1
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McGregor JN, Farris CA, Ensley S, Schneider A, Fosque LJ, Wang C, Tilden EI, Liu Y, Tu J, Elmore H, Ronayne KD, Wessel R, Dyer EL, Bhaskaran-Nair K, Holtzman DM, Hengen KB. Failure in a population: Tauopathy disrupts homeostatic set-points in emergent dynamics despite stability in the constituent neurons. Neuron 2024:S0896-6273(24)00578-6. [PMID: 39241778 DOI: 10.1016/j.neuron.2024.08.006] [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: 09/06/2023] [Revised: 06/24/2024] [Accepted: 08/09/2024] [Indexed: 09/09/2024]
Abstract
Homeostatic regulation of neuronal activity is essential for robust computation; set-points, such as firing rate, are actively stabilized to compensate for perturbations. The disruption of brain function central to neurodegenerative disease likely arises from impairments of computationally essential set-points. Here, we systematically investigated the effects of tau-mediated neurodegeneration on all known set-points in neuronal activity. We continuously tracked hippocampal neuronal activity across the lifetime of a mouse model of tauopathy. We were unable to detect effects of disease in measures of single-neuron firing activity. By contrast, as tauopathy progressed, there was disruption of network-level neuronal activity, quantified by measuring neuronal pairwise interactions and criticality, a homeostatically controlled, ideal computational regime. Deviations in criticality correlated with symptoms, predicted underlying anatomical pathology, occurred in a sleep-wake-dependent manner, and could be used to reliably classify an animal's genotype. This work illustrates how neurodegeneration may disrupt the computational capacity of neurobiological systems.
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Affiliation(s)
- James N McGregor
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Clayton A Farris
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Sahara Ensley
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Aidan Schneider
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Leandro J Fosque
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Chao Wang
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer's Disease Research Center, Washington University in Saint Louis, St. Louis, MO, USA; Institute for Brain Science and Disease, Chongqing Medical University, Chongqing 400016, China
| | - Elizabeth I Tilden
- Department of Neuroscience, Washington University in Saint Louis, St. Louis, MO, USA
| | - Yuqi Liu
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Jianhong Tu
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Halla Elmore
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Keenan D Ronayne
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ralf Wessel
- Department of Physics, Washington University in Saint Louis, St. Louis, MO, USA
| | - Eva L Dyer
- Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | | | - David M Holtzman
- Department of Neurology, Hope Center for Neurological Disorders, Knight Alzheimer's Disease Research Center, Washington University in Saint Louis, St. Louis, MO, USA
| | - Keith B Hengen
- Department of Biology, Washington University in Saint Louis, St. Louis, MO, USA.
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2
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Srinivasan K, Ribeiro TL, Kells P, Plenz D. The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality. Sci Rep 2024; 14:19329. [PMID: 39164334 PMCID: PMC11335857 DOI: 10.1038/s41598-024-70014-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 08/12/2024] [Indexed: 08/22/2024] Open
Abstract
Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches-scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent, χ = 2, reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally, χ is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores χ = 2, even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies χ = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common 'crackling noise' approach fails to determine χ under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.
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Affiliation(s)
- Keshav Srinivasan
- Section on Critical Brain Dynamics, National Institute of Mental Health, Porter Neuroscience Research Center, Rm 3A-1000, 35 Convent Drive, Bethesda, MD, 20892, USA
| | - Tiago L Ribeiro
- Section on Critical Brain Dynamics, National Institute of Mental Health, Porter Neuroscience Research Center, Rm 3A-1000, 35 Convent Drive, Bethesda, MD, 20892, USA
| | - Patrick Kells
- Section on Critical Brain Dynamics, National Institute of Mental Health, Porter Neuroscience Research Center, Rm 3A-1000, 35 Convent Drive, Bethesda, MD, 20892, USA
| | - Dietmar Plenz
- Section on Critical Brain Dynamics, National Institute of Mental Health, Porter Neuroscience Research Center, Rm 3A-1000, 35 Convent Drive, Bethesda, MD, 20892, USA.
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3
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Critical dynamics in spontaneous EEG predict anesthetic-induced loss of consciousness and perturbational complexity. Commun Biol 2024; 7:946. [PMID: 39103539 DOI: 10.1038/s42003-024-06613-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Accepted: 07/22/2024] [Indexed: 08/07/2024] Open
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigate dynamical properties of the resting-state electroencephalogram (EEG) of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. Importantly, all participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams), enabling an experimental dissociation between unresponsiveness and unconsciousness. For each condition, we measure (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related metrics, revealing that states of unconsciousness are characterized by a distancing from both avalanche criticality and the edge of chaos. We then ask whether these same dynamical properties are predictive of the perturbational complexity index (PCI), a TMS-based measure that has shown remarkably high sensitivity in detecting consciousness independently of behavior. We successfully predict individual subjects' PCI values with considerably high accuracy from resting-state EEG dynamical properties alone. Our results establish a firm link between perturbational complexity and criticality, and provide further evidence that criticality is a necessary condition for the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, QC, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, QC, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, WI, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Laval, QC, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Montreal, QC, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, QC, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, QC, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, QC, Canada.
- School of Physical and Occupational Therapy, McGill University, Montreal, QC, Canada.
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4
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Serafim F, Carvalho TTA, Copelli M, Carelli PV. Maximum-entropy-based metrics for quantifying critical dynamics in spiking neuron data. Phys Rev E 2024; 110:024401. [PMID: 39294971 DOI: 10.1103/physreve.110.024401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Accepted: 07/08/2024] [Indexed: 09/21/2024]
Abstract
An important working hypothesis to investigate brain activity is whether it operates in a critical regime. Recently, maximum-entropy phenomenological models have emerged as an alternative way of identifying critical behavior in neuronal data sets. In the present paper, we investigate the signatures of criticality from a firing rate-based maximum-entropy approach on data sets generated by computational models, and we compare them to experimental results. We found that the maximum entropy approach consistently identifies critical behavior around the phase transition in models and rules out criticality in models without phase transition. The maximum-entropy-model results are compatible with results for cortical data from urethane-anesthetized rats data, providing further support for criticality in the brain.
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Affiliation(s)
| | - Tawan T A Carvalho
- Departamento de Física, Centro de Ciência Exatas e da Natureza, Universidade Federal de Pernambuco, Recife PE 50670-901, Brazil
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057 Braga, Portugal
- ICVS/3B's-PT Government Associate Laboratory, 4806-909 Braga/Guimares, Portugal
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5
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Parr AC, Sydnor VJ, Calabro FJ, Luna B. Adolescent-to-adult gains in cognitive flexibility are adaptively supported by reward sensitivity, exploration, and neural variability. Curr Opin Behav Sci 2024; 58:101399. [PMID: 38826569 PMCID: PMC11138371 DOI: 10.1016/j.cobeha.2024.101399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Cognitive flexibility exhibits dynamic changes throughout development, with different forms of flexibility showing dissociable developmental trajectories. In this review, we propose that an adolescent-specific mode of flexibility in the face of changing environmental contingencies supports the emergence of adolescent-to-adult gains in cognitive shifting efficiency. We first describe how cognitive shifting abilities monotonically improve from childhood to adulthood, accompanied by increases in brain state flexibility, neural variability, and excitatory/inhibitory balance. We next summarize evidence supporting the existence of a dopamine-driven, adolescent peak in flexible behavior that results in reward seeking, undirected exploration, and environmental sampling. We propose a neurodevelopmental framework that relates these adolescent behaviors to the refinement of neural phenotypes relevant to mature cognitive flexibility, and thus highlight the importance of the adolescent period in fostering healthy neurocognitive trajectories.
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Affiliation(s)
- Ashley C. Parr
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA, 14213, USA
| | - Valerie J. Sydnor
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA, 14213, USA
| | - Finnegan J. Calabro
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA, 14213, USA
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh PA, 14213, USA
- Department of Psychology, University of Pittsburgh, Pittsburgh PA, 14213, USA
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6
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Liu M, Yu C, Shi J, Xu Y, Li Z, Huang J, Si Z, Yao L, Yin K, Zhao Z. Effects of one-week bilateral cerebellar iTBS on resting-state functional brain network and multi-task attentional performance in healthy individuals: A randomized, sham-controlled trial. Neuroimage 2024; 295:120648. [PMID: 38761882 DOI: 10.1016/j.neuroimage.2024.120648] [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: 02/26/2024] [Revised: 04/29/2024] [Accepted: 05/13/2024] [Indexed: 05/20/2024] Open
Abstract
BACKGROUND Cerebellar intermittent theta burst stimulation (iTBS) modulates the excitability of the cerebral cortex and may enhance attentional performance. To date, few studies have conducted iTBS on healthy subjects for one week and used electroencephalography (EEG) to investigate the effect of multiple stimulation sessions on resting-state functional brain networks and the daily stimulation effect on attentional performance. METHODS 16 healthy subjects participated in a one-week experiment, receiving bilateral cerebellar iTBS or sham stimulation and engaging in multi-task attentional training. The primary measures were the one-week attentional performance and pre- and post-experiment resting-state EEG activities. Amplitude Envelope Correlation (AEC) was used to construct the functional connectivity in the eye-open (EO) and eye-closed (EC) phases. RESULTS At least three sessions of iTBS were required to enhance multi-task performance significantly, whereas only one or two sessions failed to elicit the improvement. Compared with the control group, iTBS induced significant changes in PSD, AEC functional connectivity, and AEC network properties during the EO phase, while it had little effect during the EC phase. During the EO phase, the network property changes of the iTBS subject were correlated with improved attentional performance. CONCLUSION The multi-task performance requires multiple stimulations to enhance. iTBS affects the resting-state alpha band brain activities during the EO rather than the EC phase. The AEC network properties may serve as a biomarker to assess the attentional potential of healthy subjects.
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Affiliation(s)
- Meiliang Liu
- School of Artificial Intelligence, Beijing Normal University, Beijing, China.
| | - Chao Yu
- Nanjing Research Institute of Electronics Technology, Nanjing, China.
| | - Jinping Shi
- Department of Neurology, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing, China
| | - Yunfang Xu
- School of Artificial Intelligence, Beijing Normal University, Beijing, China
| | - Zijin Li
- School of Artificial Intelligence, Beijing Normal University, Beijing, China
| | - Junhao Huang
- School of Artificial Intelligence, Beijing Normal University, Beijing, China
| | - Zhengye Si
- School of Artificial Intelligence, Beijing Normal University, Beijing, China
| | - Li Yao
- School of Artificial Intelligence, Beijing Normal University, Beijing, China
| | - Kuiying Yin
- Nanjing Research Institute of Electronics Technology, Nanjing, China.
| | - Zhiwen Zhao
- School of Artificial Intelligence, Beijing Normal University, Beijing, China; Advanced Institute of Natural Sciences, Beijing Normal University, Zhuhai, China.
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7
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Wehrheim MH, Faskowitz J, Schubert A, Fiebach CJ. Reliability of variability and complexity measures for task and task-free BOLD fMRI. Hum Brain Mapp 2024; 45:e26778. [PMID: 38980175 PMCID: PMC11232465 DOI: 10.1002/hbm.26778] [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: 12/21/2023] [Revised: 05/06/2024] [Accepted: 06/24/2024] [Indexed: 07/10/2024] Open
Abstract
Brain activity continuously fluctuates over time, even if the brain is in controlled (e.g., experimentally induced) states. Recent years have seen an increasing interest in understanding the complexity of these temporal variations, for example with respect to developmental changes in brain function or between-person differences in healthy and clinical populations. However, the psychometric reliability of brain signal variability and complexity measures-which is an important precondition for robust individual differences as well as longitudinal research-is not yet sufficiently studied. We examined reliability (split-half correlations) and test-retest correlations for task-free (resting-state) BOLD fMRI as well as split-half correlations for seven functional task data sets from the Human Connectome Project to evaluate their reliability. We observed good to excellent split-half reliability for temporal variability measures derived from rest and task fMRI activation time series (standard deviation, mean absolute successive difference, mean squared successive difference), and moderate test-retest correlations for the same variability measures under rest conditions. Brain signal complexity estimates (several entropy and dimensionality measures) showed moderate to good reliabilities under both, rest and task activation conditions. We calculated the same measures also for time-resolved (dynamic) functional connectivity time series and observed moderate to good reliabilities for variability measures, but poor reliabilities for complexity measures derived from functional connectivity time series. Global (i.e., mean across cortical regions) measures tended to show higher reliability than region-specific variability or complexity estimates. Larger subcortical regions showed similar reliability as cortical regions, but small regions showed lower reliability, especially for complexity measures. Lastly, we also show that reliability scores are only minorly dependent on differences in scan length and replicate our results across different parcellation and denoising strategies. These results suggest that the variability and complexity of BOLD activation time series are robust measures well-suited for individual differences research. Temporal variability of global functional connectivity over time provides an important novel approach to robustly quantifying the dynamics of brain function. PRACTITIONER POINTS: Variability and complexity measures of BOLD activation show good split-half reliability and moderate test-retest reliability. Measures of variability of global functional connectivity over time can robustly quantify neural dynamics. Length of fMRI data has only a minor effect on reliability.
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Affiliation(s)
- Maren H. Wehrheim
- Department of PsychologyGoethe University FrankfurtFrankfurtGermany
- Department of Computer Science and MathematicsGoethe University FrankfurtFrankfurtGermany
- Frankfurt Institute for Advanced Studies (FIAS)FrankfurtGermany
| | - Joshua Faskowitz
- Department of Psychological and Brain SciencesIndiana UniversityBloomingtonUSA
| | - Anna‐Lena Schubert
- Department of PsychologyJohannes Gutenberg‐Universität MainzMainzGermany
| | - Christian J. Fiebach
- Department of PsychologyGoethe University FrankfurtFrankfurtGermany
- Brain Imaging CenterGoethe University FrankfurtFrankfurtGermany
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8
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Yang B, Liu H, Jiang T, Yu S. Fluctuation in cortical excitation/inhibition modulates capability of attention across time scales ranging from hours to seconds. Cereb Cortex 2024; 34:bhae309. [PMID: 39076112 DOI: 10.1093/cercor/bhae309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/04/2024] [Accepted: 07/13/2024] [Indexed: 07/31/2024] Open
Abstract
Sustained attention, as the basis of general cognitive ability, naturally varies across different time scales, spanning from hours, e.g. from wakefulness to drowsiness state, to seconds, e.g. trial-by-trail fluctuation in a task session. Whether there is a unified mechanism underneath such trans-scale variability remains unclear. Here we show that fluctuation of cortical excitation/inhibition (E/I) is a strong modulator to sustained attention in humans across time scales. First, we observed the ability to attend varied across different brain states (wakefulness, postprandial somnolence, sleep deprived), as well as within any single state with larger swings. Second, regardless of the time scale involved, we found highly attentive state was always linked to more balanced cortical E/I characterized by electroencephalography (EEG) features, while deviations from the balanced state led to temporal decline in attention, suggesting the fluctuation of cortical E/I as a common mechanism underneath trans-scale attentional variability. Furthermore, we found the variations of both sustained attention and cortical E/I indices exhibited fractal structure in the temporal domain, exhibiting features of self-similarity. Taken together, these results demonstrate that sustained attention naturally varies across different time scales in a more complex way than previously appreciated, with the cortical E/I as a shared neurophysiological modulator.
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Affiliation(s)
- Binghao Yang
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
| | - Hao Liu
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
| | - Tianzi Jiang
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
- Xiaoxiang Institute for Brain Health and Yongzhou Central Hospital, No. 151, Xiaoshui West Road, Lingling District, Yongzhou 425000, Hunan Province, China
| | - Shan Yu
- Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, No. 19, Yuquan Road, Shijingshan District, Beijing 100049, China
- Key Laboratory of Brain Cognition and Brain-inspired Intelligence Technology, Chinese Academy of Sciences, No. 230, Yueyang Road, Shanghai 200031, China
- Lead contact. Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, No. 95, Zhongguancun East Road, Haidian District, Beijing 100190, China
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9
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Salners T, Dahmen KA, Beggs J. Simple model for the prediction of seizure durations. Phys Rev E 2024; 110:014401. [PMID: 39161021 DOI: 10.1103/physreve.110.014401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Accepted: 06/12/2024] [Indexed: 08/21/2024]
Abstract
A simple model is used to simulate seizures in a population of spiking excitatory neurons experiencing a uniform effect from inhibitory neurons. A key feature is introduced into the model, i.e., a mechanism that weakens the firing thresholds. This weakening mechanism adds memory to the dynamics. We find a seizure-prone state in a "mode-switching" phase. In this phase, the system can suddenly switch from a "healthy" state with small scale-free avalanches to a "seizure" state with almost periodic large avalanches ("seizures"). Simulations of the model predict statistics for the average time spent in the seizure state (the seizure "duration") that agree with experiments and theoretical examples of similar behavior in neuronal systems. Our study points to. different connections between seizures and fracture and also offers an alternative view on the type of critical point controlling neuronal avalanches.
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Cheng T, Hu Y, Qin X, Ma J, Zha D, Xie H, Ji T, Liu Q, Wang Z, Hao H, Wu Y, Li L. A predictive model combining connectomics and entropy biomarkers to discriminate long-term vagus nerve stimulation efficacy for pediatric patients with drug-resistant epilepsy. CNS Neurosci Ther 2024; 30:e14751. [PMID: 39015946 PMCID: PMC11252558 DOI: 10.1111/cns.14751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 04/22/2024] [Accepted: 04/23/2024] [Indexed: 07/18/2024] Open
Abstract
AIMS To predict the vagus nerve stimulation (VNS) efficacy for pediatric drug-resistant epilepsy (DRE) patients, we aim to identify preimplantation biomarkers through clinical features and electroencephalogram (EEG) signals and thus establish a predictive model from a multi-modal feature set with high prediction accuracy. METHODS Sixty-five pediatric DRE patients implanted with VNS were included and followed up. We explored the topological network and entropy features of preimplantation EEG signals to identify the biomarkers for VNS efficacy. A Support Vector Machine (SVM) integrated these biomarkers to distinguish the efficacy groups. RESULTS The proportion of VNS responders was 58.5% (38/65) at the last follow-up. In the analysis of parieto-occipital α band activity, higher synchronization level and nodal efficiency were found in responders. The central-frontal θ band activity showed significantly lower entropy in responders. The prediction model reached an accuracy of 81.5%, a precision of 80.1%, and an AUC (area under the receiver operating characteristic curve) of 0.838. CONCLUSION Our results revealed that, compared to nonresponders, VNS responders had a more efficient α band brain network, especially in the parieto-occipital region, and less spectral complexity of θ brain activities in the central-frontal region. We established a predictive model integrating both preimplantation clinical and EEG features and exhibited great potential for discriminating the VNS responders. This study contributed to the understanding of the VNS mechanism and improved the performance of the current predictive model.
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Affiliation(s)
- Tung‐yang Cheng
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
| | - Yingbing Hu
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
- Tsinghua‐Berkeley Shenzhen InstituteTsinghua UniversityShenzhenChina
| | - Xiaoya Qin
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
- Tsinghua‐Berkeley Shenzhen InstituteTsinghua UniversityShenzhenChina
| | - Jiayi Ma
- Department of PediatricsPeking University First HospitalBeijingChina
| | - Daqi Zha
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
| | - Han Xie
- Department of PediatricsPeking University First HospitalBeijingChina
| | - Taoyun Ji
- Department of PediatricsPeking University First HospitalBeijingChina
- Pediatric Epilepsy CenterPeking University First HospitalBeijingChina
| | - Qingzhu Liu
- Pediatric Epilepsy CenterPeking University First HospitalBeijingChina
| | - Zhiyan Wang
- CAS Key Laboratory of Mental Health, Institute of PsychologyChinese Academy of SciencesBeijingChina
- Department of PsychologyUniversity of Chinese Academy of SciencesBeijingChina
| | - Hongwei Hao
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
| | - Ye Wu
- Department of PediatricsPeking University First HospitalBeijingChina
- Pediatric Epilepsy CenterPeking University First HospitalBeijingChina
| | - Luming Li
- National Engineering Research Center of Neuromodulation, School of Aerospace EngineeringTsinghua UniversityBeijingChina
- IDG/McGovern Institute for Brain Research at Tsinghua UniversityBeijingChina
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11
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Srinivasan K, Ribeiro TL, Kells P, Plenz D. The recovery of parabolic avalanches in spatially subsampled neuronal networks at criticality. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.26.582056. [PMID: 38464324 PMCID: PMC10925085 DOI: 10.1101/2024.02.26.582056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Scaling relationships are key in characterizing complex systems at criticality. In the brain, they are evident in neuronal avalanches-scale-invariant cascades of neuronal activity quantified by power laws. Avalanches manifest at the cellular level as cascades of neuronal groups that fire action potentials simultaneously. Such spatiotemporal synchronization is vital to theories on brain function yet avalanche synchronization is often underestimated when only a fraction of neurons is observed. Here, we investigate biases from fractional sampling within a balanced network of excitatory and inhibitory neurons with all-to-all connectivity and critical branching process dynamics. We focus on how mean avalanche size scales with avalanche duration. For parabolic avalanches, this scaling is quadratic, quantified by the scaling exponent, χ = 2 , reflecting rapid spatial expansion of simultaneous neuronal firing over short durations. However, in networks sampled fractionally, χ is significantly lower. We demonstrate that applying temporal coarse-graining and increasing a minimum threshold for coincident firing restores χ = 2 , even when as few as 0.1% of neurons are sampled. This correction crucially depends on the network being critical and fails for near sub- and supercritical branching dynamics. Using cellular 2-photon imaging, our approach robustly identifies χ = 2 over a wide parameter regime in ongoing neuronal activity from frontal cortex of awake mice. In contrast, the common 'crackling noise' approach fails to determine χ under similar sampling conditions at criticality. Our findings overcome scaling bias from fractional sampling and demonstrate rapid, spatiotemporal synchronization of neuronal assemblies consistent with scale-invariant, parabolic avalanches at criticality.
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Affiliation(s)
- Keshav Srinivasan
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Tiago L. Ribeiro
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Patrick Kells
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
| | - Dietmar Plenz
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD 20892, USA
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12
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Yang J, Feng P, Wu Y. Neuronal avalanche dynamics regulated by spike-timing-dependent plasticity under different topologies and heterogeneities. Cogn Neurodyn 2024; 18:1307-1321. [PMID: 38826660 PMCID: PMC11143121 DOI: 10.1007/s11571-023-09966-8] [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: 12/31/2022] [Revised: 03/18/2023] [Accepted: 03/26/2023] [Indexed: 06/04/2024] Open
Abstract
Neuronal avalanches, a critical state of network self-organization, have been widely observed in electrophysiological records at different signal levels and spatial scales of the brain, which has significant influence on information transmission and processing in the brain. In this paper, the collective behavior of neuron firing is studied based on Leaky Integrate-and-Fire model and we induce spike-timing-dependent plasticity (STDP) to update the connection weight through competition between adjacent neurons in different network topologies. The result shows that STDP can facilitate the synchronization of the network and increase the probability of large-scale neuron avalanche obviously. Moreover, both the structure of STDP and network connection density can affect the generation of avalanche critical states, specifically, learning rate has positive correlation effect on the slope of power-law distribution and time constant has negative correction on it. However, when we the increase of heterogeneity in network, STDP can only has obvious promotion in synchrony under suitable level of heterogeneity. And we find that the process of long-term potentiation is sensitive to the adjustment of time constant and learning rate, unlike long-term depression, which is only sensitive to learning rate in heterogeneity network. It is suggested that presented results could facilitate our understanding on synchronization in various neural networks under the effect of STDP learning rules.
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Affiliation(s)
- Jiayi Yang
- State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an, 710049 Shanxi China
| | - Peihua Feng
- State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an, 710049 Shanxi China
| | - Ying Wu
- State Key Laboratory for Strength and Vibration of Mechanical Structures, School of Aerospace Engineering, Xi’an Jiaotong University, Xi’an, 710049 Shanxi China
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13
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Fontenele AJ, Sooter JS, Norman VK, Gautam SH, Shew WL. Low-dimensional criticality embedded in high-dimensional awake brain dynamics. SCIENCE ADVANCES 2024; 10:eadj9303. [PMID: 38669340 PMCID: PMC11051676 DOI: 10.1126/sciadv.adj9303] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 03/26/2024] [Indexed: 04/28/2024]
Abstract
Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. We offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality-a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescales agrees with established theory of critical dynamics. Our results suggest that the cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.
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14
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Simões TSAN, Filho CINS, Herrmann HJ, Andrade JS, de Arcangelis L. Thermodynamic analog of integrate-and-fire neuronal networks by maximum entropy modelling. Sci Rep 2024; 14:9480. [PMID: 38664504 PMCID: PMC11045794 DOI: 10.1038/s41598-024-60117-3] [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: 01/29/2024] [Accepted: 04/18/2024] [Indexed: 04/28/2024] Open
Abstract
Recent results have evidenced that spontaneous brain activity signals are organized in bursts with scale free features and long-range spatio-temporal correlations. These observations have stimulated a theoretical interpretation of results inspired in critical phenomena. In particular, relying on maximum entropy arguments, certain aspects of time-averaged experimental neuronal data have been recently described using Ising-like models, allowing the study of neuronal networks under an analogous thermodynamical framework. This method has been so far applied to a variety of experimental datasets, but never to a biologically inspired neuronal network with short and long-term plasticity. Here, we apply for the first time the Maximum Entropy method to an Integrate-and-fire (IF) model that can be tuned at criticality, offering a controlled setting for a systematic study of criticality and finite-size effects in spontaneous neuronal activity, as opposed to experiments. We consider generalized Ising Hamiltonians whose local magnetic fields and interaction parameters are assigned according to the average activity of single neurons and correlation functions between neurons of the IF networks in the critical state. We show that these Hamiltonians exhibit a spin glass phase for low temperatures, having mostly negative intrinsic fields and a bimodal distribution of interaction constants that tends to become unimodal for larger networks. Results evidence that the magnetization and the response functions exhibit the expected singular behavior near the critical point. Furthermore, we also found that networks with higher percentage of inhibitory neurons lead to Ising-like systems with reduced thermal fluctuations. Finally, considering only neuronal pairs associated with the largest correlation functions allows the study of larger system sizes.
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Affiliation(s)
- T S A N Simões
- Department of Mathematics and Physics, University of Campania "Luigi Vanvitelli", Viale Lincoln, 5, 81100, Caserta, Italy.
| | - C I N Sampaio Filho
- Departamento de Física, Fortaleza, Universidade Federal do Ceará, Ceará, 60451-970, Brazil
| | - H J Herrmann
- Departamento de Física, Fortaleza, Universidade Federal do Ceará, Ceará, 60451-970, Brazil
- ESPCI, PMMH, Paris, 7 quai St., 75005, Bernard, France
| | - J S Andrade
- Departamento de Física, Fortaleza, Universidade Federal do Ceará, Ceará, 60451-970, Brazil
| | - L de Arcangelis
- Department of Mathematics and Physics, University of Campania "Luigi Vanvitelli", Viale Lincoln, 5, 81100, Caserta, Italy
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15
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Smith GC, Griffith KR, Sicher AR, Brockway DF, Proctor EA, Crowley NA. MODERATE ALCOHOL CONSUMPTION INDUCES LASTING IMPACTS ON PREFRONTAL CORTICAL SIGNALING IN MICE. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587955. [PMID: 38617243 PMCID: PMC11014573 DOI: 10.1101/2024.04.03.587955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Both alcohol use disorder (AUD) and Alzheimer's Disease and Related Dementias (ADRD) appear to include disruption in the balance of excitation and inhibition in the cortex, but their potential interactions are unclear. We examined the effect of moderate voluntary binge alcohol consumption on the aged, pre-disease neuronal environment by measuring intrinsic excitability and spontaneous neurotransmission on prefrontal cortical pyramidal (excitatory, glutamatergic) and non-pyramidal (inhibitory, GABAergic) neurons following a prolonged period of abstinence from alcohol in mice. Results highlight that binge alcohol consumption has lasting impacts on the electrophysiological properties of prefrontal cortical neurons. A profound increase in excitatory events onto layer 2/3 non-pyramidal neurons following alcohol consumption was seen, along with altered intrinsic excitability of pyramidal neurons, which could have a range of effects on Alzheimer's Disease progression in humans. These results indicate that moderate voluntary alcohol influences the pre-disease environment in aging and highlight the need for further mechanistic investigation into this risk factor.
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Affiliation(s)
- Grace C. Smith
- Department of Biology, The Pennsylvania State University, University Park, PA, USA 16802
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA 16802
| | - Keith R. Griffith
- Department of Biology, The Pennsylvania State University, University Park, PA, USA 16802
| | - Avery R. Sicher
- Department of Biology, The Pennsylvania State University, University Park, PA, USA 16802
- Neuroscience Graduate Program, Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, USA 16802
| | - Dakota F. Brockway
- Department of Biology, The Pennsylvania State University, University Park, PA, USA 16802
- Neuroscience Graduate Program, Huck Institute of the Life Sciences, The Pennsylvania State University, University Park, PA, USA 16802
| | - Elizabeth A. Proctor
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA 16802
- Departments of Neurosurgery Penn State College of Medicine, Hershey PA, USA 17033; and Engineering Science and Mechanics, University Park, PA, USA 16802
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
| | - Nicole A. Crowley
- Department of Biology, The Pennsylvania State University, University Park, PA, USA 16802
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, PA, USA 16802
- Department of Pharmacology, Penn State College of Medicine, Hershey, PA, USA
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16
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van Nifterick AM, Scheijbeler EP, Gouw AA, de Haan W, Stam CJ. Local signal variability and functional connectivity: Sensitive measures of the excitation-inhibition ratio? Cogn Neurodyn 2024; 18:519-537. [PMID: 38699618 PMCID: PMC11061092 DOI: 10.1007/s11571-023-10003-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 06/08/2023] [Accepted: 08/13/2023] [Indexed: 05/05/2024] Open
Abstract
A novel network version of permutation entropy, the inverted joint permutation entropy (JPEinv), holds potential as non-invasive biomarker of abnormal excitation-inhibition (E-I) ratio in Alzheimer's disease (AD). In this computational modelling study, we test the hypotheses that this metric, and related measures of signal variability and functional connectivity, are sensitive to altered E-I ratios. The E-I ratio in each neural mass of a whole-brain computational network model was systematically varied. We evaluated whether JPEinv, local signal variability (by permutation entropy) and functional connectivity (by weighted symbolic mutual information (wsMI)) were related to E-I ratio, on whole-brain and regional level. The hub disruption index can identify regions primarily affected in terms of functional connectivity strength (or: degree) by the altered E-I ratios. Analyses were performed for a range of coupling strengths, filter and time-delay settings. On whole-brain level, higher E-I ratios were associated with higher functional connectivity (by JPEinv and wsMI) and lower local signal variability. These relationships were nonlinear and depended on the coupling strength, filter and time-delay settings. On regional level, hub-like regions showed a selective decrease in functional degree (by JPEinv and wsMI) upon a lower E-I ratio, and non-hub-like regions showed a selective increase in degree upon a higher E-I ratio. These results suggest that abnormal functional connectivity and signal variability, as previously reported in patients across the AD continuum, can inform us about altered E-I ratios. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-023-10003-x.
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Affiliation(s)
- Anne M. van Nifterick
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Elliz P. Scheijbeler
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Alida A. Gouw
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Willem de Haan
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cornelis J. Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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17
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Williams CL, Belkowitz AR, Nance MG, Mortman ET, Bae S, Ahmed SB, Puglia MH. Parent attention-orienting behavior is associated with neural entropy in infancy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.585061. [PMID: 38562688 PMCID: PMC10983866 DOI: 10.1101/2024.03.14.585061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Parents play a significant role in directing infant's attention to environmental stimuli via joint attention. We hypothesized that infants whose parents provide more bids for joint attention will display a more complex neural response when viewing social scenes. Sixty-one 8-month-old infants underwent electroencephalography (EEG) while viewing videos of joint- and parallel-play and participated in a parent-infant free play interaction. EEG data was analyzed using multiscale entropy, which quantifies moment-to-moment neural variability. Free play interactions were coded for parent alternating gaze, a behavioral mechanism for directing attention to environmental cues. We found a significant positive association between parent alternating gaze and neural entropy in frontal and central brain regions. These results suggest a relationship between parent behavior and infant neural mechanisms that regulate social attention, underlying the importance of parent cues in the formation of neural networks in infancy.
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Affiliation(s)
| | | | | | | | - Soni Bae
- University of Virginia, Department of Neurology
| | | | - Meghan H. Puglia
- University of Virginia, Department of Psychology
- University of Virginia, Department of Neurology
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18
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Ribeiro TL, Jendrichovsky P, Yu S, Martin DA, Kanold PO, Chialvo DR, Plenz D. Trial-by-trial variability in cortical responses exhibits scaling of spatial correlations predicted from critical dynamics. Cell Rep 2024; 43:113762. [PMID: 38341856 PMCID: PMC10956720 DOI: 10.1016/j.celrep.2024.113762] [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: 04/14/2022] [Revised: 01/05/2024] [Accepted: 01/25/2024] [Indexed: 02/13/2024] Open
Abstract
In the mammalian cortex, even simple sensory inputs or movements activate many neurons, with each neuron responding variably to repeated stimuli-a phenomenon known as trial-by-trial variability. Understanding the spatial patterns and dynamics of this variability is challenging. Using cellular 2-photon imaging, we study visual and auditory responses in the primary cortices of awake mice. We focus on how individual neurons' responses differed from the overall population. We find consistent spatial correlations in these differences that are unique to each trial and linearly scale with the cortical area observed, a characteristic of critical dynamics as confirmed in our neuronal simulations. Using chronic multi-electrode recordings, we observe similar scaling in the prefrontal and premotor cortex of non-human primates during self-initiated and visually cued motor tasks. These results suggest that trial-by-trial variability, rather than being random noise, reflects a critical, fluctuation-dominated state in the cortex, supporting the brain's efficiency in processing information.
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Affiliation(s)
- Tiago L Ribeiro
- Section on Critical Brain Dynamics, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter Jendrichovsky
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Shan Yu
- Section on Critical Brain Dynamics, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA; Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, China
| | - Daniel A Martin
- Center for Complex Systems & Brain Sciences (CEMSC3), Instituto de Ciencias Físicas, (ICIFI) Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín (UNSAM), San Martín 1650 Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290 Buenos Aires, Argentina
| | - Patrick O Kanold
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21205, USA; Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Dante R Chialvo
- Center for Complex Systems & Brain Sciences (CEMSC3), Instituto de Ciencias Físicas, (ICIFI) Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín (UNSAM), San Martín 1650 Buenos Aires, Argentina; Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2290 Buenos Aires, Argentina
| | - Dietmar Plenz
- Section on Critical Brain Dynamics, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892, USA.
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19
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Pan W, Zhao F, Han B, Dong Y, Zeng Y. Emergence of brain-inspired small-world spiking neural network through neuroevolution. iScience 2024; 27:108845. [PMID: 38327781 PMCID: PMC10847652 DOI: 10.1016/j.isci.2024.108845] [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: 05/08/2023] [Revised: 08/23/2023] [Accepted: 01/03/2024] [Indexed: 02/09/2024] Open
Abstract
Studies suggest that the brain's high efficiency and low energy consumption may be closely related to its small-world topology and critical dynamics. However, existing efforts on the performance-oriented structural evolution of spiking neural networks (SNNs) are time-consuming and ignore the core structural properties of the brain. Here, we introduce a multi-objective Evolutionary Liquid State Machine (ELSM), which blends the small-world coefficient and criticality to evolve models and guide the emergence of brain-inspired, efficient structures. Experiments reveal ELSM's consistent and comparable performance, achieving 97.23% on NMNIST and outperforming LSM models on MNIST and Fashion-MNIST with 98.12% and 88.81% accuracies, respectively. Further analysis shows its versatility and spontaneous evolution of topologies such as hub nodes, short paths, long-tailed degree distributions, and numerous communities. This study evolves recurrent spiking neural networks into brain-inspired energy-efficient structures, showcasing versatility in multiple tasks and potential for adaptive general artificial intelligence.
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Affiliation(s)
- Wenxuan Pan
- 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 101408, China
| | - Feifei Zhao
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
| | - Bing Han
- 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 101408, China
| | - Yiting Dong
- Brain-inspired Cognitive Intelligence Lab, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, 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 101408, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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20
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Liang J, Yang Z, Zhou C. Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits. Neuroscientist 2024:10738584231221766. [PMID: 38291889 DOI: 10.1177/10738584231221766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.
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Affiliation(s)
- Junhao Liang
- Eberhard Karls University of Tübingen and Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Zhuda Yang
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Life Science Imaging Centre, Hong Kong Baptist University, Kowloon Tong, Hong Kong
- Research Centre, Hong Kong Baptist University Institute of Research and Continuing Education, Shenzhen, China
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21
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Noda T, Takahashi H. Stochastic resonance in sparse neuronal network: functional role of ongoing activity to detect weak sensory input in awake auditory cortex of rat. Cereb Cortex 2024; 34:bhad428. [PMID: 37955660 PMCID: PMC10793590 DOI: 10.1093/cercor/bhad428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2022] [Revised: 10/10/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023] Open
Abstract
The awake cortex is characterized by a higher level of ongoing spontaneous activity, but it has a better detectability of weak sensory inputs than the anesthetized cortex. However, the computational mechanism underlying this paradoxical nature of awake neuronal activity remains to be elucidated. Here, we propose a hypothetical stochastic resonance, which improves the signal-to-noise ratio (SNR) of weak sensory inputs through nonlinear relations between ongoing spontaneous activities and sensory-evoked activities. Prestimulus and tone-evoked activities were investigated via in vivo extracellular recording with a dense microelectrode array covering the entire auditory cortex in rats in both awake and anesthetized states. We found that tone-evoked activities increased supralinearly with the prestimulus activity level in the awake state and that the SNR of weak stimulus representation was optimized at an intermediate level of prestimulus ongoing activity. Furthermore, the temporally intermittent firing pattern, but not the trial-by-trial reliability or the fluctuation of local field potential, was identified as a relevant factor for SNR improvement. Since ongoing activity differs among neurons, hypothetical stochastic resonance or "sparse network stochastic resonance" might offer beneficial SNR improvement at the single-neuron level, which is compatible with the sparse representation in the sensory cortex.
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Affiliation(s)
- Takahiro Noda
- Department of Mechano-informatics, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
| | - Hirokazu Takahashi
- Department of Mechano-informatics, Graduate School of Information Science and Technology, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
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22
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Bai X, Yu C, Zhai J. Topological data analysis of the firings of a network of stochastic spiking neurons. Front Neural Circuits 2024; 17:1308629. [PMID: 38239606 PMCID: PMC10794443 DOI: 10.3389/fncir.2023.1308629] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/06/2023] [Indexed: 01/22/2024] Open
Abstract
Topological data analysis is becoming more and more popular in recent years. It has found various applications in many different fields, for its convenience in analyzing and understanding the structure and dynamic of complex systems. We used topological data analysis to analyze the firings of a network of stochastic spiking neurons, which can be in a sub-critical, critical, or super-critical state depending on the value of the control parameter. We calculated several topological features regarding Betti curves and then analyzed the behaviors of these features, using them as inputs for machine learning to discriminate the three states of the network.
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Affiliation(s)
| | - Chaojun Yu
- School of Mathematical Sciences, Zhejiang University, Hangzhou, China
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23
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Chwiłka M, Karbowski J. Explicit mutual information for simple networks and neurons with lognormal activities. Phys Rev E 2024; 109:014117. [PMID: 38366499 DOI: 10.1103/physreve.109.014117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 12/13/2023] [Indexed: 02/18/2024]
Abstract
Networks with stochastic variables described by heavy-tailed lognormal distribution are ubiquitous in nature, and hence they deserve an exact information-theoretic characterization. We derive analytical formulas for mutual information between elements of different networks with correlated lognormally distributed activities. In a special case, we find an explicit expression for mutual information between neurons when neural activities and synaptic weights are lognormally distributed, as suggested by experimental data. Comparison of this expression with the case when these two variables have short tails reveals that mutual information with heavy tails for neurons and synapses is generally larger and can diverge for some finite variances in presynaptic firing rates and synaptic weights. This result suggests that evolution might prefer brains with heterogeneous dynamics to optimize information processing.
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Affiliation(s)
- Maurycy Chwiłka
- Department of Mathematics, Informatics, and Mechanics, Institute of Applied Mathematics and Mechanics, University of Warsaw, Ulica Banacha 2, 02-097 Warsaw, Poland
| | - Jan Karbowski
- Department of Mathematics, Informatics, and Mechanics, Institute of Applied Mathematics and Mechanics, University of Warsaw, Ulica Banacha 2, 02-097 Warsaw, Poland
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24
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Manos T, Diaz-Pier S, Fortel I, Driscoll I, Zhan L, Leow A. Enhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes. Front Comput Neurosci 2023; 17:1295395. [PMID: 38188355 PMCID: PMC10770256 DOI: 10.3389/fncom.2023.1295395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Accepted: 12/05/2023] [Indexed: 01/09/2024] Open
Abstract
The human brain, composed of billions of neurons and synaptic connections, is an intricate network coordinating a sophisticated balance of excitatory and inhibitory activities between brain regions. The dynamical balance between excitation and inhibition is vital for adjusting neural input/output relationships in cortical networks and regulating the dynamic range of their responses to stimuli. To infer this balance using connectomics, we recently introduced a computational framework based on the Ising model, which was first developed to explain phase transitions in ferromagnets, and proposed a novel hybrid resting-state structural connectome (rsSC). Here, we show that a generative model based on the Kuramoto phase oscillator can be used to simulate static and dynamic functional connectomes (FC) with rsSC as the coupling weight coefficients, such that the simulated FC aligns well with the observed FC when compared with that simulated traditional structural connectome.
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Affiliation(s)
- Thanos Manos
- ETIS, ENSEA, CNRS, UMR8051, CY Cergy-Paris University, Cergy, France
- Laboratoire de Physique Théorique et Modélisation, UMR 8089, CNRS, Cergy-Pontoise, CY Cergy Paris Université, Cergy, France
| | - Sandra Diaz-Pier
- Simulation and Data Lab Neuroscience, Institute for Advanced Simulation, Jülich Supercomputing Centre (JSC), JARA, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Igor Fortel
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States
| | - Ira Driscoll
- Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI, United States
| | - Liang Zhan
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, United States
| | - Alex Leow
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, United States
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, United States
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25
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Ouyang G, Wang S, Liu M, Zhang M, Zhou C. Multilevel and multifaceted brain response features in spiking, ERP and ERD: experimental observation and simultaneous generation in a neuronal network model with excitation-inhibition balance. Cogn Neurodyn 2023; 17:1417-1431. [PMID: 37969943 PMCID: PMC10640466 DOI: 10.1007/s11571-022-09889-w] [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: 06/20/2022] [Revised: 08/26/2022] [Accepted: 09/14/2022] [Indexed: 11/25/2022] Open
Abstract
Brain as a dynamic system responds to stimulations with specific patterns affected by its inherent ongoing dynamics. The patterns are manifested across different levels of organization-from spiking activity of neurons to collective oscillations in local field potential (LFP) and electroencephalogram (EEG). The multilevel and multifaceted response activities show patterns seemingly distinct and non-comparable from each other, but they should be coherently related because they are generated from the same underlying neural dynamic system. A coherent understanding of the interrelationships between different levels/aspects of activity features is important for understanding the complex brain functions. Here, based on analysis of data from human EEG, monkey LFP and neuronal spiking, we demonstrated that the brain response activities from different levels of neural system are highly coherent: the external stimulus simultaneously generated event-related potentials, event-related desynchronization, and variation in neuronal spiking activities that precisely match with each other in the temporal unfolding. Based on a biologically plausible but generic network of conductance-based integrate-and-fire excitatory and inhibitory neurons with dense connections, we showed that the multiple key features can be simultaneously produced at critical dynamical regimes supported by excitation-inhibition (E-I) balance. The elucidation of the inherent coherency of various neural response activities and demonstration of a simple dynamical neural circuit system having the ability to simultaneously produce multiple features suggest the plausibility of understanding high-level brain function and cognition from elementary and generic neuronal dynamics. Supplementary Information The online version contains supplementary material available at 10.1007/s11571-022-09889-w.
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Affiliation(s)
- Guang Ouyang
- Faculty of Education, The University of Hong Kong, Pok Fu Lam, Hong Kong China
| | - Shengjun Wang
- Department of Physics, Shaanxi Normal University, Xi’an, 710119 China
| | - Mianxin Liu
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong China
| | - Mingsha Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, 100875 China
| | - Changsong Zhou
- Department of Physics, Centre for Nonlinear Studies and Beijing-Hong Kong-Singapore Joint Centre for Nonlinear and Complex Systems (Hong Kong), Institute of Computational and Theoretical Studies, Hong Kong Baptist University, Kowloon Tong, Hong Kong China
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26
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Ayala-Rodríguez JD, García-Colunga J. Maternal separation modifies spontaneous synaptic activity in the infralimbic cortex of stress-resilient male rats. PLoS One 2023; 18:e0294151. [PMID: 37943747 PMCID: PMC10635473 DOI: 10.1371/journal.pone.0294151] [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: 08/09/2023] [Accepted: 10/25/2023] [Indexed: 11/12/2023] Open
Abstract
Glutamate and GABA signaling systems are necessary to maintain proper function of the central nervous system through excitation/inhibition (E/I) balance. Alteration of this balance in the medial prefrontal cortex (mPFC), as an effect of early-life stress, may lead to the development of anxiety and depressive disorders. Few studies exist in the infralimbic division of the mPFC to understand the effect of early-life stress at different ages, which is the purpose of the present work. Newborn Sprague Dawley male rats were subjected to maternal separation (MS) for two weeks. First, tests measuring anxiety- and depression-like behaviors were performed on adolescent and adult rats subjected to MS (MS-rats). Then, to establish a relationship with behavioral results, electrophysiological recordings were performed in neurons of the infralimbic cortex in acute brain slices of infant, adolescent, and adult rats. In the behavioral tests, there were no significant differences in MS-rats compared to control rats at any age. Moreover, MS had no effect on the passive membrane properties nor neuronal excitability in the infralimbic cortex, whereas spontaneous synaptic activity in infralimbic neurons was altered. The frequency of spontaneous glutamatergic synaptic events increased in infant MS-rats, whereas in adolescent MS-rats both the frequency and the amplitude of spontaneous GABAergic events increased without any effect on glutamatergic synaptic responses. In adult MS-rats, these two parameters decreased in spontaneous GABAergic synaptic events, whereas only the frequency of glutamatergic events decreased. These data suggest that rats subjected to MS did not exhibit behavioral changes and presented an age-dependent E/I imbalance in the infralimbic cortex, possibly due to differential changes in neurotransmitter release and/or receptor expression.
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Affiliation(s)
- Jesús David Ayala-Rodríguez
- Departamento de Neurobiología Celular y Molecular, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Jesús García-Colunga
- Departamento de Neurobiología Celular y Molecular, Instituto de Neurobiología, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
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27
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Klinger K, del Ángel M, Çalışkan G, Stork O. Increasing NPYergic transmission in the hippocampus rescues aging-related deficits of long-term potentiation in the mouse dentate gyrus. Front Aging Neurosci 2023; 15:1283581. [PMID: 38020778 PMCID: PMC10673643 DOI: 10.3389/fnagi.2023.1283581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Accepted: 10/26/2023] [Indexed: 12/01/2023] Open
Abstract
Loss of neuropeptide Y (NPY)-expressing interneurons in the hippocampus and decaying cholinergic neuromodulation are thought to contribute to impaired cognitive function during aging. However, the interaction of these two neuromodulatory systems in maintaining hippocampal synaptic plasticity during healthy aging has not been explored so far. Here we report profound sex differences in the Neuropeptide-Y (NPY) levels in the dorsal dentate gyrus (DG) with higher NPY concentrations in the male mice compared to their female counterparts and a reduction of NPY levels during aging specifically in males. This change in aged males is accompanied by a deficit in theta burst-induced long-term potentiation (LTP) in the medial perforant path-to-dorsal DG (MPP-DG) synapse, which can be rescued by enhancing cholinergic activation with the acetylcholine esterase blocker, physostigmine. Importantly, NPYergic transmission is required for this rescue of LTP. Moreover, exogenous NPY application alone is sufficient to recover LTP induction in aged male mice, even in the absence of the cholinergic stimulator. Together, our results suggest that in male mice NPYergic neurotransmission is a critical factor for maintaining dorsal DG LTP during aging.
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Affiliation(s)
- Katharina Klinger
- Department of Genetics and Molecular Neurobiology, Institute of Biology, Otto-von-Guericke University, Magdeburg, Germany
- Research Group “Synapto-Oscillopathies”, Institute of Biology, Otto-von-Guericke-University, Magdeburg, Germany
| | - Miguel del Ángel
- Department of Genetics and Molecular Neurobiology, Institute of Biology, Otto-von-Guericke University, Magdeburg, Germany
| | - Gürsel Çalışkan
- Department of Genetics and Molecular Neurobiology, Institute of Biology, Otto-von-Guericke University, Magdeburg, Germany
- Research Group “Synapto-Oscillopathies”, Institute of Biology, Otto-von-Guericke-University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
| | - Oliver Stork
- Department of Genetics and Molecular Neurobiology, Institute of Biology, Otto-von-Guericke University, Magdeburg, Germany
- Center for Behavioral Brain Sciences, Magdeburg, Germany
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Magdeburg, Germany
- German Center for Mental Health (DZPG), Magdeburg, Germany
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28
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Wang SH, Siebenhühner F, Arnulfo G, Myrov V, Nobili L, Breakspear M, Palva S, Palva JM. Critical-like Brain Dynamics in a Continuum from Second- to First-Order Phase Transition. J Neurosci 2023; 43:7642-7656. [PMID: 37816599 PMCID: PMC10634584 DOI: 10.1523/jneurosci.1889-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 06/07/2023] [Accepted: 09/25/2023] [Indexed: 10/12/2023] Open
Abstract
The classic brain criticality hypothesis postulates that the brain benefits from operating near a continuous second-order phase transition. Slow feedback regulation of neuronal activity could, however, lead to a discontinuous first-order transition and thereby bistable activity. Observations of bistability in awake brain activity have nonetheless remained scarce and its functional significance unclear. Moreover, there is no empirical evidence to support the hypothesis that the human brain could flexibly operate near either a first- or second-order phase transition despite such a continuum being common in models. Here, using computational modeling, we found bistable synchronization dynamics to emerge through elevated positive feedback and occur exclusively in a regimen of critical-like dynamics. We then assessed bistability in vivo with resting-state MEG in healthy adults (7 females, 11 males) and stereo-electroencephalography in epilepsy patients (28 females, 36 males). This analysis revealed that a large fraction of the neocortices exhibited varying degrees of bistability in neuronal oscillations from 3 to 200 Hz. In line with our modeling results, the neuronal bistability was positively correlated with classic assessment of brain criticality across narrow-band frequencies. Excessive bistability was predictive of epileptic pathophysiology in the patients, whereas moderate bistability was positively correlated with task performance in the healthy subjects. These empirical findings thus reveal the human brain as a one-of-a-kind complex system that exhibits critical-like dynamics in a continuum between continuous and discontinuous phase transitions.SIGNIFICANCE STATEMENT In the model, while synchrony per se was controlled by connectivity, increasing positive local feedback led to gradually emerging bistable synchrony with scale-free dynamics, suggesting a continuum between second- and first-order phase transitions in synchrony dynamics inside a critical-like regimen. In resting-state MEG and SEEG, bistability of ongoing neuronal oscillations was pervasive across brain areas and frequency bands and was observed only with concurring critical-like dynamics as the modeling predicted. As evidence for functional relevance, moderate bistability was positively correlated with executive functioning in the healthy subjects, and excessive bistability was associated with epileptic pathophysiology. These findings show that critical-like neuronal dynamics in vivo involves both continuous and discontinuous phase transitions in a frequency-, neuroanatomy-, and state-dependent manner.
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Affiliation(s)
- Sheng H Wang
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
- Doctoral Programme Brain & Mind, University of Helsinki, 00014 Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Center, 00290 Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University, 00076 Espoo, Finland
| | - Felix Siebenhühner
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Center, 00290 Helsinki, Finland
| | - Gabriele Arnulfo
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
- Department of Informatics, Bioengineering, Robotics and System Engineering, University of Genoa, 16136 Genoa, Italy
| | - Vladislav Myrov
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University, 00076 Espoo, Finland
| | - Lino Nobili
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Children's Sciences, University of Genoa, 16136 Genoa, Italy
- Child Neuropsychiatry Unit, Istituto Di Ricovero e Cura a Carattere Scientifico Istituto Giannina Gaslini, 16147 Genoa, Italy
- Centre of Epilepsy Surgery "C. Munari," Department of Neuroscience, Niguarda Hospital, 20162 Milan, Italy
| | - Michael Breakspear
- College of Engineering, Science and Environment, College of Health and Medicine, University of Newcastle, Callaghan, 2308 Australia
| | - Satu Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
- Centre for Cognitive Neuroimaging, Institute of Neuroscience & Psychology, University of Glasgow, Glasgow G12 8QB, United Kingdom
| | - J Matias Palva
- Neuroscience Center, Helsinki Institute of Life Science, University of Helsinki, 00014 Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University, 00076 Espoo, Finland
- Centre for Cognitive Neuroimaging, Institute of Neuroscience & Psychology, University of Glasgow, Glasgow G12 8QB, United Kingdom
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29
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Maschke C, O'Byrne J, Colombo MA, Boly M, Gosseries O, Laureys S, Rosanova M, Jerbi K, Blain-Moraes S. Criticality of resting-state EEG predicts perturbational complexity and level of consciousness during anesthesia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.26.564247. [PMID: 37994368 PMCID: PMC10664178 DOI: 10.1101/2023.10.26.564247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2023]
Abstract
Consciousness has been proposed to be supported by electrophysiological patterns poised at criticality, a dynamical regime which exhibits adaptive computational properties, maximally complex patterns and divergent sensitivity to perturbation. Here, we investigated dynamical properties of the resting-state electroencephalogram of healthy subjects undergoing general anesthesia with propofol, xenon or ketamine. We then studied the relation of these dynamic properties with the perturbational complexity index (PCI), which has shown remarkably high sensitivity in detecting consciousness independent of behavior. All participants were unresponsive under anesthesia, while consciousness was retained only during ketamine anesthesia (in the form of vivid dreams)., enabling an experimental dissociation between unresponsiveness and unconsciousness. We estimated (i) avalanche criticality, (ii) chaoticity, and (iii) criticality-related measures, and found that states of unconsciousness were characterized by a distancing from both the edge of activity propagation and the edge of chaos. We were then able to predict individual subjects' PCI (i.e., PCImax) with a mean absolute error below 7%. Our results establish a firm link between the PCI and criticality and provide further evidence for the role of criticality in the emergence of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- Integrated Program in Neuroscience, McGill University, Montreal, Canada
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
| | - Jordan O'Byrne
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
| | | | - Melanie Boly
- Department of Neurology and Department of Psychiatry, University of Wisconsin, Madison, USA
| | - Olivia Gosseries
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- Centre du cerveau, CHU of Liège, Liège, Belgium
| | - Steven Laureys
- Coma Science Group, GIGA Consciousness, University of Liège, Liège, Belgium
- CERVO Brain Research Centre, Laval University, Canada
- Consciousness Science Institute, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Mario Rosanova
- Department of Biomedical and Clinical Sciences, University of Milan, Milan, Italy
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada
- MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada
- Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada
- School of Physical and Occupational Therapy, McGill University, Montreal, Canada
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30
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Yang B, Zhang H, Jiang T, Yu S. Natural brain state change with E/I balance shifting toward inhibition is associated with vigilance impairment. iScience 2023; 26:107963. [PMID: 37822500 PMCID: PMC10562778 DOI: 10.1016/j.isci.2023.107963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 07/25/2023] [Accepted: 09/15/2023] [Indexed: 10/13/2023] Open
Abstract
The delicate balance between cortical excitation and inhibition (E/I) plays a pivotal role in brain state changes. While previous studies have associated cortical hyperexcitability with brain state changes induced by sleep deprivation, whether cortical hypoexcitability is also linked to brain state changes and, if so, how it could affect cognitive performance remain unknown. Here, we address these questions by examining the brain state change occurring after meals, i.e., postprandial somnolence, and comparing it with that induced by sleep deprivation. By analyzing features representing network excitability based on electroencephalogram (EEG) signals, we confirmed cortical hyperexcitability under sleep deprivation but revealed hypoexcitability under postprandial somnolence. In addition, we found that both sleep deprivation and postprandial somnolence adversely affected the level of vigilance. These results indicate that cortical E/I balance toward inhibition is associated with brain state changes, and deviation from the balanced state, regardless of its direction, could impair cognitive performance.
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Affiliation(s)
- Binghao Yang
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Haoran Zhang
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
| | - Tianzi Jiang
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 101408, China
- Research Center for Augmented Intelligence, Zhejiang Lab, Hangzhou 311121, China
| | - Shan Yu
- Brainnetome Center, Laboratory of Brain Atlas and Brain-inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
- School of Future Technology, University of Chinese Academy of Sciences, Beijing 101408, China
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31
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Fortel I, Zhan L, Ajilore O, Wu Y, Mackin S, Leow A. Disrupted excitation-inhibition balance in cognitively normal individuals at risk of Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.21.554061. [PMID: 37662359 PMCID: PMC10473582 DOI: 10.1101/2023.08.21.554061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Background Sex differences impact Alzheimer's disease (AD) neuropathology, but cell-to-network level dysfunctions in the prodromal phase are unclear. Alterations in hippocampal excitation-inhibition balance (EIB) have recently been linked to early AD pathology. Objective Examine how AD risk factors (age, APOE-ɛ4, amyloid-β) relate to hippocampal EIB in cognitively normal males and females using connectome-level measures. Methods Individuals from the OASIS-3 cohort (age 42-95) were studied (N = 437), with a subset aged 65+ undergoing neuropsychological testing (N = 231). Results In absence of AD risk factors (APOE-ɛ4/Aβ+), whole-brain EIB decreases with age more significantly in males than females (p = 0.021, β = -0.007). Regression modeling including APOE-ɛ4 allele carriers (Aβ-) yielded a significant positive AGE-by-APOE interaction in the right hippocampus for females only (p = 0.013, β = 0.014), persisting with inclusion of Aβ+ individuals (p = 0.012, β = 0.014). Partial correlation analyses of neuropsychological testing showed significant associations with EIB in females: positive correlations between right hippocampal EIB with categorical fluency and whole-brain EIB with the trail-making test (p < 0.05). Conclusion Sex differences in EIB emerge during normal aging and progresses differently with AD risk. Results suggest APOE-ɛ4 disrupts hippocampal balance more than amyloid in females. Increased excitation correlates positively with neuropsychological performance in the female group, suggesting a duality in terms of potential beneficial effects prior to cognitive impairment. This underscores the translational relevance of APOE-ɛ4 related hyperexcitation in females, potentially informing therapeutic targets or early interventions to mitigate AD progression in this vulnerable population.
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Affiliation(s)
- Igor Fortel
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL
| | - Liang Zhan
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL
| | - Yichao Wu
- Department of Math, Statistics and Computer Science, University of Illinois at Chicago, Chicago, IL
| | - Scott Mackin
- Department of Psychiatry, University of California - San Francisco, San Francisco, CA
| | - Alex Leow
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL
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32
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Fuscà M, Siebenhühner F, Wang SH, Myrov V, Arnulfo G, Nobili L, Palva JM, Palva S. Brain criticality predicts individual levels of inter-areal synchronization in human electrophysiological data. Nat Commun 2023; 14:4736. [PMID: 37550300 PMCID: PMC10406818 DOI: 10.1038/s41467-023-40056-9] [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: 12/07/2022] [Accepted: 07/10/2023] [Indexed: 08/09/2023] Open
Abstract
Neuronal oscillations and their synchronization between brain areas are fundamental for healthy brain function. Yet, synchronization levels exhibit large inter-individual variability that is associated with behavioral variability. We test whether individual synchronization levels are predicted by individual brain states along an extended regime of critical-like dynamics - the Griffiths phase (GP). We use computational modelling to assess how synchronization is dependent on brain criticality indexed by long-range temporal correlations (LRTCs). We analyze LRTCs and synchronization of oscillations from resting-state magnetoencephalography and stereo-electroencephalography data. Synchronization and LRTCs are both positively linearly and quadratically correlated among healthy subjects, while in epileptogenic areas they are negatively linearly correlated. These results show that variability in synchronization levels is explained by the individual position along the GP with healthy brain areas operating in its subcritical and epileptogenic areas in its supercritical side. We suggest that the GP is fundamental for brain function allowing individual variability while retaining functional advantages of criticality.
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Affiliation(s)
- Marco Fuscà
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
| | - Felix Siebenhühner
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- BioMag Laboratory, HUS Medical Imaging Center, University of Helsinki, Aalto University, and Helsinki University Hospital, Helsinki, Finland
| | - Sheng H Wang
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
- CEA, NeuroSpin, Gif-sur-Yvette, France
- MIND team, Inria, Université Paris-Saclay, Bures-sur-Yvette, France
| | - Vladislav Myrov
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Gabriele Arnulfo
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Dept. of Informatics, Bioengineering, Robotics and System engineering, University of Genoa, Genoa, Italy
| | - Lino Nobili
- Child Neuropsychiatry Unit, IRCCS, Istituto G. Gaslini, Department of Neuroscience (DINOGMI), University of Genoa, Genoa, Italy
- "Claudio Munari" Epilepsy Surgery Centre, Niguarda Hospital, Milan, Italy
| | - J Matias Palva
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Department of Neuroscience and Biomedical Engineering, Aalto University, Espoo, Finland
| | - Satu Palva
- Centre for Cognitive Neuroimaging, School of Psychology and Neuroscience, University of Glasgow, Glasgow, UK.
- Neuroscience Center, HiLIFE-Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland.
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33
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Meyer CT, Kralj JM. Cell-autonomous diversification in bacteria arises from calcium dynamics self-organizing at a critical point. SCIENCE ADVANCES 2023; 9:eadg3028. [PMID: 37540744 PMCID: PMC10403213 DOI: 10.1126/sciadv.adg3028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 07/03/2023] [Indexed: 08/06/2023]
Abstract
How dynamic bacterial calcium is regulated, with kinetics faster than typical mechanisms of cellular adaptation, is unknown. We discover bacterial calcium fluctuations are temporal-fractals resulting from a property known as self-organized criticality (SOC). SOC processes are poised at a phase transition separating ordered and chaotic dynamical regimes and are observed in many natural and anthropogenic systems. SOC in bacterial calcium emerges due to calcium channel coupling mediated via membrane voltage. Environmental or genetic perturbations modify calcium dynamics and the critical exponent suggesting a continuum of critical attractors. Moving along this continuum alters the collective information capacity of bacterial populations. We find that the stochastic transition from motile to sessile lifestyle is partially mediated by SOC-governed calcium fluctuations through the regulation of c-di-GMP. In summary, bacteria co-opt the physics of phase transitions to maintain dynamic calcium equilibrium, and this enables cell-autonomous population diversification during surface colonization by leveraging the stochasticity inherent at a boundary between phases.
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Janarek J, Drogosz Z, Grela J, Ochab JK, Oświęcimka P. Investigating structural and functional aspects of the brain's criticality in stroke. Sci Rep 2023; 13:12341. [PMID: 37524891 PMCID: PMC10390586 DOI: 10.1038/s41598-023-39467-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/26/2023] [Indexed: 08/02/2023] Open
Abstract
This paper addresses the question of the brain's critical dynamics after an injury such as a stroke. It is hypothesized that the healthy brain operates near a phase transition (critical point), which provides optimal conditions for information transmission and responses to inputs. If structural damage could cause the critical point to disappear and thus make self-organized criticality unachievable, it would offer the theoretical explanation for the post-stroke impairment of brain function. In our contribution, however, we demonstrate using network models of the brain, that the dynamics remain critical even after a stroke. In cases where the average size of the second-largest cluster of active nodes, which is one of the commonly used indicators of criticality, shows an anomalous behavior, it results from the loss of integrity of the network, quantifiable within graph theory, and not from genuine non-critical dynamics. We propose a new simple model of an artificial stroke that explains this anomaly. The proposed interpretation of the results is confirmed by an analysis of real connectomes acquired from post-stroke patients and a control group. The results presented refer to neurobiological data; however, the conclusions reached apply to a broad class of complex systems that admit a critical state.
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Affiliation(s)
- Jakub Janarek
- Institute of Theoretical Physics, Jagiellonian University, 30-348, Kraków, Poland
| | - Zbigniew Drogosz
- Institute of Theoretical Physics, Jagiellonian University, 30-348, Kraków, Poland
| | - Jacek Grela
- Institute of Theoretical Physics, Jagiellonian University, 30-348, Kraków, Poland
- Mark Kac Center for Complex Systems Research, Jagiellonian University, 30-348, Kraków, Poland
| | - Jeremi K Ochab
- Institute of Theoretical Physics, Jagiellonian University, 30-348, Kraków, Poland.
- Mark Kac Center for Complex Systems Research, Jagiellonian University, 30-348, Kraków, Poland.
| | - Paweł Oświęcimka
- Institute of Theoretical Physics, Jagiellonian University, 30-348, Kraków, Poland
- Mark Kac Center for Complex Systems Research, Jagiellonian University, 30-348, Kraków, Poland
- Complex Systems Theory Department, Institute of Nuclear Physics, Polish Academy of Sciences, 31-342, Kraków, Poland
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Fontenele AJ, Sooter JS, Norman VK, Gautam SH, Shew WL. Low dimensional criticality embedded in high dimensional awake brain dynamics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.05.522896. [PMID: 37546833 PMCID: PMC10401950 DOI: 10.1101/2023.01.05.522896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Whether cortical neurons operate in a strongly or weakly correlated dynamical regime determines fundamental information processing capabilities and has fueled decades of debate. Here we offer a resolution of this debate; we show that two important dynamical regimes, typically considered incompatible, can coexist in the same local cortical circuit by separating them into two different subspaces. In awake mouse motor cortex, we find a low-dimensional subspace with large fluctuations consistent with criticality - a dynamical regime with moderate correlations and multi-scale information capacity and transmission. Orthogonal to this critical subspace, we find a high-dimensional subspace containing a desynchronized dynamical regime, which may optimize input discrimination. The critical subspace is apparent only at long timescales, which explains discrepancies among some previous studies. Using a computational model, we show that the emergence of a low-dimensional critical subspace at large timescale agrees with established theory of critical dynamics. Our results suggest that cortex leverages its high dimensionality to multiplex dynamical regimes across different subspaces.
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Affiliation(s)
- Antonio J. Fontenele
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - J. Samuel Sooter
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - V. Kindler Norman
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - Shree Hari Gautam
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
| | - Woodrow L. Shew
- UA Integrative Systems Neuroscience Group, Department of Physics, University of Arkansas, Fayetteville, AR, USA, 72701
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Páscoa Dos Santos F, Vohryzek J, Verschure PFMJ. Multiscale effects of excitatory-inhibitory homeostasis in lesioned cortical networks: A computational study. PLoS Comput Biol 2023; 19:e1011279. [PMID: 37418506 DOI: 10.1371/journal.pcbi.1011279] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 06/18/2023] [Indexed: 07/09/2023] Open
Abstract
Stroke-related disruptions in functional connectivity (FC) often spread beyond lesioned areas and, given the localized nature of lesions, it is unclear how the recovery of FC is orchestrated on a global scale. Since recovery is accompanied by long-term changes in excitability, we propose excitatory-inhibitory (E-I) homeostasis as a driving mechanism. We present a large-scale model of the neocortex, with synaptic scaling of local inhibition, showing how E-I homeostasis can drive the post-lesion restoration of FC and linking it to changes in excitability. We show that functional networks could reorganize to recover disrupted modularity and small-worldness, but not network dynamics, suggesting the need to consider forms of plasticity beyond synaptic scaling of inhibition. On average, we observed widespread increases in excitability, with the emergence of complex lesion-dependent patterns related to biomarkers of relevant side effects of stroke, such as epilepsy, depression and chronic pain. In summary, our results show that the effects of E-I homeostasis extend beyond local E-I balance, driving the restoration of global properties of FC, and relating to post-stroke symptomatology. Therefore, we suggest the framework of E-I homeostasis as a relevant theoretical foundation for the study of stroke recovery and for understanding the emergence of meaningful features of FC from local dynamics.
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Affiliation(s)
- Francisco Páscoa Dos Santos
- Eodyne Systems SL, Barcelona, Spain
- Department of Information and Communication Technologies, Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Jakub Vohryzek
- Centre for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, United Kingdom
| | - Paul F M J Verschure
- Donders Institute for Brain, Cognition and Behavior, Radboud University, Nijmegen, The Netherlands
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Oprisan SA, Clementsmith X, Tompa T, Lavin A. Empirical mode decomposition of local field potential data from optogenetic experiments. Front Comput Neurosci 2023; 17:1223879. [PMID: 37476356 PMCID: PMC10354259 DOI: 10.3389/fncom.2023.1223879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 06/19/2023] [Indexed: 07/22/2023] Open
Abstract
Introduction This study investigated the effects of cocaine administration and parvalbumin-type interneuron stimulation on local field potentials (LFPs) recorded in vivo from the medial prefrontal cortex (mPFC) of six mice using optogenetic tools. Methods The local network was subject to a brief 10 ms laser pulse, and the response was recorded for 2 s over 100 trials for each of the six subjects who showed stable coupling between the mPFC and the optrode. Due to the strong non-stationary and nonlinearity of the LFP, we used the adaptive, data-driven, Empirical Mode Decomposition (EMD) method to decompose the signal into orthogonal Intrinsic Mode Functions (IMFs). Results Through trial and error, we found that seven is the optimum number of orthogonal IMFs that overlaps with known frequency bands of brain activity. We found that the Index of Orthogonality (IO) of IMF amplitudes was close to zero. The Index of Energy Conservation (IEC) for each decomposition was close to unity, as expected for orthogonal decompositions. We found that the power density distribution vs. frequency follows a power law with an average scaling exponent of ~1.4 over the entire range of IMF frequencies 2-2,000 Hz. Discussion The scaling exponent is slightly smaller for cocaine than the control, suggesting that neural activity avalanches under cocaine have longer life spans and sizes.
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Affiliation(s)
- Sorinel A. Oprisan
- Department of Physics and Astronomy, College of Charleston, Charleston, SC, United States
| | - Xandre Clementsmith
- Department of Computer Science, College of Charleston, Charleston, SC, United States
| | - Tamas Tompa
- Faculty of Healthcare, Department of Preventive Medicine, University of Miskolc, Miskolc, Hungary
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States
| | - Antonieta Lavin
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, United States
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Walter N, Meinersen-Schmidt N, Kulla P, Loew T, Kruse J, Hinterberger T. Sensory-Processing Sensitivity Is Associated with Increased Neural Entropy. ENTROPY (BASEL, SWITZERLAND) 2023; 25:890. [PMID: 37372234 DOI: 10.3390/e25060890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 05/17/2023] [Accepted: 05/30/2023] [Indexed: 06/29/2023]
Abstract
BACKGROUND This study aimed at answering the following research questions: (1) Does the self-reported level of sensory-processing sensitivity (SPS) correlate with complexity, or criticality features of the electroencephalogram (EEG)? (2) Are there significant EEG differences comparing individuals with high and low levels of SPS? METHODS One hundred fifteen participants were measured with 64-channel EEG during a task-free resting state. The data were analyzed using criticality theory tools (detrended fluctuation analysis, neuronal avalanche analysis) and complexity measures (sample entropy, Higuchi's fractal dimension). Correlations with the 'Highly Sensitive Person Scale' (HSPS-G) scores were determined. Then, the cohort's lowest and the highest 30% were contrasted as opposites. EEG features were compared between the two groups by applying a Wilcoxon signed-rank test. RESULTS During resting with eyes open, HSPS-G scores correlated significantly positively with the sample entropy and Higuchi's fractal dimension (Spearman's ρ = 0.22, p < 0.05). The highly sensitive group revealed higher sample entropy values (1.83 ± 0.10 vs. 1.77 ± 0.13, p = 0.031). The increased sample entropy in the highly sensitive group was most pronounced in the central, temporal, and parietal regions. CONCLUSION For the first time, neurophysiological complexity features associated with SPS during a task-free resting state were demonstrated. Evidence is provided that neural processes differ between low- and highly-sensitive persons, whereby the latter displayed increased neural entropy. The findings support the central theoretical assumption of enhanced information processing and could be important for developing biomarkers for clinical diagnostics.
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Affiliation(s)
- Nike Walter
- Department of Psychosomatic Medicine, University Hospital Regensburg, 93059 Regensburg, Germany
| | - Nicole Meinersen-Schmidt
- Department for Clinical Psychology and Trauma Therapy, University of the Bundeswehr Munich, 85579 Neubiberg, Germany
| | - Patricia Kulla
- Department for Clinical Psychology and Trauma Therapy, University of the Bundeswehr Munich, 85579 Neubiberg, Germany
| | - Thomas Loew
- Department of Psychosomatic Medicine, University Hospital Regensburg, 93059 Regensburg, Germany
| | - Joachim Kruse
- Department for Clinical Psychology and Trauma Therapy, University of the Bundeswehr Munich, 85579 Neubiberg, Germany
| | - Thilo Hinterberger
- Department of Psychosomatic Medicine, University Hospital Regensburg, 93059 Regensburg, Germany
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Yurchenko SB. A systematic approach to brain dynamics: cognitive evolution theory of consciousness. Cogn Neurodyn 2023; 17:575-603. [PMID: 37265655 PMCID: PMC10229528 DOI: 10.1007/s11571-022-09863-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 06/29/2022] [Accepted: 07/21/2022] [Indexed: 12/18/2022] Open
Abstract
The brain integrates volition, cognition, and consciousness seamlessly over three hierarchical (scale-dependent) levels of neural activity for their emergence: a causal or 'hard' level, a computational (unconscious) or 'soft' level, and a phenomenal (conscious) or 'psyche' level respectively. The cognitive evolution theory (CET) is based on three general prerequisites: physicalism, dynamism, and emergentism, which entail five consequences about the nature of consciousness: discreteness, passivity, uniqueness, integrity, and graduation. CET starts from the assumption that brains should have primarily evolved as volitional subsystems of organisms, not as prediction machines. This emphasizes the dynamical nature of consciousness in terms of critical dynamics to account for metastability, avalanches, and self-organized criticality of brain processes, then coupling it with volition and cognition in a framework unified over the levels. Consciousness emerges near critical points, and unfolds as a discrete stream of momentary states, each volitionally driven from oldest subcortical arousal systems. The stream is the brain's way of making a difference via predictive (Bayesian) processing. Its objective observables could be complexity measures reflecting levels of consciousness and its dynamical coherency to reveal how much knowledge (information gain) the brain acquires over the stream. CET also proposes a quantitative classification of both disorders of consciousness and mental disorders within that unified framework.
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Maschke C, Duclos C, Owen AM, Jerbi K, Blain-Moraes S. Aperiodic brain activity and response to anesthesia vary in disorders of consciousness. Neuroimage 2023; 275:120154. [PMID: 37209758 DOI: 10.1016/j.neuroimage.2023.120154] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/28/2023] [Accepted: 05/02/2023] [Indexed: 05/22/2023] Open
Abstract
In the human electroencephalogram (EEG), oscillatory power peaks co-exist with non-oscillatory, aperiodic activity. Although EEG analysis has traditionally focused exclusively on oscillatory power, recent investigations have shown that the aperiodic EEG component can distinguish conscious wakefulness from sleep and anesthetic-induced unconsciousness. This study investigates the aperiodic EEG component of individuals in a disorder of consciousness (DOC); how it changes in response to exposure to anesthesia; and how it relates to the brain's information richness and criticality. High-density EEG was recorded from 43 individuals in a DOC, with 16 of these individuals undergoing a protocol of propofol anesthesia. The aperiodic component was defined by the spectral slope of the power spectral density. Our results demonstrate that the EEG aperiodic component is more informative about the participants' level of consciousness than the oscillatory component, especially for patients that suffered from a stroke. Importantly, the pharmacologically induced change in the spectral slope from 30-45 Hz positively correlated with individual's pre-anesthetic level of consciousness. The pharmacologically induced loss of information-richness and criticality was associated with individual's pre-anesthetic aperiodic component. During exposure to anesthesia, the aperiodic component was correlated with 3-month recovery status for individuals with DOC. The aperiodic EEG component has been historically neglected; this research highlights the necessity of considering this measure for the assessment of individuals in DOC and future research that seeks to understand the neurophysiological underpinnings of consciousness.
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Affiliation(s)
- Charlotte Maschke
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada; Integrated Program in Neuroscience, McGill University, Montreal, Canada
| | - Catherine Duclos
- Hôpital du Sacré-Cœur de Montréal, Centre intégré universitaire de Santé et de Services Sociaux du Nord-de-l'île-de-Montréal, Montréal, Québec Canada; Department of Anesthesiology and Pain Medicine, Université de Montréal, Montréal, Québec Canada
| | - Adrian M Owen
- Department of Physiology and Pharmacology, Western University, London, Ontario, Canada; Western Institute for Neuroscience, Western University, London, Ontario, Canada; Department of Psychology, Western University, London, Ontario, Canada
| | - Karim Jerbi
- Cognitive & Computational Neuroscience Lab, Psychology Department, University of Montreal, Québec, Canada; MILA (Québec Artificial Intelligence Institute), Montréal, Québec, Canada; Centre UNIQUE (Union Neurosciences & Intelligence Artificielle), Montréal, Québec, Canada
| | - Stefanie Blain-Moraes
- Montreal General Hospital, McGill University Health Centre, Montreal, Canada; School of Physical and Occupational Therapy, McGill University, Montreal, Canada.
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Arsiwalla XD, Srinivasan N, Simione L, Kleiner J, Raffone A. Editorial: Rising stars in: consciousness research 2021. Front Psychol 2023; 14:1205982. [PMID: 37260961 PMCID: PMC10228500 DOI: 10.3389/fpsyg.2023.1205982] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 04/25/2023] [Indexed: 06/02/2023] Open
Affiliation(s)
- Xerxes D. Arsiwalla
- Department of Information and Communication Technologies, Pompeu Fabra University, Barcelona, Spain
- Association for Mathematical Consciousness Science, Munich, Germany
| | - Narayanan Srinivasan
- Department of Cognitive Science, Indian Institute of Technology Kanpur, Kanpur, India
| | - Luca Simione
- Institute of Cognitive Sciences and Technologies, Consiglio Nazionale delle Ricerche, Rome, Italy
- Faculty of Interpreting and Translation, UNINT Università degli Studi Internazionali di Roma, Rome, Italy
| | - Johannes Kleiner
- Association for Mathematical Consciousness Science, Munich, Germany
- Munich Center for Mathematical Philosophy, Ludwig Maximilian University of Munich, Munich, Germany
- Munich Graduate School of Systemic Neurosciences, Ludwig Maximilian University of Munich, Munich, Germany
| | - Antonino Raffone
- Department of Psychology, Sapienza University of Rome, Rome, Italy
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Capek E, Ribeiro TL, Kells P, Srinivasan K, Miller SR, Geist E, Victor M, Vakili A, Pajevic S, Chialvo DR, Plenz D. Parabolic avalanche scaling in the synchronization of cortical cell assemblies. Nat Commun 2023; 14:2555. [PMID: 37137888 PMCID: PMC10156782 DOI: 10.1038/s41467-023-37976-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Accepted: 04/07/2023] [Indexed: 05/05/2023] Open
Abstract
Neurons in the cerebral cortex fire coincident action potentials during ongoing activity and in response to sensory inputs. These synchronized cell assemblies are fundamental to cortex function, yet basic dynamical aspects of their size and duration are largely unknown. Using 2-photon imaging of neurons in the superficial cortex of awake mice, we show that synchronized cell assemblies organize as scale-invariant avalanches that quadratically grow with duration. The quadratic avalanche scaling was only found for correlated neurons, required temporal coarse-graining to compensate for spatial subsampling of the imaged cortex, and suggested cortical dynamics to be critical as demonstrated in simulations of balanced E/I-networks. The corresponding time course of an inverted parabola with exponent of χ = 2 described cortical avalanches of coincident firing for up to 5 s duration over an area of 1 mm2. These parabolic avalanches maximized temporal complexity in the ongoing activity of prefrontal and somatosensory cortex and in visual responses of primary visual cortex. Our results identify a scale-invariant temporal order in the synchronization of highly diverse cortical cell assemblies in the form of parabolic avalanches.
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Affiliation(s)
- Elliott Capek
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Tiago L Ribeiro
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Patrick Kells
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Keshav Srinivasan
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
- Department of Physics, University of Maryland, College Park, MD, USA
| | - Stephanie R Miller
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Elias Geist
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Mitchell Victor
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Ali Vakili
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Sinisa Pajevic
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA
| | - Dante R Chialvo
- CEMSC3, Escuela de Ciencia y Tecnologia, UNSAM, San Martín, P. Buenos Aires, Argentina
| | - Dietmar Plenz
- Section on Critical Brain Dynamics, National Institute of Mental Health, Bethesda, MD, USA.
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Varley TF. Decomposing past and future: Integrated information decomposition based on shared probability mass exclusions. PLoS One 2023; 18:e0282950. [PMID: 36952508 PMCID: PMC10035902 DOI: 10.1371/journal.pone.0282950] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Accepted: 02/27/2023] [Indexed: 03/25/2023] Open
Abstract
A core feature of complex systems is that the interactions between elements in the present causally constrain their own futures, and the futures of other elements as the system evolves through time. To fully model all of these interactions (between elements, as well as ensembles of elements), it is possible to decompose the total information flowing from past to future into a set of non-overlapping temporal interactions that describe all the different modes by which information can be stored, transferred, or modified. To achieve this, I propose a novel information-theoretic measure of temporal dependency (Iτsx) based on the logic of local probability mass exclusions. This integrated information decomposition can reveal emergent and higher-order interactions within the dynamics of a system, as well as refining existing measures. To demonstrate the utility of this framework, I apply the decomposition to spontaneous spiking activity recorded from dissociated neural cultures of rat cerebral cortex to show how different modes of information processing are distributed over the system. Furthermore, being a localizable analysis, Iτsx can provide insight into the computational structure of single moments. I explore the time-resolved computational structure of neuronal avalanches and find that different types of information atoms have distinct profiles over the course of an avalanche, with the majority of non-trivial information dynamics happening before the first half of the cascade is completed. These analyses allow us to move beyond the historical focus on single measures of dependency such as information transfer or information integration, and explore a panoply of different relationships between elements (and groups of elements) in complex systems.
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Affiliation(s)
- Thomas F. Varley
- Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States of America
- School of Informatics, Computing, and Engineering, Indiana University Bloomington, Bloomington, IN, United States of America
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Müller PM, Meisel C. Spatial and temporal correlations in human cortex are inherently linked and predicted by functional hierarchy, vigilance state as well as antiepileptic drug load. PLoS Comput Biol 2023; 19:e1010919. [PMID: 36867652 PMCID: PMC10027224 DOI: 10.1371/journal.pcbi.1010919] [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: 09/29/2022] [Revised: 03/20/2023] [Accepted: 02/03/2023] [Indexed: 03/04/2023] Open
Abstract
The ability of neural circuits to integrate information over time and across different cortical areas is believed an essential ingredient for information processing in the brain. Temporal and spatial correlations in cortex dynamics have independently been shown to capture these integration properties in task-dependent ways. A fundamental question remains if temporal and spatial integration properties are linked and what internal and external factors shape these correlations. Previous research on spatio-temporal correlations has been limited in duration and coverage, thus providing only an incomplete picture of their interdependence and variability. Here, we use long-term invasive EEG data to comprehensively map temporal and spatial correlations according to cortical topography, vigilance state and drug dependence over extended periods of time. We show that temporal and spatial correlations in cortical networks are intimately linked, decline under antiepileptic drug action, and break down during slow-wave sleep. Further, we report temporal correlations in human electrophysiology signals to increase with the functional hierarchy in cortex. Systematic investigation of a neural network model suggests that these dynamical features may arise when dynamics are poised near a critical point. Our results provide mechanistic and functional links between specific measurable changes in the network dynamics relevant for characterizing the brain's changing information processing capabilities.
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Affiliation(s)
- Paul Manuel Müller
- Computational Neurology Lab, Department of Neurology, Charité–Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
- NeuroCure Cluster of Excellence, Charité–Universitätsmedizin Berlin, Berlin, Germany
| | - Christian Meisel
- Computational Neurology Lab, Department of Neurology, Charité–Universitätsmedizin Berlin, Berlin, Germany
- Berlin Institute of Health, Berlin, Germany
- NeuroCure Cluster of Excellence, Charité–Universitätsmedizin Berlin, Berlin, Germany
- Center for Stroke Research Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience, Berlin, Germany
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Alvankar Golpayegan H, de Candia A. Bistability and criticality in the stochastic Wilson-Cowan model. Phys Rev E 2023; 107:034404. [PMID: 37073019 DOI: 10.1103/physreve.107.034404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 02/17/2023] [Indexed: 04/20/2023]
Abstract
We study a stochastic version of the Wilson-Cowan model of neural dynamics, where the response function of neurons grows faster than linearly above the threshold. The model shows a region of parameters where two attractive fixed points of the dynamics exist simultaneously. One fixed point is characterized by lower activity and scale-free critical behavior, while the second fixed point corresponds to a higher (supercritical) persistent activity, with small fluctuations around a mean value. When the number of neurons is not too large, the system can switch between these two different states with a probability depending on the parameters of the network. Along with alternation of states, the model displays a bimodal distribution of the avalanches of activity, with a power-law behavior corresponding to the critical state, and a bump of very large avalanches due to the high-activity supercritical state. The bistability is due to the presence of a first-order (discontinuous) transition in the phase diagram, and the observed critical behavior is connected with the line where the low-activity state becomes unstable (spinodal line).
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Affiliation(s)
- Hanieh Alvankar Golpayegan
- Dipartimento di Neuroscienze, Scienze Riproduttive e Odontostomatologiche, Università di Napoli Federico II, Via S. Pansini 5, 80131 Napoli, Italy
| | - Antonio de Candia
- Dipartimento di Fisica "E. Pancini", Università di Napoli Federico II, Complesso Universitario di Monte Sant'Angelo, via Cintia, 80126 Napoli, Italy
- INFN, Sezione di Napoli, Gruppo collegato di Salerno, 84084 Fisciano (SA), Italy
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46
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Manos T, Diaz-Pier S, Fortel I, Driscoll I, Zhan L, Leow A. Enhanced simulations of whole-brain dynamics using hybrid resting-state structural connectomes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.16.528836. [PMID: 36824821 PMCID: PMC9948985 DOI: 10.1101/2023.02.16.528836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
The human brain, composed of billions of neurons and synaptic connections, is an intricate network coordinating a sophisticated balance of excitatory and inhibitory activity between brain regions. The dynamical balance between excitation and inhibition is vital for adjusting neural input/output relationships in cortical networks and regulating the dynamic range of their responses to stimuli. To infer this balance using connectomics, we recently introduced a computational framework based on the Ising model, first developed to explain phase transitions in ferromagnets, and proposed a novel hybrid resting-state structural connectome (rsSC). Here, we show that a generative model based on the Kuramoto phase oscillator can be used to simulate static and dynamic functional connectomes (FC) with rsSC as the coupling weight coefficients, such that the simulated FC well aligns with the observed FC when compared to that simulated with traditional structural connectome. Simulations were performed using the open source framework The Virtual Brain on High Performance Computing infrastructure.
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47
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Liu Y, Xu S, Yang Y, Zhang K, He E, Liang W, Luo J, Wu Y, Cai X. Nanomaterial-based microelectrode arrays for in vitro bidirectional brain-computer interfaces: a review. MICROSYSTEMS & NANOENGINEERING 2023; 9:13. [PMID: 36726940 PMCID: PMC9884667 DOI: 10.1038/s41378-022-00479-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 10/04/2022] [Accepted: 10/21/2022] [Indexed: 06/18/2023]
Abstract
A bidirectional in vitro brain-computer interface (BCI) directly connects isolated brain cells with the surrounding environment, reads neural signals and inputs modulatory instructions. As a noninvasive BCI, it has clear advantages in understanding and exploiting advanced brain function due to the simplified structure and high controllability of ex vivo neural networks. However, the core of ex vivo BCIs, microelectrode arrays (MEAs), urgently need improvements in the strength of signal detection, precision of neural modulation and biocompatibility. Notably, nanomaterial-based MEAs cater to all the requirements by converging the multilevel neural signals and simultaneously applying stimuli at an excellent spatiotemporal resolution, as well as supporting long-term cultivation of neurons. This is enabled by the advantageous electrochemical characteristics of nanomaterials, such as their active atomic reactivity and outstanding charge conduction efficiency, improving the performance of MEAs. Here, we review the fabrication of nanomaterial-based MEAs applied to bidirectional in vitro BCIs from an interdisciplinary perspective. We also consider the decoding and coding of neural activity through the interface and highlight the various usages of MEAs coupled with the dissociated neural cultures to benefit future developments of BCIs.
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Affiliation(s)
- Yaoyao Liu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Shihong Xu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Yan Yang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Kui Zhang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Enhui He
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Wei Liang
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Jinping Luo
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Yirong Wu
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
| | - Xinxia Cai
- State Key Laboratory of Transducer Technology, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, 100190 China
- School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049 PR China
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Fortel I, Zhan L, Ajilore O, Wu Y, Mackin S, Leow A. Disrupted Excitation-Inhibition Balance in Cognitively Normal Individuals at Risk of Alzheimer's Disease. J Alzheimers Dis 2023; 95:1449-1467. [PMID: 37718795 PMCID: PMC11260287 DOI: 10.3233/jad-230035] [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] [Indexed: 09/19/2023]
Abstract
BACKGROUND Sex differences impact Alzheimer's disease (AD) neuropathology, but cell-to-network level dysfunctions in the prodromal phase are unclear. Alterations in hippocampal excitation-inhibition balance (EIB) have recently been linked to early AD pathology. OBJECTIVE Examine how AD risk factors (age, APOEɛ4, amyloid-β) relate to hippocampal EIB in cognitively normal males and females using connectome-level measures. METHODS Individuals from the OASIS-3 cohort (age 42-95) were studied (N = 437), with a subset aged 65+ undergoing neuropsychological testing (N = 231). RESULTS In absence of AD risk factors (APOEɛ4/Aβ+), whole-brain EIB decreases with age more significantly in males than females (p = 0.021, β= -0.007). Regression modeling including APOEɛ4 allele carriers (Aβ-) yielded a significant positive AGE-by-APOE interaction in the right hippocampus for females only (p = 0.013, β= 0.014), persisting with inclusion of Aβ+ individuals (p = 0.012, β= 0.014). Partial correlation analyses of neuropsychological testing showed significant associations with EIB in females: positive correlations between right hippocampal EIB with categorical fluency and whole-brain EIB with the Trail Making Test (p < 0.05). CONCLUSIONS Sex differences in EIB emerge during normal aging and progresses differently with AD risk. Results suggest APOEɛ4 disrupts hippocampal balance more than amyloid in females. Increased excitation correlates positively with neuropsychological performance in the female group, suggesting a duality in terms of potential beneficial effects prior to cognitive impairment. This underscores the translational relevance of APOEɛ4 related hyperexcitation in females, potentially informing therapeutic targets or early interventions to mitigate AD progression in this vulnerable population.
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Affiliation(s)
- Igor Fortel
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, USA
| | - Liang Zhan
- Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA, USA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
| | - Yichao Wu
- Department of Math, Statistics and Computer Science, University of Illinois at Chicago, Chicago, IL, USA
| | - Scott Mackin
- Department of Psychiatry, University of California – San Francisco, San Francisco, CA, USA
| | - Alex Leow
- Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL, USA
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA
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Fukai T. Computational models of Idling brain activity for memory processing. Neurosci Res 2022; 189:75-82. [PMID: 36592825 DOI: 10.1016/j.neures.2022.12.024] [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: 12/28/2022] [Accepted: 12/29/2022] [Indexed: 01/01/2023]
Abstract
Studying the underlying neural mechanisms of cognitive functions of the brain is one of the central questions in modern biology. Moreover, it has significantly impacted the development of novel technologies in artificial intelligence. Spontaneous activity is a unique feature of the brain and is currently lacking in many artificially constructed intelligent machines. Spontaneous activity may represent the brain's idling states, which are internally driven by neuronal networks and possibly participate in offline processing during awake, sleep, and resting states. Evidence is accumulating that the brain's spontaneous activity is not mere noise but part of the mechanisms to process information about previous experiences. A bunch of literature has shown how previous sensory and behavioral experiences influence the subsequent patterns of brain activity with various methods in various animals. It seems, however, that the patterns of neural activity and their computational roles differ significantly from area to area and from function to function. In this article, I review the various forms of the brain's spontaneous activity, especially those observed during memory processing, and some attempts to model the generation mechanisms and computational roles of such activities.
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Affiliation(s)
- Tomoki Fukai
- Okinawa Institute of Science and Technology, Tancha 1919-1, Onna-son, Okinawa 904-0495, Japan.
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Shpurov I, Froese T. Evidence of Critical Dynamics in Movements of Bees inside a Hive. ENTROPY (BASEL, SWITZERLAND) 2022; 24:1840. [PMID: 36554245 PMCID: PMC9777906 DOI: 10.3390/e24121840] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 12/14/2022] [Accepted: 12/15/2022] [Indexed: 06/17/2023]
Abstract
Social insects such as honey bees exhibit complex behavioral patterns, and their distributed behavioral coordination enables decision-making at the colony level. It has, therefore, been proposed that a high-level description of their collective behavior might share commonalities with the dynamics of neural processes in brains. Here, we investigated this proposal by focusing on the possibility that brains are poised at the edge of a critical phase transition and that such a state is enabling increased computational power and adaptability. We applied mathematical tools developed in computational neuroscience to a dataset of bee movement trajectories that were recorded within the hive during the course of many days. We found that certain characteristics of the activity of the bee hive system are consistent with the Ising model when it operates at a critical temperature, and that the system's behavioral dynamics share features with the human brain in the resting state.
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