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Lin Y, Huang S, Mao J, Li M, Haihambo N, Wang F, Liang Y, Chen W, Han C. The neural oscillatory mechanism underlying human brain fingerprint recognition using a portable EEG acquisition device. Neuroimage 2024; 294:120637. [PMID: 38714216 DOI: 10.1016/j.neuroimage.2024.120637] [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: 01/29/2024] [Revised: 03/31/2024] [Accepted: 05/04/2024] [Indexed: 05/09/2024] Open
Abstract
In recent years, brainprint recognition has emerged as a novel method of personal identity verification. Although studies have demonstrated the feasibility of this technology, some limitations hinder its further development into the society, such as insufficient efficiency (extended wear time for multi-channel EEG cap), complex experimental paradigms (more time in learning and completing experiments), and unclear neurobiological characteristics (lack of intuitive biomarkers and an inability to eliminate the impact of noise on individual differences). Overall, these limitations are due to the incomplete understanding of the underlying neural mechanisms. Therefore, this study aims to investigate the neural mechanisms behind brainwave recognition and simplify the operation process. We recorded prefrontal resting-state EEG data from 40 participants, which is followed up over nine months using a single-channel portable brainwave device. We found that portable devices can effectively and stably capture the characteristics of different subjects in the alpha band (8-13Hz) over long periods, as well as capturing their individual differences (no alpha peak, 1 alpha peak, or 2 alpha peaks). Through correlation analysis, alpha-band activity can reveal the uniqueness of the subjects compared to others within one minute. We further used a descriptive model to dissect the oscillatory and non-oscillatory components in the alpha band, demonstrating the different contributions of fine oscillatory features to individual differences (especially amplitude and bandwidth). Our study validated the feasibility of portable brainwave devices in brainwave recognition and the underlying neural oscillation mechanisms. The fine characteristics of various alpha oscillations will contribute to the accuracy of brainwave recognition, providing new insights for the development of future brainwave recognition technology.
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Affiliation(s)
- Yuchen Lin
- The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Shaojia Huang
- Shenzhen Shuimu AI Technology Co., Ltd, Shenzhen, China
| | - Jidong Mao
- Shenzhen Shuimu AI Technology Co., Ltd, Shenzhen, China
| | - Meijia Li
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium
| | - Naem Haihambo
- Faculty of Psychology and Center for Neuroscience, Vrije Universiteit Brussel, Brussels, Belgium
| | - Fang Wang
- Shenzhen Shuimu AI Technology Co., Ltd, Shenzhen, China
| | - Yuping Liang
- Shenzhen Shuimu AI Technology Co., Ltd, Shenzhen, China
| | - Wufang Chen
- Shenzhen Shuimu AI Technology Co., Ltd, Shenzhen, China
| | - Chuanliang Han
- School of Biomedical Sciences and Gerald Choa Neuroscience Institute, The Chinese University of Hong Kong, Hong Kong SAR, China.
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2
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Sano M, Nishiura Y, Morikawa I, Hoshino A, Uemura JI, Iwatsuki K, Hirata H, Hoshiyama M. Analysis of the alpha activity envelope in electroencephalography in relation to the ratio of excitatory to inhibitory neural activity. PLoS One 2024; 19:e0305082. [PMID: 38870189 PMCID: PMC11175473 DOI: 10.1371/journal.pone.0305082] [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: 11/01/2023] [Accepted: 05/23/2024] [Indexed: 06/15/2024] Open
Abstract
Alpha waves, one of the major components of resting and awake cortical activity in human electroencephalography (EEG), are known to show waxing and waning, but this phenomenon has rarely been analyzed. In the present study, we analyzed this phenomenon from the viewpoint of excitation and inhibition. The alpha wave envelope was subjected to secondary differentiation. This gave the positive (acceleration positive, Ap) and negative (acceleration negative, An) values of acceleration and their ratio (Ap-An ratio) at each sampling point of the envelope signals for 60 seconds. This analysis was performed on 36 participants with Alzheimer's disease (AD), 23 with frontotemporal dementia (FTD) and 29 age-matched healthy participants (NC) whose data were provided as open datasets. The mean values of the Ap-An ratio for 60 seconds at each EEG electrode were compared between the NC and AD/FTD groups. The AD (1.41 ±0.01 (SD)) and FTD (1.40 ±0.02) groups showed a larger Ap-An ratio than the NC group (1.38 ±0.02, p<0.05). A significant correlation between the envelope amplitude of alpha activity and the Ap-An ratio was observed at most electrodes in the NC group (Pearson's correlation coefficient, r = -0.92 ±0.15, mean for all electrodes), whereas the correlation was disrupted in AD (-0.09 ±0.21, p<0.05) and disrupted in the frontal region in the FTD group. The present method analyzed the envelope of alpha waves from a new perspective, that of excitation and inhibition, and it could detect properties of the EEG, Ap-An ratio, that have not been revealed by existing methods. The present study proposed a new method to analyze the alpha activity envelope in electroencephalography, which could be related to excitatory and inhibitory neural activity.
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Affiliation(s)
- Misako Sano
- Department of Preventive Rehabilitation Sciences, School of Health Sciences, Nagoya University, Nagoya, Japan
| | - Yuko Nishiura
- Department of Preventive Rehabilitation Sciences, School of Health Sciences, Nagoya University, Nagoya, Japan
| | - Izumi Morikawa
- Department of Preventive Rehabilitation Sciences, School of Health Sciences, Nagoya University, Nagoya, Japan
- Music Division, Nagoya University of the Arts, Kitanagoya, Japan
| | - Aiko Hoshino
- Department of Preventive Rehabilitation Sciences, School of Health Sciences, Nagoya University, Nagoya, Japan
| | - Jun-ichi Uemura
- Department of Preventive Rehabilitation Sciences, School of Health Sciences, Nagoya University, Nagoya, Japan
| | - Katsuyuki Iwatsuki
- Department of Hand Surgery, Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Hitoshi Hirata
- Department of Hand Surgery, Graduate School of Medicine, Nagoya University, Nagoya, Japan
| | - Minoru Hoshiyama
- Department of Preventive Rehabilitation Sciences, School of Health Sciences, Nagoya University, Nagoya, Japan
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3
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Yang H, Han F, Wang Q. A large-scale neuronal network modelling study: Stimulus size modulates gamma oscillations in the primary visual cortex by long-range connections. Eur J Neurosci 2024. [PMID: 38812400 DOI: 10.1111/ejn.16429] [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: 10/06/2023] [Revised: 05/04/2024] [Accepted: 05/13/2024] [Indexed: 05/31/2024]
Abstract
Stimulus size modulation of neuronal firing activity is a fundamental property of the primary visual cortex. Numerous biological experiments have shown that stimulus size modulation is affected by multiple factors at different spatiotemporal scales, but the exact pathways and mechanisms remain incompletely understood. In this paper, we establish a large-scale neuronal network model of primary visual cortex with layer 2/3 to study how gamma oscillation properties are modulated by stimulus size and especially how long-range connections affect the modulation as realistic neuronal properties and spatial distributions of synaptic connections are considered. It is shown that long-range horizontal synaptic connections are sufficient to produce dimensional modulation of firing rates and gamma oscillations. In particular, with increasing grating stimulus size, the firing rate increases and then decreases, the peak frequency of gamma oscillations decreases and the spectral power increases. These are consistent with biological experimental observations. Furthermore, we explain in detail how the number and spatial distribution of long-range connections affect the size modulation of gamma oscillations by using the analysis of neuronal firing activity and synaptic current fluctuations. Our results provide a mechanism explanation for size modulation of gamma oscillations in the primary visual cortex and reveal the important and unique role played by long-range connections, which contributes to a deeper understanding of the cognitive function of gamma oscillations in visual cortex.
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Affiliation(s)
- Hao Yang
- College of Information Science and Technology, Donghua University, Shanghai, China
| | - Fang Han
- College of Information Science and Technology, Donghua University, Shanghai, China
| | - Qingyun Wang
- Department of Dynamics and Control, Beihang University, Beijing, China
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4
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Chen X, Cramer SR, Chan DCY, Han X, Zhang N. Sequential deactivation across the thalamus-hippocampus-mPFC pathway during loss of consciousness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.20.594986. [PMID: 38826282 PMCID: PMC11142108 DOI: 10.1101/2024.05.20.594986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
How consciousness is lost in states such as sleep or anesthesia remains a mystery. To gain insight into this phenomenon, we conducted concurrent recordings of electrophysiology signals in the anterior cingulate cortex and whole-brain functional magnetic resonance imaging (fMRI) in rats exposed to graded propofol, undergoing the transition from consciousness to unconsciousness. Our results reveal that upon the loss of consciousness (LOC), as indicated by the loss of righting reflex, there is a sharp increase in low-frequency power of the electrophysiological signal. Additionally, simultaneously measured fMRI signals exhibit a cascade of deactivation across a pathway including the hippocampus, thalamus, and medial prefrontal cortex (mPFC) surrounding the moment of LOC, followed by a broader increase in brain activity across the cortex during sustained unconsciousness. Furthermore, sliding window analysis demonstrates a temporary increase in synchrony of fMRI signals across the hippocampus-thalamus-mPFC pathway preceding LOC. These data suggest that LOC might be triggered by sequential activities in the hippocampus, thalamus and mPFC, while wide-spread activity increases in other cortical regions commonly observed during anesthesia-induced unconsciousness might be a consequence, rather than a cause of LOC. Taken together, our study identifies a cascade of neural events unfolding as the brain transitions into unconsciousness, offering critical insight into the systems-level neural mechanisms underpinning LOC.
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5
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Whyte CJ, Redinbaugh MJ, Shine JM, Saalmann YB. Thalamic contributions to the state and contents of consciousness. Neuron 2024; 112:1611-1625. [PMID: 38754373 DOI: 10.1016/j.neuron.2024.04.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 04/11/2024] [Accepted: 04/17/2024] [Indexed: 05/18/2024]
Abstract
Consciousness can be conceptualized as varying along at least two dimensions: the global state of consciousness and the content of conscious experience. Here, we highlight the cellular and systems-level contributions of the thalamus to conscious state and then argue for thalamic contributions to conscious content, including the integrated, segregated, and continuous nature of our experience. We underscore vital, yet distinct roles for core- and matrix-type thalamic neurons. Through reciprocal interactions with deep-layer cortical neurons, matrix neurons support wakefulness and determine perceptual thresholds, whereas the cortical interactions of core neurons maintain content and enable perceptual constancy. We further propose that conscious integration, segregation, and continuity depend on the convergent nature of corticothalamic projections enabling dimensionality reduction, a thalamic reticular nucleus-mediated divisive normalization-like process, and sustained coherent activity in thalamocortical loops, respectively. Overall, we conclude that the thalamus plays a central topological role in brain structures controlling conscious experience.
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Affiliation(s)
- Christopher J Whyte
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia; Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | | | - James M Shine
- Centre for Complex Systems, The University of Sydney, Sydney, NSW, Australia; Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia
| | - Yuri B Saalmann
- Department of Psychology, University of Wisconsin - Madison, Madison, WI, USA; Wisconsin National Primate Research Center, Madison, WI, USA
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6
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Koller DP, Schirner M, Ritter P. Human connectome topology directs cortical traveling waves and shapes frequency gradients. Nat Commun 2024; 15:3570. [PMID: 38670965 PMCID: PMC11053146 DOI: 10.1038/s41467-024-47860-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 04/09/2024] [Indexed: 04/28/2024] Open
Abstract
Traveling waves and neural oscillation frequency gradients are pervasive in the human cortex. While the direction of traveling waves has been linked to brain function and dysfunction, the factors that determine this direction remain elusive. We hypothesized that structural connectivity instrength gradients - defined as the gradually varying sum of incoming connection strengths across the cortex - could shape both traveling wave direction and frequency gradients. We confirm the presence of instrength gradients in the human connectome across diverse cohorts and parcellations. Using a cortical network model, we demonstrate how these instrength gradients direct traveling waves and shape frequency gradients. Our model fits resting-state MEG functional connectivity best in a regime where instrength-directed traveling waves and frequency gradients emerge. We further show how structural subnetworks of the human connectome generate opposing wave directions and frequency gradients observed in the alpha and beta bands. Our findings suggest that structural connectivity instrength gradients affect both traveling wave direction and frequency gradients.
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Grants
- P.R. acknowledges funding from the following sources: Digital Europe Grant TEF-Health # 101100700, H2020 Research and Innovation Action Grant Human Brain Project SGA2 785907, H2020 Research and Innovation Action Grant Human Brain Project SGA3 945539, H2020 Research and Innovation Action Grant EOSC VirtualBrainCloud 826421, H2020 Research and Innovation Action Grant AISN 101057655, H2020 Research Infrastructures Grant EBRAINS-PREP 101079717, H2020 European Innovation Council PHRASE 101058240, H2020 Research Infrastructures Grant EBRAIN-Health 101058516, H2020 European Research Council Grant ERC BrainModes 683049, JPND ERA PerMed PatternCog 2522FSB904, Berlin Institute of Health & Foundation Charité, Johanna Quandt Excellence Initiative, German Research Foundation SFB 1436 (project ID 425899996), German Research Foundation SFB 1315 (project ID 327654276), German Research Foundation SFB 936 (project ID 178316478), German Research Foundation SFB-TRR 295 (project ID 424778381) German Research Foundation SPP Computational Connectomics RI 2073/6-1, RI 2073/10-2, RI 2073/9-1.
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Affiliation(s)
- Dominik P Koller
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| | - Michael Schirner
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany
| | - Petra Ritter
- Berlin Institute of Health (BIH) at Charité - Universitätsmedizin Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Department of Neurology with Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin and Humboldt Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Bernstein Focus State Dependencies of Learning and Bernstein Center for Computational Neuroscience, 10115, Berlin, Germany.
- Einstein Center for Neuroscience Berlin, Charitéplatz 1, 10117, Berlin, Germany.
- Einstein Center Digital Future, Wilhelmstraße 67, 10117, Berlin, Germany.
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7
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Ohm DT, Xie SX, Capp N, Arezoumandan S, Cousins KAQ, Rascovsky K, Wolk DA, Van Deerlin VM, Lee EB, McMillan CT, Irwin DJ. Cytoarchitectonic gradients of laminar degeneration in behavioral variant frontotemporal dementia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.05.588259. [PMID: 38644997 PMCID: PMC11030243 DOI: 10.1101/2024.04.05.588259] [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
Behavioral variant frontotemporal dementia (bvFTD) is a clinical syndrome primarily caused by either tau (bvFTD-tau) or TDP-43 (bvFTD-TDP) proteinopathies. We previously found lower cortical layers and dorsolateral regions accumulate greater tau than TDP-43 pathology; however, patterns of laminar neurodegeneration across diverse cytoarchitecture in bvFTD is understudied. We hypothesized that bvFTD-tau and bvFTD-TDP have distinct laminar distributions of pyramidal neurodegeneration along cortical gradients, a topologic order of cytoarchitectonic subregions based on increasing pyramidal density and laminar differentiation. Here, we tested this hypothesis in a frontal cortical gradient consisting of five cytoarchitectonic types (i.e., periallocortex, agranular mesocortex, dysgranular mesocortex, eulaminate-I isocortex, eulaminate-II isocortex) spanning anterior cingulate, paracingulate, orbitofrontal, and mid-frontal gyri in bvFTD-tau (n=27), bvFTD-TDP (n=47), and healthy controls (HC; n=32). We immunostained all tissue for total neurons (NeuN; neuronal-nuclear protein) and pyramidal neurons (SMI32; non-phosphorylated neurofilament) and digitally quantified NeuN-immunoreactivity (ir) and SMI32-ir in supragranular II-III, infragranular V-VI, and all I-VI layers in each cytoarchitectonic type. We used linear mixed-effects models adjusted for demographic and biologic variables to compare SMI32-ir between groups and examine relationships with the cortical gradient, long-range pathways, and clinical symptoms. We found regional and laminar distributions of SMI32-ir expected for HC, validating our measures within the cortical gradient framework. While SMI32-ir loss was not related to the cortical gradient in bvFTD-TDP, SMI32-ir progressively decreased along the cortical gradient of bvFTD-tau and included greater SMI32-ir loss in supragranular eulaminate-II isocortex in bvFTD-tau vs bvFTD-TDP ( p =0.039). In a structural model for long-range laminar connectivity between infragranular mesocortex and supragranular isocortex, we found a larger laminar ratio of mesocortex-to-isocortex SMI32-ir in bvFTD-tau vs bvFTD-TDP ( p =0.019), suggesting select long-projecting pathways may contribute to isocortical-predominant degeneration in bvFTD-tau. In cytoarchitectonic types with the highest NeuN-ir, we found lower SMI32-ir in bvFTD-tau vs bvFTD-TDP ( p =0.047), suggesting pyramidal neurodegeneration may occur earlier in bvFTD-tau. Lastly, we found that reduced SMI32-ir related to behavioral severity and frontal-mediated letter fluency, not temporal-mediated confrontation naming, demonstrating the clinical relevance and specificity of frontal pyramidal neurodegeneration to bvFTD-related symptoms. Our data suggest loss of neurofilament-rich pyramidal neurons is a clinically relevant feature of bvFTD that selectively worsens along a frontal cortical gradient in bvFTD-tau, not bvFTD-TDP. Therefore, tau-mediated degeneration may preferentially involve pyramidal-rich layers that connect more distant cytoarchitectonic types. Moreover, the hierarchical arrangement of cytoarchitecture along cortical gradients may be an important neuroanatomical framework for identifying which types of cells and pathways are differentially involved between proteinopathies.
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8
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Kanayama H, Tominaga T, Tominaga Y, Kato N, Yoshimura H. Action of GABAB receptor on local network oscillation in somatosensory cortex of oral part: focusing on NMDA receptor. J Physiol Sci 2024; 74:16. [PMID: 38475711 DOI: 10.1186/s12576-024-00911-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 03/01/2024] [Indexed: 03/14/2024]
Abstract
The balance of activity between glutamatergic and GABAergic networks is particularly important for oscillatory neural activities in the brain. Here, we investigated the roles of GABAB receptors in network oscillation in the oral somatosensory cortex (OSC), focusing on NMDA receptors. Neural oscillation at the frequency of 8-10 Hz was elicited in rat brain slices after caffeine application. Oscillations comprised a non-NMDA receptor-dependent initial phase and a later NMDA receptor-dependent oscillatory phase, with the oscillator located in the upper layer of the OSC. Baclofen was applied to investigate the actions of GABAB receptors. The later NMDA receptor-dependent oscillatory phase completely disappeared, but the initial phase did not. These results suggest that GABAB receptors mainly act on NMDA receptor, in which metabotropic actions of GABAB receptors may contribute to the attenuation of NMDA receptor activities. A regulatory system for network oscillation involving GABAB receptors may be present in the OSC.
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Affiliation(s)
- Hiroyuki Kanayama
- Department of Molecular Oral Physiology, Institute of Biomedical Sciences, Tokushima University Graduate School, 3-18-15 Kuramoto, Tokushima, 770-8504, Japan
- Department of Oral and Maxillofacial Surgery, National Hospital Organization Osaka National Hospital, Osaka, 540-0006, Japan
| | - Takashi Tominaga
- Institute of Neuroscience, Tokushima Bunri University, Shido, Kagawa, 769-2123, Japan
| | - Yoko Tominaga
- Institute of Neuroscience, Tokushima Bunri University, Shido, Kagawa, 769-2123, Japan
| | - Nobuo Kato
- Department of Physiology, Kanazawa Medical University, Uchinada-Cho, Ishikawa, 920-0293, Japan
| | - Hiroshi Yoshimura
- Department of Molecular Oral Physiology, Institute of Biomedical Sciences, Tokushima University Graduate School, 3-18-15 Kuramoto, Tokushima, 770-8504, Japan.
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9
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Mendoza-Halliday D, Major AJ, Lee N, Lichtenfeld MJ, Carlson B, Mitchell B, Meng PD, Xiong YS, Westerberg JA, Jia X, Johnston KD, Selvanayagam J, Everling S, Maier A, Desimone R, Miller EK, Bastos AM. A ubiquitous spectrolaminar motif of local field potential power across the primate cortex. Nat Neurosci 2024; 27:547-560. [PMID: 38238431 PMCID: PMC10917659 DOI: 10.1038/s41593-023-01554-7] [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: 11/22/2022] [Accepted: 12/13/2023] [Indexed: 03/08/2024]
Abstract
The mammalian cerebral cortex is anatomically organized into a six-layer motif. It is currently unknown whether a corresponding laminar motif of neuronal activity patterns exists across the cortex. Here we report such a motif in the power of local field potentials (LFPs). Using laminar probes, we recorded LFPs from 14 cortical areas across the cortical hierarchy in five macaque monkeys. The laminar locations of recordings were histologically identified by electrolytic lesions. Across all areas, we found a ubiquitous spectrolaminar pattern characterized by an increasing deep-to-superficial layer gradient of high-frequency power peaking in layers 2/3 and an increasing superficial-to-deep gradient of alpha-beta power peaking in layers 5/6. Laminar recordings from additional species showed that the spectrolaminar pattern is highly preserved among primates-macaque, marmoset and human-but more dissimilar in mouse. Our results suggest the existence of a canonical layer-based and frequency-based mechanism for cortical computation.
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Affiliation(s)
- Diego Mendoza-Halliday
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Alex James Major
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Noah Lee
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | | | - Brock Carlson
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Blake Mitchell
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Patrick D Meng
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
| | - Yihan Sophy Xiong
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Jacob A Westerberg
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
- Department of Vision and Cognition, Netherlands Institute for Neuroscience, Royal Netherlands Academy of Arts and Sciences, Amsterdam, The Netherlands
| | - Xiaoxuan Jia
- School of Life Sciences, Tsinghua University, Beijing, China
- IDG/McGovern Institute for Brain Research, Tsinghua University, Beijing, China
| | - Kevin D Johnston
- Graduate Program in Neuroscience, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - Janahan Selvanayagam
- Graduate Program in Neuroscience, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, Western University, London, ON, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON, Canada
| | - Alexander Maier
- Department of Psychology, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Robert Desimone
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Earl K Miller
- The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - André M Bastos
- Department of Psychology, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Vision Research Center, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA.
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10
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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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11
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Zhang Q, Lu H, Wang J, Yang T, Bi W, Zeng Y, Yu B. Hierarchical rhythmic propagation of corticothalamic interactions for consciousness: A computational study. Comput Biol Med 2024; 169:107843. [PMID: 38141448 DOI: 10.1016/j.compbiomed.2023.107843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 11/22/2023] [Accepted: 12/11/2023] [Indexed: 12/25/2023]
Abstract
Clarifying the mechanisms of loss and recovery of consciousness in the brain is a major challenge in neuroscience, and research on the spatiotemporal organization of rhythms at the brain region scale at different levels of consciousness remains scarce. By applying computational neuroscience, an extended corticothalamic network model was developed in this study to simulate the altered states of consciousness induced by different concentration levels of propofol. The cortex area containing oscillation spread from posterior to anterior in four successive time stages, defining four groups of brain regions. A quantitative analysis showed that hierarchical rhythm propagation was mainly due to heterogeneity in the inter-brain region connections. These results indicate that the proposed model is an anatomically data-driven testbed and a simulation platform with millisecond resolution. It facilitates understanding of activity coordination across multiple areas of the conscious brain and the mechanisms of action of anesthetics in terms of brain regions.
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Affiliation(s)
- Qian Zhang
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Han Lu
- Department of Anesthesiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Jihang Wang
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Taoyi Yang
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Weida Bi
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China
| | - Yi Zeng
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, 100049, China; Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Buwei Yu
- Department of Anesthesiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
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12
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Ding X, Froudist-Walsh S, Jaramillo J, Jiang J, Wang XJ. Cell type-specific connectome predicts distributed working memory activity in the mouse brain. eLife 2024; 13:e85442. [PMID: 38174734 PMCID: PMC10807864 DOI: 10.7554/elife.85442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 12/14/2023] [Indexed: 01/05/2024] Open
Abstract
Recent advances in connectomics and neurophysiology make it possible to probe whole-brain mechanisms of cognition and behavior. We developed a large-scale model of the multiregional mouse brain for a cardinal cognitive function called working memory, the brain's ability to internally hold and process information without sensory input. The model is built on mesoscopic connectome data for interareal cortical connections and endowed with a macroscopic gradient of measured parvalbumin-expressing interneuron density. We found that working memory coding is distributed yet exhibits modularity; the spatial pattern of mnemonic representation is determined by long-range cell type-specific targeting and density of cell classes. Cell type-specific graph measures predict the activity patterns and a core subnetwork for memory maintenance. The model shows numerous attractor states, which are self-sustained internal states (each engaging a distinct subset of areas). This work provides a framework to interpret large-scale recordings of brain activity during cognition, while highlighting the need for cell type-specific connectomics.
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Affiliation(s)
- Xingyu Ding
- Center for Neural Science, New York UniversityNew YorkUnited States
| | - Sean Froudist-Walsh
- Center for Neural Science, New York UniversityNew YorkUnited States
- Bristol Computational Neuroscience Unit, School of Engineering Mathematics and Technology, University of BristolBristolUnited Kingdom
| | - Jorge Jaramillo
- Center for Neural Science, New York UniversityNew YorkUnited States
- Campus Institute for Dynamics of Biological Networks, University of GöttingenGöttingenGermany
| | - Junjie Jiang
- Center for Neural Science, New York UniversityNew YorkUnited States
- The Key Laboratory of Biomedical Information Engineering of Ministry of Education,Institute of Health and Rehabilitation Science,School of Life Science and Technology, Research Center for Brain-inspired Intelligence, Xi’an Jiaotong UniversityXi'anChina
| | - Xiao-Jing Wang
- Center for Neural Science, New York UniversityNew YorkUnited States
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13
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Antono JE, Dang S, Auksztulewicz R, Pooresmaeili A. Distinct Patterns of Connectivity between Brain Regions Underlie the Intra-Modal and Cross-Modal Value-Driven Modulations of the Visual Cortex. J Neurosci 2023; 43:7361-7375. [PMID: 37684031 PMCID: PMC10621764 DOI: 10.1523/jneurosci.0355-23.2023] [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: 02/24/2023] [Revised: 07/30/2023] [Accepted: 08/26/2023] [Indexed: 09/10/2023] Open
Abstract
Past reward associations may be signaled from different sensory modalities; however, it remains unclear how different types of reward-associated stimuli modulate sensory perception. In this human fMRI study (female and male participants), a visual target was simultaneously presented with either an intra- (visual) or a cross-modal (auditory) cue that was previously associated with rewards. We hypothesized that, depending on the sensory modality of the cues, distinct neural mechanisms underlie the value-driven modulation of visual processing. Using a multivariate approach, we confirmed that reward-associated cues enhanced the target representation in early visual areas and identified the brain valuation regions. Then, using an effective connectivity analysis, we tested three possible patterns of connectivity that could underlie the modulation of the visual cortex: a direct pathway from the frontal valuation areas to the visual areas, a mediated pathway through the attention-related areas, and a mediated pathway that additionally involved sensory association areas. We found evidence for the third model demonstrating that the reward-related information in both sensory modalities is communicated across the valuation and attention-related brain regions. Additionally, the superior temporal areas were recruited when reward was cued cross-modally. The strongest dissociation between the intra- and cross-modal reward-driven effects was observed at the level of the feedforward and feedback connections of the visual cortex estimated from the winning model. These results suggest that, in the presence of previously rewarded stimuli from different sensory modalities, a combination of domain-general and domain-specific mechanisms are recruited across the brain to adjust the visual perception.SIGNIFICANCE STATEMENT Reward has a profound effect on perception, but it is not known whether shared or disparate mechanisms underlie the reward-driven effects across sensory modalities. In this human fMRI study, we examined the reward-driven modulation of the visual cortex by visual (intra-modal) and auditory (cross-modal) reward-associated cues. Using a model-based approach to identify the most plausible pattern of inter-regional effective connectivity, we found that higher-order areas involved in the valuation and attentional processing were recruited by both types of rewards. However, the pattern of connectivity between these areas and the early visual cortex was distinct between the intra- and cross-modal rewards. This evidence suggests that, to effectively adapt to the environment, reward signals may recruit both domain-general and domain-specific mechanisms.
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Affiliation(s)
- Jessica Emily Antono
- Perception and Cognition Lab, European Neuroscience Institute Goettingen-A Joint Initiative of the University Medical Center Goettingen and the Max-Planck-Society, Germany, Goettingen, 37077, Germany
| | - Shilpa Dang
- Perception and Cognition Lab, European Neuroscience Institute Goettingen-A Joint Initiative of the University Medical Center Goettingen and the Max-Planck-Society, Germany, Goettingen, 37077, Germany
- School of Artificial Intelligence and Data Science, Indian Institute of Technology Jodhpur, Karwar, Jodhpur 342030, India
| | - Ryszard Auksztulewicz
- Center for Cognitive Neuroscience Berlin, Free University Berlin, Berlin, 14195, Germany
| | - Arezoo Pooresmaeili
- Perception and Cognition Lab, European Neuroscience Institute Goettingen-A Joint Initiative of the University Medical Center Goettingen and the Max-Planck-Society, Germany, Goettingen, 37077, Germany
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14
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Arab F, Rostami S, Dehghani-Habibabadi M, Mateos DM, Braddell R, Scholkmann F, Ismail Zibaii M, Rodrigues S, Salari V, Safari MS. Effects of optogenetic and visual stimulation on gamma activity in the visual cortex. Neurosci Lett 2023; 816:137474. [PMID: 37690497 DOI: 10.1016/j.neulet.2023.137474] [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: 04/12/2023] [Revised: 07/22/2023] [Accepted: 09/07/2023] [Indexed: 09/12/2023]
Abstract
Studying brain functions and activity during gamma oscillations can be a challenge because it requires careful planning to create the necessary conditions for a controlled experiment. Such an experiment consists of placing the brain into a gamma state and investigating cognitive processing with a careful design. Cortical oscillations in the gamma frequency range (30-80 Hz) play an essential role in a variety of cognitive processes, including visual processing and cognition. The present study aims to investigate the effects of a visual stimulus on the primary visual cortex under gamma oscillations. Specifically, we sought to explore the behavior of gamma oscillations triggered by optogenetic stimulation in the II and IV layers of the visual cortex, both with and without concurrent visual stimulation. Our results show that optogenetic stimulation increases the power of gamma oscillation in both layers of the visual cortex. However, the combined stimuli resulted in a reduction of gamma power in layer II and an increase and reinforcement in gamma power in layer IV. Modelling the results with the Wilson-Cowan model suggests changes in the input of the excitatory population due to the combined stimuli. In addition, our analysis of the data using the Lempel-Ziv complexity method supports our interpretations from the modeling. Thus, our results suggest that optogenetic stimulation enhances low gamma power in both layers of the visual cortex, while simultaneous visual stimulation has differing effects on the two layers, reducing gamma power in layer II and increasing it in layer IV.
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Affiliation(s)
- Fereshteh Arab
- Department of Physics, Isfahan University of Technology, Isfahan, Iran
| | - Sareh Rostami
- Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Diego M Mateos
- Consejo Nacional de Investigaciones Cientıficas y Tecnicas (CONICET), Argentina; Facultad de Ciencia y Tecnologıa. Universidad Aut ́onoma de Entre Ŕıos (UADER), Oro Verde, Entre Ŕıos, Argentina; Instituto de Matem ́atica Aplicada del Litoral (IMAL-CONICET-UNL), CCT CONICET, Santa Fe, Argentina
| | - Roisin Braddell
- BCAM - Basque Center for Applied Mathematics, Alameda de Mazarredo, Bilbao, Basque Country, Spain
| | - Felix Scholkmann
- Biomedical Optics Research Laboratory, Department of Neonatology, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | | | - Serafim Rodrigues
- BCAM - Basque Center for Applied Mathematics, Alameda de Mazarredo, Bilbao, Basque Country, Spain
| | - Vahid Salari
- BCAM - Basque Center for Applied Mathematics, Alameda de Mazarredo, Bilbao, Basque Country, Spain; Department of Physics and Astronomy, University of Calgary, Calgary T2N 1N4, AB, Canada.
| | - Mir-Shahram Safari
- Neuroscience Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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15
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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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16
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Messé A, Hollensteiner KJ, Delettre C, Dell-Brown LA, Pieper F, Nentwig LJ, Galindo-Leon EE, Larrat B, Mériaux S, Mangin JF, Reillo I, de Juan Romero C, Borrell V, Engler G, Toro R, Engel AK, Hilgetag CC. Structural basis of envelope and phase intrinsic coupling modes in the cerebral cortex. Neuroimage 2023; 276:120212. [PMID: 37269959 PMCID: PMC10300241 DOI: 10.1016/j.neuroimage.2023.120212] [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: 12/09/2022] [Revised: 05/09/2023] [Accepted: 05/30/2023] [Indexed: 06/05/2023] Open
Abstract
Intrinsic coupling modes (ICMs) can be observed in ongoing brain activity at multiple spatial and temporal scales. Two families of ICMs can be distinguished: phase and envelope ICMs. The principles that shape these ICMs remain partly elusive, in particular their relation to the underlying brain structure. Here we explored structure-function relationships in the ferret brain between ICMs quantified from ongoing brain activity recorded with chronically implanted micro-ECoG arrays and structural connectivity (SC) obtained from high-resolution diffusion MRI tractography. Large-scale computational models were used to explore the ability to predict both types of ICMs. Importantly, all investigations were conducted with ICM measures that are sensitive or insensitive to volume conduction effects. The results show that both types of ICMs are significantly related to SC, except for phase ICMs when using measures removing zero-lag coupling. The correlation between SC and ICMs increases with increasing frequency which is accompanied by reduced delays. Computational models produced results that were highly dependent on the specific parameter settings. The most consistent predictions were derived from measures solely based on SC. Overall, the results demonstrate that patterns of cortical functional coupling as reflected in both phase and envelope ICMs are both related, albeit to different degrees, to the underlying structural connectivity in the cerebral cortex.
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Affiliation(s)
- Arnaud Messé
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany.
| | - Karl J Hollensteiner
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Céline Delettre
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany; Unité de Neuroanatomie Appliquée et Théorique, Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, Université Paris Cité, 25-28 rue du Dr Roux, Paris 75015, France
| | - Leigh-Anne Dell-Brown
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Florian Pieper
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Lena J Nentwig
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Edgar E Galindo-Leon
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Benoît Larrat
- NeuroSpin, CEA, Paris-Saclay University, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Sébastien Mériaux
- NeuroSpin, CEA, Paris-Saclay University, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Jean-François Mangin
- NeuroSpin, CEA, Paris-Saclay University, Centre d'études de Saclay, Bâtiment 145, Gif-sur-Yvette 91191, France
| | - Isabel Reillo
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d'Alacant, Av. Santiago Ramón y Cajal s/n, Sant Joan d'Alacant 03550, Spain
| | - Camino de Juan Romero
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d'Alacant, Av. Santiago Ramón y Cajal s/n, Sant Joan d'Alacant 03550, Spain
| | - Víctor Borrell
- Developmental Neurobiology Unit, Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas - Universidad Miguel Hernández, Sant Joan d'Alacant, Av. Santiago Ramón y Cajal s/n, Sant Joan d'Alacant 03550, Spain
| | - Gerhard Engler
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Roberto Toro
- Unité de Neuroanatomie Appliquée et Théorique, Unité de Génétique Humaine et Fonctions Cognitives, Institut Pasteur, Université Paris Cité, 25-28 rue du Dr Roux, Paris 75015, France; Center for Research and Interdisciplinarity, Paris Descartes University, 24, rue du Faubourg Saint Jacques, Paris 75014, France
| | - Andreas K Engel
- Department of Neurophysiology and Pathophysiology, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany
| | - Claus C Hilgetag
- Institute of Computational Neuroscience, Hamburg Center of Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg University, Martinistraße 52, Hamburg 20246, Germany; Department of Health Sciences, Boston University, 635 Commonwealth Avenue, Boston, Massachusetts 02215, USA
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17
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Klaver LMF, Brinkhof LP, Sikkens T, Casado-Román L, Williams AG, van Mourik-Donga L, Mejías JF, Pennartz CMA, Bosman CA. Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness. Cereb Cortex 2023; 33:7564-7581. [PMID: 36935096 PMCID: PMC10267643 DOI: 10.1093/cercor/bhad061] [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: 05/31/2022] [Revised: 02/11/2023] [Accepted: 02/14/2023] [Indexed: 03/21/2023] Open
Abstract
Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12 Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80 Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18 Hz) and high-frequency (>80 Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.
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Affiliation(s)
- Lianne M F Klaver
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lotte P Brinkhof
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Tom Sikkens
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Lorena Casado-Román
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Alex G Williams
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Laura van Mourik-Donga
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
| | - Jorge F Mejías
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Cyriel M A Pennartz
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
| | - Conrado A Bosman
- Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands
- Research Priority Program Brain and Cognition, University of Amsterdam, Amsterdam, The Netherlands
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18
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Draganov M, Galiano-Landeira J, Doruk Camsari D, Ramírez JE, Robles M, Chanes L. Noninvasive modulation of predictive coding in humans: causal evidence for frequency-specific temporal dynamics. Cereb Cortex 2023:7156779. [PMID: 37154618 DOI: 10.1093/cercor/bhad127] [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: 01/13/2023] [Revised: 03/17/2023] [Accepted: 03/18/2023] [Indexed: 05/10/2023] Open
Abstract
Increasing evidence indicates that the brain predicts sensory input based on past experiences, importantly constraining how we experience the world. Despite a growing interest on this framework, known as predictive coding, most of such approaches to multiple psychological domains continue to be theoretical or primarily provide correlational evidence. We here explored the neural basis of predictive processing using noninvasive brain stimulation and provide causal evidence of frequency-specific modulations in humans. Participants received 20 Hz (associated with top-down/predictions), 50 Hz (associated with bottom-up/prediction errors), or sham transcranial alternating current stimulation on the left dorsolateral prefrontal cortex while performing a social perception task in which facial expression predictions were induced and subsequently confirmed or violated. Left prefrontal 20 Hz stimulation reinforced stereotypical predictions. In contrast, 50 Hz and sham stimulation failed to yield any significant behavioral effects. Moreover, the frequency-specific effect observed was further supported by electroencephalography data, which showed a boost of brain activity at the stimulated frequency band. These observations provide causal evidence for how predictive processing may be enabled in the human brain, setting up a needed framework to understand how it may be disrupted across brain-related conditions and potentially restored through noninvasive methods.
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Affiliation(s)
- Metodi Draganov
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Jordi Galiano-Landeira
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Deniz Doruk Camsari
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, United States
| | - Jairo-Enrique Ramírez
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
| | - Marta Robles
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
- Department of Psychiatry and Psychotherapy, Medical Faculty, LMU Munich, Munich 80336, Germany
| | - Lorena Chanes
- Department of Clinical and Health Psychology, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
- Institut de Neurociències, Universitat Autònoma de Barcelona, Barcelona 08193, Spain
- Serra Húnter Programme, Generalitat de Catalunya, Barcelona 08002, Spain
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19
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Grosu GF, Hopp AV, Moca VV, Bârzan H, Ciuparu A, Ercsey-Ravasz M, Winkel M, Linde H, Mureșan RC. The fractal brain: scale-invariance in structure and dynamics. Cereb Cortex 2023; 33:4574-4605. [PMID: 36156074 PMCID: PMC10110456 DOI: 10.1093/cercor/bhac363] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/09/2022] [Accepted: 08/10/2022] [Indexed: 11/12/2022] Open
Abstract
The past 40 years have witnessed extensive research on fractal structure and scale-free dynamics in the brain. Although considerable progress has been made, a comprehensive picture has yet to emerge, and needs further linking to a mechanistic account of brain function. Here, we review these concepts, connecting observations across different levels of organization, from both a structural and functional perspective. We argue that, paradoxically, the level of cortical circuits is the least understood from a structural point of view and perhaps the best studied from a dynamical one. We further link observations about scale-freeness and fractality with evidence that the environment provides constraints that may explain the usefulness of fractal structure and scale-free dynamics in the brain. Moreover, we discuss evidence that behavior exhibits scale-free properties, likely emerging from similarly organized brain dynamics, enabling an organism to thrive in an environment that shares the same organizational principles. Finally, we review the sparse evidence for and try to speculate on the functional consequences of fractality and scale-freeness for brain computation. These properties may endow the brain with computational capabilities that transcend current models of neural computation and could hold the key to unraveling how the brain constructs percepts and generates behavior.
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Affiliation(s)
- George F Grosu
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | | | - Vasile V Moca
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
| | - Harald Bârzan
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | - Andrei Ciuparu
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Electronics, Telecommunications and Information Technology, Technical University of Cluj-Napoca, Str. Memorandumului 28, 400114 Cluj-Napoca, Romania
| | - Maria Ercsey-Ravasz
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Faculty of Physics, Babes-Bolyai University, Str. Mihail Kogalniceanu 1, 400084 Cluj-Napoca, Romania
| | - Mathias Winkel
- Merck KGaA, Frankfurter Straße 250, 64293 Darmstadt, Germany
| | - Helmut Linde
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
- Merck KGaA, Frankfurter Straße 250, 64293 Darmstadt, Germany
| | - Raul C Mureșan
- Department of Experimental and Theoretical Neuroscience, Transylvanian Institute of Neuroscience, Str. Ploiesti 33, 400157 Cluj-Napoca, Romania
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20
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Son S, Moon J, Kim YJ, Kang MS, Lee J. Frontal-to-visual information flow explains predictive motion tracking. Neuroimage 2023; 269:119914. [PMID: 36736637 DOI: 10.1016/j.neuroimage.2023.119914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/28/2023] [Accepted: 01/30/2023] [Indexed: 02/04/2023] Open
Abstract
Predictive tracking demonstrates our ability to maintain a line of vision on moving objects even when they temporarily disappear. Models of smooth pursuit eye movements posit that our brain achieves this ability by directly streamlining motor programming from continuously updated sensory motion information. To test this hypothesis, we obtained sensory motion representation from multivariate electroencephalogram activity while human participants covertly tracked a temporarily occluded moving stimulus with their eyes remaining stationary at the fixation point. The sensory motion representation of the occluded target evolves to its maximum strength at the expected timing of reappearance, suggesting a timely modulation of the internal model of the visual target. We further characterize the spatiotemporal dynamics of the task-relevant motion information by computing the phase gradients of slow oscillations. We discovered a predominant posterior-to-anterior phase gradient immediately after stimulus occlusion; however, at the expected timing of reappearance, the axis reverses the gradient, becoming anterior-to-posterior. The behavioral bias of smooth pursuit eye movements, which is a signature of the predictive process of the pursuit, was correlated with the posterior division of the gradient. These results suggest that the sensory motion area modulated by the prediction signal is involved in updating motor programming.
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Affiliation(s)
- Sangkyu Son
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, South Korea
| | - Joonsik Moon
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea
| | - Yee-Joon Kim
- Center for Cognition and Sociality, Institute for Basic Science (IBS), Daejeon 34141, South Korea
| | - Min-Suk Kang
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea; Department of Psychology, Sungkyunkwan University, Seoul 03063, South Korea.
| | - Joonyeol Lee
- Center for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon 16419, South Korea; Department of Biomedical Engineering, Sungkyunkwan University, Suwon 16419, South Korea; Department of Intelligent Precision Healthcare Convergence, Sungkyunkwan University, Suwon 16419, South Korea.
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21
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Trepka EB, Zhu S, Xia R, Chen X, Moore T. Functional interactions among neurons within single columns of macaque V1. eLife 2022; 11:e79322. [PMID: 36321687 PMCID: PMC9662816 DOI: 10.7554/elife.79322] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 10/30/2022] [Indexed: 11/16/2022] Open
Abstract
Recent developments in high-density neurophysiological tools now make it possible to record from hundreds of single neurons within local, highly interconnected neural networks. Among the many advantages of such recordings is that they dramatically increase the quantity of identifiable, functional interactions between neurons thereby providing an unprecedented view of local circuits. Using high-density, Neuropixels recordings from single neocortical columns of primary visual cortex in nonhuman primates, we identified 1000s of functionally interacting neuronal pairs using established crosscorrelation approaches. Our results reveal clear and systematic variations in the synchrony and strength of functional interactions within single cortical columns. Despite neurons residing within the same column, both measures of interactions depended heavily on the vertical distance separating neuronal pairs, as well as on the similarity of stimulus tuning. In addition, we leveraged the statistical power afforded by the large numbers of functionally interacting pairs to categorize interactions between neurons based on their crosscorrelation functions. These analyses identified distinct, putative classes of functional interactions within the full population. These classes of functional interactions were corroborated by their unique distributions across defined laminar compartments and were consistent with known properties of V1 cortical circuitry, such as the lead-lag relationship between simple and complex cells. Our results provide a clear proof-of-principle for the use of high-density neurophysiological recordings to assess circuit-level interactions within local neuronal networks.
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Affiliation(s)
- Ethan B Trepka
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
- Neurosciences Program, Stanford UniversityStanfordUnited States
| | - Shude Zhu
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Ruobing Xia
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
| | - Xiaomo Chen
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
- Center for Neuroscience, Department of Neurobiology, Physiology, and Behavior, University of California, DavisDavisUnited States
| | - Tirin Moore
- Department of Neurobiology, Howard Hughes Medical Institute, Stanford UniversityStanfordUnited States
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22
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Connectivity concepts in neuronal network modeling. PLoS Comput Biol 2022; 18:e1010086. [PMID: 36074778 PMCID: PMC9455883 DOI: 10.1371/journal.pcbi.1010086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 04/07/2022] [Indexed: 11/19/2022] Open
Abstract
Sustainable research on computational models of neuronal networks requires published models to be understandable, reproducible, and extendable. Missing details or ambiguities about mathematical concepts and assumptions, algorithmic implementations, or parameterizations hinder progress. Such flaws are unfortunately frequent and one reason is a lack of readily applicable standards and tools for model description. Our work aims to advance complete and concise descriptions of network connectivity but also to guide the implementation of connection routines in simulation software and neuromorphic hardware systems. We first review models made available by the computational neuroscience community in the repositories ModelDB and Open Source Brain, and investigate the corresponding connectivity structures and their descriptions in both manuscript and code. The review comprises the connectivity of networks with diverse levels of neuroanatomical detail and exposes how connectivity is abstracted in existing description languages and simulator interfaces. We find that a substantial proportion of the published descriptions of connectivity is ambiguous. Based on this review, we derive a set of connectivity concepts for deterministically and probabilistically connected networks and also address networks embedded in metric space. Beside these mathematical and textual guidelines, we propose a unified graphical notation for network diagrams to facilitate an intuitive understanding of network properties. Examples of representative network models demonstrate the practical use of the ideas. We hope that the proposed standardizations will contribute to unambiguous descriptions and reproducible implementations of neuronal network connectivity in computational neuroscience.
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23
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Han C, Wang T, Wu Y, Li H, Wang E, Zhao X, Cao Q, Qian Q, Wang Y, Dou F, Liu JK, Sun L, Xing D. Compensatory mechanism of attention-deficit/hyperactivity disorder recovery in resting state alpha rhythms. Front Comput Neurosci 2022; 16:883065. [PMID: 36157841 PMCID: PMC9490822 DOI: 10.3389/fncom.2022.883065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/17/2022] [Indexed: 11/13/2022] Open
Abstract
Alpha rhythms in the human electroencephalogram (EEG), oscillating at 8-13 Hz, are located in parieto-occipital cortex and are strongest when awake people close their eyes. It has been suggested that alpha rhythms were related to attention-related functions and mental disorders (e.g., Attention-deficit/hyperactivity disorder (ADHD)). However, many studies have shown inconsistent results on the difference in alpha oscillation between ADHD and control groups. Hence it is essential to verify this difference. In this study, a dataset of EEG recording (128 channel EGI) from 87 healthy controls (HC) and 162 ADHD (141 persisters and 21 remitters) adults in a resting state with their eyes closed was used to address this question and a three-gauss model (summation of baseline and alpha components) was conducted to fit the data. To our surprise, the power of alpha components was not a significant difference among the three groups. Instead, the baseline power of remission and HC group in the alpha band is significantly stronger than that of persister groups. Our results suggest that ADHD recovery may have compensatory mechanisms and many abnormalities in EEG may be due to the influence of behavior rather than the difference in brain signals.
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Affiliation(s)
- Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- College of Life Sciences, Beijing Normal University, Beijing, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Hui Li
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Encong Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Xixi Zhao
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Qingjiu Cao
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Qiujin Qian
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Yufeng Wang
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
| | - Fei Dou
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- College of Life Sciences, Beijing Normal University, Beijing, China
- Beijing Key Laboratory of Genetic Engineering Drugs and Biotechnology, Beijing Normal University, Beijing, China
| | - Jian K. Liu
- School of Computing, University of Leeds, Leeds, United Kingdom
| | - Li Sun
- Peking University Sixth Hospital/Institute of Mental Health, Beijing, China
- National Clinical Research Center for Mental Disorder and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China
- Li Sun,
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- *Correspondence: Dajun Xing,
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24
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Hahn G, Kumar A, Schmidt H, Knösche TR, Deco G. Rate and oscillatory switching dynamics of a multilayer visual microcircuit model. eLife 2022; 11:77594. [PMID: 35994330 PMCID: PMC9395191 DOI: 10.7554/elife.77594] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Accepted: 07/21/2022] [Indexed: 11/16/2022] Open
Abstract
The neocortex is organized around layered microcircuits consisting of a variety of excitatory and inhibitory neuronal types which perform rate- and oscillation-based computations. Using modeling, we show that both superficial and deep layers of the primary mouse visual cortex implement two ultrasensitive and bistable switches built on mutual inhibitory connectivity motives between somatostatin, parvalbumin, and vasoactive intestinal polypeptide cells. The switches toggle pyramidal neurons between high and low firing rate states that are synchronized across layers through translaminar connectivity. Moreover, inhibited and disinhibited states are characterized by low- and high-frequency oscillations, respectively, with layer-specific differences in frequency and power which show asymmetric changes during state transitions. These findings are consistent with a number of experimental observations and embed firing rate together with oscillatory changes within a switch interpretation of the microcircuit.
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Affiliation(s)
- Gerald Hahn
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
| | - Arvind Kumar
- Computational Science and Technology, School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Helmut Schmidt
- Brain Networks Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Thomas R Knösche
- Brain Networks Group, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Institute of Biomedical Engineering and Informatics, Department of Computer Science and Automation, Technische Universität Ilmenau, Ilmenau, Germany
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain.,Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,School of Psychological Sciences, Turner Institute for Brain and Mental Health, Monash University, Melbourne, Australia
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25
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Visual evoked feedforward-feedback traveling waves organize neural activity across the cortical hierarchy in mice. Nat Commun 2022; 13:4754. [PMID: 35963850 PMCID: PMC9376099 DOI: 10.1038/s41467-022-32378-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 07/27/2022] [Indexed: 12/26/2022] Open
Abstract
Sensory processing is distributed among many brain regions that interact via feedforward and feedback signaling. Neuronal oscillations have been shown to mediate intercortical feedforward and feedback interactions. Yet, the macroscopic structure of the multitude of such oscillations remains unclear. Here, we show that simple visual stimuli reliably evoke two traveling waves with spatial wavelengths that cover much of the cerebral hemisphere in awake mice. 30-50 Hz feedforward waves arise in primary visual cortex (V1) and propagate rostrally, while 3-6 Hz feedback waves originate in the association cortex and flow caudally. The phase of the feedback wave modulates the amplitude of the feedforward wave and synchronizes firing between V1 and parietal cortex. Altogether, these results provide direct experimental evidence that visual evoked traveling waves percolate through the cerebral cortex and coordinate neuronal activity across broadly distributed networks mediating visual processing.
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26
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D'Angelo E, Jirsa V. The quest for multiscale brain modeling. Trends Neurosci 2022; 45:777-790. [PMID: 35906100 DOI: 10.1016/j.tins.2022.06.007] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 05/20/2022] [Accepted: 06/21/2022] [Indexed: 01/07/2023]
Abstract
Addressing the multiscale organization of the brain, which is fundamental to the dynamic repertoire of the organ, remains challenging. In principle, it should be possible to model neurons and synapses in detail and then connect them into large neuronal assemblies to explain the relationship between microscopic phenomena, large-scale brain functions, and behavior. It is more difficult to infer neuronal functions from ensemble measurements such as those currently obtained with brain activity recordings. In this article we consider theories and strategies for combining bottom-up models, generated from principles of neuronal biophysics, with top-down models based on ensemble representations of network activity and on functional principles. These integrative approaches are hoped to provide effective multiscale simulations in virtual brains and neurorobots, and pave the way to future applications in medicine and information technologies.
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Affiliation(s)
- Egidio D'Angelo
- Department of Brain and Behavioral Sciences, University of Pavia, and Brain Connectivity Center, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Mondino Foundation, Pavia, Italy.
| | - Viktor Jirsa
- Institut National de la Santé et de la Recherche Médicale (INSERM) Unité 1106, Centre National de la Recherche Scientifique (CNRS), and University of Aix-Marseille, Marseille, France
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27
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Redinbaugh MJ, Afrasiabi M, Phillips JM, Kambi NA, Mohanta S, Raz A, Saalmann YB. Thalamic deep brain stimulation paradigm to reduce consciousness: Cortico-striatal dynamics implicated in mechanisms of consciousness. PLoS Comput Biol 2022; 18:e1010294. [PMID: 35816488 PMCID: PMC9321468 DOI: 10.1371/journal.pcbi.1010294] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 07/26/2022] [Accepted: 06/10/2022] [Indexed: 11/25/2022] Open
Abstract
Anesthetic manipulations provide much-needed causal evidence for neural correlates of consciousness, but non-specific drug effects complicate their interpretation. Evidence suggests that thalamic deep brain stimulation (DBS) can either increase or decrease consciousness, depending on the stimulation target and parameters. The putative role of the central lateral thalamus (CL) in consciousness makes it an ideal DBS target to manipulate circuit-level mechanisms in cortico-striato-thalamic (CST) systems, thereby influencing consciousness and related processes. We used multi-microelectrode DBS targeted to CL in macaques while recording from frontal, parietal, and striatal regions. DBS induced episodes of abnormally long, vacant staring with low-frequency oscillations here termed vacant, perturbed consciousness (VPC). DBS modulated VPC likelihood in a frequency-specific manner. VPC events corresponded to decreases in measures of neural complexity (entropy) and integration (Φ*), proposed indices of consciousness, and substantial changes to communication in CST circuits. During VPC, power spectral density and coherence at low frequencies increased across CST circuits, especially in thalamo-parietal and cortico-striatal pathways. Decreased consciousness and neural integration corresponded to shifts in cortico-striatal network configurations that dissociated parietal and subcortical structures. Overall, the features of VPC and implicated networks were similar to those of absence epilepsy. As this same multi-microelectrode DBS method–but at different stimulation frequencies–can also increase consciousness in anesthetized macaques, it can be used to flexibly address questions of consciousness with limited confounds, as well as inform clinical investigations of other consciousness disorders. Deep brain stimulation (DBS) is an effective treatment for a number of neurological and psychiatric disorders. Recent evidence shows that thalamic DBS can increase consciousness under general anesthesia, and has the potential to be an effective treatment for disorders of consciousness like coma. However, past studies also imply that thalamic DBS can decrease consciousness by producing periods of inactivity with vacant staring. In this study, we use thalamic DBS to induce vacant periods of perturbed consciousness (VPC) while recording from frontal, parietal and subcortical brain areas. Much of modern research on consciousness focuses on cortical contributions, debating if frontal or more posterior areas are more important. We show via machine learning, information theoretic and functional connectivity measures that VPC involves altered neural communication between parietal cortex and subcortical regions, challenging a cortico-centric focus. Further, these mechanisms resemble those associated with absence epilepsy, suggesting a link between this disorder of consciousness and VPC. Finally, occurrence of VPC in our study was stimulation frequency-dependent and influenced by the experimental history of DBS. This provides insight to mechanisms of thalamic DBS, informative for clinical manipulations of consciousness.
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Affiliation(s)
- Michelle J. Redinbaugh
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- * E-mail: (YS); (MJR)
| | - Mohsen Afrasiabi
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Jessica M. Phillips
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Niranjan A. Kambi
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Sounak Mohanta
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
| | - Aeyal Raz
- Department of Anesthesiology, Rambam Health Care Campus, Haifa, Israel; Ruth and Bruce Rappaport Faculty of Medicine, Technion—Israel Institute of Technology, Haifa, Israel
| | - Yuri B. Saalmann
- Department of Psychology, University of Wisconsin-Madison, Madison, Wisconsin, United States of America
- Wisconsin National Primate Research Center, Madison, Wisconsin, United States of America
- * E-mail: (YS); (MJR)
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28
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Wang XJ. Theory of the Multiregional Neocortex: Large-Scale Neural Dynamics and Distributed Cognition. Annu Rev Neurosci 2022; 45:533-560. [PMID: 35803587 DOI: 10.1146/annurev-neuro-110920-035434] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
The neocortex is a complex neurobiological system with many interacting regions. How these regions work together to subserve flexible behavior and cognition has become increasingly amenable to rigorous research. Here, I review recent experimental and theoretical work on the modus operandi of a multiregional cortex. These studies revealed several general principles for the neocortical interareal connectivity, low-dimensional macroscopic gradients of biological properties across cortical areas, and a hierarchy of timescales for information processing. Theoretical work suggests testable predictions regarding differential excitation and inhibition along feedforward and feedback pathways in the cortical hierarchy. Furthermore, modeling of distributed working memory and simple decision-making has given rise to a novel mathematical concept, dubbed bifurcation in space, that potentially explains how different cortical areas, with a canonical circuit organization but gradients of biological heterogeneities, are able to subserve their respective (e.g., sensory coding versus executive control) functions in a modularly organized brain.
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Affiliation(s)
- Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY, USA;
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29
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Petkoski S, Jirsa VK. Normalizing the brain connectome for communication through synchronization. Netw Neurosci 2022; 6:722-744. [PMID: 36607179 PMCID: PMC9810372 DOI: 10.1162/netn_a_00231] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 01/10/2022] [Indexed: 01/10/2023] Open
Abstract
Networks in neuroscience determine how brain function unfolds, and their perturbations lead to psychiatric disorders and brain disease. Brain networks are characterized by their connectomes, which comprise the totality of all connections, and are commonly described by graph theory. This approach is deeply rooted in a particle view of information processing, based on the quantification of informational bits such as firing rates. Oscillations and brain rhythms demand, however, a wave perspective of information processing based on synchronization. We extend traditional graph theory to a dual, particle-wave, perspective, integrate time delays due to finite transmission speeds, and derive a normalization of the connectome. When applied to the database of the Human Connectome Project, it explains the emergence of frequency-specific network cores including the visual and default mode networks. These findings are robust across human subjects (N = 100) and are a fundamental network property within the wave picture. The normalized connectome comprises the particle view in the limit of infinite transmission speeds and opens the applicability of graph theory to a wide range of novel network phenomena, including physiological and pathological brain rhythms. These two perspectives are orthogonal, but not incommensurable, when understood within the novel, here-proposed, generalized framework of structural connectivity.
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Affiliation(s)
- Spase Petkoski
- Aix-Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France,* Corresponding Authors: ;
| | - Viktor K. Jirsa
- Aix-Marseille University, Inserm, INS, Institut de Neurosciences des Systèmes, Marseille, France,* Corresponding Authors: ;
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30
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Tozzi A. Bipolar reasoning in feedback pathways. Biosystems 2022; 215-216:104652. [PMID: 35247481 DOI: 10.1016/j.biosystems.2022.104652] [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: 01/13/2022] [Revised: 02/26/2022] [Accepted: 02/26/2022] [Indexed: 11/18/2022]
Abstract
Instead of the conventional 0 and 1 values, bipolar reasoning uses -1, 0, +1 to describe double-sided judgements in which neutral elements are halfway between positive and negative evaluations (e.g., "uncertain" lies between "impossible" and "totally sure"). We discuss the state-of-the-art in bipolar logics and recall two medieval forerunners, i.e., William of Ockham and Nicholas of Autrecourt, who embodied a bipolar mode of thought that is eminently modern. Starting from the trivial observation that "once a wheat sheaf is sealed and tied up, the packed down straws display the same orientation", we work up a new theory of the bipolar nature of networks, suggesting that orthodromic (i.e., feedforward, bottom-up) projections might be functionally coupled with antidromic (i.e., feedback, top-down) projections via the mathematical apparatus of presheaves/globular sets. When an entrained oscillation such as a neuronal spike propagates from A to B, changes in B might lead to changes in A, providing unexpected antidromic effects. Our account points towards the methodological feasibility of novel neural networks in which message feedback is guaranteed by backpropagation mechanisms endowed in the same feedforward circuits. Bottom-up/top-down transmission at various coarse-grained network levels provides fresh insights in far-flung scientific fields such as object persistence, memory reinforcement, visual recognition, Bayesian inferential circuits and multidimensional activity of the brain. Implying that axonal stimulation by external sources might backpropagate and modify neuronal electric oscillations, our theory also suggests testable previsions concerning the optimal location of transcranial magnetic stimulation's coils in patients affected by drug-resistant epilepsy.
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Affiliation(s)
- Arturo Tozzi
- Center for Nonlinear Science, Department of Physics, University of North Texas, Denton, TX, USA, 1155 Union Circle, #311427, Denton, TX, 76203-5017, USA.
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31
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Siu PH, Müller E, Zerbi V, Aquino K, Fulcher BD. Extracting Dynamical Understanding From Neural-Mass Models of Mouse Cortex. Front Comput Neurosci 2022; 16:847336. [PMID: 35547660 PMCID: PMC9081874 DOI: 10.3389/fncom.2022.847336] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2022] [Accepted: 03/22/2022] [Indexed: 11/13/2022] Open
Abstract
New brain atlases with high spatial resolution and whole-brain coverage have rapidly advanced our knowledge of the brain's neural architecture, including the systematic variation of excitatory and inhibitory cell densities across the mammalian cortex. But understanding how the brain's microscale physiology shapes brain dynamics at the macroscale has remained a challenge. While physiologically based mathematical models of brain dynamics are well placed to bridge this explanatory gap, their complexity can form a barrier to providing clear mechanistic interpretation of the dynamics they generate. In this work, we develop a neural-mass model of the mouse cortex and show how bifurcation diagrams, which capture local dynamical responses to inputs and their variation across brain regions, can be used to understand the resulting whole-brain dynamics. We show that strong fits to resting-state functional magnetic resonance imaging (fMRI) data can be found in surprisingly simple dynamical regimes—including where all brain regions are confined to a stable fixed point—in which regions are able to respond strongly to variations in their inputs, consistent with direct structural connections providing a strong constraint on functional connectivity in the anesthetized mouse. We also use bifurcation diagrams to show how perturbations to local excitatory and inhibitory coupling strengths across the cortex, constrained by cell-density data, provide spatially dependent constraints on resulting cortical activity, and support a greater diversity of coincident dynamical regimes. Our work illustrates methods for visualizing and interpreting model performance in terms of underlying dynamical mechanisms, an approach that is crucial for building explanatory and physiologically grounded models of the dynamical principles that underpin large-scale brain activity.
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Affiliation(s)
- Pok Him Siu
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
| | - Eli Müller
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
| | - Valerio Zerbi
- Neural Control of Movement Lab, D-HEST, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, University and ETH Zurich, Zurich, Switzerland
| | - Kevin Aquino
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
| | - Ben D. Fulcher
- School of Physics, The University of Sydney, Camperdown, NSW, Australia
- *Correspondence: Ben D. Fulcher
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32
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Gepshtein S, Pawar AS, Kwon S, Savel’ev S, Albright TD. Spatially distributed computation in cortical circuits. SCIENCE ADVANCES 2022; 8:eabl5865. [PMID: 35452288 PMCID: PMC9032974 DOI: 10.1126/sciadv.abl5865] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Accepted: 03/03/2022] [Indexed: 06/14/2023]
Abstract
The traditional view of neural computation in the cerebral cortex holds that sensory neurons are specialized, i.e., selective for certain dimensions of sensory stimuli. This view was challenged by evidence of contextual interactions between stimulus dimensions in which a neuron's response to one dimension strongly depends on other dimensions. Here, we use methods of mathematical modeling, psychophysics, and electrophysiology to address shortcomings of the traditional view. Using a model of a generic cortical circuit, we begin with the simple demonstration that cortical responses are always distributed among neurons, forming characteristic waveforms, which we call neural waves. When stimulated by patterned stimuli, circuit responses arise by interference of neural waves. Results of this process depend on interaction between stimulus dimensions. Comparison of modeled responses with responses of biological vision makes it clear that the framework of neural wave interference provides a useful alternative to the standard concept of neural computation.
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Affiliation(s)
- Sergei Gepshtein
- Systems Neurobiology Laboratories, Salk Institute for Biological Studies, La Jolla, CA, USA
- Center for Spatial Perception and Concrete Experience, University of Southern California, Los Angeles, CA, USA
| | - Ambarish S. Pawar
- Systems Neurobiology Laboratories, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Sunwoo Kwon
- Herbert Wertheim School of Optometry & Vision Science, University of California Berkeley, Berkeley, CA, USA
| | - Sergey Savel’ev
- Department of Physics, Loughborough University, Loughborough, UK
| | - Thomas D. Albright
- Systems Neurobiology Laboratories, Salk Institute for Biological Studies, La Jolla, CA, USA
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33
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Im S, Ueta Y, Otsuka T, Morishima M, Youssef M, Hirai Y, Kobayashi K, Kaneko R, Morita K, Kawaguchi Y. Corticocortical innervation subtypes of layer 5 intratelencephalic cells in the murine secondary motor cortex. Cereb Cortex 2022; 33:50-67. [PMID: 35396593 PMCID: PMC9758586 DOI: 10.1093/cercor/bhac052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 01/25/2022] [Accepted: 01/26/2022] [Indexed: 11/15/2022] Open
Abstract
Feedback projections from the secondary motor cortex (M2) to the primary motor and sensory cortices are essential for behavior selection and sensory perception. Intratelencephalic (IT) cells in layer 5 (L5) contribute feedback projections to diverse cortical areas. Here we show that L5 IT cells participating in feedback connections to layer 1 (L1) exhibit distinct projection patterns, genetic profiles, and electrophysiological properties relative to other L5 IT cells. An analysis of the MouseLight database found that L5 IT cells preferentially targeting L1 project broadly to more cortical regions, including the perirhinal and auditory cortices, and innervate a larger volume of striatum than the other L5 IT cells. We found experimentally that in upper L5 (L5a), ER81 (ETV1) was found more often in L1-preferring IT cells, and in IT cells projecting to perirhinal/auditory regions than those projecting to primary motor or somatosensory regions. The perirhinal region-projecting L5a IT cells were synaptically connected to each other and displayed lower input resistance than contra-M2 projecting IT cells including L1-preferring and nonpreferring cells. Our findings suggest that M2-L5a IT L1-preferring cells exhibit stronger ER81 expression and broader cortical/striatal projection fields than do cells that do not preferentially target L1.
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Affiliation(s)
- Sanghun Im
- National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan,Department of Physiological Sciences, The Graduate University for Advanced Studies (SOKENDAI), Okazaki 444-8787, Japan,Brain Science Institute, Tamagawa University, Machida, Tokyo 194-8610, Japan
| | - Yoshifumi Ueta
- Department of Physiology, Division of Neurophysiology, School of Medicine, Tokyo Women's Medical University, Tokyo 162-8666, Japan
| | - Takeshi Otsuka
- National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan,Department of Physiological Sciences, The Graduate University for Advanced Studies (SOKENDAI), Okazaki 444-8787, Japan
| | - Mieko Morishima
- National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan,Institute of Clinical Medicine and Research, Jikei University School of Medicine, Chiba 277-8567, Japan
| | - Mohammed Youssef
- National Institute for Physiological Sciences (NIPS), Okazaki 444-8787, Japan,Department of Animal Physiology, Faculty of Veterinary Medicine, South Valley University, Qena 83523, Egypt
| | - Yasuharu Hirai
- Laboratory of Histology and Cytology, Faculty of Medicine, Hokkaido University, Sapporo 060-8638, Japan
| | - Kenta Kobayashi
- Section of Viral Vector Development, National Institute for Physiological Sciences, Okazaki 444-8585, Japan
| | - Ryosuke Kaneko
- Bioresource Center, Gunma University Graduate School of Medicine, Gunma 371-8511, Japan,KOKORO-Biology Group, Laboratories for Integrated Biology, Graduate School of Frontier Biosciences, Osaka University, Osaka 565-0871, Japan
| | - Kenji Morita
- Physical and Health Education, Graduate School of Education, The University of Tokyo, Tokyo 113-0033, Japan,International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo 113-0033, Japan
| | - Yasuo Kawaguchi
- Corresponding author: Brain Science Institute, Tamagawa University Machida, Tokyo 1948610, Japan.
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34
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Boosting visual perceptual learning by transcranial alternating current stimulation over the visual cortex at alpha frequency. Brain Stimul 2022; 15:546-553. [DOI: 10.1016/j.brs.2022.02.018] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2021] [Revised: 02/22/2022] [Accepted: 02/28/2022] [Indexed: 11/17/2022] Open
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35
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Mejías JF, Wang XJ. Mechanisms of distributed working memory in a large-scale network of macaque neocortex. eLife 2022; 11:72136. [PMID: 35200137 PMCID: PMC8871396 DOI: 10.7554/elife.72136] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Accepted: 01/19/2022] [Indexed: 12/15/2022] Open
Abstract
Neural activity underlying working memory is not a local phenomenon but distributed across multiple brain regions. To elucidate the circuit mechanism of such distributed activity, we developed an anatomically constrained computational model of large-scale macaque cortex. We found that mnemonic internal states may emerge from inter-areal reverberation, even in a regime where none of the isolated areas is capable of generating self-sustained activity. The mnemonic activity pattern along the cortical hierarchy indicates a transition in space, separating areas engaged in working memory and those which do not. A host of spatially distinct attractor states is found, potentially subserving various internal processes. The model yields testable predictions, including the idea of counterstream inhibitory bias, the role of prefrontal areas in controlling distributed attractors, and the resilience of distributed activity to lesions or inactivation. This work provides a theoretical framework for identifying large-scale brain mechanisms and computational principles of distributed cognitive processes.
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Affiliation(s)
- Jorge F Mejías
- Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, Netherlands
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, United States
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36
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van Albada SJ, Morales-Gregorio A, Dickscheid T, Goulas A, Bakker R, Bludau S, Palm G, Hilgetag CC, Diesmann M. Bringing Anatomical Information into Neuronal Network Models. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1359:201-234. [DOI: 10.1007/978-3-030-89439-9_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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37
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Dalla Porta L, Castro DM, Copelli M, Carelli PV, Matias FS. Feedforward and feedback influences through distinct frequency bands between two spiking-neuron networks. Phys Rev E 2021; 104:054404. [PMID: 34942789 DOI: 10.1103/physreve.104.054404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 09/27/2021] [Indexed: 11/07/2022]
Abstract
Several studies on brain signals suggested that bottom-up and top-down influences are exerted through distinct frequency bands among visual cortical areas. It was recently shown that theta and gamma rhythms subserve feedforward, whereas the feedback influence is dominated by the alpha-beta rhythm in primates. A few theoretical models for reproducing these effects have been proposed so far. Here we show that a simple but biophysically plausible two-network motif composed of spiking-neuron models and chemical synapses can exhibit feedforward and feedback influences through distinct frequency bands. Different from previous studies, this kind of model allows us to study directed influences not only at the population level, by using a proxy for the local field potential, but also at the cellular level, by using the neuronal spiking series.
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Affiliation(s)
- Leonardo Dalla Porta
- Systems Neuroscience, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona 08036, Spain
| | - Daniel M Castro
- Departamento de Física, Universidade Federal de Pernambuco, Recife PE 50670-901, Brazil
| | - Mauro Copelli
- Departamento de Física, Universidade Federal de Pernambuco, Recife PE 50670-901, Brazil
| | - Pedro V Carelli
- Departamento de Física, Universidade Federal de Pernambuco, Recife PE 50670-901, Brazil
| | - Fernanda S Matias
- Instituto de Física, Universidade Federal de Alagoas, Maceió, Alagoas 57072-970, Brazil
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38
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Gamma rhythms in the visual cortex: functions and mechanisms. Cogn Neurodyn 2021; 16:745-756. [PMID: 35847544 PMCID: PMC9279528 DOI: 10.1007/s11571-021-09767-x] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Revised: 11/09/2021] [Accepted: 12/05/2021] [Indexed: 01/18/2023] Open
Abstract
Gamma-band activity, peaking around 30–100 Hz in the local field potential's power spectrum, has been found and intensively studied in many brain regions. Although gamma is thought to play a critical role in processing neural information in the brain, its cognitive functions and neural mechanisms remain unclear or debatable. Experimental studies showed that gamma rhythms are stochastic in time and vary with visual stimuli. Recent studies further showed that multiple rhythms coexist in V1 with distinct origins in different species. While all these experimental facts are a challenge for understanding the functions of gamma in the visual cortex, there are many signs of progress in computational studies. This review summarizes and discusses studies on gamma in the visual cortex from multiple perspectives and concludes that gamma rhythms are still a mystery. Combining experimental and computational studies seems the best way forward in the future.
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39
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Mohan A, Luckey A, Weisz N, Vanneste S. Predisposition to domain-wide maladaptive changes in predictive coding in auditory phantom perception. Neuroimage 2021; 248:118813. [PMID: 34923130 DOI: 10.1016/j.neuroimage.2021.118813] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Revised: 06/30/2021] [Accepted: 12/13/2021] [Indexed: 01/22/2023] Open
Abstract
Tinnitus is hypothesised to be a predictive coding problem. Previous research indicates lower sensitivity to prediction errors (PEs) in tinnitus patients while processing auditory deviants corresponding to tinnitus-specific stimuli. However, based on research with patients with hallucinations and no psychosis we hypothesise tinnitus patients may be more sensitive to PEs produced by auditory stimuli that are not related to tinnitus characteristics. Specifically in patients with minimal to no hearing loss, we hypothesise a more top-down subtype of tinnitus that may be driven by maladaptive changes in an auditory predictive coding network. To test this, we use an auditory oddball paradigm with omission of global and local deviants, a measure that is previously shown to empirically characterise hierarchical prediction errors (PEs). We observe: (1) increased predictions characterised by increased pre-stimulus response and increased alpha connectivity between the parahippocampus, dorsal anterior cingulate cortex and parahippocampus, pregenual anterior cingulate cortex and posterior cingulate cortex; (2) increased PEs characterised by increased P300 amplitude and gamma activity and increased theta connectivity between auditory cortices, parahippocampus and dorsal anterior cingulate cortex in the tinnitus group; (3) increased overall feed-forward connectivity in theta from the auditory cortex and parahippocampus to the dorsal anterior cingulate cortex; (4) correlations of pre-stimulus theta activity to tinnitus loudness and alpha activity to tinnitus distress. These results provide empirical evidence of maladaptive changes in a hierarchical predictive coding network in a subgroup of tinnitus patients with minimal to no hearing loss. The changes in pre-stimulus activity and connectivity to non-tinnitus specific stimuli suggest that tinnitus patients not only produce strong predictions about upcoming stimuli but also may be predisposed to stimulus a-specific PEs in the auditory domain. Correlations with tinnitus-related characteristics may be a biomarker for maladaptive changes in auditory predictive coding.
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Affiliation(s)
- Anusha Mohan
- Global Brain Health Institute & Institute of Neuroscience, Trinity College Dublin, College Green 2, Dublin, Ireland
| | - Alison Luckey
- Global Brain Health Institute & Institute of Neuroscience, Trinity College Dublin, College Green 2, Dublin, Ireland
| | - Nathan Weisz
- Salzburg Brain Dynamics Lab, University of Salzburg, Austria
| | - Sven Vanneste
- Global Brain Health Institute & Institute of Neuroscience, Trinity College Dublin, College Green 2, Dublin, Ireland; Lab for Clinical & Integrative Neuroscience, School of Behavioral and Brain Sciences, The University of Texas at Dallas, United States.
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40
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Schneider M, Broggini AC, Dann B, Tzanou A, Uran C, Sheshadri S, Scherberger H, Vinck M. A mechanism for inter-areal coherence through communication based on connectivity and oscillatory power. Neuron 2021; 109:4050-4067.e12. [PMID: 34637706 PMCID: PMC8691951 DOI: 10.1016/j.neuron.2021.09.037] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 07/14/2021] [Accepted: 09/17/2021] [Indexed: 11/21/2022]
Abstract
Inter-areal coherence between field potentials is a widespread phenomenon in cortex. Coherence has been hypothesized to reflect phase-synchronization between oscillators and flexibly gate communication according to behavioral and cognitive demands. We reveal an alternative mechanism where coherence is not the cause but the consequence of communication and naturally emerges because spiking activity in a sending area causes post-synaptic potentials both in the same and in other areas. Consequently, coherence depends in a lawful manner on power and phase-locking in the sender and connectivity. Changes in oscillatory power explained prominent changes in fronto-parietal and LGN-V1 coherence across behavioral conditions. Optogenetic experiments and excitatory-inhibitory network simulations identified afferent synaptic inputs rather than spiking entrainment as the principal determinant of coherence. These findings suggest that unique spectral profiles of different brain areas automatically give rise to large-scale coherence patterns that follow anatomical connectivity and continuously reconfigure as a function of behavior and cognition.
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Affiliation(s)
- 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.
| | - Ana Clara Broggini
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | | | - Athanasia Tzanou
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Cem Uran
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany
| | - Swathi Sheshadri
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Hansjörg Scherberger
- German Primate Center, 37077 Göttingen, Germany; Faculty of Biology and Psychology, University of Goettingen, 37073 Goettingen, Germany
| | - Martin Vinck
- Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, 60528 Frankfurt am Main, Germany; Donders Centre for Neuroscience, Department of Neuroinformatics, Radboud University Nijmegen, 6525 Nijmegen, the Netherlands.
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41
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Han C, Wang T, Yang Y, Wu Y, Li Y, Dai W, Zhang Y, Wang B, Yang G, Cao Z, Kang J, Wang G, Li L, Yu H, Yeh CI, Xing D. Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex. PLoS Biol 2021; 19:e3001466. [PMID: 34932558 PMCID: PMC8691622 DOI: 10.1371/journal.pbio.3001466] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/03/2021] [Indexed: 12/26/2022] Open
Abstract
Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.
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Affiliation(s)
- Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yi Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yang Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Weifeng Dai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yange Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bin Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Guanzhong Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ziqi Cao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jian Kang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Gang Wang
- Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Liang Li
- Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Hongbo Yu
- Vision Research Laboratory, Center for Brain Science Research and School of Life Sciences, Fudan University, Shanghai, China
| | - Chun-I Yeh
- Department of Psychology, National Taiwan University, Taipei, Taiwan, China
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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42
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Froudist-Walsh S, Bliss DP, Ding X, Rapan L, Niu M, Knoblauch K, Zilles K, Kennedy H, Palomero-Gallagher N, Wang XJ. A dopamine gradient controls access to distributed working memory in the large-scale monkey cortex. Neuron 2021; 109:3500-3520.e13. [PMID: 34536352 PMCID: PMC8571070 DOI: 10.1016/j.neuron.2021.08.024] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/08/2021] [Accepted: 08/17/2021] [Indexed: 12/13/2022]
Abstract
Dopamine is required for working memory, but how it modulates the large-scale cortex is unknown. Here, we report that dopamine receptor density per neuron, measured by autoradiography, displays a macroscopic gradient along the macaque cortical hierarchy. This gradient is incorporated in a connectome-based large-scale cortex model endowed with multiple neuron types. The model captures an inverted U-shaped dependence of working memory on dopamine and spatial patterns of persistent activity observed in over 90 experimental studies. Moreover, we show that dopamine is crucial for filtering out irrelevant stimuli by enhancing inhibition from dendrite-targeting interneurons. Our model revealed that an activity-silent memory trace can be realized by facilitation of inter-areal connections and that adjusting cortical dopamine induces a switch from this internal memory state to distributed persistent activity. Our work represents a cross-level understanding from molecules and cell types to recurrent circuit dynamics underlying a core cognitive function distributed across the primate cortex.
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Affiliation(s)
| | - Daniel P Bliss
- Center for Neural Science, New York University, New York, NY 10003, USA
| | - Xingyu Ding
- Center for Neural Science, New York University, New York, NY 10003, USA
| | | | - Meiqi Niu
- Research Centre Jülich, INM-1, Jülich, Germany
| | - Kenneth Knoblauch
- INSERM U846, Stem Cell & Brain Research Institute, 69500 Bron, France; Université de Lyon, Université Lyon I, 69003 Lyon, France
| | - Karl Zilles
- Research Centre Jülich, INM-1, Jülich, Germany
| | - Henry Kennedy
- INSERM U846, Stem Cell & Brain Research Institute, 69500 Bron, France; Université de Lyon, Université Lyon I, 69003 Lyon, France; Institute of Neuroscience, State Key Laboratory of Neuroscience, Chinese Academy of Sciences (CAS), Key Laboratory of Primate Neurobiology CAS, Shanghai, China
| | - Nicola Palomero-Gallagher
- Research Centre Jülich, INM-1, Jülich, Germany; C. & O. Vogt Institute for Brain Research, Heinrich-Heine-University, 40225 Düsseldorf, Germany
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY 10003, USA.
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43
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Theodoni P, Majka P, Reser DH, Wójcik DK, Rosa MGP, Wang XJ. Structural Attributes and Principles of the Neocortical Connectome in the Marmoset Monkey. Cereb Cortex 2021; 32:15-28. [PMID: 34274966 PMCID: PMC8634603 DOI: 10.1093/cercor/bhab191] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2020] [Revised: 05/23/2021] [Accepted: 06/01/2021] [Indexed: 12/12/2022] Open
Abstract
The marmoset monkey has become an important primate model in Neuroscience. Here, we characterize salient statistical properties of interareal connections of the marmoset cerebral cortex, using data from retrograde tracer injections. We found that the connectivity weights are highly heterogeneous, spanning 5 orders of magnitude, and are log-normally distributed. The cortico-cortical network is dense, heterogeneous and has high specificity. The reciprocal connections are the most prominent and the probability of connection between 2 areas decays with their functional dissimilarity. The laminar dependence of connections defines a hierarchical network correlated with microstructural properties of each area. The marmoset connectome reveals parallel streams associated with different sensory systems. Finally, the connectome is spatially embedded with a characteristic length that obeys a power law as a function of brain volume across rodent and primate species. These findings provide a connectomic basis for investigations of multiple interacting areas in a complex large-scale cortical system underlying cognitive processes.
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Affiliation(s)
- Panagiota Theodoni
- Center for Neural Science, New York University, New York, NY 10003, USA.,New York University Shanghai, Shanghai 200122, China.,NYU-ECNU Institute of Brain and Cognitive Science at New York University Shanghai, Shanghai 200062, China
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw 02-093, Poland.,Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia.,Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - David H Reser
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia.,Graduate Entry Medicine Program, Monash Rural Health-Churchill, Monash University, Churchill, VIC 3842, Australia
| | - Daniel K Wójcik
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw 02-093, Poland
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, VIC 3800, Australia.,Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, VIC 3800, Australia
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, NY 10003, USA
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44
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Cortical interaction of bilateral inputs is similar for noxious and innocuous stimuli but leads to different perceptual effects. Exp Brain Res 2021; 239:2803-2819. [PMID: 34279670 DOI: 10.1007/s00221-021-06175-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Accepted: 07/10/2021] [Indexed: 12/20/2022]
Abstract
The cerebral integration of somatosensory inputs from multiple sources is essential to produce adapted behaviors. Previous studies suggest that bilateral somatosensory inputs interact differently depending on stimulus characteristics, including their noxious nature. The aim of this study was to clarify how bilateral inputs evoked by noxious laser stimuli, noxious shocks, and innocuous shocks interact in terms of perception and brain responses. The experiment comprised two conditions (right-hand stimulation and concurrent stimulation of both hands) in which painful laser stimuli, painful shocks and non-painful shocks were delivered. Perception, somatosensory-evoked potentials (P45, N100, P260), laser-evoked potentials (N1, N2 and P2) and event-related spectral perturbations (delta to gamma oscillation power) were compared between conditions and stimulus modalities. The amplitude of negative vertex potentials (N2 or N100) and the power of delta/theta oscillations were increased in the bilateral compared with unilateral condition, regardless of the stimulus type (P < 0.01). However, gamma oscillation power increased for painful and non-painful shocks (P < 0.01), but not for painful laser stimuli (P = 0.08). Despite the similarities in terms of brain activity, bilateral inputs interacted differently for painful stimuli, for which perception remained unchanged, and non-painful stimuli, for which perception increased. This may reflect a ceiling effect for the attentional capture by noxious stimuli and warrants further investigations to examine the regulation of such interactions by bottom-up and top-down processes.
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45
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Varga B, Soós B, Jákli B, Bálint E, Somogyvári Z, Négyessy L. Network Path Convergence Shapes Low-Level Processing in the Visual Cortex. Front Syst Neurosci 2021; 15:645709. [PMID: 34108867 PMCID: PMC8181740 DOI: 10.3389/fnsys.2021.645709] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 04/21/2021] [Indexed: 11/13/2022] Open
Abstract
Hierarchical counterstream via feedforward and feedback interactions is a major organizing principle of the cerebral cortex. The counterstream, as a topological feature of the network of cortical areas, is captured by the convergence and divergence of paths through directed links. So defined, the convergence degree (CD) reveals the reciprocal nature of forward and backward connections, and also hierarchically relevant integrative properties of areas through their inward and outward connections. We asked if topology shapes large-scale cortical functioning by studying the role of CD in network resilience and Granger causal coupling in a model of hierarchical network dynamics. Our results indicate that topological synchronizability is highly vulnerable to attacking edges based on CD, while global network efficiency depends mostly on edge betweenness, a measure of the connectedness of a link. Furthermore, similar to anatomical hierarchy determined by the laminar distribution of connections, CD highly correlated with causal coupling in feedforward gamma, and feedback alpha-beta band synchronizations in a well-studied subnetwork, including low-level visual cortical areas. In contrast, causal coupling did not correlate with edge betweenness. Considering the entire network, the CD-based hierarchy correlated well with both the anatomical and functional hierarchy for low-level areas that are far apart in the hierarchy. Conversely, in a large part of the anatomical network where hierarchical distances are small between the areas, the correlations were not significant. These findings suggest that CD-based and functional hierarchies are interrelated in low-level processing in the visual cortex. Our results are consistent with the idea that the interplay of multiple hierarchical features forms the basis of flexible functional cortical interactions.
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Affiliation(s)
- Bálint Varga
- Computational Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary.,János Szentágothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary
| | - Bettina Soós
- Computational Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary.,Faculty of Science and Engineering, University of Groningen, Groningen, Netherlands
| | - Balázs Jákli
- Faculty of Information Technology and Bionics, Pázmány Péter Catholic University, Budapest, Hungary
| | - Eszter Bálint
- Department of Anatomy, Histology and Embryology, Semmelweis University, Budapest, Hungary
| | - Zoltán Somogyvári
- Computational Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
| | - László Négyessy
- Computational Neuroscience and Complex Systems Research Group, Department of Computational Sciences, Wigner Research Centre for Physics, Budapest, Hungary
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46
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Biswas D, Pallikkulath S, Chakravarthy VS. A Complex-Valued Oscillatory Neural Network for Storage and Retrieval of Multidimensional Aperiodic Signals. Front Comput Neurosci 2021; 15:551111. [PMID: 34108869 PMCID: PMC8181409 DOI: 10.3389/fncom.2021.551111] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2020] [Accepted: 04/06/2021] [Indexed: 11/13/2022] Open
Abstract
Recurrent neural networks with associative memory properties are typically based on fixed-point dynamics, which is fundamentally distinct from the oscillatory dynamics of the brain. There have been proposals for oscillatory associative memories, but here too, in the majority of cases, only binary patterns are stored as oscillatory states in the network. Oscillatory neural network models typically operate at a single/common frequency. At multiple frequencies, even a pair of oscillators with real coupling exhibits rich dynamics of Arnold tongues, not easily harnessed to achieve reliable memory storage and retrieval. Since real brain dynamics comprises of a wide range of spectral components, there is a need for oscillatory neural network models that operate at multiple frequencies. We propose an oscillatory neural network that can model multiple time series simultaneously by performing a Fourier-like decomposition of the signals. We show that these enhanced properties of a network of Hopf oscillators become possible by operating in the complex-variable domain. In this model, the single neural oscillator is modeled as a Hopf oscillator, with adaptive frequency and dynamics described over the complex domain. We propose a novel form of coupling, dubbed "power coupling," between complex Hopf oscillators. With power coupling, expressed naturally only in the complex-variable domain, it is possible to achieve stable (normalized) phase relationships in a network of multifrequency oscillators. Network connections are trained either by Hebb-like learning or by delta rule, adapted to the complex domain. The network is capable of modeling N-channel electroencephalogram time series with high accuracy and shows the potential as an effective model of large-scale brain dynamics.
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Affiliation(s)
- Dipayan Biswas
- Laboratory for Computational Neuroscience, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India
| | - Sooryakiran Pallikkulath
- Laboratory for Computational Neuroscience, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India.,Department of Mechanical Engineering, Indian Institute of Technology Madras, Chennai, India
| | - V Srinivasa Chakravarthy
- Laboratory for Computational Neuroscience, Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai, India
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47
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Cerebellar Purkinje cells can differentially modulate coherence between sensory and motor cortex depending on region and behavior. Proc Natl Acad Sci U S A 2021; 118:2015292118. [PMID: 33443203 PMCID: PMC7812746 DOI: 10.1073/pnas.2015292118] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Activity of sensory and motor cortices is essential for sensorimotor integration. In particular, coherence between these areas may indicate binding of critical functions like perception, motor planning, action, or sleep. Evidence is accumulating that cerebellar output modulates cortical activity and coherence, but how, when, and where it does so is unclear. We studied activity in and coherence between S1 and M1 cortices during whisker stimulation in the absence and presence of optogenetic Purkinje cell stimulation in crus 1 and 2 of awake mice, eliciting strong simple spike rate modulation. Without Purkinje cell stimulation, whisker stimulation triggers fast responses in S1 and M1 involving transient coherence in a broad spectrum. Simultaneous stimulation of Purkinje cells and whiskers affects amplitude and kinetics of sensory responses in S1 and M1 and alters the estimated S1-M1 coherence in theta and gamma bands, allowing bidirectional control dependent on behavioral context. These effects are absent when Purkinje cell activation is delayed by 20 ms. Focal stimulation of Purkinje cells revealed site specificity, with cells in medial crus 2 showing the most prominent and selective impact on estimated coherence, i.e., a strong suppression in the gamma but not the theta band. Granger causality analyses and computational modeling of the involved networks suggest that Purkinje cells control S1-M1 phase consistency predominantly via ventrolateral thalamus and M1. Our results indicate that activity of sensorimotor cortices can be dynamically and functionally modulated by specific cerebellar inputs, highlighting a widespread role of the cerebellum in coordinating sensorimotor behavior.
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48
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Zhang G, Cui Y, Zhang Y, Cao H, Zhou G, Shu H, Yao D, Xia Y, Chen K, Guo D. Computational exploration of dynamic mechanisms of steady state visual evoked potentials at the whole brain level. Neuroimage 2021; 237:118166. [PMID: 34000401 DOI: 10.1016/j.neuroimage.2021.118166] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 05/05/2021] [Accepted: 05/11/2021] [Indexed: 01/23/2023] Open
Abstract
Periodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear entrainment and resonance, and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.
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Affiliation(s)
- Ge Zhang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Yan Cui
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Yangsong Zhang
- School of Computer Science and Technology, Southwest University of Science and Technology, Mianyang 621010, China
| | - Hefei Cao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Guanyu Zhou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Haifeng Shu
- Department of Neurosurgery, The General Hospital of Western Theater Command, Chengdu 610083, China
| | - Dezhong Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China; School of Electrical Engineering, Zhengzhou University, Zhengzhou 450001, China.
| | - Yang Xia
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Ke Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China
| | - Daqing Guo
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for NeuroInformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 611731, China; Research Unit of NeuroInformation, Chinese Academy of Medical Sciences, 2019RU035, Chengdu, China.
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49
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Afrasiabi M, Redinbaugh MJ, Phillips JM, Kambi NA, Mohanta S, Raz A, Haun AM, Saalmann YB. Consciousness depends on integration between parietal cortex, striatum, and thalamus. Cell Syst 2021; 12:363-373.e11. [PMID: 33730543 PMCID: PMC8084606 DOI: 10.1016/j.cels.2021.02.003] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 11/10/2020] [Accepted: 02/18/2021] [Indexed: 11/19/2022]
Abstract
The neural substrates of consciousness remain elusive. Competing theories that attempt to explain consciousness disagree on the contribution of frontal versus posterior cortex and omit subcortical influences. This lack of understanding impedes the ability to monitor consciousness, which can lead to adverse clinical consequences. To test substrates and measures of consciousness, we recorded simultaneously from frontal cortex, parietal cortex, and subcortical structures, the striatum and thalamus, in awake, sleeping, and anesthetized macaques. We manipulated consciousness on a finer scale using thalamic stimulation, rousing macaques from continuously administered anesthesia. Our results show that, unlike measures targeting complexity, a measure additionally capturing neural integration (Φ∗) robustly correlated with changes in consciousness. Machine learning approaches show parietal cortex, striatum, and thalamus contributed more than frontal cortex to decoding differences in consciousness. These findings highlight the importance of integration between parietal and subcortical structures and challenge a key role for frontal cortex in consciousness.
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Affiliation(s)
- Mohsen Afrasiabi
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53705, USA.
| | | | - Jessica M Phillips
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Niranjan A Kambi
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Sounak Mohanta
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Aeyal Raz
- Department of Anesthesiology, Rambam Health Care Campus, Haifa 3109601, Israel; The Ruth and Bruce Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa 3200003, Israel
| | - Andrew M Haun
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Yuri B Saalmann
- Department of Psychology, University of Wisconsin-Madison, Madison, WI 53705, USA; Wisconsin National Primate Research Center, Madison, WI 53705, USA.
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50
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Pettine WW, Louie K, Murray JD, Wang XJ. Excitatory-inhibitory tone shapes decision strategies in a hierarchical neural network model of multi-attribute choice. PLoS Comput Biol 2021; 17:e1008791. [PMID: 33705386 PMCID: PMC7987200 DOI: 10.1371/journal.pcbi.1008791] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 03/23/2021] [Accepted: 02/15/2021] [Indexed: 12/14/2022] Open
Abstract
We are constantly faced with decisions between alternatives defined by multiple attributes, necessitating an evaluation and integration of different information sources. Time-varying signals in multiple brain areas are implicated in decision-making; but we lack a rigorous biophysical description of how basic circuit properties, such as excitatory-inhibitory (E/I) tone and cascading nonlinearities, shape attribute processing and choice behavior. Furthermore, how such properties govern choice performance under varying levels of environmental uncertainty is unknown. We investigated two-attribute, two-alternative decision-making in a dynamical, cascading nonlinear neural network with three layers: an input layer encoding choice alternative attribute values; an intermediate layer of modules processing separate attributes; and a final layer producing the decision. Depending on intermediate layer E/I tone, the network displays distinct regimes characterized by linear (I), convex (II) or concave (III) choice indifference curves. In regimes I and II, each option's attribute information is additively integrated. In regime III, time-varying nonlinear operations amplify the separation between offer distributions by selectively attending to the attribute with the larger differences in input values. At low environmental uncertainty, a linear combination most consistently selects higher valued alternatives. However, at high environmental uncertainty, regime III is more likely than a linear operation to select alternatives with higher value. Furthermore, there are conditions where readout from the intermediate layer could be experimentally indistinguishable from the final layer. Finally, these principles are used to examine multi-attribute decisions in systems with reduced inhibitory tone, leading to predictions of different choice patterns and overall performance between those with restrictions on inhibitory tone and neurotypicals.
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Affiliation(s)
- Warren Woodrich Pettine
- Center for Neural Science, New York University, New York, United States of America
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States of America
| | - Kenway Louie
- Center for Neural Science, New York University, New York, United States of America
| | - John D. Murray
- Department of Psychiatry, Yale University School of Medicine, New Haven, United States of America
| | - Xiao-Jing Wang
- Center for Neural Science, New York University, New York, United States of America
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