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de Araújo E Silva M, Fiorin FDS, Santiago RMDM, Rodrigues AC. Brain connectivity analysis in preictal phases of seizure induced by pentylenetetrazol in rats. Brain Res 2024; 1842:149118. [PMID: 38986828 DOI: 10.1016/j.brainres.2024.149118] [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: 02/05/2024] [Revised: 06/28/2024] [Accepted: 07/06/2024] [Indexed: 07/12/2024]
Abstract
Abnormal patterns of brain connectivity characterize epilepsy. However, little is known about these patterns during the stages preceding a seizure induced by pentylenetetrazol (PTZ). To investigate brain connectivity in male Wistar rats during the preictal phase of PTZ-induced seizures (60 mg/kg), we recorded local field potentials in the primary motor (M1) cortex, the ventral anterior (VA) nucleus of the thalamus, the hippocampal CA1 area, and the dentate gyrus (DG) during the baseline period and after PTZ administration. While there were no changes in power density between the baseline and preictal periods, we observed an increase in directional functional connectivity in theta from the hippocampal formation to M1 and VA, as well as in middle gamma from DG to CA1 and from CA1 to M1, and also in slow gamma from M1 to CA1. These findings are supported by increased phase coherence between DG-M1 in theta and CA1-M1 in middle gamma, as well as enhanced phase-amplitude coupling of delta-middle gamma in M1 and delta-fast gamma in CA1. Interestingly, we also noted a slight decrease in phase synchrony between CA1 and VA in slow gamma. Together, these results demonstrate increased functional connectivity between brain regions during the PTZ-induced preictal period, with this increase being particularly driven by the hippocampal formation.
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Affiliation(s)
- Mariane de Araújo E Silva
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil
| | - Fernando da Silva Fiorin
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil.
| | - Rodrigo Marques de Melo Santiago
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil
| | - Abner Cardoso Rodrigues
- Graduate Program in Neuroengineering, Edmond and Lily Safra International Institute of Neuroscience, Santos Dumont Institute, Brazil
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2
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Gao Z, Xiao Y, Zhu F, Tao B, Zhao Q, Yu W, Sweeney JA, Gong Q, Lui S. Multilayer network analysis reveals instability of brain dynamics in untreated first-episode schizophrenia. Cereb Cortex 2024; 34:bhae402. [PMID: 39375878 DOI: 10.1093/cercor/bhae402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2024] [Revised: 09/10/2024] [Accepted: 09/18/2024] [Indexed: 10/09/2024] Open
Abstract
Although aberrant static functional brain network activity has been reported in schizophrenia, little is known about how the dynamics of neural function are altered in first-episode schizophrenia and are modulated by antipsychotic treatment. The baseline resting-state functional magnetic resonance imaging data were acquired from 122 first-episode drug-naïve schizophrenia patients and 128 healthy controls (HCs), and 44 patients were rescanned after 1-year of antipsychotic treatment. Multilayer network analysis was applied to calculate the network switching rates between brain states. Compared to HCs, schizophrenia patients at baseline showed significantly increased network switching rates. This effect was observed mainly in the sensorimotor (SMN) and dorsal attention networks (DAN), and in temporal and parietal regions at the nodal level. Switching rates were reduced after 1-year of antipsychotic treatment at the global level and in DAN. Switching rates at baseline at the global level and in the inferior parietal lobule were correlated with the treatment-related reduction of negative symptoms. These findings suggest that instability of functional network activity plays an important role in the pathophysiology of acute psychosis in early-stage schizophrenia. The normalization of network stability after antipsychotic medication suggests that this effect may represent a systems-level mechanism for their therapeutic efficacy.
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Affiliation(s)
- Ziyang Gao
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - Yuan Xiao
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - Fei Zhu
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - Bo Tao
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - Qiannan Zhao
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - Wei Yu
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati College of Medicine, 260 Stetson Street, Cincinnati, OH 45219, United States
| | - Qiyong Gong
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
| | - Su Lui
- Department of Radiology, and Functional and Molecular Imaging key Laboratory of Sichuan Province, West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Huaxi MR Research Center (HMRRC), West China Hospital of Sichuan University, Guoxuexiang 37#, Wuhou, Chengdu 610041, China
- Research Unit of Psychoradiology, Chinese Academy of Medical Sciences, Chengdu 610041, Guoxuexiang 37#, Wuhou, China
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Iglesias-Parro S, Soriano MF, Ibáñez-Molina AJ, Pérez-Matres AV, Ruiz de Miras J. Examining Neural Connectivity in Schizophrenia Using Task-Based EEG: A Graph Theory Approach. SENSORS (BASEL, SWITZERLAND) 2023; 23:8722. [PMID: 37960422 PMCID: PMC10647645 DOI: 10.3390/s23218722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Revised: 10/19/2023] [Accepted: 10/23/2023] [Indexed: 11/15/2023]
Abstract
Schizophrenia (SZ) is a complex disorder characterized by a range of symptoms and behaviors that have significant consequences for individuals, families, and society in general. Electroencephalography (EEG) is a valuable tool for understanding the neural dynamics and functional abnormalities associated with schizophrenia. Research studies utilizing EEG have identified specific patterns of brain activity in individuals diagnosed with schizophrenia that may reflect disturbances in neural synchronization and information processing in cortical circuits. Considering the temporal dynamics of functional connectivity provides a more comprehensive understanding of brain networks' organization and how they change during different cognitive states. This temporal perspective would enhance our understanding of the underlying mechanisms of schizophrenia. In the present study, we will use measures based on graph theory to obtain dynamic and static indicators in order to evaluate differences in the functional connectivity of individuals diagnosed with SZ and healthy controls using an ecologically valid task. At the static level, patients showed alterations in their ability to segregate information, particularly in the default mode network (DMN). As for dynamic measures, patients showed reduced values in most metrics (segregation, integration, centrality, and resilience), reflecting a reduced number of dynamic states of brain networks. Our results show the utility of combining static and dynamic indicators of functional connectivity from EEG sensors.
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Affiliation(s)
| | - María F. Soriano
- Mental Health Unit, San Agustín Hospital de Linares, 23700 Linares, Spain
| | | | - Ana V. Pérez-Matres
- Department of Software Engineering, University of Granada, 18071 Granada, Spain
| | - Juan Ruiz de Miras
- Department of Software Engineering, University of Granada, 18071 Granada, Spain
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Li Y, Ran Y, Chen Q. Abnormal static and dynamic functional network connectivity of the whole-brain in children with generalized tonic-clonic seizures. Front Neurosci 2023; 17:1236696. [PMID: 37670842 PMCID: PMC10475552 DOI: 10.3389/fnins.2023.1236696] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 08/07/2023] [Indexed: 09/07/2023] Open
Abstract
Introduction Generalized tonic-clonic seizures (GTCS) are a subtype of generalized seizures exhibiting bursts of bilaterally synchronous generalized spike-wave discharges. Numerous neuroimaging studies have reported aberrant functional activity and topological organization of brain network in epilepsy patients with GTCS, but most studies have focused on adults. However, the effect of GTCS on the spatial and temporal properties of brain function in children remains unclear. The present study aimed to explore whole-brain static (sFC) and dynamic functional connectivity (dFC) in children with GTCS. Methods Twenty-three children with GTCS and 32 matched healthy controls (HCs) were recruited for the present study. Resting-state functional magnetic resonance imaging (MRI) data were collected for each subject. The group independent component analysis method was used to obtain independent components (ICs). Then, sFC and dFC methods were applied and the differences in functional connectivity (FC) were compared between the children with GTCS and the HCs. Additionally, we investigated the correlations between the dFC indicators and epilepsy duration. Results Compared to HCs, GTCS patients exhibited a significant decrease in sFC strengths among most networks. The K-means clustering method was implemented for dFC analysis, and the optimal number of clusters was estimated: two discrete connectivity configurations, State 1 (strong connection) and State 2 (weak connection). The decreased dFC mainly occurred in State 1, especially the dFC between the visual network (VIS) and somatomotor network (SMN); but the increased dFC mainly occurred in State 2 among most networks in GTCS children. In addition, GTCS children showed significantly shorter mean dwell time and lower fractional windows in stronger connected State 1, while GTCS children showed significantly longer mean dwell time in weaker connected State 2. In addition, the dFC properties, including mean dwell time and fractional windows, were significantly correlated with epilepsy duration. Conclusion Our results indicated that GTCS epilepsy not only alters the connectivity strength but also changes the temporal properties of connectivity in networks in the whole brain. These findings also emphasized the differences in sFC and dFC in children with GTCS. Combining sFC and dFC methods may provide more comprehensive understanding of the abnormal changes in brain architecture in children with GTCS.
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Affiliation(s)
- Yongxin Li
- Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
| | - Yun Ran
- Formula-Pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children’s Hospital, Shenzhen, China
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Das SK, Sao AK, Biswal BB. Estimation of neuronal task information in fMRI using zero frequency resonator. Neuroimage 2023; 267:119865. [PMID: 36610681 PMCID: PMC10635735 DOI: 10.1016/j.neuroimage.2023.119865] [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: 04/19/2022] [Revised: 12/14/2022] [Accepted: 01/03/2023] [Indexed: 01/06/2023] Open
Abstract
In functional magnetic resonance imaging (fMRI), temporal onsets of BOLD events contain crucial information on activity-inducing signals and make a significant impact in the analysis of functional connectivity (FC). In literature, the estimation of the onsets of the BOLD events from the acquired blood oxygen level-dependent (BOLD) signal using fMRI is mostly performed by choosing locations with a high value of the BOLD signal. This approach may give false onset points because it can incorporate redundant onsets which could be due to non-neuronal activity or can exclude true low-valued BOLD signals. In this study, we present a novel approach to estimating the temporal onsets of the BOLD events using a zero frequency resonator (ZFR) without necessitating information regarding the experimental paradigm (EP). The proposed approach exploits the impulse-like characteristic of activity-inducing signal to estimate the temporal onset points of BOLD events using ZFR which has been widely studied in the area of speech signal processing to estimate the glottal closure instances. The idea behind the approach is that an ideal neuronal impulse has, in principle, equal energy at all frequencies, including around the zero frequency, and will preserve the information of the temporal onsets of the BOLD events at its output. The ZFR-based approach estimates two important features, namely: 1) task-induced temporal onsets of the BOLD events in the fMRI time course and 2) high SNR (HSNR) regions around the estimated BOLD events. Both the estimated features are used to obtain the FC. Results are demonstrated using both the synthetic and experimental (event-related finger tapping and block design working memory) data. We show that a small number of plausible time points, estimated by ZFR, can convey sufficient information indicating the associated activation pattern. The method also illustrates its significance over the conventional correlation and threshold-based conditional rate analysis to estimate FC. The study demonstrates that ZFR-estimated BOLD events and HSNR regions can produce sufficient functionality of the brain in the task paradigm.
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Affiliation(s)
- Sukesh Kumar Das
- Indian Institute of Technology Mandi, Mandi, HP 175005, Himachal Pradesh, India.
| | - Anil K Sao
- Indian Institute of Technology Bhilai, Bhilai, Chhattisgarh 492015, Chhattisgarh, India.
| | - Bharat B Biswal
- New Jersey Institute of Technology, Newark, NJ 07102, New Jersey, USA.
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Penalba-Sánchez L, Oliveira-Silva P, Sumich AL, Cifre I. Increased functional connectivity patterns in mild Alzheimer's disease: A rsfMRI study. Front Aging Neurosci 2023; 14:1037347. [PMID: 36698861 PMCID: PMC9869068 DOI: 10.3389/fnagi.2022.1037347] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Accepted: 12/08/2022] [Indexed: 01/12/2023] Open
Abstract
Background Alzheimer's disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer's disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques. Methods In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer's disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer's disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson's correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed. Results Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition. Conclusion The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings.
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Affiliation(s)
- Lucía Penalba-Sánchez
- Facultat de Psicologia, Ciències de l’educació i de l’Esport, Blanquerna, Universitat Ramon Llull, Barcelona, Spain,Human Neurobehavioral Laboratory (HNL), Research Centre for Human Development (CEDH), Faculdade de Educação e Psicologia, Universidade Católica Portuguesa, Porto, Portugal,NTU Psychology, School of Social Sciences, Nottingham Trent University, Nottingham, United Kingdom,*Correspondence: Lucía Penalba-Sánchez,
| | - Patrícia Oliveira-Silva
- Human Neurobehavioral Laboratory (HNL), Research Centre for Human Development (CEDH), Faculdade de Educação e Psicologia, Universidade Católica Portuguesa, Porto, Portugal
| | - Alexander Luke Sumich
- NTU Psychology, School of Social Sciences, Nottingham Trent University, Nottingham, United Kingdom
| | - Ignacio Cifre
- Facultat de Psicologia, Ciències de l’educació i de l’Esport, Blanquerna, Universitat Ramon Llull, Barcelona, Spain
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Simos NJ, Manolitsi K, Luppi AI, Kagialis A, Antonakakis M, Zervakis M, Antypa D, Kavroulakis E, Maris TG, Vakis A, Stamatakis EA, Papadaki E. Chronic Mild Traumatic Brain Injury: Aberrant Static and Dynamic Connectomic Features Identified Through Machine Learning Model Fusion. Neuroinformatics 2022; 21:427-442. [PMID: 36456762 PMCID: PMC10085953 DOI: 10.1007/s12021-022-09615-1] [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: 08/28/2022] [Revised: 10/25/2022] [Accepted: 11/13/2022] [Indexed: 12/04/2022]
Abstract
AbstractTraumatic Brain Injury (TBI) is a frequently occurring condition and approximately 90% of TBI cases are classified as mild (mTBI). However, conventional MRI has limited diagnostic and prognostic value, thus warranting the utilization of additional imaging modalities and analysis procedures. The functional connectomic approach using resting-state functional MRI (rs-fMRI) has shown great potential and promising diagnostic capabilities across multiple clinical scenarios, including mTBI. Additionally, there is increasing recognition of a fundamental role of brain dynamics in healthy and pathological cognition. Here, we undertake an in-depth investigation of mTBI-related connectomic disturbances and their emotional and cognitive correlates. We leveraged machine learning and graph theory to combine static and dynamic functional connectivity (FC) with regional entropy values, achieving classification accuracy up to 75% (77, 74 and 76% precision, sensitivity and specificity, respectively). As compared to healthy controls, the mTBI group displayed hypoconnectivity in the temporal poles, which correlated positively with semantic (r = 0.43, p < 0.008) and phonemic verbal fluency (r = 0.46, p < 0.004), while hypoconnectivity in the right dorsal posterior cingulate correlated positively with depression symptom severity (r = 0.54, p < 0.0006). These results highlight the importance of residual FC in these regions for preserved cognitive and emotional function in mTBI. Conversely, hyperconnectivity was observed in the right precentral and supramarginal gyri, which correlated negatively with semantic verbal fluency (r=-0.47, p < 0.003), indicating a potential ineffective compensatory mechanism. These novel results are promising toward understanding the pathophysiology of mTBI and explaining some of its most lingering emotional and cognitive symptoms.
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Affiliation(s)
- Nicholas J. Simos
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology–Hellas, 70013 Heraklion, Greece
| | - Katina Manolitsi
- Department of Neurosurgery, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
- Department of Psychiatry, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
| | - Andrea I. Luppi
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Rd, CB2 0SP Cambridge, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Rd, CB2 0SP Cambridge, UK
| | - Antonios Kagialis
- Department of Psychiatry, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
| | - Marios Antonakakis
- Digital Image and Signal Processing Laboratory, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece
| | - Michalis Zervakis
- Digital Image and Signal Processing Laboratory, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece
| | - Despina Antypa
- Department of Psychiatry, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
| | - Eleftherios Kavroulakis
- Department of Radiology, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
| | - Thomas G. Maris
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology–Hellas, 70013 Heraklion, Greece
- Department of Radiology, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
| | - Antonios Vakis
- Department of Neurosurgery, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
| | - Emmanuel A. Stamatakis
- Division of Anaesthesia, School of Clinical Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Rd, CB2 0SP Cambridge, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Rd, CB2 0SP Cambridge, UK
| | - Efrosini Papadaki
- Computational Bio-Medicine Laboratory, Institute of Computer Science, Foundation for Research and Technology–Hellas, 70013 Heraklion, Greece
- Department of Radiology, School of Medicine & University Hospital of Heraklion, University of Crete, Crete, Greece
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Zhang Y, Li C, Chen D, Tian R, Yan X, Zhou Y, Song Y, Yang Y, Wang X, Zhou B, Gao Y, Jiang Y, Zhang X. Repeated High-Definition Transcranial Direct Current Stimulation Modulated Temporal Variability of Brain Regions in Core Neurocognitive Networks Over the Left Dorsolateral Prefrontal Cortex in Mild Cognitive Impairment Patients. J Alzheimers Dis 2022; 90:655-666. [DOI: 10.3233/jad-220539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Background: Early intervention of amnestic mild cognitive impairment (aMCI) may be the most promising way for delaying or even preventing the progression to Alzheimer’s disease. Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique that has been recognized as a promising approach for the treatment of aMCI. Objective: In this paper, we aimed to investigate the modulating mechanism of tDCS on the core neurocognitive networks of brain. Methods: We used repeated anodal high-definition transcranial direct current stimulation (HD-tDCS) over the left dorsolateral prefrontal cortex and assessed the effect on cognition and dynamic functional brain network in aMCI patients. We used a novel method called temporal variability to depict the characteristics of the dynamic brain functional networks. Results: We found that true anodal stimulation significantly improved cognitive performance as measured by the Montreal Cognitive Assessment after simulation. Meanwhile, the Mini-Mental State Examination scores showed a clear upward trend. More importantly, we found significantly altered temporal variability of dynamic functional connectivity of regions belonging to the default mode network, central executive network, and the salience network after true anodal stimulation, indicating anodal HD-tDCS may enhance brain function by modulating the temporal variability of the brain regions. Conclusion: These results imply that ten days of anodal repeated HD-tDCS over the LDLPFC exerts beneficial effects on the temporal variability of the functional architecture of the brain, which may be a potential neural mechanism by which HD-tDCS enhances brain functions. Repeated HD-tDCS may have clinical uses for the intervention of brain function decline in aMCI patients.
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Affiliation(s)
- Yanchun Zhang
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China
- Department of Rehabilitation, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Chenxi Li
- Department of the Psychology of Military Medicine, Air Force Medical University, Xi’an, Shaanxi, P.R. China
| | - Deqiang Chen
- Department of CT, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Rui Tian
- Department of Rehabilitation, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Xinyue Yan
- Department of Rehabilitation, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Yingwen Zhou
- Department of MR, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Yancheng Song
- Department of MR, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Yanlong Yang
- Department of MR, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Xiaoxuan Wang
- Department of MR, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Bo Zhou
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China
| | - Yuhong Gao
- Institute of Geriatrics, Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yujuan Jiang
- Department of Rehabilitation, Cangzhou Central Hospital, Cangzhoug, Hebei Province, China
| | - Xi Zhang
- Department of Neurology, Second Medical Center, National Clinical Research Center for Geriatric Disease, Chinese PLA General Hospital, Beijing, China
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9
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Li Y, Wang J, Wang X, Chen Q, Qin B, Chen J. Reconfiguration of static and dynamic thalamo-cortical network functional connectivity of epileptic children with generalized tonic-clonic seizures. Front Neurosci 2022; 16:953356. [PMID: 35937891 PMCID: PMC9353948 DOI: 10.3389/fnins.2022.953356] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 06/24/2022] [Indexed: 12/05/2022] Open
Abstract
Objective A number of studies in adults and children with generalized tonic-clonic seizure (GTCS) have reported the alterations in morphometry, functional activity, and functional connectivity (FC) in the thalamus. However, the neural mechanisms underlying the alterations in the thalamus of patients with GTCS are not well understood, particularly in children. The aim of the current study was to explore the temporal properties of functional pathways connecting thalamus in children with GTCS. Methods Here, we recruited 24 children with GTCS and 36 age-matched healthy controls. Static and dynamic FC approaches were used to evaluate alterations in the temporal variability of thalamo-cortical networks in children with GTCS. The dynamic effective connectivity (dEC) method was also used to evaluate the directions of the fluctuations in effective connectivity. In addition, the relationships between the dynamic properties and clinical features were assessed. Results The static FC analysis presented significantly decreased connectivity patterns between the bilateral thalamus and between the thalamus and right inferior temporal gyrus. The dynamic connectivity analysis found decreased FC variability in the thalamo-cortical network of children with epilepsy. Dynamic EC analyses identified increased connectivity variability from the frontal gyrus to the bilateral thalamus, and decreased connectivity variability from the right thalamus to the left thalamus and from the right thalamus to the right superior parietal lobe. In addition, correlation analysis revealed that both static FC and connectivity temporal variability in the thalamo-cortical network related to the clinical features (epilepsy duration and epilepsy onset time). Significance Our findings of both increased and decreased connectivity variability in the thalamo-cortical network imply a dynamic restructuring of the functional pathways connecting the thalamus in children with GTCS. These alterations in static and temporal dynamic pathways connecting the bilateral thalamus may extend our understanding of the neural mechanisms underlying the GTCS in children.
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Affiliation(s)
- Yongxin Li
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
- *Correspondence: Yongxin Li,
| | - Jianping Wang
- The Second Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiao Wang
- Epilepsy Center and Department of Neurosurgery, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children’s Hospital, Shenzhen, China
| | - Bing Qin
- Epilepsy Center and Department of Neurosurgery, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Jiaxu Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China
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10
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Li Y, Qin B, Chen Q, Chen J. Altered dynamic functional network connectivity within default mode network of epileptic children with generalized tonic-clonic seizures. Epilepsy Res 2022; 184:106969. [PMID: 35738202 DOI: 10.1016/j.eplepsyres.2022.106969] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 05/13/2022] [Accepted: 06/14/2022] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Generalized tonic-clonic seizures (GTCS) is a group of epileptic disorders characterized by widespread generalized spike-and-waves discharges along with unresponsiveness and convulsions. Abnormal connectivity in the DMN is the common findings in children with generalized epilepsy. However, the neural mechanisms underlying the altered brain connectivity of DMN in children with GTCS remain unclear. The aim of the current study was to explore the temporal properties of functional connectivity states by dynamic functional connectivity (dFC) within the DMN of GTCS children. METHODS We collected resting-state functional MRI data from 22 GTCS children and 29 age-matched healthy controls. Sliding window approach and k-mean clustering analysis were applied to analyze the dFC and identify transient states of the DMN. Furthermore, the relationship between the dynamic properties and clinical features was assessed. RESULTS The dFC analyses identified two reoccurring states: a more frequent and weak connected state (State 1) and a less frequent and strong connected state (State 2). Relative to the normal control, GTCS children spent more time in State 1 showing weak connections and spent less time in State 2 showing strong connections. Dynamic functional network connectivity strength within the DMN showed both increase and decrease in patient group. In addition, the changes of dynamic metric were found to be correlated with epilepsy duration. SIGNIFICANT Our findings imply abnormal interactions and the state dynamics in DMN of the children with GTCS. These disruptions of temporal dynamic in DMN may provide significance for understanding the neural mechanism underlying the GTCS in children and suggest that dFC method can be considered as a valuable tool in children with epilepsy.
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Affiliation(s)
- Yongxin Li
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
| | - Bing Qin
- Epilepsy Center and Department of Neurosurgery, The First Affiliated Hospital, Jinan University, Guangzhou, China
| | - Qian Chen
- Department of Pediatric Neurosurgery, Shenzhen Children's Hospital, Shenzhen, China
| | - Jiaxu Chen
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, Formula-pattern Research Center, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
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11
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Chen Z, Feng T. Neural connectome features of procrastination: Current progress and future direction. Brain Cogn 2022; 161:105882. [PMID: 35679698 DOI: 10.1016/j.bandc.2022.105882] [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: 03/26/2022] [Revised: 05/23/2022] [Accepted: 05/26/2022] [Indexed: 11/02/2022]
Abstract
Procrastination refers to an irrationally delay for intended courses of action despite of anticipating a negative consequence due to this delay. Previous studies tried to reveal the neural substrates of procrastination in terms of connectome-based biomarkers. Based on this, we proposed a unified triple brain network model for procrastination and pinpointed out what challenges we are facing in understanding neural mechanism of procrastination. Specifically, based on neuroanatomical features, the unified triple brain network model proposed that connectome-based underpinning of procrastination could be ascribed to the abnormalities of self-control network (i.e., dorsolateral prefrontal cortex, DLPFC), emotion-regulation network (i.e., orbital frontal cortex, OFC), and episodic prospection network (i.e., para-hippocampus cortex, PHC). Moreover, based on the brain functional features, procrastination had been attributed to disruptive neural circuits on FPN (frontoparietal network)-SCN (subcortical network) and FPN-SAN (salience network), which led us to hypothesize the crucial roles of interplay between these networks on procrastination in unified triple brain network model. Despite of these findings, poor interpretability and computational model limited further understanding for procrastination from theoretical and neural perspectives. On balance, the current study provided an overview to show current progress on the connectome-based biomarkers for procrastination, and proposed the integrative neurocognitive model of procrastination.
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Affiliation(s)
- Zhiyi Chen
- Faculty of Psychology, Southwest University, Chongqing, China; Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, China
| | - Tingyong Feng
- Faculty of Psychology, Southwest University, Chongqing, China; Key Laboratory of Cognition and Personality, Ministry of Education, Southwest University, Chongqing, China.
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12
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Xu L, Feng J, Yu L. Avalanche criticality in individuals, fluid intelligence, and working memory. Hum Brain Mapp 2022; 43:2534-2553. [PMID: 35146831 PMCID: PMC9057106 DOI: 10.1002/hbm.25802] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 01/23/2022] [Indexed: 02/06/2023] Open
Abstract
The critical brain hypothesis suggests that efficient neural computation can be achieved through critical brain dynamics. However, the relationship between human cognitive performance and scale‐free brain dynamics remains unclear. In this study, we investigated the whole‐brain avalanche activity and its individual variability in the human resting‐state functional magnetic resonance imaging (fMRI) data. We showed that though the group‐level analysis was inaccurate because of individual variability, the subject wise scale‐free avalanche activity was significantly associated with maximal synchronization entropy of their brain activity. Meanwhile, the complexity of functional connectivity, as well as structure–function coupling, is maximized in subjects with maximal synchronization entropy. We also observed order–disorder phase transitions in resting‐state brain dynamics and found that there were longer times spent in the subcritical regime. These results imply that large‐scale brain dynamics favor the slightly subcritical regime of phase transition. Finally, we showed evidence that the neural dynamics of human participants with higher fluid intelligence and working memory scores are closer to criticality. We identified brain regions whose critical dynamics showed significant positive correlations with fluid intelligence performance and found that these regions were located in the prefrontal cortex and inferior parietal cortex, which were believed to be important nodes of brain networks underlying human intelligence. Our results reveal the possible role that avalanche criticality plays in cognitive performance and provide a simple method to identify the critical point and map cortical states on a spectrum of neural dynamics, ranging from subcriticality to supercriticality.
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Affiliation(s)
- Longzhou Xu
- School of Physical Science and Technology, Lanzhou University, Lanzhou, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK.,School of Mathematical Sciences, School of Life Science and the Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China
| | - Lianchun Yu
- School of Physical Science and Technology, Lanzhou University, Lanzhou, China.,Lanzhou Center for Theoretical Physics, Key Laboratory of Theoretical Physics of Gansu Province, Lanzhou University, Lanzhou, China.,The School of Nationalities' Educators, Qinghai Normal University, Xining, China
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13
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Cifre I, Miller Flores MT, Penalba L, Ochab JK, Chialvo DR. Revisiting Nonlinear Functional Brain Co-activations: Directed, Dynamic, and Delayed. Front Neurosci 2021; 15:700171. [PMID: 34712111 PMCID: PMC8546168 DOI: 10.3389/fnins.2021.700171] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 08/23/2021] [Indexed: 12/12/2022] Open
Abstract
The center stage of neuro-imaging is currently occupied by studies of functional correlations between brain regions. These correlations define the brain functional networks, which are the most frequently used framework to represent and interpret a variety of experimental findings. In the previous study, we first demonstrated that the relatively stronger blood oxygenated level dependent (BOLD) activations contain most of the information relevant to understand functional connectivity, and subsequent work confirmed that a large compression of the original signals can be obtained without significant loss of information. In this study, we revisit the correlation properties of these epochs to define a measure of nonlinear dynamic directed functional connectivity (nldFC) across regions of interest. We show that the proposed metric provides at once, without extensive numerical complications, directed information of the functional correlations, as well as a measure of temporal lags across regions, overall offering a different and complementary perspective in the analysis of brain co-activation patterns. In this study, we provide further details for the computations of these measures and for a proof of concept based on replicating existing results from an Autistic Syndrome database, and discuss the main features and advantages of the proposed strategy for the study of brain functional correlations.
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Affiliation(s)
- Ignacio Cifre
- Facultat de Psicologia, Ciències de l'Educació i de l'Esport, Blanquerna, Universitat Ramon Llull, Barcelona, Spain.,Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Buenos Aires, Argentina
| | - Maria T Miller Flores
- Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Buenos Aires, Argentina
| | - Lucia Penalba
- Facultat de Psicologia, Ciències de l'Educació i de l'Esport, Blanquerna, Universitat Ramon Llull, Barcelona, Spain
| | - Jeremi K Ochab
- Institute of Theoretical Physics and Mark Kac Center for Complex Systems Research, Jagiellonian University, Krakow, Poland
| | - Dante R Chialvo
- Center for Complex Systems and Brain Sciences (CEMSC3), Escuela de Ciencia y Tecnología, Universidad Nacional de San Martín, Buenos Aires, Argentina.,Consejo Nacional de Investigaciones Científicas y Tecnológicas (CONICET), Buenos Aires, Argentina
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14
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Othman EA. Editorial for "Progressive Deterioration of Dynamic Functional Network Connectivity in Patients With HBV-Related Cirrhosis". J Magn Reson Imaging 2021; 54:1841-1842. [PMID: 34021675 DOI: 10.1002/jmri.27742] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Accepted: 05/04/2021] [Indexed: 11/09/2022] Open
Affiliation(s)
- Elza Azri Othman
- Department of Medical Imaging, Faculty of Health Sciences, Universiti Sultan Zainal Abidin, Kuala Terengganu, Malaysia
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15
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Rolls ET. Attractor cortical neurodynamics, schizophrenia, and depression. Transl Psychiatry 2021; 11:215. [PMID: 33846293 PMCID: PMC8041760 DOI: 10.1038/s41398-021-01333-7] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2021] [Revised: 03/09/2021] [Accepted: 03/24/2021] [Indexed: 12/17/2022] Open
Abstract
The local recurrent collateral connections between cortical neurons provide a basis for attractor neural networks for memory, attention, decision-making, and thereby for many aspects of human behavior. In schizophrenia, a reduction of the firing rates of cortical neurons, caused for example by reduced NMDA receptor function or reduced spines on neurons, can lead to instability of the high firing rate attractor states that normally implement short-term memory and attention in the prefrontal cortex, contributing to the cognitive symptoms. Reduced NMDA receptor function in the orbitofrontal cortex by reducing firing rates may produce negative symptoms, by reducing reward, motivation, and emotion. Reduced functional connectivity between some brain regions increases the temporal variability of the functional connectivity, contributing to the reduced stability and more loosely associative thoughts. Further, the forward projections have decreased functional connectivity relative to the back projections in schizophrenia, and this may reduce the effects of external bottom-up inputs from the world relative to internal top-down thought processes. Reduced cortical inhibition, caused by a reduction of GABA neurotransmission, can lead to instability of the spontaneous firing states of cortical networks, leading to a noise-induced jump to a high firing rate attractor state even in the absence of external inputs, contributing to the positive symptoms of schizophrenia. In depression, the lateral orbitofrontal cortex non-reward attractor network system is over-connected and has increased sensitivity to non-reward, providing a new approach to understanding depression. This is complemented by under-sensitivity and under-connectedness of the medial orbitofrontal cortex reward system in depression.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, UK.
- Department of Computer Science, University of Warwick, Coventry, UK.
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16
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Rolls ET, Cheng W, Feng J. Brain dynamics: Synchronous peaks, functional connectivity, and its temporal variability. Hum Brain Mapp 2021; 42:2790-2801. [PMID: 33742498 PMCID: PMC8127146 DOI: 10.1002/hbm.25404] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 02/11/2021] [Accepted: 03/01/2021] [Indexed: 12/26/2022] Open
Abstract
We describe advances in the understanding of brain dynamics that are important for understanding the operation of the cerebral cortex in health and disease. Peaks in the resting state fMRI BOLD signal in many different brain areas can become synchronized. In data from 1,017 participants from the Human Connectome Project, we show that early visual and connected areas have the highest probability of synchronized peaks. We show that these cortical areas also have low temporal variability of their functional connectivity. We show that there is an approximately reciprocal relation between the probability that a brain region will be involved in synchronized peaks and the temporal variability of the connectivity of a brain region. We show that a high probability of synchronized peaks and a low temporal variability of the connectivity of cortical areas are related to high mean functional connectivity, and provide an account of how these dynamics with some of the properties of avalanches arise. These discoveries help to advance our understanding of cortical operation in health, and in some mental disorders including schizophrenia.
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Affiliation(s)
- Edmund T Rolls
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK.,Oxford Centre for Computational Neuroscience, Oxford, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.,Department of Computer Science, University of Warwick, Coventry, UK
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