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Fan JM, Kudo K, Verma P, Ranasinghe KG, Morise H, Findlay AM, Vossel K, Kirsch HE, Raj A, Krystal AD, Nagarajan SS. Cortical Synchrony and Information Flow during Transition from Wakefulness to Light Non-Rapid Eye Movement Sleep. J Neurosci 2023; 43:8157-8171. [PMID: 37788939 PMCID: PMC10697405 DOI: 10.1523/jneurosci.0197-23.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 07/07/2023] [Accepted: 08/06/2023] [Indexed: 10/05/2023] Open
Abstract
Sleep is a highly stereotyped phenomenon, requiring robust spatiotemporal coordination of neural activity. Understanding how the brain coordinates neural activity with sleep onset can provide insights into the physiological functions subserved by sleep and the pathologic phenomena associated with sleep onset. We quantified whole-brain network changes in synchrony and information flow during the transition from wakefulness to light non-rapid eye movement (NREM) sleep, using MEG imaging in a convenient sample of 14 healthy human participants (11 female; mean 63.4 years [SD 11.8 years]). We furthermore performed computational modeling to infer excitatory and inhibitory properties of local neural activity. The transition from wakefulness to light NREM was identified to be encoded in spatially and temporally specific patterns of long-range synchrony. Within the delta band, there was a global increase in connectivity from wakefulness to light NREM, which was highest in frontoparietal regions. Within the theta band, there was an increase in connectivity in fronto-parieto-occipital regions and a decrease in temporal regions from wakefulness to Stage 1 sleep. Patterns of information flow revealed that mesial frontal regions receive hierarchically organized inputs from broad cortical regions upon sleep onset, including direct inflow from occipital regions and indirect inflow via parieto-temporal regions within the delta frequency band. Finally, biophysical neural mass modeling demonstrated changes in the anterior-to-posterior distribution of cortical excitation-to-inhibition with increased excitation-to-inhibition model parameters in anterior regions in light NREM compared with wakefulness. Together, these findings uncover whole-brain corticocortical structure and the orchestration of local and long-range, frequency-specific cortical interactions in the sleep-wake transition.SIGNIFICANCE STATEMENT Our work uncovers spatiotemporal cortical structure of neural synchrony and information flow upon the transition from wakefulness to light non-rapid eye movement sleep. Mesial frontal regions were identified to receive hierarchically organized inputs from broad cortical regions, including both direct inputs from occipital regions and indirect inputs via the parieto-temporal regions within the delta frequency range. Biophysical neural mass modeling revealed a spatially heterogeneous, anterior-posterior distribution of cortical excitation-to-inhibition. Our findings shed light on the orchestration of local and long-range cortical neural structure that is fundamental to sleep onset, and support an emerging view of cortically driven regulation of sleep homeostasis.
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Affiliation(s)
- Joline M Fan
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan 243-0460
| | - Parul Verma
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Kamalini G Ranasinghe
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
| | - Hirofumi Morise
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
- Medical Imaging Center, Ricoh Company, Ltd., Kanazawa, Japan 243-0460
| | - Anne M Findlay
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Keith Vossel
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
- Mary S. Easton Center for Alzheimer's Disease Research, Department of Neurology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, California 90095
| | - Heidi E Kirsch
- Department of Neurology, University of California-San Francisco, San Francisco, California 94143
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Ashish Raj
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
| | - Andrew D Krystal
- Department of Psychiatry, University of California-San Francisco, San Francisco, California 94143
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California-San Francisco, San Francisco, California 94143
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Gansel KS. Neural synchrony in cortical networks: mechanisms and implications for neural information processing and coding. Front Integr Neurosci 2022; 16:900715. [PMID: 36262373 PMCID: PMC9574343 DOI: 10.3389/fnint.2022.900715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 09/13/2022] [Indexed: 11/13/2022] Open
Abstract
Synchronization of neuronal discharges on the millisecond scale has long been recognized as a prevalent and functionally important attribute of neural activity. In this article, I review classical concepts and corresponding evidence of the mechanisms that govern the synchronization of distributed discharges in cortical networks and relate those mechanisms to their possible roles in coding and cognitive functions. To accommodate the need for a selective, directed synchronization of cells, I propose that synchronous firing of distributed neurons is a natural consequence of spike-timing-dependent plasticity (STDP) that associates cells repetitively receiving temporally coherent input: the “synchrony through synaptic plasticity” hypothesis. Neurons that are excited by a repeated sequence of synaptic inputs may learn to selectively respond to the onset of this sequence through synaptic plasticity. Multiple neurons receiving coherent input could thus actively synchronize their firing by learning to selectively respond at corresponding temporal positions. The hypothesis makes several predictions: first, the position of the cells in the network, as well as the source of their input signals, would be irrelevant as long as their input signals arrive simultaneously; second, repeating discharge patterns should get compressed until all or some part of the signals are synchronized; and third, this compression should be accompanied by a sparsening of signals. In this way, selective groups of cells could emerge that would respond to some recurring event with synchronous firing. Such a learned response pattern could further be modulated by synchronous network oscillations that provide a dynamic, flexible context for the synaptic integration of distributed signals. I conclude by suggesting experimental approaches to further test this new hypothesis.
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Duprez J, Tabbal J, Hassan M, Modolo J, Kabbara A, Mheich A, Drapier S, Vérin M, Sauleau P, Wendling F, Benquet P, Houvenaghel JF. Spatio-temporal dynamics of large-scale electrophysiological networks during cognitive action control in healthy controls and Parkinson's disease patients. Neuroimage 2022; 258:119331. [PMID: 35660459 DOI: 10.1016/j.neuroimage.2022.119331] [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: 12/13/2021] [Revised: 05/16/2022] [Accepted: 05/23/2022] [Indexed: 10/18/2022] Open
Abstract
Among the cognitive symptoms that are associated with Parkinson's disease (PD), alterations in cognitive action control (CAC) are commonly reported in patients. CAC enables the suppression of an automatic action, in favor of a goal-directed one. The implementation of CAC is time-resolved and arguably associated with dynamic changes in functional brain networks. However, the electrophysiological functional networks involved, their dynamic changes, and how these changes are affected by PD, still remain unknown. In this study, to address this gap of knowledge, 10 PD patients and 10 healthy controls (HC) underwent a Simon task while high-density electroencephalography (HD-EEG) was recorded. Source-level dynamic connectivity matrices were estimated using the phase-locking value in the beta (12-25 Hz) and gamma (30-45 Hz) frequency bands. Temporal independent component analyses were used as a dimension reduction tool to isolate the task-related brain network states. Typical microstate metrics were quantified to investigate the presence of these states at the subject-level. Our results first confirmed that PD patients experienced difficulties in inhibiting automatic responses during the task. At the group-level, we found three functional network states in the beta band that involved fronto-temporal, temporo-cingulate and fronto-frontal connections with typical CAC-related prefrontal and cingulate nodes (e.g., inferior frontal cortex). The presence of these networks did not differ between PD patients and HC when analyzing microstates metrics, and no robust correlations with behavior were found. In the gamma band, five networks were found, including one fronto-temporal network that was identical to the one found in the beta band. These networks also included CAC-related nodes previously identified in different neuroimaging modalities. Similarly to the beta networks, no subject-level differences were found between PD patients and HC. Interestingly, in both frequency bands, the dominant network at the subject-level was never the one that was the most durably modulated by the task. Altogether, this study identified the dynamic functional brain networks observed during CAC, but did not highlight PD-related changes in these networks that might explain behavioral changes. Although other new methods might be needed to investigate the presence of task-related networks at the subject-level, this study still highlights that task-based dynamic functional connectivity is a promising approach in understanding the cognitive dysfunctions observed in PD and beyond.
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Key Words
- Cognitive control
- DIFFIT, Difference in data fitting
- DLPFC, Dorso-lateral prefrontal cortex
- EEG, Electroencephalography
- FC, Functional connectivity
- Functional connectivity
- HC, Healthy controls
- HD-EEG, High-density EEG
- ICA, Independent component analysis
- IFC, Inferior frontal cortex
- MEG, Magnetoencephalography
- Networks, Dynamics
- PD, Parkinson's disease
- PLV, Phase locking value
- Parkinson's disease Abbreviations CAC, Cognitive action control
- ROIS, Regions of interest
- RT, Reaction time
- Simon task
- dBNS, Dynamic brain network state
- dFC, Dynamic functional connectivity
- fMRI, Functional magnetic resonance imaging
- high density EEG
- pre-SMA, Pre-supplementary motor area
- tICA, Temporal ICA
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Affiliation(s)
- Joan Duprez
- Univ Rennes, LTSI - U1099, F-35000 Rennes, France
| | - Judie Tabbal
- Univ Rennes, LTSI - U1099, F-35000 Rennes, France; Azm Center for Research in Biotechnology and Its Applications, EDST, Lebanese University, Beirut, Lebanon
| | - Mahmoud Hassan
- MINDig, F-35000 Rennes, France; School of Engineering, Reykjavik University, Iceland
| | | | | | | | - Sophie Drapier
- CIC INSERM 1414, Rennes, France; Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France
| | - Marc Vérin
- Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France; Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France
| | - Paul Sauleau
- Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France; Neurophysiology department, Rennes University Hospital, France
| | | | | | - Jean-François Houvenaghel
- Neurology Department, Pontchaillou Hospital, Rennes University Hospital, France; Behavioral and Basal Ganglia' Research Unit, University of Rennes 1-Rennes University Hospital, France
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Sánchez-Claros J, Pariz A, Valizadeh A, Canals S, Mirasso CR. Information Transmission in Delay-Coupled Neuronal Circuits in the Presence of a Relay Population. Front Syst Neurosci 2021; 15:705371. [PMID: 34393731 PMCID: PMC8357994 DOI: 10.3389/fnsys.2021.705371] [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: 05/05/2021] [Accepted: 06/30/2021] [Indexed: 12/04/2022] Open
Abstract
Synchronization between neuronal populations is hypothesized to play a crucial role in the communication between brain networks. The binding of features, or the association of computations occurring in spatially segregated areas, is supposed to take place when a stable synchronization between cortical areas occurs. While a direct cortico-cortical connection typically fails to support this mechanism, the participation of a third area, a relay element, mediating in the communication was proposed to overcome this limitation. Among the different structures that could play the role of coordination during the binding process, the thalamus is the best placed region to carry out this task. In this paper we study how information flows in a canonical motif that mimics a cortico-thalamo-cortical circuit composed by three mutually coupled neuronal populations (also called the V-motif). Through extensive numerical simulations, we found that the amount of information transferred between the oscillating neuronal populations is determined by the delay in their connections and the mismatch in their oscillation frequencies (detuning). While the transmission from a cortical population is mostly restricted to positive detuning, transmission from the relay (thalamic) population to the cortical populations is robust for a broad range of detuning values, including negative values, while permitting feedback communication from the cortex at high frequencies, thus supporting robust bottom up and top down interaction. In this case, a strong feedback transmission between the cortex to thalamus supports the possibility of robust bottom-up and top-down interactions in this motif. Interestingly, adding a cortico-cortical bidirectional connection to the V-motif (C-motif) expands the dynamics of the system with distinct operation modes. While overall transmission efficiency is decreased, new communication channels establish cortico-thalamo-cortical association loops. Switching between operation modes depends on the synaptic strength of the cortico-cortical connections. Our results support a role of the transthalamic V-motif in the binding of spatially segregated cortical computations, and suggest an important regulatory role of the direct cortico-cortical connection.
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Affiliation(s)
- Jaime Sánchez-Claros
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC, UIB-CSIC), Campus UIB, Palma de Mallorca, Spain
| | - Aref Pariz
- Institute for Advanced Studies in Basic Sciences, Zanjan, Iran.,Department of Biology, University of Ottawa, Ottawa, ON, Canada
| | | | - Santiago Canals
- Instituto de Neurociencias, Consejo Superior de Investigaciones Científicas, Universidad Miguel Hernández, Sant Joan d'Alacant, Spain
| | - Claudio R Mirasso
- Instituto de Física Interdisciplinar y Sistemas Complejos (IFISC, UIB-CSIC), Campus UIB, Palma de Mallorca, Spain
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5
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Khan AF, Zhang F, Yuan H, Ding L. Brain-wide functional diffuse optical tomography of resting state networks. J Neural Eng 2021; 18. [PMID: 33946052 DOI: 10.1088/1741-2552/abfdf9] [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: 11/15/2020] [Accepted: 05/04/2021] [Indexed: 02/07/2023]
Abstract
Objective.Diffuse optical tomography (DOT) has the potential in reconstructing resting state networks (RSNs) in human brains with high spatio-temporal resolutions and multiple contrasts. While several RSNs have been reported and successfully reconstructed using DOT, its full potential in recovering a collective set of distributed brain-wide networks with the number of RSNs close to those reported using functional magnetic resonance imaging (fMRI) has not been demonstrated.Approach.The present study developed a novel brain-wide DOT (BW-DOT) framework that integrates a cap-based whole-head optode placement system with multiple computational approaches, i.e. finite-element modeling, inverse source reconstruction, data-driven pattern recognition, and statistical correlation tomography, to reconstruct RSNs in dual contrasts of oxygenated (HbO) and deoxygenated hemoglobins (HbR).Main results.Our results from the proposed framework revealed a comprehensive set of RSNs and their subnetworks, which collectively cover almost the entire neocortical surface of the human brain, both at the group level and individual participants. The spatial patterns of these DOT RSNs suggest statistically significant similarities to fMRI RSN templates. Our results also reported the networks involving the medial prefrontal cortex and precuneus that had been missed in previous DOT studies. Furthermore, RSNs obtained from HbO and HbR suggest similarity in terms of both the number of RSN types reconstructed and their corresponding spatial patterns, while HbR RSNs show statistically more similarity to fMRI RSN templates and HbO RSNs indicate more bilateral patterns over two hemispheres. In addition, the BW-DOT framework allowed consistent reconstructions of RSNs across individuals and across recording sessions, indicating its high robustness and reproducibility, respectively.Significance.Our present results suggest the feasibility of using the BW-DOT, as a neuroimaging tool, in simultaneously mapping multiple RSNs and its potential values in studying RSNs, particularly in patient populations under diverse conditions and needs, due to its advantages in accessibility over fMRI.
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Affiliation(s)
- Ali F Khan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States of America
| | - Fan Zhang
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States of America
| | - Han Yuan
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States of America.,Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States of America
| | - Lei Ding
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, United States of America.,Institute for Biomedical Engineering, Science, and Technology, University of Oklahoma, Norman, OK, United States of America
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6
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Oscillation-Based Connectivity Architecture Is Dominated by an Intrinsic Spatial Organization, Not Cognitive State or Frequency. J Neurosci 2020; 41:179-192. [PMID: 33203739 DOI: 10.1523/jneurosci.2155-20.2020] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2020] [Revised: 10/10/2020] [Accepted: 11/03/2020] [Indexed: 11/21/2022] Open
Abstract
Functional connectivity of neural oscillations (oscillation-based FC) is thought to afford dynamic information exchange across task-relevant neural ensembles. Although oscillation-based FC is classically defined relative to a prestimulus baseline, giving rise to rapid, context-dependent changes in individual connections, studies of distributed spatial patterns show that oscillation-based FC is omnipresent, occurring even in the absence of explicit cognitive demands. Thus, the issue of whether oscillation-based FC is primarily shaped by cognitive state or is intrinsic in nature remains open. Accordingly, we sought to reconcile these observations by interrogating the ECoG recordings of 18 presurgical human patients (8 females) for state dependence of oscillation-based FC in five canonical frequency bands across an array of six task states. FC analysis of phase and amplitude coupling revealed a highly similar, largely state-invariant (i.e., intrinsic) spatial component across cognitive states. This spatial organization was shared across all frequency bands. Crucially, however, each band also exhibited temporally independent FC dynamics capable of supporting frequency-specific information exchange. In conclusion, the spatial organization of oscillation-based FC is largely stable over cognitive states (i.e., primarily intrinsic in nature) and shared across frequency bands. Together, our findings converge with previous observations of spatially invariant patterns of FC derived from extremely slow and aperiodic fluctuations in fMRI signals. Our observations indicate that "background" FC should be accounted for in conceptual frameworks of oscillation-based FC targeting task-related changes.SIGNIFICANCE STATEMENT A fundamental property of neural activity is that it is periodic, enabling functional connectivity (FC) between distant regions through coupling of their oscillations. According to task-based studies, such oscillation-based FC is rapid and malleable to meet cognitive task demands. Studying distributed FC patterns instead of FC in a few individual connections, we found that oscillation-based FC is largely stable across various cognitive states and shares a common layout across oscillation frequencies. This stable spatial organization of FC in fast oscillatory brain signals parallels the known stability of fMRI-based intrinsic FC architecture. Despite the observed spatial state and frequency invariance, FC of individual connections was temporally independent between frequency bands, suggesting a putative mechanism for malleable frequency-specific FC to support cognitive tasks.
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7
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O'Reilly C, Elsabbagh M. Intracranial recordings reveal ubiquitous in-phase and in-antiphase functional connectivity between homotopic brain regions in humans. J Neurosci Res 2020; 99:887-897. [PMID: 33190333 DOI: 10.1002/jnr.24748] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 09/26/2020] [Accepted: 10/18/2020] [Indexed: 02/02/2023]
Abstract
Whether neuronal populations exhibit zero-lag (in-phase or in-antiphase) functional connectivity is a fundamental question when conceptualizing communication between cell assemblies. It also has profound implications on how we assess such interactions. Given that the brain is a delayed network due to the finite conduction velocity of the electrical impulses traveling across its fibers, the existence of long-distance zero-lag functional connectivity may be considered improbable. However, in this study, using human intracranial recordings we demonstrate that most interhemispheric connectivity between homotopic cerebral regions is zero-lagged and that this type of connectivity is ubiquitous. Volume conduction can be safely discarded as a confounding factor since it is known to drop almost completely within short interelectrode distances (<20 mm) in intracranial recordings. This finding should guide future electrophysiological connectivity studies and highlight the importance of considering the role of zero-lag connectivity in our understanding of communication between cell assemblies.
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Affiliation(s)
- Christian O'Reilly
- Azrieli Centre for Autism Research, Montreal Neurological Institute-Hospital, McGill University, Montreal, QC, Canada
| | - Mayada Elsabbagh
- Azrieli Centre for Autism Research, Montreal Neurological Institute-Hospital, McGill University, Montreal, QC, Canada
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8
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Mostame P, Sadaghiani S. Phase- and amplitude-coupling are tied by an intrinsic spatial organization but show divergent stimulus-related changes. Neuroimage 2020; 219:117051. [DOI: 10.1016/j.neuroimage.2020.117051] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Revised: 06/08/2020] [Accepted: 06/10/2020] [Indexed: 12/27/2022] Open
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9
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Sadaghiani S, Wirsich J. Intrinsic connectome organization across temporal scales: New insights from cross-modal approaches. Netw Neurosci 2020; 4:1-29. [PMID: 32043042 PMCID: PMC7006873 DOI: 10.1162/netn_a_00114] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2019] [Accepted: 11/11/2019] [Indexed: 12/17/2022] Open
Abstract
The discovery of a stable, whole-brain functional connectivity organization that is largely independent of external events has drastically extended our view of human brain function. However, this discovery has been primarily based on functional magnetic resonance imaging (fMRI). The role of this whole-brain organization in fast oscillation-based connectivity as measured, for example, by electroencephalography (EEG) and magnetoencephalography (MEG) is only beginning to emerge. Here, we review studies of intrinsic connectivity and its whole-brain organization in EEG, MEG, and intracranial electrophysiology with a particular focus on direct comparisons to connectome studies in fMRI. Synthesizing this literature, we conclude that irrespective of temporal scale over four orders of magnitude, intrinsic neurophysiological connectivity shows spatial similarity to the connectivity organization commonly observed in fMRI. A shared structural connectivity basis and cross-frequency coupling are possible mechanisms contributing to this similarity. Acknowledging that a stable whole-brain organization governs long-range coupling across all timescales of neural processing motivates researchers to take "baseline" intrinsic connectivity into account when investigating brain-behavior associations, and further encourages more widespread exploration of functional connectomics approaches beyond fMRI by using EEG and MEG modalities.
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Affiliation(s)
- Sepideh Sadaghiani
- Psychology Department, University of Illinois at Urbana-Champaign, Urbana, IL, USA
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - Jonathan Wirsich
- Beckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, IL, USA
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10
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Exploring the Correlation Between M/EEG Source–Space and fMRI Networks at Rest. Brain Topogr 2020; 33:151-160. [DOI: 10.1007/s10548-020-00753-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Accepted: 01/23/2020] [Indexed: 11/26/2022]
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11
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Nickel MM, Ta Dinh S, May ES, Tiemann L, Hohn VD, Gross J, Ploner M. Neural oscillations and connectivity characterizing the state of tonic experimental pain in humans. Hum Brain Mapp 2019; 41:17-29. [PMID: 31498948 PMCID: PMC7267966 DOI: 10.1002/hbm.24784] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/26/2019] [Accepted: 08/26/2019] [Indexed: 01/07/2023] Open
Abstract
Pain is a complex phenomenon that is served by neural oscillations and connectivity involving different brain areas and frequencies. Here, we aimed to systematically and comprehensively assess the pattern of neural oscillations and connectivity characterizing the state of tonic experimental pain in humans. To this end, we applied 10-min heat pain stimuli consecutively to the right and left hand of 39 healthy participants and recorded electroencephalography. We systematically analyzed global and local measures of oscillatory brain activity, connectivity, and graph theory-based network measures during tonic pain and compared them to a nonpainful control condition. Local measures showed suppressions of oscillatory activity at alpha frequencies together with stronger connectivity at alpha and beta frequencies in sensorimotor areas during tonic pain. Furthermore, sensorimotor areas contralateral to stimulation showed significantly increased connectivity to a common area in the medial prefrontal cortex at alpha frequencies. Together, these observations indicate that the state of tonic experimental pain is associated with a sensorimotor-prefrontal network connected at alpha frequencies. These findings represent a step further toward understanding the brain mechanisms underlying long-lasting pain states in health and disease.
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Affiliation(s)
- Moritz M Nickel
- Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Son Ta Dinh
- Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Elisabeth S May
- Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Laura Tiemann
- Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Vanessa D Hohn
- Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine, Technical University of Munich, Munich, Germany
| | - Joachim Gross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.,Institute for Biomagnetism and Biosignalanalysis, University of Münster, Münster, Germany
| | - Markus Ploner
- Department of Neurology and TUM-Neuroimaging Center, TUM School of Medicine, Technical University of Munich, Munich, Germany
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12
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John YJ, Zikopoulos B, Bullock D, Barbas H. Visual Attention Deficits in Schizophrenia Can Arise From Inhibitory Dysfunction in Thalamus or Cortex. COMPUTATIONAL PSYCHIATRY (CAMBRIDGE, MASS.) 2018; 2:223-257. [PMID: 30627672 PMCID: PMC6317791 DOI: 10.1162/cpsy_a_00023] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 10/17/2018] [Indexed: 01/13/2023]
Abstract
Schizophrenia is associated with diverse cognitive deficits, including disorders of attention-related oculomotor behavior. At the structural level, schizophrenia is associated with abnormal inhibitory control in the circuit linking cortex and thalamus. We developed a spiking neural network model that demonstrates how dysfunctional inhibition can degrade attentive gaze control. Our model revealed that perturbations of two functionally distinct classes of cortical inhibitory neurons, or of the inhibitory thalamic reticular nucleus, disrupted processing vital for sustained attention to a stimulus, leading to distractibility. Because perturbation at each circuit node led to comparable but qualitatively distinct disruptions in attentive tracking or fixation, our findings support the search for new eye movement metrics that may index distinct underlying neural defects. Moreover, because the cortico-thalamic circuit is a common motif across sensory, association, and motor systems, the model and extensions can be broadly applied to study normal function and the neural bases of other cognitive deficits in schizophrenia.
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Affiliation(s)
- Yohan J. John
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA
| | - Basilis Zikopoulos
- Human Systems Neuroscience Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA
- Graduate Program for Neuroscience, Boston University, and School of Medicine, Boston, Massachusetts, USA
| | - Daniel Bullock
- Graduate Program for Neuroscience, Boston University, and School of Medicine, Boston, Massachusetts, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, Massachusetts, USA
| | - Helen Barbas
- Neural Systems Laboratory, Department of Health Sciences, Boston University, Boston, Massachusetts, USA
- Graduate Program for Neuroscience, Boston University, and School of Medicine, Boston, Massachusetts, USA
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13
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Viriyopase A, Memmesheimer RM, Gielen S. Analyzing the competition of gamma rhythms with delayed pulse-coupled oscillators in phase representation. Phys Rev E 2018; 98:022217. [PMID: 30253475 DOI: 10.1103/physreve.98.022217] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Indexed: 12/27/2022]
Abstract
Networks of neurons can generate oscillatory activity as result of various types of coupling that lead to synchronization. A prominent type of oscillatory activity is gamma (30-80 Hz) rhythms, which may play an important role in neuronal information processing. Two mechanisms have mainly been proposed for their generation: (1) interneuron network gamma (ING) and (2) pyramidal-interneuron network gamma (PING). In vitro and in vivo experiments have shown that both mechanisms can exist in the same cortical circuits. This raises the questions: How do ING and PING interact when both can in principle occur? Are the network dynamics a superposition, or do ING and PING interact in a nonlinear way and if so, how? In this article, we first generalize the phase representation for nonlinear one-dimensional pulse coupled oscillators as introduced by Mirollo and Strogatz to type II oscillators whose phase response curve (PRC) has zero crossings. We then give a full theoretical analysis for the regular gamma-like oscillations of simple networks consisting of two neural oscillators, an "E neuron" mimicking a synchronized group of pyramidal cells, and an "I neuron" representing such a group of interneurons. Motivated by experimental findings, we choose the E neuron to have a type I PRC [leaky integrate-and-fire (LIF) neuron], while the I neuron has either a type I or type II PRC (LIF or "sine" neuron). The phase representation allows us to define in a simple manner scenarios of interaction between the two neurons, which are independent of the types and the details of the neuron models. The presence of delay in the couplings leads to an increased number of scenarios relevant for gamma-like oscillatory patterns. We analytically derive the set of such scenarios and describe their occurrence in terms of parameter values such as synaptic connectivity and drive to the E and I neurons. The networks can be tuned to oscillate in an ING or PING mode. We focus particularly on the transition region where both rhythms compete to govern the network dynamics and compare with oscillations in reduced networks, which can only generate either ING or PING. Our analytically derived oscillation frequency diagrams indicate that except for small coexistence regions, the networks generate ING if the oscillation frequency of the reduced ING network exceeds that of the reduced PING network, and vice versa. For networks with the LIF I neuron, the network oscillation frequency slightly exceeds the frequencies of corresponding reduced networks, while it lies between them for networks with the sine I neuron. In networks oscillating in ING (PING) mode, the oscillation frequency responds faster to changes in the drive to the I (E) neuron than to changes in the drive to the E (I) neuron. This finding suggests a method to analyze which mechanism governs an observed network oscillation. Notably, also when the network operates in ING mode, the E neuron can spike before the I neuron such that relative spike times of the pyramidal cells and the interneurons alone are not conclusive for distinguishing ING and PING.
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Affiliation(s)
- Atthaphon Viriyopase
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.,Department of Biophysics, Faculty of Science, Radboud University Nijmegen, Nijmegen, The Netherlands.,Department of Neuroinformatics, Faculty of Science, Radboud University Nijmegen, Nijmegen, The Netherlands
| | - Raoul-Martin Memmesheimer
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.,Department of Neuroinformatics, Faculty of Science, Radboud University Nijmegen, Nijmegen, The Netherlands.,Center for Theoretical Neuroscience, Columbia University, New York, New York 10027, USA.,FIAS-Frankfurt Institute for Advanced Studies, Frankfurt am Main, Germany.,Neural Network Dynamics and Computation, Institute of Genetics, University of Bonn, Bonn, Germany
| | - Stan Gielen
- Donders Institute for Brain, Cognition, and Behaviour, Radboud University Nijmegen, Nijmegen, The Netherlands.,Department of Biophysics, Faculty of Science, Radboud University Nijmegen, Nijmegen, The Netherlands
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14
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The cortical focus in childhood absence epilepsy; evidence from nonlinear analysis of scalp EEG recordings. Clin Neurophysiol 2018; 129:602-617. [DOI: 10.1016/j.clinph.2017.11.029] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Revised: 11/05/2017] [Accepted: 11/29/2017] [Indexed: 11/19/2022]
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15
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West TO, Berthouze L, Halliday DM, Litvak V, Sharott A, Magill PJ, Farmer SF. Propagation of beta/gamma rhythms in the cortico-basal ganglia circuits of the parkinsonian rat. J Neurophysiol 2018; 119:1608-1628. [PMID: 29357448 PMCID: PMC6008089 DOI: 10.1152/jn.00629.2017] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Much of the motor impairment associated with Parkinson’s disease is thought to arise from pathological activity in the networks formed by the basal ganglia (BG) and motor cortex. To evaluate several hypotheses proposed to explain the emergence of pathological oscillations in parkinsonism, we investigated changes to the directed connectivity in BG networks following dopamine depletion. We recorded local field potentials (LFPs) in the cortex and basal ganglia of rats rendered parkinsonian by injection of 6-hydroxydopamine (6-OHDA) and in dopamine-intact controls. We performed systematic analyses of the networks using a novel tool for estimation of directed interactions (nonparametric directionality, NPD). We used a “conditioned” version of the NPD analysis that reveals the dependence of the correlation between two signals on a third reference signal. We find evidence of the dopamine dependency of both low-beta (14–20 Hz) and high-beta/low-gamma (20–40 Hz) directed network interactions. Notably, 6-OHDA lesions were associated with enhancement of the cortical “hyperdirect” connection to the subthalamic nucleus (STN) and its feedback to the cortex and striatum. We find that pathological beta synchronization resulting from 6-OHDA lesioning is widely distributed across the network and cannot be located to any individual structure. Furthermore, we provide evidence that high-beta/gamma oscillations propagate through the striatum in a pathway that is independent of STN. Rhythms at high beta/gamma show susceptibility to conditioning that indicates a hierarchical organization compared with those at low beta. These results further inform our understanding of the substrates for pathological rhythms in salient brain networks in parkinsonism. NEW & NOTEWORTHY We present a novel analysis of electrophysiological recordings in the cortico-basal ganglia network with the aim of evaluating several hypotheses concerning the origins of abnormal brain rhythms associated with Parkinson’s disease. We present evidence for changes in the directed connections within the network following chronic dopamine depletion in rodents. These findings speak to the plausibility of a “short-circuiting” of the network that gives rise to the conditions from which pathological synchronization may arise.
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Affiliation(s)
- Timothy O West
- Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), Department of Physics and Astronomy, University College London , London , United Kingdom.,Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London , London , United Kingdom
| | - Luc Berthouze
- Centre for Computational Neuroscience and Robotics, University of Sussex , Falmer , United Kingdom.,UCL Great Ormond Street Institute of Child Health , London , United Kingdom
| | - David M Halliday
- Department of Electronic Engineering, University of York , York , United Kingdom
| | - Vladimir Litvak
- Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London , London , United Kingdom
| | - Andrew Sharott
- Medical Research Council Brain Network Dynamics Unit, University of Oxford , Oxford , United Kingdom
| | - Peter J Magill
- Medical Research Council Brain Network Dynamics Unit, University of Oxford , Oxford , United Kingdom.,Oxford Parkinson's Disease Centre, University of Oxford , Oxford , United Kingdom
| | - Simon F Farmer
- Department of Neurology, National Hospital for Neurology & Neurosurgery , London , United Kingdom.,Sobell Department of Motor Neuroscience and Movement Disorders, Institute of Neurology, University College London , London , United Kingdom
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16
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Abstract
The phenomenon of “remote synchronization” (RS), first observed in a star network of oscillators, involves synchronization of unconnected peripheral nodes through a hub that maintains independent dynamics. In the RS regime the central hub was thought to serve as a passive gate for information transfer between nodes. Here, we investigate the physical origin of this phenomenon. Surprisingly, we find that a hub node can drive remote synchronization of peripheral oscillators even in the presence of a repulsive mean field, thus actively governing network dynamics while remaining asynchronous. We study this novel phenomenon in complex networks endowed with multiple hub-nodes, a ubiquitous feature of many real-world systems, including brain connectivity networks. We show that a change in the natural frequency of a single hub can alone reshape synchronization patterns across the entire network, and switch from direct to remote synchronization, or to hub-driven desynchronization. Hub-driven RS may provide a mechanism to account for the role of structural hubs in the organization of brain functional connectivity networks.
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17
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Slovik M, Rosin B, Moshel S, Mitelman R, Schechtman E, Eitan R, Raz A, Bergman H. Ketamine induced converged synchronous gamma oscillations in the cortico-basal ganglia network of nonhuman primates. J Neurophysiol 2017; 118:917-931. [PMID: 28468999 DOI: 10.1152/jn.00765.2016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 04/19/2017] [Accepted: 04/28/2017] [Indexed: 11/22/2022] Open
Abstract
N-methyl-d-aspartate (NMDA) antagonists are widely used in anesthesia, pain management, and schizophrenia animal model studies, and recently as potential antidepressants. However, the mechanisms underlying their anesthetic, psychotic, cognitive, and emotional effects are still elusive. The basal ganglia (BG) integrate input from different cortical domains through their dopamine-modulated connections to achieve optimal behavior control. NMDA antagonists have been shown to induce gamma oscillations in human EEG recordings and in rodent cortical and BG networks. However, network relations and implications to the primate brain are still unclear. We recorded local field potentials (LFPs) simultaneously from the primary motor cortex (M1) and the external globus pallidus (GPe) of four vervet monkeys (26 sessions, 97 and 76 cortical and pallidal LFPs, respectively) before and after administration of ketamine (NMDA antagonist, 10 mg/kg im). Ketamine induced robust, spontaneous gamma (30-50 Hz) oscillations in M1 and GPe. These oscillations were initially modulated by ultraslow oscillations (~0.3 Hz) and were highly synchronized within and between M1 and the GPe (mean coherence magnitude = 0.76, 0.88, and 0.41 for M1-M1, GPe-GPe, and M1-GPe pairs). Phase differences were distributed evenly around zero with broad and very narrow distribution for the M1-M1 and GPe-GPe pairs (-3.5 ± 31.8° and -0.4 ± 6.0°), respectively. The distribution of M1-GPe phase shift was skewed to the left with a mean of -18.4 ± 20.9°. The increased gamma coherence between M1 and GPe, two central stages in the cortico-BG loops, suggests a global abnormal network phenomenon with a unique spectral signature, which is enabled by the BG funneling architecture.NEW & NOTEWORTHY This study is the first to show spontaneous gamma oscillations under NMDA antagonist in nonhuman primates. These oscillations appear in synchrony in the cortex and the basal ganglia. Phase analysis refutes the confounding effects of volume conduction and supports the funneling and amplifying architecture of the cortico-basal ganglia loops. These results suggest an abnormal network phenomenon with a unique spectral signature that could account for pathological mental and neurological states.
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Affiliation(s)
- Maya Slovik
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel; .,Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.,Department of Family Medicine, Clalit Health Services, Jerusalem, Israel
| | - Boris Rosin
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,Department of Ophthalmology, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Shay Moshel
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Interdisciplinary Center for Neural Computation and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel.,The Research Laboratory of Brain Imaging and Stimulation, The Jerusalem Mental Health Center, Kfar-Shaul Eitanim, Hebrew University-Hadassah Medical School, Jerusalem, Israel
| | - Rea Mitelman
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Interdisciplinary Center for Neural Computation and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
| | - Eitan Schechtman
- The Interdisciplinary Center for Neural Computation and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel
| | - Renana Eitan
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,Functional Neuroimaging Laboratory, Department of Psychiatry, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Aeyal Raz
- Department of Anesthesiology, University of Wisconsin, School of Medicine and Public Health, Madison, Wisconsin.,Department of Anesthesiology, Rambam Health Care Campus, Haifa, Israel; and
| | - Hagai Bergman
- Department of Medical Neurobiology, Institute of Medical Research Israel-Canada, The Hebrew University-Hadassah Medical School, Jerusalem, Israel.,The Interdisciplinary Center for Neural Computation and Edmond and Lily Safra Center for Brain Sciences, The Hebrew University, Jerusalem, Israel.,Department of Neurosurgery, Hadassah Medical Center, Jerusalem, Israel
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18
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Zhang L, Motter AE, Nishikawa T. Incoherence-Mediated Remote Synchronization. PHYSICAL REVIEW LETTERS 2017; 118:174102. [PMID: 28498705 DOI: 10.1103/physrevlett.118.174102] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2016] [Indexed: 06/07/2023]
Abstract
In previously identified forms of remote synchronization between two nodes, the intermediate portion of the network connecting the two nodes is not synchronized with them but generally exhibits some coherent dynamics. Here we report on a network phenomenon we call incoherence-mediated remote synchronization (IMRS), in which two noncontiguous parts of the network are identically synchronized while the dynamics of the intermediate part is statistically and information-theoretically incoherent. We identify mirror symmetry in the network structure as a mechanism allowing for such behavior, and show that IMRS is robust against dynamical noise as well as against parameter changes. IMRS may underlie neuronal information processing and potentially lead to network solutions for encryption key distribution and secure communication.
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Affiliation(s)
- Liyue Zhang
- Center for Information Photonics and Communications, Southwest Jiaotong University, Chengdu, Sichuan 610031, China
- Department of Physics and Astronomy, Northwestern University, Evanston, Illinois 60208, USA
| | - Adilson E Motter
- Department of Physics and Astronomy, Northwestern University, Evanston, Illinois 60208, USA
- Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois 60208, USA
| | - Takashi Nishikawa
- Department of Physics and Astronomy, Northwestern University, Evanston, Illinois 60208, USA
- Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois 60208, USA
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19
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Garagnani M, Lucchese G, Tomasello R, Wennekers T, Pulvermüller F. A Spiking Neurocomputational Model of High-Frequency Oscillatory Brain Responses to Words and Pseudowords. Front Comput Neurosci 2017; 10:145. [PMID: 28149276 PMCID: PMC5241316 DOI: 10.3389/fncom.2016.00145] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Accepted: 12/26/2016] [Indexed: 12/22/2022] Open
Abstract
Experimental evidence indicates that neurophysiological responses to well-known meaningful sensory items and symbols (such as familiar objects, faces, or words) differ from those to matched but novel and senseless materials (unknown objects, scrambled faces, and pseudowords). Spectral responses in the high beta- and gamma-band have been observed to be generally stronger to familiar stimuli than to unfamiliar ones. These differences have been hypothesized to be caused by the activation of distributed neuronal circuits or cell assemblies, which act as long-term memory traces for learned familiar items only. Here, we simulated word learning using a biologically constrained neurocomputational model of the left-hemispheric cortical areas known to be relevant for language and conceptual processing. The 12-area spiking neural-network architecture implemented replicates physiological and connectivity features of primary, secondary, and higher-association cortices in the frontal, temporal, and occipital lobes of the human brain. We simulated elementary aspects of word learning in it, focussing specifically on semantic grounding in action and perception. As a result of spike-driven Hebbian synaptic plasticity mechanisms, distributed, stimulus-specific cell-assembly (CA) circuits spontaneously emerged in the network. After training, presentation of one of the learned "word" forms to the model correlate of primary auditory cortex induced periodic bursts of activity within the corresponding CA, leading to oscillatory phenomena in the entire network and spontaneous across-area neural synchronization. Crucially, Morlet wavelet analysis of the network's responses recorded during presentation of learned meaningful "word" and novel, senseless "pseudoword" patterns revealed stronger induced spectral power in the gamma-band for the former than the latter, closely mirroring differences found in neurophysiological data. Furthermore, coherence analysis of the simulated responses uncovered dissociated category specific patterns of synchronous oscillations in distant cortical areas, including indirectly connected primary sensorimotor areas. Bridging the gap between cellular-level mechanisms, neuronal-population behavior, and cognitive function, the present model constitutes the first spiking, neurobiologically, and anatomically realistic model able to explain high-frequency oscillatory phenomena indexing language processing on the basis of dynamics and competitive interactions of distributed cell-assembly circuits which emerge in the brain as a result of Hebbian learning and sensorimotor experience.
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Affiliation(s)
- Max Garagnani
- Department of Computing, Goldsmiths, University of LondonLondon, UK
- Brain Language Laboratory, Department of Philosophy and Humanities, Freie Universität BerlinBerlin, Germany
| | - Guglielmo Lucchese
- Brain Language Laboratory, Department of Philosophy and Humanities, Freie Universität BerlinBerlin, Germany
| | - Rosario Tomasello
- Brain Language Laboratory, Department of Philosophy and Humanities, Freie Universität BerlinBerlin, Germany
- Berlin School of Mind and Brain, Humboldt Universität zu BerlinBerlin, Germany
| | - Thomas Wennekers
- Centre for Robotics and Neural Systems, University of PlymouthPlymouth, UK
| | - Friedemann Pulvermüller
- Brain Language Laboratory, Department of Philosophy and Humanities, Freie Universität BerlinBerlin, Germany
- Berlin School of Mind and Brain, Humboldt Universität zu BerlinBerlin, Germany
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20
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Boeijinga PH. Multimodal EEG Recordings, Psychometrics and Behavioural Analysis. Neuropsychobiology 2016; 72:206-18. [PMID: 26901154 DOI: 10.1159/000437434] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2015] [Accepted: 07/06/2015] [Indexed: 11/19/2022]
Abstract
High spatial and temporal resolution measurements of neuronal activity are preferably combined. In an overview on how this approach can take shape, multimodal electroencephalography (EEG) is treated in 2 main parts: by experiments without a task and in the experimentally cued working brain. It concentrates first on the alpha rhythm properties and next on data-driven search for patterns such as the default mode network. The high-resolution volumic distributions of neuronal metabolic indices result in distributed cortical regions and possibly relate to numerous nuclei, observable in a non-invasive manner in the central nervous system of humans. The second part deals with paradigms in which nowadays assessment of target-related networks can align level-dependent blood oxygenation, electrical responses and behaviour, taking the temporal resolution advantages of event-related potentials. Evidence-based electrical propagation in serial tasks during performance is now to a large extent attributed to interconnected pathways, particularly chronometry-dependent ones, throughout a chain including a dorsal stream, next ventral cortical areas taking the flow of information towards inferior temporal domains. The influence of aging is documented, and results of the first multimodal studies in neuropharmacology are consistent. Finally a scope on implementation of advanced clinical applications and personalized marker strategies in neuropsychiatry is indicated.
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21
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Self-Organized Near-Zero-Lag Synchronization Induced by Spike-Timing Dependent Plasticity in Cortical Populations. PLoS One 2015; 10:e0140504. [PMID: 26474165 PMCID: PMC4608682 DOI: 10.1371/journal.pone.0140504] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 09/21/2015] [Indexed: 12/30/2022] Open
Abstract
Several cognitive tasks related to learning and memory exhibit synchronization of macroscopic cortical areas together with synaptic plasticity at neuronal level. Therefore, there is a growing effort among computational neuroscientists to understand the underlying mechanisms relating synchrony and plasticity in the brain. Here we numerically study the interplay between spike-timing dependent plasticity (STDP) and anticipated synchronization (AS). AS emerges when a dominant flux of information from one area to another is accompanied by a negative time lag (or phase). This means that the receiver region pulses before the sender does. In this paper we study the interplay between different synchronization regimes and STDP at the level of three-neuron microcircuits as well as cortical populations. We show that STDP can promote auto-organized zero-lag synchronization in unidirectionally coupled neuronal populations. We also find synchronization regimes with negative phase difference (AS) that are stable against plasticity. Finally, we show that the interplay between negative phase difference and STDP provides limited synaptic weight distribution without the need of imposing artificial boundaries.
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22
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Ghasemi Esfahani Z, Valizadeh A. Zero-lag synchronization despite inhomogeneities in a relay system. PLoS One 2014; 9:e112688. [PMID: 25486522 PMCID: PMC4259331 DOI: 10.1371/journal.pone.0112688] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2014] [Accepted: 10/10/2014] [Indexed: 11/18/2022] Open
Abstract
A novel proposal for the zero-lag synchronization of the delayed coupled neurons, is to connect them indirectly via a third relay neuron. In this study, we develop a Poincaré map to investigate the robustness of the synchrony in such a relay system against inhomogeneity in the neurons and synaptic parameters. We show that when the inhomogeneity does not violate the symmetry of the system, synchrony is maintained and in some cases inhomogeneity enhances synchrony. On the other hand if the inhomogeneity breaks the symmetry of the system, zero lag synchrony can not be preserved. In this case we give analytical results for the phase lag of the spiking of the neurons in the stable state.
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23
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Barardi A, Sancristóbal B, Garcia-Ojalvo J. Phase-coherence transitions and communication in the gamma range between delay-coupled neuronal populations. PLoS Comput Biol 2014; 10:e1003723. [PMID: 25058021 PMCID: PMC4110076 DOI: 10.1371/journal.pcbi.1003723] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Accepted: 06/01/2014] [Indexed: 11/28/2022] Open
Abstract
Synchronization between neuronal populations plays an important role in information transmission between brain areas. In particular, collective oscillations emerging from the synchronized activity of thousands of neurons can increase the functional connectivity between neural assemblies by coherently coordinating their phases. This synchrony of neuronal activity can take place within a cortical patch or between different cortical regions. While short-range interactions between neurons involve just a few milliseconds, communication through long-range projections between different regions could take up to tens of milliseconds. How these heterogeneous transmission delays affect communication between neuronal populations is not well known. To address this question, we have studied the dynamics of two bidirectionally delayed-coupled neuronal populations using conductance-based spiking models, examining how different synaptic delays give rise to in-phase/anti-phase transitions at particular frequencies within the gamma range, and how this behavior is related to the phase coherence between the two populations at different frequencies. We have used spectral analysis and information theory to quantify the information exchanged between the two networks. For different transmission delays between the two coupled populations, we analyze how the local field potential and multi-unit activity calculated from one population convey information in response to a set of external inputs applied to the other population. The results confirm that zero-lag synchronization maximizes information transmission, although out-of-phase synchronization allows for efficient communication provided the coupling delay, the phase lag between the populations, and the frequency of the oscillations are properly matched.
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Affiliation(s)
- Alessandro Barardi
- Departament of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
- Departament de Física i Enginyeria Nuclear, Universitat Politècnica de Catalunya, Terrassa, Spain
| | - Belen Sancristóbal
- Center for Genomic Regulation, Barcelona Biomedical Research Park, Barcelona, Spain
| | - Jordi Garcia-Ojalvo
- Departament of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona Biomedical Research Park, Barcelona, Spain
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24
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Thivierge JP, Comas R, Longtin A. Attractor dynamics in local neuronal networks. Front Neural Circuits 2014; 8:22. [PMID: 24688457 PMCID: PMC3960591 DOI: 10.3389/fncir.2014.00022] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2013] [Accepted: 03/02/2014] [Indexed: 12/01/2022] Open
Abstract
Patterns of synaptic connectivity in various regions of the brain are characterized by the presence of synaptic motifs, defined as unidirectional and bidirectional synaptic contacts that follow a particular configuration and link together small groups of neurons. Recent computational work proposes that a relay network (two populations communicating via a third, relay population of neurons) can generate precise patterns of neural synchronization. Here, we employ two distinct models of neuronal dynamics and show that simulated neural circuits designed in this way are caught in a global attractor of activity that prevents neurons from modulating their response on the basis of incoming stimuli. To circumvent the emergence of a fixed global attractor, we propose a mechanism of selective gain inhibition that promotes flexible responses to external stimuli. We suggest that local neuronal circuits may employ this mechanism to generate precise patterns of neural synchronization whose transient nature delimits the occurrence of a brief stimulus.
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Affiliation(s)
| | - Rosa Comas
- School of Psychology, University of Ottawa ON, Canada
| | - André Longtin
- Department of Physics, University of Ottawa ON, Canada
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25
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Quantitative EEG analysis using error reduction ratio-causality test; validation on simulated and real EEG data. Clin Neurophysiol 2014; 125:32-46. [DOI: 10.1016/j.clinph.2013.06.012] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2013] [Revised: 05/08/2013] [Accepted: 06/15/2013] [Indexed: 01/19/2023]
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26
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Canavier CC, Wang S, Chandrasekaran L. Effect of phase response curve skew on synchronization with and without conduction delays. Front Neural Circuits 2013; 7:194. [PMID: 24376399 PMCID: PMC3858834 DOI: 10.3389/fncir.2013.00194] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2013] [Accepted: 11/23/2013] [Indexed: 11/13/2022] Open
Abstract
A central problem in cortical processing including sensory binding and attentional gating is how neurons can synchronize their responses with zero or near-zero time lag. For a spontaneously firing neuron, an input from another neuron can delay or advance the next spike by different amounts depending upon the timing of the input relative to the previous spike. This information constitutes the phase response curve (PRC). We present a simple graphical method for determining the effect of PRC shape on synchronization tendencies and illustrate it using type 1 PRCs, which consist entirely of advances (delays) in response to excitation (inhibition). We obtained the following generic solutions for type 1 PRCs, which include the pulse-coupled leaky integrate and fire model. For pairs with mutual excitation, exact synchrony can be stable for strong coupling because of the stabilizing effect of the causal limit region of the PRC in which an input triggers a spike immediately upon arrival. However, synchrony is unstable for short delays, because delayed inputs arrive during a refractory period and cannot trigger an immediate spike. Right skew destabilizes antiphase and enables modes with time lags that grow as the conduction delay is increased. Therefore, right skew favors near synchrony at short conduction delays and a gradual transition between synchrony and antiphase for pairs coupled by mutual excitation. For pairs with mutual inhibition, zero time lag synchrony is stable for conduction delays ranging from zero to a substantial fraction of the period for pairs. However, for right skew there is a preferred antiphase mode at short delays. In contrast to mutual excitation, left skew destabilizes antiphase for mutual inhibition so that synchrony dominates at short delays as well. These pairwise synchronization tendencies constrain the synchronization properties of neurons embedded in larger networks.
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Affiliation(s)
- Carmen C Canavier
- Department of Cell Biology and Anatomy, Louisiana State University School of Medicine, Louisiana State University Health Sciences Center New Orleans, LA, USA ; Neuroscience Center, Louisiana State University Health Sciences Center New Orleans, LA, USA
| | - Shuoguo Wang
- Department of Cell Biology and Anatomy, Louisiana State University School of Medicine, Louisiana State University Health Sciences Center New Orleans, LA, USA
| | - Lakshmi Chandrasekaran
- Department of Cell Biology and Anatomy, Louisiana State University School of Medicine, Louisiana State University Health Sciences Center New Orleans, LA, USA
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27
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Lord LD, Expert P, Huckins JF, Turkheimer FE. Cerebral energy metabolism and the brain's functional network architecture: an integrative review. J Cereb Blood Flow Metab 2013; 33:1347-54. [PMID: 23756687 PMCID: PMC3764392 DOI: 10.1038/jcbfm.2013.94] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2013] [Revised: 05/15/2013] [Accepted: 05/15/2013] [Indexed: 12/20/2022]
Abstract
Recent functional magnetic resonance imaging (fMRI) studies have emphasized the contributions of synchronized activity in distributed brain networks to cognitive processes in both health and disease. The brain's 'functional connectivity' is typically estimated from correlations in the activity time series of anatomically remote areas, and postulated to reflect information flow between neuronal populations. Although the topological properties of functional brain networks have been studied extensively, considerably less is known regarding the neurophysiological and biochemical factors underlying the temporal coordination of large neuronal ensembles. In this review, we highlight the critical contributions of high-frequency electrical oscillations in the γ-band (30 to 100 Hz) to the emergence of functional brain networks. After describing the neurobiological substrates of γ-band dynamics, we specifically discuss the elevated energy requirements of high-frequency neural oscillations, which represent a mechanistic link between the functional connectivity of brain regions and their respective metabolic demands. Experimental evidence is presented for the high oxygen and glucose consumption, and strong mitochondrial performance required to support rhythmic cortical activity in the γ-band. Finally, the implications of mitochondrial impairments and deficits in glucose metabolism for cognition and behavior are discussed in the context of neuropsychiatric and neurodegenerative syndromes characterized by large-scale changes in the organization of functional brain networks.
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Affiliation(s)
- Louis-David Lord
- Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, Massachusetts, USA
| | - Paul Expert
- Institute of Psychiatry, King's College London, London, UK
| | - Jeremy F Huckins
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, USA
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28
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Sadeghi S, Valizadeh A. Synchronization of delayed coupled neurons in presence of inhomogeneity. J Comput Neurosci 2013; 36:55-66. [PMID: 23744009 DOI: 10.1007/s10827-013-0461-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2013] [Revised: 05/02/2013] [Accepted: 05/09/2013] [Indexed: 10/26/2022]
Abstract
In principle, two directly coupled limit cycle oscillators can overcome mismatch in intrinsic rates and match their frequencies, but zero phase lag synchronization is just achievable in the limit of zero mismatch, i.e., with identical oscillators. Delay in communication, on the other hand, can exert phase shift in the activity of the coupled oscillators. In this study, we address the question of how phase locked, and in particular zero phase lag synchronization, can be achieved for a heterogeneous system of two delayed coupled neurons. We have analytically studied the possibility of inphase synchronization and near inphase synchronization when the neurons are not identical or the connections are not exactly symmetric. We have shown that while any single source of inhomogeneity can violate isochronous synchrony, multiple sources of inhomogeneity can compensate for each other and maintain synchrony. Numeric studies on biologically plausible models also support the analytic results.
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Affiliation(s)
- S Sadeghi
- Institute for Advanced Studies in Basic Sciences (IASBS), P. O. Box 45195-1159, Zanjan, Iran
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29
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Nicosia V, Valencia M, Chavez M, Díaz-Guilera A, Latora V. Remote synchronization reveals network symmetries and functional modules. PHYSICAL REVIEW LETTERS 2013; 110:174102. [PMID: 23679731 DOI: 10.1103/physrevlett.110.174102] [Citation(s) in RCA: 104] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2012] [Revised: 02/12/2013] [Indexed: 06/02/2023]
Abstract
We study a Kuramoto model in which the oscillators are associated with the nodes of a complex network and the interactions include a phase frustration, thus preventing full synchronization. The system organizes into a regime of remote synchronization where pairs of nodes with the same network symmetry are fully synchronized, despite their distance on the graph. We provide analytical arguments to explain this result, and we show how the frustration parameter affects the distribution of phases. An application to brain networks suggests that anatomical symmetry plays a role in neural synchronization by determining correlated functional modules across distant locations.
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Affiliation(s)
- Vincenzo Nicosia
- School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, United Kingdom
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30
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Vardi R, Timor R, Marom S, Abeles M, Kanter I. Synchronization by elastic neuronal latencies. PHYSICAL REVIEW. E, STATISTICAL, NONLINEAR, AND SOFT MATTER PHYSICS 2013; 87:012724. [PMID: 23410376 DOI: 10.1103/physreve.87.012724] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2012] [Revised: 12/11/2012] [Indexed: 06/01/2023]
Abstract
Psychological and physiological considerations entail that formation and functionality of neuronal cell assemblies depend upon synchronized repeated activation such as zero-lag synchronization. Several mechanisms for the emergence of this phenomenon have been suggested, including the global network quantity, the greatest common divisor of neuronal circuit delay loops. However, they require strict biological prerequisites such as precisely matched delays and connectivity, and synchronization is represented as a stationary mode of activity instead of a transient phenomenon. Here we show that the unavoidable increase in neuronal response latency to ongoing stimulation serves as a nonuniform gradual stretching of neuronal circuit delay loops. This apparent nuisance is revealed to be an essential mechanism in various types of neuronal time controllers, where synchronization emerges as a transient phenomenon and without predefined precisely matched synaptic delays. These findings are described in an experimental procedure where conditioned stimulations were enforced on a circuit of neurons embedded within a large-scale network of cortical cells in vitro, and are corroborated and extended by simulations of circuits composed of Hodgkin-Huxley neurons with time-dependent latencies. These findings announce a cortical time scale for time controllers based on tens of microseconds stretching of neuronal circuit delay loops per spike. They call for a reexamination of the role of the temporal periodic mode in brain functionality using advanced in vitro and in vivo experiments.
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Affiliation(s)
- Roni Vardi
- Gonda Interdisciplinary Brain Research Center, and the Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 52900, Israel
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