Sue L Rhamidda
- Departamento de Física, FFCLRP, Universidade de São Paulo, Ribeirão Preto, SP 14040-901, Brazil
| | - Mauricio Girardi-Schappo
- Departamento de Física, Universidade Federal de Santa Catarina, Florianópolis, SC 88040-900, Brazil
| | - Osame Kinouchi
- Departamento de Física, FFCLRP, Universidade de São Paulo, Ribeirão Preto, SP 14040-901, Brazil
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10
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Fontenele AJ, Sooter JS, Norman VK, Gautam SH, Shew WL. Low-dimensional criticality embedded in high-dimensional awake brain dynamics. SCIENCE ADVANCES 2024; 10:eadj9303. [PMID: 38669340 PMCID: PMC11051676 DOI: 10.1126/sciadv.adj9303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/26/2024] [Indexed: 04/28/2024]
Abstract
Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. We offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality-a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescales agrees with established theory of critical dynamics. Our results suggest that the cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.
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11
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Lewis CM, Wunderle T, Fries P. Top-down modulation of visual cortical stimulus encoding and gamma independent of firing rates. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.11.589006. [PMID: 38645050 PMCID: PMC11030389 DOI: 10.1101/2024.04.11.589006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/23/2024]
Abstract
Neurons in primary visual cortex integrate sensory input with signals reflecting the animal's internal state to support flexible behavior. Internal variables, such as expectation, attention, or current goals, are imposed in a top-down manner via extensive feedback projections from higher-order areas. We optogenetically activated a high-order visual area, area 21a, in the lightly anesthetized cat (OptoTD), while recording from neuronal populations in V1. OptoTD induced strong, up to several fold, changes in gamma-band synchronization together with much smaller changes in firing rate, and the two effects showed no correlation. OptoTD effects showed specificity for the features of the simultaneously presented visual stimuli. OptoTD-induced changes in gamma synchronization, but not firing rates, were predictive of simultaneous changes in the amount of encoded stimulus information. Our findings suggest that one important role of top-down signals is to modulate synchronization and the information encoded by populations of sensory neurons.
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12
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Papo D, Buldú JM. Does the brain behave like a (complex) network? I. Dynamics. Phys Life Rev 2024; 48:47-98. [PMID: 38145591 DOI: 10.1016/j.plrev.2023.12.006] [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: 12/08/2023] [Accepted: 12/10/2023] [Indexed: 12/27/2023]
Abstract
Graph theory is now becoming a standard tool in system-level neuroscience. However, endowing observed brain anatomy and dynamics with a complex network structure does not entail that the brain actually works as a network. Asking whether the brain behaves as a network means asking whether network properties count. From the viewpoint of neurophysiology and, possibly, of brain physics, the most substantial issues a network structure may be instrumental in addressing relate to the influence of network properties on brain dynamics and to whether these properties ultimately explain some aspects of brain function. Here, we address the dynamical implications of complex network, examining which aspects and scales of brain activity may be understood to genuinely behave as a network. To do so, we first define the meaning of networkness, and analyse some of its implications. We then examine ways in which brain anatomy and dynamics can be endowed with a network structure and discuss possible ways in which network structure may be shown to represent a genuine organisational principle of brain activity, rather than just a convenient description of its anatomy and dynamics.
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Affiliation(s)
- D Papo
- Department of Neuroscience and Rehabilitation, Section of Physiology, University of Ferrara, Ferrara, Italy; Center for Translational Neurophysiology, Fondazione Istituto Italiano di Tecnologia, Ferrara, Italy.
| | - J M Buldú
- Complex Systems Group & G.I.S.C., Universidad Rey Juan Carlos, Madrid, Spain
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13
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Douchamps V, di Volo M, Torcini A, Battaglia D, Goutagny R. Gamma oscillatory complexity conveys behavioral information in hippocampal networks. Nat Commun 2024; 15:1849. [PMID: 38418832 PMCID: PMC10902292 DOI: 10.1038/s41467-024-46012-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 02/09/2024] [Indexed: 03/02/2024] Open
Abstract
The hippocampus and entorhinal cortex exhibit rich oscillatory patterns critical for cognitive functions. In the hippocampal region CA1, specific gamma-frequency oscillations, timed at different phases of the ongoing theta rhythm, are hypothesized to facilitate the integration of information from varied sources and contribute to distinct cognitive processes. Here, we show that gamma elements -a multidimensional characterization of transient gamma oscillatory episodes- occur at any frequency or phase relative to the ongoing theta rhythm across all CA1 layers in male mice. Despite their low power and stochastic-like nature, individual gamma elements still carry behavior-related information and computational modeling suggests that they reflect neuronal firing. Our findings challenge the idea of rigid gamma sub-bands, showing that behavior shapes ensembles of irregular gamma elements that evolve with learning and depend on hippocampal layers. Widespread gamma diversity, beyond randomness, may thus reflect complexity, likely functional but invisible to classic average-based analyses.
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Affiliation(s)
- Vincent Douchamps
- Université de Strasbourg, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), CNRS, UMR 7364, Strasbourg, France
| | - Matteo di Volo
- Université Claude Bernard Lyon 1, Institut National de la Santé et de la Recherche Médicale, Stem Cell and Brain Research Institute, U1208, Bron, France
- CY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation (LPTM), CNRS, UMR 8089, 95302, Cergy-Pontoise, France
| | - Alessandro Torcini
- CY Cergy Paris Université, Laboratoire de Physique Théorique et Modélisation (LPTM), CNRS, UMR 8089, 95302, Cergy-Pontoise, France
- CNR - Consiglio Nazionale delle Ricerche, Istituto dei Sistemi Complessi, via Madonna del Piano 10, 50019, Sesto Fiorentino, Italy
| | - Demian Battaglia
- Université de Strasbourg, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), CNRS, UMR 7364, Strasbourg, France.
- Aix-Marseille Université, Institut de Neurosciences des Systèmes (INS), INSERM, UMR 1106, Marseille, France.
- University of Strasbourg Institute for Advanced Studies (USIAS), Strasbourg, France.
| | - Romain Goutagny
- Université de Strasbourg, Laboratoire de Neurosciences Cognitives et Adaptatives (LNCA), CNRS, UMR 7364, Strasbourg, France.
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14
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Schwock F, Bloch J, Khateeb K, Zhou J, Atlas L, Yazdan-Shahmorad A. Inferring Neural Communication Dynamics from Field Potentials Using Graph Diffusion Autoregression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582177. [PMID: 38464147 PMCID: PMC10925120 DOI: 10.1101/2024.02.26.582177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Estimating dynamic network communication is attracting increased attention, spurred by rapid advancements in multi-site neural recording technologies and efforts to better understand cognitive processes. Yet, traditional methods, which infer communication from statistical dependencies among distributed neural recordings, face core limitations: they do not model neural interactions in a biologically plausible way, neglect spatial information from the recording setup, and yield predominantly static estimates that cannot capture rapid changes in the brain. To address these issues, we introduce a graph diffusion autoregressive model. Designed for distributed field potential recordings, our model combines vector autoregression with a network communication process to produce a high-resolution communication signal. We successfully validated the model on simulated neural activity and recordings from subdural and intracortical micro-electrode arrays placed in macaque sensorimotor cortex demonstrating its ability to describe rapid communication dynamics induced by optogenetic stimulation, changes in resting state communication, and the trial-by-trial variability during a reach task.
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Affiliation(s)
- Felix Schwock
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA
- Primate Research Center, Seattle, WA, USA
| | - Julien Bloch
- Department of Bioengineering, University of Washington, Seattle, WA, USA. Washington National
- Primate Research Center, Seattle, WA, USA
| | - Karam Khateeb
- Department of Bioengineering, University of Washington, Seattle, WA, USA. Washington National
- Primate Research Center, Seattle, WA, USA
| | - Jasmine Zhou
- Department of Bioengineering, University of Washington, Seattle, WA, USA. Washington National
- Primate Research Center, Seattle, WA, USA
| | - Les Atlas
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA
| | - Azadeh Yazdan-Shahmorad
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA. Washington National
- Primate Research Center, Seattle, WA, USA
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15
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Yamaguchi YY, Terada Y. Reconstruction of phase dynamics from macroscopic observations based on linear and nonlinear response theories. Phys Rev E 2024; 109:024217. [PMID: 38491619 DOI: 10.1103/physreve.109.024217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 01/22/2024] [Indexed: 03/18/2024]
Abstract
We propose a method to reconstruct the phase dynamics in rhythmical interacting systems from macroscopic responses to weak inputs by developing linear and nonlinear response theories, which predict the responses in a given system. By solving an inverse problem, the method infers an unknown system: the natural frequency distribution, the coupling function, and the time delay which is inevitable in real systems. In contrast to previous methods, our method requires neither strong invasiveness nor microscopic observations. We demonstrate that the method reconstructs two phase systems from observed responses accurately. The qualitative methodological advantages demonstrated by our quantitative numerical examinations suggest its broad applicability in various fields, including brain systems, which are often observed through macroscopic signals such as electroencephalograms and functional magnetic response imaging.
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Affiliation(s)
| | - Yu Terada
- Department of Neurobiology, University of California San Diego, La Jolla, California 92093, USA
- Institute for Physics of Intelligence, Department of Physics, Graduate School of Science, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
- Laboratory for Neural Computation and Adaptation, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
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16
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Aboutorabi E, Baloni Ray S, Kaping D, Shahbazi F, Treue S, Esghaei M. Phase of neural oscillations as a reference frame for attention-based routing in visual cortex. Prog Neurobiol 2024; 233:102563. [PMID: 38142770 DOI: 10.1016/j.pneurobio.2023.102563] [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: 06/21/2023] [Revised: 12/04/2023] [Accepted: 12/20/2023] [Indexed: 12/26/2023]
Abstract
Selective attention allows the brain to efficiently process the image projected onto the retina, selectively focusing neural processing resources on behaviorally relevant visual information. While previous studies have documented the crucial role of the action potential rate of single neurons in relaying such information, little is known about how the activity of single neurons relative to their neighboring network contributes to the efficient representation of attended stimuli and transmission of this information to downstream areas. Here, we show in the dorsal visual pathway of monkeys (medial superior temporal area) that neurons fire spikes preferentially at a specific phase of the ongoing population beta (∼20 Hz) oscillations of the surrounding local network. This preferred spiking phase shifts towards a later phase when monkeys selectively attend towards (rather than away from) the receptive field of the neuron. This shift of the locking phase is positively correlated with the speed at which animals report a visual change. Furthermore, our computational modeling suggests that neural networks can manipulate the preferred phase of coupling by imposing differential synaptic delays on postsynaptic potentials. This distinction between the locking phase of neurons activated by the spatially attended stimulus vs. that of neurons activated by the unattended stimulus, may enable the neural system to discriminate relevant from irrelevant sensory inputs and consequently filter out distracting stimuli information by aligning the spikes which convey relevant/irrelevant information to distinct phases linked to periods of better/worse perceptual sensitivity for higher cortices. This strategy may be used to reserve the narrow windows of highest perceptual efficacy to the processing of the most behaviorally relevant information, ensuring highly efficient responses to attended sensory events.
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Affiliation(s)
- Ehsan Aboutorabi
- Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada; Robarts Research Institute, Western University, London, Ontario, Canada
| | - Sonia Baloni Ray
- Indraprastha Institute of Information Technology, New Delhi, India
| | - Daniel Kaping
- Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Farhad Shahbazi
- Department of Physics, Isfahan University of Technology, Isfahan, Iran
| | - Stefan Treue
- Cognitive Neuroscience Laboratory, German Primate Center - Leibniz Institute for Primate Research, Goettingen, Germany; Faculty for Biology and Psychology, University of Goettingen, Germany; Leibniz ScienceCampus Primate Cognition, Goettingen, Germany
| | - Moein Esghaei
- Cognitive Neuroscience Laboratory, German Primate Center - Leibniz Institute for Primate Research, Goettingen, Germany; Westa Higher Education Center, Karaj, Iran.
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17
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Nesse WH, Clark KL, Noudoost B. Information representation in an oscillating neural field model modulated by working memory signals. Front Comput Neurosci 2024; 17:1253234. [PMID: 38303900 PMCID: PMC10830742 DOI: 10.3389/fncom.2023.1253234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 11/27/2023] [Indexed: 02/03/2024] Open
Abstract
We study how stimulus information can be represented in the dynamical signatures of an oscillatory model of neural activity-a model whose activity can be modulated by input akin to signals involved in working memory (WM). We developed a neural field model, tuned near an oscillatory instability, in which the WM-like input can modulate the frequency and amplitude of the oscillation. Our neural field model has a spatial-like domain in which an input that preferentially targets a point-a stimulus feature-on the domain will induce feature-specific activity changes. These feature-specific activity changes affect both the mean rate of spikes and the relative timing of spiking activity to the global field oscillation-the phase of the spiking activity. From these two dynamical signatures, we define both a spike rate code and an oscillatory phase code. We assess the performance of these two codes to discriminate stimulus features using an information-theoretic analysis. We show that global WM input modulations can enhance phase code discrimination while simultaneously reducing rate code discrimination. Moreover, we find that the phase code performance is roughly two orders of magnitude larger than that of the rate code defined for the same model solutions. The results of our model have applications to sensory areas of the brain, to which prefrontal areas send inputs reflecting the content of WM. These WM inputs to sensory areas have been established to induce oscillatory changes similar to our model. Our model results suggest a mechanism by which WM signals may enhance sensory information represented in oscillatory activity beyond the comparatively weak representations based on the mean rate activity.
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Affiliation(s)
- William H. Nesse
- Department of Mathematics, University of Utah, Salt Lake City, UT, United States
| | - Kelsey L. Clark
- Department of Ophthalmology, University of Utah, Salt Lake City, UT, United States
| | - Behrad Noudoost
- Department of Ophthalmology, University of Utah, Salt Lake City, UT, United States
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18
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Voges N, Lima V, Hausmann J, Brovelli A, Battaglia D. Decomposing Neural Circuit Function into Information Processing Primitives. J Neurosci 2024; 44:e0157232023. [PMID: 38050070 PMCID: PMC10866194 DOI: 10.1523/jneurosci.0157-23.2023] [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: 01/27/2023] [Revised: 09/01/2023] [Accepted: 09/19/2023] [Indexed: 12/06/2023] Open
Abstract
It is challenging to measure how specific aspects of coordinated neural dynamics translate into operations of information processing and, ultimately, cognitive functions. An obstacle is that simple circuit mechanisms-such as self-sustained or propagating activity and nonlinear summation of inputs-do not directly give rise to high-level functions. Nevertheless, they already implement simple the information carried by neural activity. Here, we propose that distinct functions, such as stimulus representation, working memory, or selective attention, stem from different combinations and types of low-level manipulations of information or information processing primitives. To test this hypothesis, we combine approaches from information theory with simulations of multi-scale neural circuits involving interacting brain regions that emulate well-defined cognitive functions. Specifically, we track the information dynamics emergent from patterns of neural dynamics, using quantitative metrics to detect where and when information is actively buffered, transferred or nonlinearly merged, as possible modes of low-level processing (storage, transfer and modification). We find that neuronal subsets maintaining representations in working memory or performing attentional gain modulation are signaled by their boosted involvement in operations of information storage or modification, respectively. Thus, information dynamic metrics, beyond detecting which network units participate in cognitive processing, also promise to specify how and when they do it, that is, through which type of primitive computation, a capability that may be exploited for the analysis of experimental recordings.
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Affiliation(s)
- Nicole Voges
- Institut de Neurosciences de La Timone, UMR 7289, CNRS, Aix-Marseille Université, Marseille 13005, France
- Institute for Language, Communication and the Brain (ILCB), Aix-Marseille Université, Marseille 13005, France
| | - Vinicius Lima
- Institut de Neurosciences des Systèmes (INS), UMR 1106, Aix-Marseille Université, Marseille 13005, France
| | - Johannes Hausmann
- R&D Department, Hyland Switzerland Sarl, Corcelles NE 2035, Switzerland
| | - Andrea Brovelli
- Institut de Neurosciences de La Timone, UMR 7289, CNRS, Aix-Marseille Université, Marseille 13005, France
- Institute for Language, Communication and the Brain (ILCB), Aix-Marseille Université, Marseille 13005, France
| | - Demian Battaglia
- Institute for Language, Communication and the Brain (ILCB), Aix-Marseille Université, Marseille 13005, France
- Institut de Neurosciences des Systèmes (INS), UMR 1106, Aix-Marseille Université, Marseille 13005, France
- University of Strasbourg Institute for Advanced Studies (USIAS), Strasbourg 67000, France
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19
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Di Dona G, Ronconi L. Beta oscillations in vision: a (preconscious) neural mechanism for the dorsal visual stream? Front Psychol 2023; 14:1296483. [PMID: 38155693 PMCID: PMC10753839 DOI: 10.3389/fpsyg.2023.1296483] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Accepted: 11/15/2023] [Indexed: 12/30/2023] Open
Abstract
Neural oscillations in alpha (8-12 Hz) and beta (13-30 Hz) frequency bands are thought to reflect feedback/reentrant loops and large-scale cortical interactions. In the last decades a main effort has been made in linking perception with alpha-band oscillations, with converging evidence showing that alpha oscillations have a key role in the temporal and featural binding of visual input, configuring the alpha rhythm a key determinant of conscious visual experience. Less attention has been historically dedicated to link beta oscillations and visual processing. Nonetheless, increasing studies report that task conditions that require to segregate/integrate stimuli in space, to disentangle local/global shapes, to spatially reorganize visual inputs, and to achieve motion perception or form-motion integration, rely on the activity of beta oscillations, with a main hub in parietal areas. In the present review, we summarize the evidence linking oscillations within the beta band and visual perception. We propose that beta oscillations represent a neural code that supports the functionality of the magnocellular-dorsal (M-D) visual pathway, serving as a fast primary neural code to exert top-down influences on the slower parvocellular-ventral visual pathway activity. Such M-D-related beta activity is proposed to act mainly pre-consciously, providing the spatial coordinates of vision and guiding the conscious extraction of objects identity that are achieved with slower alpha rhythms in ventral areas. Finally, within this new theoretical framework, we discuss the potential role of M-D-related beta oscillations in visuo-spatial attention, oculo-motor behavior and reading (dis)abilities.
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Affiliation(s)
- Giuseppe Di Dona
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy
| | - Luca Ronconi
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy
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20
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Dimitriadis SI, Routley B, Linden DEJ, Singh KD. Multiplexity of human brain oscillations as a personal brain signature. Hum Brain Mapp 2023; 44:5624-5640. [PMID: 37668332 PMCID: PMC10619372 DOI: 10.1002/hbm.26466] [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: 02/06/2023] [Revised: 07/11/2023] [Accepted: 08/08/2023] [Indexed: 09/06/2023] Open
Abstract
Human individuality is likely underpinned by the constitution of functional brain networks that ensure consistency of each person's cognitive and behavioral profile. These functional networks should, in principle, be detectable by noninvasive neurophysiology. We use a method that enables the detection of dominant frequencies of the interaction between every pair of brain areas at every temporal segment of the recording period, the dominant coupling modes (DoCM). We apply this method to brain oscillations, measured with magnetoencephalography (MEG) at rest in two independent datasets, and show that the spatiotemporal evolution of DoCMs constitutes an individualized brain fingerprint. Based on this successful fingerprinting we suggest that DoCMs are important targets for the investigation of neural correlates of individual psychological parameters and can provide mechanistic insight into the underlying neurophysiological processes, as well as their disturbance in brain diseases.
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Affiliation(s)
- Stavros I. Dimitriadis
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of MedicineCardiff UniversityCardiffWalesUK
- Department of Clinical Psychology and PsychobiologyUniversity of BarcelonaBarcelonaSpain
| | - B. Routley
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
| | - David E. J. Linden
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, School of MedicineCardiff UniversityCardiffWalesUK
- School for Mental Health and Neuroscience, Faculty of Health Medicine and Life SciencesMaastricht UniversityMaastrichtThe Netherlands
| | - Krish D. Singh
- Cardiff University Brain Research Imaging Centre, School of PsychologyCardiff UniversityCardiffWalesUK
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21
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Schmidt R, Rose J, Muralidharan V. Transient oscillations as computations for cognition: Analysis, modeling and function. Curr Opin Neurobiol 2023; 83:102796. [PMID: 37804772 DOI: 10.1016/j.conb.2023.102796] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 08/31/2023] [Accepted: 09/06/2023] [Indexed: 10/09/2023]
Abstract
Our view of neural oscillations is currently changing. The dominant picture of sustained oscillations is now often replaced by transient oscillations occurring in bursts. This phenomenon seems to be quite comprehensive, as it has been reported for different oscillation frequencies, including the theta, beta, and gamma bands, as well as cortical and subcortical regions in a variety of cognitive tasks and species. Here we review recent developments in their analysis, computational modeling, and functional roles. For the analysis of transient oscillations methods using lagged coherence and Hidden Markov Models have been developed and applied in recent studies to ascertain their transient nature and study their contribution to cognitive functions. Furthermore, computational models have been developed that account for their stochastic nature, which poses interesting functional constraints. Finally, as transient oscillations have been observed across many species, they are likely of functional significance and we consider challenges in characterizing their function.
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Affiliation(s)
- Robert Schmidt
- Institute for Neural Computation, Faculty of Computer Science, Ruhr-University Bochum, Germany.
| | - Jonas Rose
- Neural Basis of Learning, Institute of Cognitive Neuroscience, Faculty of Psychology, Ruhr University Bochum, Germany
| | - Vignesh Muralidharan
- Center for Brain Science and Application, School of AI and Data Science, Indian Institute of Technology Jodhpur, India. https://twitter.com/vigmdhrn
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22
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Romano A, Troisi Lopez E, Cipriano L, Liparoti M, Minino R, Polverino A, Cavaliere C, Aiello M, Granata C, Sorrentino G, Sorrentino P. Topological changes of fast large-scale brain dynamics in mild cognitive impairment predict early memory impairment: a resting-state, source reconstructed, magnetoencephalography study. Neurobiol Aging 2023; 132:36-46. [PMID: 37717553 DOI: 10.1016/j.neurobiolaging.2023.08.003] [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: 11/22/2022] [Revised: 08/08/2023] [Accepted: 08/10/2023] [Indexed: 09/19/2023]
Abstract
Functional connectivity has been used as a framework to investigate widespread brain interactions underlying cognitive deficits in mild cognitive impairment (MCI). However, many functional connectivity metrics focus on the average of the periodic activities, disregarding the aperiodic bursts of activity (i.e., the neuronal avalanches) characterizing the large-scale dynamic activities of the brain. Here, we apply the recently described avalanche transition matrix framework to source-reconstructed magnetoencephalography signals in a cohort of 32 MCI patients and 32 healthy controls to describe the spatio-temporal features of neuronal avalanches and explore their topological properties. Our results showed that MCI patients showed a more centralized network (as assessed by higher values of the degree divergence and leaf fraction) as compared to healthy controls. Furthermore, we found that the degree divergence (in the theta band) was predictive of hippocampal memory impairment. These findings highlight the role of the changes of aperiodic bursts in clinical conditions and may contribute to a more thorough phenotypical assessment of patients.
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Affiliation(s)
- Antonella Romano
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Emahnuel Troisi Lopez
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Lorenzo Cipriano
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Marianna Liparoti
- Department of Developmental and Social Psychology, University of Rome "La Sapienza", Rome, Italy
| | - Roberta Minino
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy
| | - Arianna Polverino
- Institute of Diagnosis and Treatment, Hermitage Capodimonte, Naples, Italy
| | - Carlo Cavaliere
- IRCCS SYNLAB-SDN, Naples Via Emanuele Gianturco, Naples, Italy
| | - Marco Aiello
- IRCCS SYNLAB-SDN, Naples Via Emanuele Gianturco, Naples, Italy
| | - Carmine Granata
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy
| | - Giuseppe Sorrentino
- Department of Motor and Wellness Sciences, University of Naples "Parthenope", Naples, Italy; Institute of Diagnosis and Treatment, Hermitage Capodimonte, Naples, Italy; Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy.
| | - Pierpaolo Sorrentino
- Institute of Applied Sciences and Intelligent Systems, National Research Council, Pozzuoli, Italy; Institut de Neurosciences des Systèmes, Inserm, INS, Aix-Marseille University, Marseille, France
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23
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Munn BR, Müller EJ, Aru J, Whyte CJ, Gidon A, Larkum ME, Shine JM. A thalamocortical substrate for integrated information via critical synchronous bursting. Proc Natl Acad Sci U S A 2023; 120:e2308670120. [PMID: 37939085 PMCID: PMC10655573 DOI: 10.1073/pnas.2308670120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Accepted: 09/21/2023] [Indexed: 11/10/2023] Open
Abstract
Understanding the neurobiological mechanisms underlying consciousness remains a significant challenge. Recent evidence suggests that the coupling between distal-apical and basal-somatic dendrites in thick-tufted layer 5 pyramidal neurons (L5PN), regulated by the nonspecific-projecting thalamus, is crucial for consciousness. Yet, it is uncertain whether this thalamocortical mechanism can support emergent signatures of consciousness, such as integrated information. To address this question, we constructed a biophysical network of dual-compartment thick-tufted L5PN, with dendrosomatic coupling controlled by thalamic inputs. Our findings demonstrate that integrated information is maximized when nonspecific thalamic inputs drive the system into a regime of time-varying synchronous bursting. Here, the system exhibits variable spiking dynamics with broad pairwise correlations, supporting the enhanced integrated information. Further, the observed peak in integrated information aligns with criticality signatures and empirically observed layer 5 pyramidal bursting rates. These results suggest that the thalamocortical core of the mammalian brain may be evolutionarily configured to optimize effective information processing, providing a potential neuronal mechanism that integrates microscale theories with macroscale signatures of consciousness.
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Affiliation(s)
- Brandon R. Munn
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
| | - Eli J. Müller
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
| | - Jaan Aru
- Institute of Computer Science, University of Tartu, Tartu51009, Estonia
| | - Christopher J. Whyte
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
| | - Albert Gidon
- Institute of Biology, Humboldt University of Berlin, Berlin10099, Germany
- NeuroCure Center of Excellence, Charité Universitätsmedizin Berlin, Berlin10099, Germany
| | - Matthew E. Larkum
- Institute of Biology, Humboldt University of Berlin, Berlin10099, Germany
- NeuroCure Center of Excellence, Charité Universitätsmedizin Berlin, Berlin10099, Germany
| | - James M. Shine
- Brain and Mind Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney2050, Australia
- Complex Systems, School of Physics, Faculty of Science, University of Sydney, Sydney2050, Australia
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24
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Katsanevaki C, Bastos AM, Cagnan H, Bosman CA, Friston KJ, Fries P. Attentional effects on local V1 microcircuits explain selective V1-V4 communication. Neuroimage 2023; 281:120375. [PMID: 37714390 DOI: 10.1016/j.neuroimage.2023.120375] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 09/10/2023] [Accepted: 09/11/2023] [Indexed: 09/17/2023] Open
Abstract
Selective attention implements preferential routing of attended stimuli, likely through increasing the influence of the respective synaptic inputs on higher-area neurons. As the inputs of competing stimuli converge onto postsynaptic neurons, presynaptic circuits might offer the best target for attentional top-down influences. If those influences enabled presynaptic circuits to selectively entrain postsynaptic neurons, this might explain selective routing. Indeed, when two visual stimuli induce two gamma rhythms in V1, only the gamma induced by the attended stimulus entrains gamma in V4. Here, we modelled induced responses with a Dynamic Causal Model for Cross-Spectral Densities and found that selective entrainment can be explained by attentional modulation of intrinsic V1 connections. Specifically, local inhibition was decreased in the granular input layer and increased in the supragranular output layer of the V1 circuit that processed the attended stimulus. Thus, presynaptic attentional influences and ensuing entrainment were sufficient to mediate selective routing.
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Affiliation(s)
- Christini Katsanevaki
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany.
| | - André M Bastos
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; Department of Psychology and Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN 37240, USA
| | - Hayriye Cagnan
- The Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK; Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford OX1 3TH, UK
| | - Conrado A Bosman
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen 6525 EN, the Netherlands; Swammerdam Institute for Life Sciences, Center for Neuroscience, University of Amsterdam, Amsterdam 1098 XH, the Netherlands
| | - Karl J Friston
- The Wellcome Trust Centre for Neuroimaging, University College London, London WC1N 3AR, UK
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt 60528, Germany; International Max Planck Research School for Neural Circuits, Frankfurt 60438, Germany; Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen 6525 EN, the Netherlands
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25
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Parto-Dezfouli M, Vezoli J, Bosman CA, Fries P. Enhanced behavioral performance through interareal gamma and beta synchronization. Cell Rep 2023; 42:113249. [PMID: 37837620 PMCID: PMC10679823 DOI: 10.1016/j.celrep.2023.113249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Revised: 07/18/2023] [Accepted: 09/26/2023] [Indexed: 10/16/2023] Open
Abstract
Cognitive functioning requires coordination between brain areas. Between visual areas, feedforward gamma synchronization improves behavioral performance. Here, we investigate whether similar principles hold across brain regions and frequency bands, using simultaneous electrocorticographic recordings from 15 areas of two macaque monkeys during performance of a selective attention task. Short behavioral reaction times (RTs), suggesting efficient interareal communication, occurred when occipital areas V1, V2, V4, and DP showed gamma synchronization, and fronto-central areas S1, 5, F1, F2, and F4 showed beta synchronization. For both area clusters and corresponding frequency bands, deviations from the typically observed phase relations increased RTs. Across clusters and frequency bands, good phase relations occurred in a correlated manner specifically when they processed the behaviorally relevant stimulus. Furthermore, the fronto-central cluster exerted a beta-band influence onto the occipital cluster whose strength predicted short RTs. These results suggest that local gamma and beta synchronization and their inter-regional coordination jointly improve behavioral performance.
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Affiliation(s)
- Mohsen Parto-Dezfouli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Conrado Arturo Bosman
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands; Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1090 GE Amsterdam, the Netherlands
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany; Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, the Netherlands.
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26
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Scarpetta S, Morrisi N, Mutti C, Azzi N, Trippi I, Ciliento R, Apicella I, Messuti G, Angiolelli M, Lombardi F, Parrino L, Vaudano AE. Criticality of neuronal avalanches in human sleep and their relationship with sleep macro- and micro-architecture. iScience 2023; 26:107840. [PMID: 37766992 PMCID: PMC10520337 DOI: 10.1016/j.isci.2023.107840] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 06/30/2023] [Accepted: 09/03/2023] [Indexed: 09/29/2023] Open
Abstract
Sleep plays a key role in preserving brain function, keeping brain networks in a state that ensures optimal computation. Empirical evidence indicates that this state is consistent with criticality, where scale-free neuronal avalanches emerge. However, the connection between sleep architecture and brain tuning to criticality remains poorly understood. Here, we characterize the critical behavior of avalanches and study their relationship with sleep macro- and micro-architectures, in particular, the cyclic alternating pattern (CAP). We show that avalanches exhibit robust scaling behaviors, with exponents obeying scaling relations consistent with the mean-field directed percolation universality class. We demonstrate that avalanche dynamics is modulated by the NREM-REM cycles and that, within NREM sleep, avalanche occurrence correlates with CAP activation phases-indicating a potential link between CAP and brain tuning to criticality. The results open new perspectives on the collective dynamics underlying CAP function, and on the relationship between sleep architecture, avalanches, and self-organization to criticality.
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Affiliation(s)
- Silvia Scarpetta
- Department of Physics, University of Salerno, 84084 Fisciano, Italy
- INFN sez. Napoli Gr. Coll. Salerno, 84084 Fisciano, Italy
| | - Niccolò Morrisi
- Nephrology, Dialysis and Transplant Unit, University Hospital of Modena, 41121 Modena, Italy
| | - Carlotta Mutti
- Sleep Disorders Center, Department of Medicine and Surgery, University of Parma, 43121 Parma, Italy
| | - Nicoletta Azzi
- Sleep Disorders Center, Department of Medicine and Surgery, University of Parma, 43121 Parma, Italy
| | - Irene Trippi
- Sleep Disorders Center, Department of Medicine and Surgery, University of Parma, 43121 Parma, Italy
| | - Rosario Ciliento
- Department of Neurology, University of Wisconsin, Madison, WI 53705, USA
| | - Ilenia Apicella
- INFN sez. Napoli Gr. Coll. Salerno, 84084 Fisciano, Italy
- Department of Physics, University of Naples “Federico II”, 80126 Napoli, Italy
| | - Giovanni Messuti
- Department of Physics, University of Salerno, 84084 Fisciano, Italy
- INFN sez. Napoli Gr. Coll. Salerno, 84084 Fisciano, Italy
| | - Marianna Angiolelli
- Department of Physics, University of Salerno, 84084 Fisciano, Italy
- INFN sez. Napoli Gr. Coll. Salerno, 84084 Fisciano, Italy
- Engineering Department, University Campus Bio-Medico of Rome, 00128 Roma, Italy
| | - Fabrizio Lombardi
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
- Department of Biomedical Sciences, University of Padova, Via Ugo Bassi 58B, 35131 Padova, Italy
| | - Liborio Parrino
- Sleep Disorders Center, Department of Medicine and Surgery, University of Parma, 43121 Parma, Italy
| | - Anna Elisabetta Vaudano
- Neurology Unit, Azienda Ospedaliero-Universitaria of Modena, OCB Hospital, 41125 Modena, Italy
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, 41125 Modena, Italy
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27
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Uehara K, Yasuhara M, Koguchi J, Oku T, Shiotani S, Morise M, Furuya S. Brain network flexibility as a predictor of skilled musical performance. Cereb Cortex 2023; 33:10492-10503. [PMID: 37566918 DOI: 10.1093/cercor/bhad298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Revised: 07/25/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
Interactions between the body and the environment are dynamically modulated by upcoming sensory information and motor execution. To adapt to this behavioral state-shift, brain activity must also be flexible and possess a large repertoire of brain networks so as to switch them flexibly. Recently, flexible internal brain communications, i.e. brain network flexibility, have come to be recognized as playing a vital role in integrating various sensorimotor information. Therefore, brain network flexibility is one of the key factors that define sensorimotor skill. However, little is known about how flexible communications within the brain characterize the interindividual variation of sensorimotor skill and trial-by-trial variability within individuals. To address this, we recruited skilled musical performers and used a novel approach that combined multichannel-scalp electroencephalography, behavioral measurements of musical performance, and mathematical approaches to extract brain network flexibility. We found that brain network flexibility immediately before initiating the musical performance predicted interindividual differences in the precision of tone timbre when required for feedback control, but not for feedforward control. Furthermore, brain network flexibility in broad cortical regions predicted skilled musical performance. Our results provide novel evidence that brain network flexibility plays an important role in building skilled sensorimotor performance.
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Affiliation(s)
- Kazumasa Uehara
- Neural Information Dynamics Laboratory, Department of Computer Science and Engineering, Toyohashi University of Technology, Toyohashi, Japan
- Sony Computer Science Laboratories Inc, Tokyo 1410022, Japan
| | - Masaki Yasuhara
- Sony Computer Science Laboratories Inc, Tokyo 1410022, Japan
- Neural Engineering Laboratory, Department of Science of Technology Innovation, Nagaoka University of Technology, Nagaoka, Japan
| | - Junya Koguchi
- Sony Computer Science Laboratories Inc, Tokyo 1410022, Japan
- Graduate School of Advanced Mathematical Sciences, Meiji University, Tokyo, Japan
| | | | | | - Masanori Morise
- Sony Computer Science Laboratories Inc, Tokyo 1410022, Japan
- School of Interdisciplinary Mathematical Sciences, Meiji University, Tokyo, Japan
| | - Shinichi Furuya
- Sony Computer Science Laboratories Inc, Tokyo 1410022, Japan
- NeuroPiano Institute, Kyoto 6008086, Japan
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28
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Jain PB, Nguyen TT, Mináč J, Muller LE, Budzinski RC. Composed solutions of synchronized patterns in multiplex networks of Kuramoto oscillators. CHAOS (WOODBURY, N.Y.) 2023; 33:103128. [PMID: 37844292 DOI: 10.1063/5.0161399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 09/18/2023] [Indexed: 10/18/2023]
Abstract
Networks with different levels of interactions, including multilayer and multiplex networks, can display a rich diversity of dynamical behaviors and can be used to model and study a wide range of systems. Despite numerous efforts to investigate these networks, obtaining mathematical descriptions for the dynamics of multilayer and multiplex systems is still an open problem. Here, we combine ideas and concepts from linear algebra and graph theory with nonlinear dynamics to offer a novel approach to study multiplex networks of Kuramoto oscillators. Our approach allows us to study the dynamics of a large, multiplex network by decomposing it into two smaller systems: one representing the connection scheme within layers (intra-layer), and the other representing the connections between layers (inter-layer). Particularly, we use this approach to compose solutions for multiplex networks of Kuramoto oscillators. These solutions are given by a combination of solutions for the smaller systems given by the intra- and inter-layer systems, and in addition, our approach allows us to study the linear stability of these solutions.
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Affiliation(s)
- Priya B Jain
- Department of Mathematics, Western University, London, Ontario N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Western Academy for Advanced Research, Western University, London, Ontario N6A 3K7, Canada
| | - Tung T Nguyen
- Department of Mathematics, Western University, London, Ontario N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Western Academy for Advanced Research, Western University, London, Ontario N6A 3K7, Canada
| | - Ján Mináč
- Department of Mathematics, Western University, London, Ontario N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Western Academy for Advanced Research, Western University, London, Ontario N6A 3K7, Canada
| | - Lyle E Muller
- Department of Mathematics, Western University, London, Ontario N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Western Academy for Advanced Research, Western University, London, Ontario N6A 3K7, Canada
| | - Roberto C Budzinski
- Department of Mathematics, Western University, London, Ontario N6A 3K7, Canada
- Western Institute for Neuroscience, Western University, London, Ontario N6A 3K7, Canada
- Western Academy for Advanced Research, Western University, London, Ontario N6A 3K7, Canada
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29
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Si H, Sun X. Inter-areal transmission of multiple neural signals through frequency-division-multiplexing communication. Cogn Neurodyn 2023; 17:1153-1165. [PMID: 37786658 PMCID: PMC10542065 DOI: 10.1007/s11571-022-09914-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 10/26/2022] [Accepted: 11/17/2022] [Indexed: 12/03/2022] Open
Abstract
Inter-areal information transmission in the brain cortex relates to cognitive functions. Researches used to pay attention to activity pattern transmission, signals gating, or routing in neuronal networks. However, the underlying mechanism of simultaneous transmission of multiple neural signals in the same channel across networks remains unclear. In this work, we construct a two-layer feedforward neuronal network (sender-receiver) with each layer's intrinsic rhythms consisting of slow- (low-frequency) and fast- gamma rhythms (high-frequency), investigating how to realize simultaneous transmission of multiple signals in neuronal systems. With the aid of resonance and frequency analysis, it is shown that low- and high-frequency signals can be transmitted simultaneously in such a feedforward network through frequency division multiplexing (FDM) communication. The transmission performance is related to the local resonance, connectivity, as well as background noise. Moreover, low- and high-frequency signals can also be gated or selected with appropriate adjustments of recurrent connection strength and delay, and background noise. Our model might provide a novel insight into the underlying mechanism of complex signals communication between different cortex areas.
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Affiliation(s)
- Hao Si
- School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876 China
| | - Xiaojuan Sun
- School of Science, Beijing University of Posts and Telecommunications, Beijing, 100876 China
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30
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Clawson W, Waked B, Madec T, Ghestem A, Quilichini PP, Battaglia D, Bernard C. Perturbed Information Processing Complexity in Experimental Epilepsy. J Neurosci 2023; 43:6573-6587. [PMID: 37550052 PMCID: PMC10513075 DOI: 10.1523/jneurosci.0383-23.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 07/07/2023] [Accepted: 07/20/2023] [Indexed: 08/09/2023] Open
Abstract
Comorbidities, such as cognitive deficits, which often accompany epilepsies, constitute a basal state, while seizures are rare and transient events. This suggests that neural dynamics, in particular those supporting cognitive function, are altered in a permanent manner in epilepsy. Here, we test the hypothesis that primitive processes of information processing at the core of cognitive function (i.e., storage and sharing of information) are altered in the hippocampus and the entorhinal cortex in experimental epilepsy in adult, male Wistar rats. We find that information storage and sharing are organized into substates across the stereotypic states of slow and theta oscillations in both epilepsy and control conditions. However, their internal composition and organization through time are disrupted in epilepsy, partially losing brain state selectivity compared with controls, and shifting toward a regimen of disorder. We propose that the alteration of information processing at this algorithmic level of computation, the theoretical intermediate level between structure and function, may be a mechanism behind the emergent and widespread comorbidities associated with epilepsy, and perhaps other disorders.SIGNIFICANCE STATEMENT Comorbidities, such as cognitive deficits, which often accompany epilepsies, constitute a basal state, while seizures are rare and transient events. This suggests that neural dynamics, in particular those supporting cognitive function, are altered in a permanent manner in epilepsy. Here, we show that basic processes of information processing at the core of cognitive function (i.e., storage and sharing of information) are altered in the hippocampus and the entorhinal cortex (two regions involved in memory processes) in experimental epilepsy. Such disruption of information processing at the algorithmic level itself could underlie the general performance impairments in epilepsy.
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Affiliation(s)
- Wesley Clawson
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
- Allen Discovery Center, Tufts University, Medford, Massachusetts
| | - Benjamin Waked
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Tanguy Madec
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Antoine Ghestem
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Pascale P Quilichini
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
| | - Demian Battaglia
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
- University of Strasbourg Institute for Advanced Studies, Strasbourg, France
| | - Christophe Bernard
- Aix Marseille Université, INSERM, INS, Institut de Neurosciences des Systèmes, Marseille, France
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31
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Banaie Boroujeni K, Womelsdorf T. Routing states transition during oscillatory bursts and attentional selection. Neuron 2023; 111:2929-2944.e11. [PMID: 37463578 PMCID: PMC10529654 DOI: 10.1016/j.neuron.2023.06.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Revised: 05/22/2023] [Accepted: 06/20/2023] [Indexed: 07/20/2023]
Abstract
Brain-wide information routing relies on the spatio-temporal dynamics of neural activity, but it remains unclear how routing states emerge at fast spiking timescales and relate to slower activity dynamics during cognitive processes. Here, we show that localized spiking events participate in directional routing states with spiking activity in distant brain areas that dynamically switch or amplify states during oscillatory bursts, attentional selection, and decision-making. Modeling and neural recordings from lateral prefrontal cortex (LPFC), anterior cingulate cortex (ACC), and striatum of nonhuman primates revealed that cross-regional routing states arise within 20 ms following individual neuron spikes, with LPFC spikes leading the activity in ACC and striatum. The baseline routing state amplified during LPFC beta bursts between LPFC and striatum and switched direction during ACC theta/alpha bursts between ACC and LPFC. Selective attention amplified theta-/alpha-band-specific lead ensembles in ACC, while decision-making increased the lead of ACC and LPFC spikes to the striatum.
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Affiliation(s)
- Kianoush Banaie Boroujeni
- Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA; Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA.
| | - Thilo Womelsdorf
- Department of Psychology, Vanderbilt University, Nashville, TN 37240, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN 37240, USA
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32
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Seguin C, Sporns O, Zalesky A. Brain network communication: concepts, models and applications. Nat Rev Neurosci 2023; 24:557-574. [PMID: 37438433 DOI: 10.1038/s41583-023-00718-5] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/08/2023] [Indexed: 07/14/2023]
Abstract
Understanding communication and information processing in nervous systems is a central goal of neuroscience. Over the past two decades, advances in connectomics and network neuroscience have opened new avenues for investigating polysynaptic communication in complex brain networks. Recent work has brought into question the mainstay assumption that connectome signalling occurs exclusively via shortest paths, resulting in a sprawling constellation of alternative network communication models. This Review surveys the latest developments in models of brain network communication. We begin by drawing a conceptual link between the mathematics of graph theory and biological aspects of neural signalling such as transmission delays and metabolic cost. We organize key network communication models and measures into a taxonomy, aimed at helping researchers navigate the growing number of concepts and methods in the literature. The taxonomy highlights the pros, cons and interpretations of different conceptualizations of connectome signalling. We showcase the utility of network communication models as a flexible, interpretable and tractable framework to study brain function by reviewing prominent applications in basic, cognitive and clinical neurosciences. Finally, we provide recommendations to guide the future development, application and validation of network communication models.
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Affiliation(s)
- Caio Seguin
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia.
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.
| | - Olaf Sporns
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA
- Program in Neuroscience, Indiana University, Bloomington, IN, USA
- Program in Cognitive Science, Indiana University, Bloomington, IN, USA
- Indiana University Network Science Institute, Indiana University, Bloomington, IN, USA
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, University of Melbourne and Melbourne Health, Melbourne, Victoria, Australia
- Department of Biomedical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Victoria, Australia
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33
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Comeaux P, Clark K, Noudoost B. A recruitment through coherence theory of working memory. Prog Neurobiol 2023; 228:102491. [PMID: 37393039 PMCID: PMC10530428 DOI: 10.1016/j.pneurobio.2023.102491] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 06/14/2023] [Accepted: 06/21/2023] [Indexed: 07/03/2023]
Abstract
The interactions between prefrontal cortex and other areas during working memory have been studied for decades. Here we outline a conceptual framework describing interactions between these areas during working memory, and review evidence for key elements of this model. We specifically suggest that a top-down signal sent from prefrontal to sensory areas drives oscillations in these areas. Spike timing within sensory areas becomes locked to these working-memory-driven oscillations, and the phase of spiking conveys information about the representation available within these areas. Downstream areas receiving these phase-locked spikes from sensory areas can recover this information via a combination of coherent oscillations and gating of input efficacy based on the phase of their local oscillations. Although the conceptual framework is based on prefrontal interactions with sensory areas during working memory, we also discuss the broader implications of this framework for flexible communication between brain areas in general.
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Affiliation(s)
- Phillip Comeaux
- Dept. of Biomedical Engineering, University of Utah, 36 S. Wasatch Drive, Salt Lake City, UT 84112, USA; Dept. of Ophthalmology and Visual Sciences, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
| | - Kelsey Clark
- Dept. of Ophthalmology and Visual Sciences, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA
| | - Behrad Noudoost
- Dept. of Ophthalmology and Visual Sciences, University of Utah, 65 Mario Capecchi Drive, Salt Lake City, UT 84132, USA.
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34
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Liu ZQ, Shafiei G, Baillet S, Misic B. Spatially heterogeneous structure-function coupling in haemodynamic and electromagnetic brain networks. Neuroimage 2023; 278:120276. [PMID: 37451374 DOI: 10.1016/j.neuroimage.2023.120276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 07/04/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023] Open
Abstract
The relationship between structural and functional connectivity in the brain is a key question in connectomics. Here we quantify patterns of structure-function coupling across the neocortex, by comparing structural connectivity estimated using diffusion MRI with functional connectivity estimated using both neurophysiological (MEG-based) and haemodynamic (fMRI-based) recordings. We find that structure-function coupling is heterogeneous across brain regions and frequency bands. The link between structural and functional connectivity is generally stronger in multiple MEG frequency bands compared to resting state fMRI. Structure-function coupling is greater in slower and intermediate frequency bands compared to faster frequency bands. We also find that structure-function coupling systematically follows the archetypal sensorimotor-association hierarchy, as well as patterns of laminar differentiation, peaking in granular layer IV. Finally, structure-function coupling is better explained using structure-informed inter-regional communication metrics than using structural connectivity alone. Collectively, these results place neurophysiological and haemodynamic structure-function relationships in a common frame of reference and provide a starting point for a multi-modal understanding of structure-function coupling in the brain.
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Affiliation(s)
- Zhen-Qi Liu
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Golia Shafiei
- Lifespan Informatics and Neuroimaging Center (PennLINC), Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sylvain Baillet
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada
| | - Bratislav Misic
- McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University, Montréal, Canada.
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35
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Pope M, Seguin C, Varley TF, Faskowitz J, Sporns O. Co-evolving dynamics and topology in a coupled oscillator model of resting brain function. Neuroimage 2023; 277:120266. [PMID: 37414231 DOI: 10.1016/j.neuroimage.2023.120266] [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: 01/25/2023] [Revised: 05/24/2023] [Accepted: 07/04/2023] [Indexed: 07/08/2023] Open
Abstract
Dynamic models of ongoing BOLD fMRI brain dynamics and models of communication strategies have been two important approaches to understanding how brain network structure constrains function. However, dynamic models have yet to widely incorporate one of the most important insights from communication models: the brain may not use all of its connections in the same way or at the same time. Here we present a variation of a phase delayed Kuramoto coupled oscillator model that dynamically limits communication between nodes on each time step. An active subgraph of the empirically derived anatomical brain network is chosen in accordance with the local dynamic state on every time step, thus coupling dynamics and network structure in a novel way. We analyze this model with respect to its fit to empirical time-averaged functional connectivity, finding that, with the addition of only one parameter, it significantly outperforms standard Kuramoto models with phase delays. We also perform analyses on the novel time series of active edges it produces, demonstrating a slowly evolving topology moving through intermittent episodes of integration and segregation. We hope to demonstrate that the exploration of novel modeling mechanisms and the investigation of dynamics of networks in addition to dynamics on networks may advance our understanding of the relationship between brain structure and function.
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Affiliation(s)
- Maria Pope
- Program in Neuroscience, Indiana University, Bloomington, IN 47405, United States; School of Informatics, Computing & Engineering, Indiana University, Bloomington, IN 47405, United States.
| | - Caio Seguin
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, United States
| | - Thomas F Varley
- School of Informatics, Computing & Engineering, Indiana University, Bloomington, IN 47405, United States; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, United States
| | - Joshua Faskowitz
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, United States
| | - Olaf Sporns
- Program in Neuroscience, Indiana University, Bloomington, IN 47405, United States; Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, United States; Network Science Institute, Indiana University, Bloomington, IN 47405, United States; Cognitive Science Program, Indiana University, Bloomington, IN 47405, United States
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36
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Champion KP, Gozel O, Lankow BS, Ermentrout GB, Goldman MS. An oscillatory mechanism for multi-level storage in short-term memory. Commun Biol 2023; 6:829. [PMID: 37563448 PMCID: PMC10415352 DOI: 10.1038/s42003-023-05200-7] [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: 04/01/2022] [Accepted: 08/01/2023] [Indexed: 08/12/2023] Open
Abstract
Oscillatory activity is commonly observed during the maintenance of information in short-term memory, but its role remains unclear. Non-oscillatory models of short-term memory storage are able to encode stimulus identity through their spatial patterns of activity, but are typically limited to either an all-or-none representation of stimulus amplitude or exhibit a biologically implausible exact-tuning condition. Here we demonstrate a simple mechanism by which oscillatory input enables a circuit to generate persistent or sequential activity that encodes information not only in the spatial pattern of activity, but also in the amplitude of activity. This is accomplished through a phase-locking phenomenon that permits many different amplitudes of persistent activity to be stored without requiring exact tuning of model parameters. Altogether, this work proposes a class of models for the storage of information in working memory, a potential role for brain oscillations, and a dynamical mechanism for maintaining multi-stable neural representations.
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Affiliation(s)
- Kathleen P Champion
- Department of Applied Mathematics, University of Washington, Seattle, WA, 98195, USA
| | - Olivia Gozel
- Departments of Neurobiology and Statistics, University of Chicago, Chicago, IL, 60637, USA
- Grossman Center for Quantitative Biology and Human Behavior, University of Chicago, Chicago, IL, 60637, USA
| | - Benjamin S Lankow
- Center for Neuroscience, University of California, Davis, Davis, CA, 95618, USA
| | - G Bard Ermentrout
- Department of Mathematics, University of Pittsburgh, Pittsburgh, PA, 15213, USA.
| | - Mark S Goldman
- Center for Neuroscience, University of California, Davis, Davis, CA, 95618, USA.
- Department of Neurobiology, Physiology, and Behavior, and Department of Ophthalmology and Vision Science, University of California, Davis, Davis, CA, 95618, USA.
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37
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Fontenele AJ, Sooter JS, Norman VK, Gautam SH, Shew WL. Low dimensional criticality embedded in high dimensional awake brain dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522896. [PMID: 37546833 PMCID: PMC10401950 DOI: 10.1101/2023.01.05.522896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. Here we offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality - a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescale agrees with established theory of critical dynamics. Our results suggest that cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.
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Affiliation(s)
- Antonio J. Fontenele
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - J. Samuel Sooter
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - V. Kindler Norman
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - Shree Hari Gautam
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - Woodrow L. Shew
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
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38
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Pérez-Cervera A, Gutkin B, Thomas PJ, Lindner B. A universal description of stochastic oscillators. Proc Natl Acad Sci U S A 2023; 120:e2303222120. [PMID: 37432992 PMCID: PMC10629544 DOI: 10.1073/pnas.2303222120] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Accepted: 05/18/2023] [Indexed: 07/13/2023] Open
Abstract
Many systems in physics, chemistry, and biology exhibit oscillations with a pronounced random component. Such stochastic oscillations can emerge via different mechanisms, for example, linear dynamics of a stable focus with fluctuations, limit-cycle systems perturbed by noise, or excitable systems in which random inputs lead to a train of pulses. Despite their diverse origins, the phenomenology of random oscillations can be strikingly similar. Here, we introduce a nonlinear transformation of stochastic oscillators to a complex-valued function [Formula: see text](x) that greatly simplifies and unifies the mathematical description of the oscillator's spontaneous activity, its response to an external time-dependent perturbation, and the correlation statistics of different oscillators that are weakly coupled. The function [Formula: see text] (x) is the eigenfunction of the Kolmogorov backward operator with the least negative (but nonvanishing) eigenvalue λ1 = μ1 + iω1. The resulting power spectrum of the complex-valued function is exactly given by a Lorentz spectrum with peak frequency ω1 and half-width μ1; its susceptibility with respect to a weak external forcing is given by a simple one-pole filter, centered around ω1; and the cross-spectrum between two coupled oscillators can be easily expressed by a combination of the spontaneous power spectra of the uncoupled systems and their susceptibilities. Our approach makes qualitatively different stochastic oscillators comparable, provides simple characteristics for the coherence of the random oscillation, and gives a framework for the description of weakly coupled oscillators.
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Affiliation(s)
- Alberto Pérez-Cervera
- Department of Applied Mathematics, Instituto de Matemática Interdisciplinar, Universidad Complutense de Madrid, Madrid28040, Spain
| | - Boris Gutkin
- Group for Neural Theory, LNC2 INSERM U960, Département d’Etudes Cognitives, Ecole Normale Supérieure - Paris Science Letters University, Paris75005, France
| | - Peter J. Thomas
- Department of Mathematics, Applied Mathematics, and Statistics, Case Western Reserve University, Cleveland, OH44106
| | - Benjamin Lindner
- Bernstein Center for Computational Neuroscience Berlin, Berlin10115, Germany
- Department of Physics, Humboldt Universität zu Berlin, BerlinD-12489, Germany
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Cho S, Choi JH. A guide towards optimal detection of transient oscillatory bursts with unknown parameters. J Neural Eng 2023; 20:046007. [PMID: 37339619 DOI: 10.1088/1741-2552/acdffd] [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: 09/26/2022] [Accepted: 06/20/2023] [Indexed: 06/22/2023]
Abstract
Objectives. Recent event-based analyses of transient neural activities have characterized the oscillatory bursts as a neural signature that bridges dynamic neural states to cognition and behaviors. Following this insight, our study aimed to (1) compare the efficacy of common burst detection algorithms under varying signal-to-noise ratios and event durations using synthetic signals and (2) establish a strategic guideline for selecting the optimal algorithm for real datasets with undefined properties.Approach.We tested the robustness of burst detection algorithms using a simulation dataset comprising bursts of multiple frequencies. To systematically assess their performance, we used a metric called 'detection confidence', quantifying classification accuracy and temporal precision in a balanced manner. Given that burst properties in empirical data are often unknown in advance, we then proposed a selection rule to identify an optimal algorithm for a given dataset and validated its application on local field potentials of basolateral amygdala recorded from male mice (n=8) exposed to a natural threat.Main Results.Our simulation-based evaluation demonstrated that burst detection is contingent upon event duration, whereas accurately pinpointing burst onsets is more susceptible to noise level. For real data, the algorithm chosen based on the selection rule exhibited superior detection and temporal accuracy, although its statistical significance differed across frequency bands. Notably, the algorithm chosen by human visual screening differed from the one recommended by the rule, implying a potential misalignment between human priors and mathematical assumptions of the algorithms.Significance.Therefore, our findings underscore that the precise detection of transient bursts is fundamentally influenced by the chosen algorithm. The proposed algorithm-selection rule suggests a potentially viable solution, while also emphasizing the inherent limitations originating from algorithmic design and volatile performances across datasets. Consequently, this study cautions against relying solely on heuristic-based approaches, advocating for a careful algorithm selection in burst detection studies.
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Affiliation(s)
- SungJun Cho
- Center for Neuroscience, Korea Institute of Science and Technology, Hwarang-ro 14-gil 5, Seongbuk-gu, Seoul 02792, Republic of Korea
- Oxford Centre for Human Brain Activity, Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, United Kingdom
| | - Jee Hyun Choi
- Center for Neuroscience, Korea Institute of Science and Technology, Hwarang-ro 14-gil 5, Seongbuk-gu, Seoul 02792, Republic of Korea
- Department of Neural Sciences, University of Science and Technology, 217, Gajeong-ro, Yuseong-gu, Daejeon 34113, Republic of Korea
- Department of Physics and Center for Theoretical Physics, Seoul National University, Gwanak-ro, Gwanak-gu, Seoul 08826, Republic of Korea
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40
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Celotto M, Bím J, Tlaie A, De Feo V, Lemke S, Chicharro D, Nili H, Bieler M, Hanganu-Opatz IL, Donner TH, Brovelli A, Panzeri S. An information-theoretic quantification of the content of communication between brain regions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.14.544903. [PMID: 37398375 PMCID: PMC10312682 DOI: 10.1101/2023.06.14.544903] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Quantifying the amount, content and direction of communication between brain regions is key to understanding brain function. Traditional methods to analyze brain activity based on the Wiener-Granger causality principle quantify the overall information propagated by neural activity between simultaneously recorded brain regions, but do not reveal the information flow about specific features of interest (such as sensory stimuli). Here, we develop a new information theoretic measure termed Feature-specific Information Transfer (FIT), quantifying how much information about a specific feature flows between two regions. FIT merges the Wiener-Granger causality principle with information-content specificity. We first derive FIT and prove analytically its key properties. We then illustrate and test them with simulations of neural activity, demonstrating that FIT identifies, within the total information flowing between regions, the information that is transmitted about specific features. We then analyze three neural datasets obtained with different recording methods, magneto- and electro-encephalography, and spiking activity, to demonstrate the ability of FIT to uncover the content and direction of information flow between brain regions beyond what can be discerned with traditional anaytical methods. FIT can improve our understanding of how brain regions communicate by uncovering previously hidden feature-specific information flow.
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Affiliation(s)
- Marco Celotto
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto (TN), Italy
- Department of Pharmacy and Biotechnology, University of Bologna, Bologna, Italy
| | - Jan Bím
- Datamole, s. r. o, Vitezne namesti 577/2 Dejvice, 160 00 Praha 6, The Czech Republic
| | - Alejandro Tlaie
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto (TN), Italy
| | - Vito De Feo
- Artificial Intelligence Team, Future Health Technology, and Brain-Computer Interfaces laboratories, School of Computer Science and Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK
| | - Stefan Lemke
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, United States
| | - Daniel Chicharro
- Department of Computer Science, City, University of London, London, UK
| | - Hamed Nili
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Malte Bieler
- Mobile Technology Lab, School of Economics, Innovation and Technology, University College Kristiania, Oslo, Norway
| | - Ileana L. Hanganu-Opatz
- Institute of Developmental Neurophysiology, Center for Molecular Neurobiology, University Medical Center, Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias H. Donner
- Section Computational Cognitive Neuroscience, Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Andrea Brovelli
- Institut de Neurosciences de la Timone, UMR 7289, Aix Marseille Université, CNRS, Marseille, France
| | - Stefano Panzeri
- Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Neural Computation Laboratory, Istituto Italiano di Tecnologia, Rovereto (TN), Italy
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41
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Yiling Y, Shapcott K, Peter A, Klon-Lipok J, Xuhui H, Lazar A, Singer W. Robust encoding of natural stimuli by neuronal response sequences in monkey visual cortex. Nat Commun 2023; 14:3021. [PMID: 37231014 DOI: 10.1038/s41467-023-38587-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Accepted: 05/08/2023] [Indexed: 05/27/2023] Open
Abstract
Parallel multisite recordings in the visual cortex of trained monkeys revealed that the responses of spatially distributed neurons to natural scenes are ordered in sequences. The rank order of these sequences is stimulus-specific and maintained even if the absolute timing of the responses is modified by manipulating stimulus parameters. The stimulus specificity of these sequences was highest when they were evoked by natural stimuli and deteriorated for stimulus versions in which certain statistical regularities were removed. This suggests that the response sequences result from a matching operation between sensory evidence and priors stored in the cortical network. Decoders trained on sequence order performed as well as decoders trained on rate vectors but the former could decode stimulus identity from considerably shorter response intervals than the latter. A simulated recurrent network reproduced similarly structured stimulus-specific response sequences, particularly once it was familiarized with the stimuli through non-supervised Hebbian learning. We propose that recurrent processing transforms signals from stationary visual scenes into sequential responses whose rank order is the result of a Bayesian matching operation. If this temporal code were used by the visual system it would allow for ultrafast processing of visual scenes.
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Affiliation(s)
- Yang Yiling
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany
- Faculty of Biological Sciences, Goethe-University Frankfurt am Main, 60438, Frankfurt am Main, Germany
| | - Katharine Shapcott
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany
| | - Alina Peter
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
- International Max Planck Research School (IMPRS) for Neural Circuits, 60438, Frankfurt am Main, Germany
- Faculty of Biological Sciences, Goethe-University Frankfurt am Main, 60438, Frankfurt am Main, Germany
| | - Johanna Klon-Lipok
- Max Planck Institute for Brain Research, 60438, Frankfurt am Main, Germany
| | - Huang Xuhui
- Intelligent Science and Technology Academy, China Aerospace Science and Industry Corporation (CASIC), 100144, Beijing, China
- Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
| | - Andreea Lazar
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany
| | - Wolf Singer
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528, Frankfurt am Main, Germany.
- Frankfurt Institute for Advanced Studies, 60438, Frankfurt am Main, Germany.
- Max Planck Institute for Brain Research, 60438, Frankfurt am Main, Germany.
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42
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Holt CJ, Miller KD, Ahmadian Y. The stabilized supralinear network accounts for the contrast dependence of visual cortical gamma oscillations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540442. [PMID: 37214812 PMCID: PMC10197697 DOI: 10.1101/2023.05.11.540442] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
When stimulated, neural populations in the visual cortex exhibit fast rhythmic activity with frequencies in the gamma band (30-80 Hz). The gamma rhythm manifests as a broad resonance peak in the power-spectrum of recorded local field potentials, which exhibits various stimulus dependencies. In particular, in macaque primary visual cortex (V1), the gamma peak frequency increases with increasing stimulus contrast. Moreover, this contrast dependence is local: when contrast varies smoothly over visual space, the gamma peak frequency in each cortical column is controlled by the local contrast in that column's receptive field. No parsimonious mechanistic explanation for these contrast dependencies of V1 gamma oscillations has been proposed. The stabilized supralinear network (SSN) is a mechanistic model of cortical circuits that has accounted for a range of visual cortical response nonlinearities and contextual modulations, as well as their contrast dependence. Here, we begin by showing that a reduced SSN model without retinotopy robustly captures the contrast dependence of gamma peak frequency, and provides a mechanistic explanation for this effect based on the observed non-saturating and supralinear input-output function of V1 neurons. Given this result, the local dependence on contrast can trivially be captured in a retinotopic SSN which however lacks horizontal synaptic connections between its cortical columns. However, long-range horizontal connections in V1 are in fact strong, and underlie contextual modulation effects such as surround suppression. We thus explored whether a retinotopically organized SSN model of V1 with strong excitatory horizontal connections can exhibit both surround suppression and the local contrast dependence of gamma peak frequency. We found that retinotopic SSNs can account for both effects, but only when the horizontal excitatory projections are composed of two components with different patterns of spatial fall-off with distance: a short-range component that only targets the source column, combined with a long-range component that targets columns neighboring the source column. We thus make a specific qualitative prediction for the spatial structure of horizontal connections in macaque V1, consistent with the columnar structure of cortex.
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Affiliation(s)
- Caleb J Holt
- Institute of Neuroscience, Department of Physics, University of Oregon, OR, USA
| | - Kenneth D Miller
- Center for Theoretical Neuroscience, Swartz Program in Theoretical Neuroscience, Kavli Institute for Brain Science, and Dept. of Neuroscience, College of Physicians and Surgeons and Morton B. Zuckerman Mind Brain Behavior Institute, Columbia University, NY, USA
| | - Yashar Ahmadian
- Computational and Biological Learning Lab, Department of Engineering, University of Cambridge, Cambridge, UK
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43
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Paré D, Headley DB. The amygdala mediates the facilitating influence of emotions on memory through multiple interacting mechanisms. Neurobiol Stress 2023; 24:100529. [PMID: 36970449 PMCID: PMC10034520 DOI: 10.1016/j.ynstr.2023.100529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 02/09/2023] [Accepted: 02/14/2023] [Indexed: 02/25/2023] Open
Abstract
Emotionally arousing experiences are better remembered than neutral ones, highlighting that memory consolidation differentially promotes retention of experiences depending on their survival value. This paper reviews evidence indicating that the basolateral amygdala (BLA) mediates the facilitating influence of emotions on memory through multiple mechanisms. Emotionally arousing events, in part by triggering the release of stress hormones, cause a long-lasting enhancement in the firing rate and synchrony of BLA neurons. BLA oscillations, particularly gamma, play an important role in synchronizing the activity of BLA neurons. In addition, BLA synapses are endowed with a unique property, an elevated post-synaptic expression of NMDA receptors. As a result, the synchronized gamma-related recruitment of BLA neurons facilitates synaptic plasticity at other inputs converging on the same target neurons. Given that emotional experiences are spontaneously remembered during wake and sleep, and that REM sleep is favorable to the consolidation of emotional memories, we propose a synthesis for the various lines of evidence mentioned above: gamma-related synchronized firing of BLA cells potentiates synapses between cortical neurons that were recruited during an emotional experience, either by tagging these cells for subsequent reactivation or by enhancing the effects of reactivation itself.
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Affiliation(s)
- Denis Paré
- Center for Molecular and Behavioral Neuroscience, Rutgers University - Newark, 197 University Avenue, Newark, NJ, 07102, USA
| | - Drew B. Headley
- Center for Molecular and Behavioral Neuroscience, Rutgers University - Newark, 197 University Avenue, Newark, NJ, 07102, USA
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44
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Vinck M, Uran C, Spyropoulos G, Onorato I, Broggini AC, Schneider M, Canales-Johnson A. Principles of large-scale neural interactions. Neuron 2023; 111:987-1002. [PMID: 37023720 DOI: 10.1016/j.neuron.2023.03.015] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/27/2023] [Accepted: 03/09/2023] [Indexed: 04/08/2023]
Abstract
What mechanisms underlie flexible inter-areal communication in the cortex? We consider four mechanisms for temporal coordination and their contributions to communication: (1) Oscillatory synchronization (communication-through-coherence); (2) communication-through-resonance; (3) non-linear integration; and (4) linear signal transmission (coherence-through-communication). We discuss major challenges for communication-through-coherence based on layer- and cell-type-specific analyses of spike phase-locking, heterogeneity of dynamics across networks and states, and computational models for selective communication. We argue that resonance and non-linear integration are viable alternative mechanisms that facilitate computation and selective communication in recurrent networks. Finally, we consider communication in relation to cortical hierarchy and critically examine the hypothesis that feedforward and feedback communication use fast (gamma) and slow (alpha/beta) frequencies, respectively. Instead, we propose that feedforward propagation of prediction errors relies on the non-linear amplification of aperiodic transients, whereas gamma and beta rhythms represent rhythmic equilibrium states that facilitate sustained and efficient information encoding and amplification of short-range feedback via resonance.
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Affiliation(s)
- Martin Vinck
- Ernst Struengmann 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.
| | - Cem Uran
- Ernst Struengmann 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
| | - Georgios Spyropoulos
- Ernst Struengmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Irene Onorato
- Ernst Struengmann 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
| | - Ana Clara Broggini
- Ernst Struengmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Marius Schneider
- Ernst Struengmann 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
| | - Andres Canales-Johnson
- Department of Psychology, University of Cambridge, CB2 3EB Cambridge, UK; Centro de Investigacion en Neuropsicologia y Neurociencias Cognitivas, Facultad de Ciencias de la Salud, Universidad Catolica del Maule, 3480122 Talca, Chile.
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45
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Fernandez-Ruiz A, Sirota A, Lopes-Dos-Santos V, Dupret D. Over and above frequency: Gamma oscillations as units of neural circuit operations. Neuron 2023; 111:936-953. [PMID: 37023717 PMCID: PMC7614431 DOI: 10.1016/j.neuron.2023.02.026] [Citation(s) in RCA: 25] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2022] [Revised: 11/30/2022] [Accepted: 02/16/2023] [Indexed: 04/08/2023]
Abstract
Gamma oscillations (∼30-150 Hz) are widespread correlates of neural circuit functions. These network activity patterns have been described across multiple animal species, brain structures, and behaviors, and are usually identified based on their spectral peak frequency. Yet, despite intensive investigation, whether gamma oscillations implement causal mechanisms of specific brain functions or represent a general dynamic mode of neural circuit operation remains unclear. In this perspective, we review recent advances in the study of gamma oscillations toward a deeper understanding of their cellular mechanisms, neural pathways, and functional roles. We discuss that a given gamma rhythm does not per se implement any specific cognitive function but rather constitutes an activity motif reporting the cellular substrates, communication channels, and computational operations underlying information processing in its generating brain circuit. Accordingly, we propose shifting the attention from a frequency-based to a circuit-level definition of gamma oscillations.
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Affiliation(s)
| | - Anton Sirota
- Bernstein Center for Computational Neuroscience, Faculty of Medicine, Ludwig-Maximilians Universität München, Planegg-Martinsried, Germany.
| | - Vítor Lopes-Dos-Santos
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - David Dupret
- Medical Research Council Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
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46
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Heck DH, Fox MB, Correia Chapman B, McAfee SS, Liu Y. Cerebellar control of thalamocortical circuits for cognitive function: A review of pathways and a proposed mechanism. Front Syst Neurosci 2023; 17:1126508. [PMID: 37064161 PMCID: PMC10097962 DOI: 10.3389/fnsys.2023.1126508] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Accepted: 03/13/2023] [Indexed: 04/18/2023] Open
Abstract
There is general agreement that cerebrocerebellar interactions via cerebellothalamocortical pathways are essential for a cerebellar cognitive and motor functions. Cerebellothalamic projections were long believed target mainly the ventral lateral (VL) and part of the ventral anterior (VA) nuclei, which project to cortical motor and premotor areas. Here we review new insights from detailed tracing studies, which show that projections from the cerebellum to the thalamus are widespread and reach almost every thalamic subnucleus, including nuclei involved in cognitive functions. These new insights into cerebellothalamic pathways beyond the motor thalamus are consistent with the increasing evidence of cerebellar cognitive function. However, the function of cerebellothalamic pathways and how they are involved in the various motor and cognitive functions of the cerebellum is still unknown. We briefly review literature on the role of the thalamus in coordinating the coherence of neuronal oscillations in the neocortex. The coherence of oscillations, which measures the stability of the phase relationship between two oscillations of the same frequency, is considered an indicator of increased functional connectivity between two structures showing coherent oscillations. Through thalamocortical interactions coherence patterns dynamically create and dissolve functional cerebral cortical networks in a task dependent manner. Finally, we review evidence for an involvement of the cerebellum in coordinating coherence of oscillations between cerebral cortical structures. We conclude that cerebellothalamic pathways provide the necessary anatomical substrate for a proposed role of the cerebellum in coordinating neuronal communication between cerebral cortical areas by coordinating the coherence of oscillations.
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Affiliation(s)
- Detlef H. Heck
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
| | - Mia B. Fox
- Department of Anatomy and Neurobiology, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Brittany Correia Chapman
- Department of Neuroscience, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Samuel S. McAfee
- St. Jude Children’s Research Hospital, Memphis, TN, United States
| | - Yu Liu
- Department of Biomedical Sciences, University of Minnesota Medical School, Duluth, MN, United States
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47
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Parto-Dezfouli M, Vezoli J, Bosman CA, Fries P. Enhanced Behavioral Performance through Interareal Gamma and Beta Synchronization. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.06.531093. [PMID: 36945499 PMCID: PMC10028832 DOI: 10.1101/2023.03.06.531093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2023]
Abstract
Cognitive functioning requires coordination between brain areas. Between visual areas, feedforward gamma synchronization improves behavioral performance. Here, we investigate whether similar principles hold across brain regions and frequency bands, using simultaneous local field potential recordings from 15 areas during performance of a selective attention task. Short behavioral reaction times (RTs), an index of efficient interareal communication, occurred when occipital areas V1, V2, V4, DP showed gamma synchronization, and fronto-central areas S1, 5, F1, F2, F4 showed beta synchronization. For both area clusters and corresponding frequency bands, deviations from the typically observed phase relations increased RTs. Across clusters and frequency bands, good phase relations occurred in a correlated manner specifically when they processed the behaviorally relevant stimulus. Furthermore, the fronto-central cluster exerted a beta-band influence onto the occipital cluster whose strength predicted short RTs. These results suggest that local gamma and beta synchronization and their inter-regional coordination jointly improve behavioral performance.
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Affiliation(s)
- Mohsen Parto-Dezfouli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Julien Vezoli
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
| | - Conrado Arturo Bosman
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Faculty of Science, University of Amsterdam, 1098 XH Amsterdam, Netherlands
| | - Pascal Fries
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt, Germany
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen, 6525 EN Nijmegen, Netherlands
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48
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de la Fuente LA, Zamberlan F, Bocaccio H, Kringelbach M, Deco G, Perl YS, Pallavicini C, Tagliazucchi E. Temporal irreversibility of neural dynamics as a signature of consciousness. Cereb Cortex 2023; 33:1856-1865. [PMID: 35512291 DOI: 10.1093/cercor/bhac177] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Revised: 04/16/2022] [Accepted: 04/18/2022] [Indexed: 11/14/2022] Open
Abstract
Dissipative systems evolve in the preferred temporal direction indicated by the thermodynamic arrow of time. The fundamental nature of this temporal asymmetry led us to hypothesize its presence in the neural activity evoked by conscious perception of the physical world, and thus its covariance with the level of conscious awareness. We implemented a data-driven deep learning framework to decode the temporal inversion of electrocorticography signals acquired from non-human primates. Brain activity time series recorded during conscious wakefulness could be distinguished from their inverted counterparts with high accuracy, both using frequency and phase information. However, classification accuracy was reduced for data acquired during deep sleep and under ketamine-induced anesthesia; moreover, the predictions obtained from multiple independent neural networks were less consistent for sleep and anesthesia than for conscious wakefulness. Finally, the analysis of feature importance scores highlighted transitions between slow ($\approx$20 Hz) and fast frequencies (>40 Hz) as the main contributors to the temporal asymmetry observed during conscious wakefulness. Our results show that a preferred temporal direction is manifest in the neural activity evoked by conscious mentation and in the phenomenology of the passage of time, establishing common ground to tackle the relationship between brain and subjective experience.
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Affiliation(s)
- Laura Alethia de la Fuente
- Department of Physics, University of Buenos Aires 1428, Argentina.,Institute of Cognitive and Translational Neuroscience, INECO Foundation, Favaloro University, Buenos Aires 1058, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina
| | - Federico Zamberlan
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina.,Cognitive Science and Artificial Intelligence Department, Tilburg University, Tilburg 5000, The Netherlands
| | - Hernán Bocaccio
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford OX1, UK.,Department of Psychiatry, University of Oxford, Oxford OX3, UK.,Center for Music in the Brain, Department of Clinical Medicine, Aarhus University 8000, DK
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain.,Institució Catalana de la Recerca i Estudis Avançats (ICREA), Barcelona 08010, Spain.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig 04103, Germany.,School of Psychological Sciences, Monash University, Melbourne, Clayton VIC 3800, Australia
| | - Yonatan Sanz Perl
- Department of Physics, University of Buenos Aires 1428, Argentina.,Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona 08018, Spain
| | - Carla Pallavicini
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina
| | - Enzo Tagliazucchi
- Department of Physics, University of Buenos Aires 1428, Argentina.,National Scientific and Technical Research Council, Buenos Aires 1425, Argentina.,Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibanez, Santiago 7910000, Chile
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49
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MacDowell CJ, Libby A, Jahn CI, Tafazoli S, Buschman TJ. Multiplexed Subspaces Route Neural Activity Across Brain-wide Networks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.08.527772. [PMID: 36798411 PMCID: PMC9934668 DOI: 10.1101/2023.02.08.527772] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/13/2023]
Abstract
Cognition is flexible. Behaviors can change on a moment-by-moment basis. Such flexibility is thought to rely on the brain's ability to route information through different networks of brain regions in order to support different cognitive computations. However, the mechanisms that determine which network of brain regions is engaged are unknown. To address this, we combined cortex-wide calcium imaging with high-density electrophysiological recordings in eight cortical and subcortical regions of mice. Different dimensions within the population activity of each brain region were functionally connected with different cortex-wide 'subspace networks' of regions. These subspace networks were multiplexed, allowing a brain region to simultaneously interact with multiple independent, yet overlapping, networks. Alignment of neural activity within a region to a specific subspace network dimension predicted how neural activity propagated between regions. Thus, changing the geometry of the neural representation within a brain region could be a mechanism to selectively engage different brain-wide networks to support cognitive flexibility.
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Affiliation(s)
- Camden J. MacDowell
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ
- Rutgers Robert Wood Johnson Medical School, 125 Paterson St, New Brunswick, NJ
| | - Alexandra Libby
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ
| | - Caroline I. Jahn
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ
| | - Sina Tafazoli
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ
| | - Timothy J. Buschman
- Princeton Neuroscience Institute, Princeton University, Washington Rd, Princeton, NJ
- Department of Psychology, Princeton University, Washington Rd, Princeton, NJ
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Madadi Asl M, Valizadeh A, Tass PA. Decoupling of interacting neuronal populations by time-shifted stimulation through spike-timing-dependent plasticity. PLoS Comput Biol 2023; 19:e1010853. [PMID: 36724144 PMCID: PMC9891531 DOI: 10.1371/journal.pcbi.1010853] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 01/05/2023] [Indexed: 02/02/2023] Open
Abstract
The synaptic organization of the brain is constantly modified by activity-dependent synaptic plasticity. In several neurological disorders, abnormal neuronal activity and pathological synaptic connectivity may significantly impair normal brain function. Reorganization of neuronal circuits by therapeutic stimulation has the potential to restore normal brain dynamics. Increasing evidence suggests that the temporal stimulation pattern crucially determines the long-lasting therapeutic effects of stimulation. Here, we tested whether a specific pattern of brain stimulation can enable the suppression of pathologically strong inter-population synaptic connectivity through spike-timing-dependent plasticity (STDP). More specifically, we tested how introducing a time shift between stimuli delivered to two interacting populations of neurons can effectively decouple them. To that end, we first used a tractable model, i.e., two bidirectionally coupled leaky integrate-and-fire (LIF) neurons, to theoretically analyze the optimal range of stimulation frequency and time shift for decoupling. We then extended our results to two reciprocally connected neuronal populations (modules) where inter-population delayed connections were modified by STDP. As predicted by the theoretical results, appropriately time-shifted stimulation causes a decoupling of the two-module system through STDP, i.e., by unlearning pathologically strong synaptic interactions between the two populations. Based on the overall topology of the connections, the decoupling of the two modules, in turn, causes a desynchronization of the populations that outlasts the cessation of stimulation. Decoupling effects of the time-shifted stimulation can be realized by time-shifted burst stimulation as well as time-shifted continuous simulation. Our results provide insight into the further optimization of a variety of multichannel stimulation protocols aiming at a therapeutic reshaping of diseased brain networks.
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Affiliation(s)
- Mojtaba Madadi Asl
- School of Biological Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
| | - Alireza Valizadeh
- Pasargad Institute for Advanced Innovative Solutions (PIAIS), Tehran, Iran
- Department of Physics, Institute for Advanced Studies in Basic Sciences (IASBS), Zanjan, Iran
| | - Peter A. Tass
- Department of Neurosurgery, Stanford University School of Medicine, Stanford, CA, United States of America
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