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Taddei M, Cuesta P, Annunziata S, Bulgheroni S, Esposito S, Visani E, Granvillano A, Dotta S, Rossi DS, Panzica F, Franceschetti S, Varotto G, Riva D. Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study. Neurol Sci 2024:10.1007/s10072-024-07528-2. [PMID: 38639894 DOI: 10.1007/s10072-024-07528-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 04/09/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features. METHODS The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years. RESULTS A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects. CONCLUSIONS The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.
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Affiliation(s)
- Matilde Taddei
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Pablo Cuesta
- Department of Radiology, Rehabilitation, and Physiotherapy, Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
| | - Silvia Annunziata
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
- Fondazione Don Carlo Gnocchi Onlus-IRCCS S. Maria Nascente, Via Capecelatro 66, 20148, Milan, Italy
| | - Sara Bulgheroni
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Silvia Esposito
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Elisa Visani
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Alice Granvillano
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Sara Dotta
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Davide Sebastiano Rossi
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Ferruccio Panzica
- Clinical Engineering Service, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Silvana Franceschetti
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Giulia Varotto
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy.
- Epilepsy Unit, Bioengineering Group, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, University Politécnica de Madrid, Madrid, Spain.
| | - Daria Riva
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
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Bodensohn L, Maurer A, Daamen M, Upadhyay N, Werkhausen J, Lohaus M, Manunzio U, Manunzio C, Radbruch A, Attenberger U, Boecker H. Inverted U-shape-like functional connectivity alterations in cognitive resting-state networks depending on exercise intensity: An fMRI study. Brain Cogn 2024; 177:106156. [PMID: 38613926 DOI: 10.1016/j.bandc.2024.106156] [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: 10/30/2023] [Revised: 03/04/2024] [Accepted: 04/01/2024] [Indexed: 04/15/2024]
Abstract
Acute physical activity influences cognitive performance. However, the relationship between exercise intensity, neural network activity, and cognitive performance remains poorly understood. This study examined the effects of different exercise intensities on resting-state functional connectivity (rsFC) and cognitive performance. Twenty male athletes (27.3 ± 3.6 years) underwent cycling exercises of different intensities (high, low, rest/control) on different days in randomized order. Before and after, subjects performed resting-state functional magnetic resonance imaging and a behavioral Attention Network Test (ANT). Independent component analysis and Linear mixed effects models examined rsFC changes within ten resting-state networks. No significant changes were identified in ANT performance. Resting-state analyses revealed a significant interaction in the Left Frontoparietal Network, driven by a non-significant rsFC increase after low-intensity and a significant rsFC decrease after high-intensity exercise, suggestive of an inverted U-shape relationship between exercise intensity and rsFC. Similar but trend-level rsFC interactions were observed in the Dorsal Attention Network (DAN) and the Cerebellar Basal Ganglia Network. Explorative correlation analysis revealed a significant positive association between rsFC increases in the right superior parietal lobule (part of DAN) and better ANT orienting in the low-intensity condition. Results indicate exercise intensity-dependent subacute rsFC changes in cognition-related networks, but their cognitive-behavioral relevance needs further investigation.
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Affiliation(s)
- Luisa Bodensohn
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany
| | - Angelika Maurer
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany.
| | - Marcel Daamen
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany; German Center for Neurodegenerative Diseases, Venusberg-Campus 1, Building 99, 53127 Bonn, Germany
| | - Neeraj Upadhyay
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany
| | - Judith Werkhausen
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany
| | - Marvin Lohaus
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany
| | - Ursula Manunzio
- Department of Pediatric Cardiology, University Hospital Bonn, Venusberg-Campus 1, Building 82, 53127 Bonn, Germany
| | - Christian Manunzio
- Department of Pediatric Cardiology, University Hospital Bonn, Venusberg-Campus 1, Building 82, 53127 Bonn, Germany
| | - Alexander Radbruch
- Department of Neuroradiology, University Hospital Bonn, Venusberg-Campus 1, Building 81, 53127 Bonn, Germany
| | - Ulrike Attenberger
- Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 74, 53127 Bonn, Germany
| | - Henning Boecker
- Clinical Functional Imaging Lab, Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, Building 07, 53127 Bonn, Germany
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Cash RFH, Zalesky A. Personalized and Circuit-Based Transcranial Magnetic Stimulation: Evidence, Controversies, and Opportunities. Biol Psychiatry 2024; 95:510-522. [PMID: 38040047 DOI: 10.1016/j.biopsych.2023.11.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 11/13/2023] [Accepted: 11/18/2023] [Indexed: 12/03/2023]
Abstract
The development of neuroimaging methodologies to map brain connectivity has transformed our understanding of psychiatric disorders, the distributed effects of brain stimulation, and how transcranial magnetic stimulation can be best employed to target and ameliorate psychiatric symptoms. In parallel, neuroimaging research has revealed that higher-order brain regions such as the prefrontal cortex, which represent the most common therapeutic brain stimulation targets for psychiatric disorders, show some of the highest levels of interindividual variation in brain connectivity. These findings provide the rationale for personalized target site selection based on person-specific brain network architecture. Recent advances have made it possible to determine reproducible personalized targets with millimeter precision in clinically tractable acquisition times. These advances enable the potential advantages of spatially personalized transcranial magnetic stimulation targeting to be evaluated and translated to basic and clinical applications. In this review, we outline the motivation for target site personalization, preliminary support (mostly in depression), convergent evidence from other brain stimulation modalities, and generalizability beyond depression and the prefrontal cortex. We end by detailing methodological recommendations, controversies, and notable alternatives. Overall, while this research area appears highly promising, the value of personalized targeting remains unclear, and dedicated large prospective randomized clinical trials using validated methodology are critical.
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Affiliation(s)
- Robin F H Cash
- Melbourne Neuropsychiatry Centre and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia.
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria, Australia
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4
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Grecucci A, Monachesi B, Messina I. Reduced GM-WM concentration inside the Default Mode Network in individuals with high emotional intelligence and low anxiety: a data fusion mCCA+jICA approach. Soc Cogn Affect Neurosci 2024; 19:nsae018. [PMID: 38451879 PMCID: PMC10919484 DOI: 10.1093/scan/nsae018] [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: 10/08/2023] [Revised: 01/05/2024] [Accepted: 02/16/2024] [Indexed: 03/09/2024] Open
Abstract
The concept of emotional intelligence (EI) refers to the ability to recognize and regulate emotions to appropriately guide cognition and behaviour. Unfortunately, studies on the neural bases of EI are scant, and no study so far has exhaustively investigated grey matter (GM) and white matter (WM) contributions to it. To fill this gap, we analysed trait measure of EI and structural MRI data from 128 healthy participants to shed new light on where and how EI is encoded in the brain. In addition, we explored the relationship between the neural substrates of trait EI and trait anxiety. A data fusion unsupervised machine learning approach (mCCA + jICA) was used to decompose the brain into covarying GM-WM networks and to assess their association with trait-EI. Results showed that high levels trait-EI are associated with decrease in GM-WM concentration in a network spanning from frontal to parietal and temporal regions, among which insula, cingulate, parahippocampal gyrus, cuneus and precuneus. Interestingly, we also found that the higher the GM-WM concentration in the same network, the higher the trait anxiety. These findings encouragingly highlight the neural substrates of trait EI and their relationship with anxiety. The network is discussed considering its overlaps with the Default Mode Network.
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Affiliation(s)
- Alessandro Grecucci
- Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Rovereto (TN), Italy 38068, Italy
- Centre for Medical Sciences, CISMed, University of Trento, Trento, Italy 38122, Italy
| | - Bianca Monachesi
- Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Rovereto (TN), Italy 38068, Italy
| | - Irene Messina
- Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Rovereto (TN), Italy 38068, Italy
- Faculty of Social and Communication Sciences, Universitas Mercatorum, Rome, Italy
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Bruno A, Lothmann K, Bludau S, Mohlberg H, Amunts K. New organizational principles and 3D cytoarchitectonic maps of the dorsolateral prefrontal cortex in the human brain. FRONTIERS IN NEUROIMAGING 2024; 3:1339244. [PMID: 38455685 PMCID: PMC10917992 DOI: 10.3389/fnimg.2024.1339244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 01/29/2024] [Indexed: 03/09/2024]
Abstract
Areas of the dorsolateral prefrontal cortex (DLPFC) are part of the frontoparietal control, default mode, salience, and ventral attention networks. The DLPFC is involved in executive functions, like working memory, value encoding, attention, decision-making, and behavioral control. This functional heterogeneity is not reflected in existing neuroanatomical maps. For example, previous cytoarchitectonic studies have divided the DLPFC into two or four areas. Macroanatomical parcellations of this region rely on gyri and sulci, which are not congruent with cytoarchitectonic parcellations. Therefore, this study aimed to provide a microstructural analysis of the human DLPFC and 3D maps of cytoarchitectonic areas to help address the observed functional variability in studies of the DLPFC. We analyzed ten human post-mortem brains in serial cell-body stained brain sections and mapped areal boundaries using a statistical image analysis approach. Five new areas (i.e., SFG2, SFG3, SFG4, MFG4, and MFG5) were identified on the superior and middle frontal gyrus, i.e., regions corresponding to parts of Brodmann areas 9 and 46. Gray level index profiles were used to determine interregional cytoarchitectural differences. The five new areas were reconstructed in 3D, and probability maps were generated in commonly used reference spaces, considering the variability of areas in stereotaxic space. Hierarchical cluster analysis revealed a high degree of similarity within the identified DLPFC areas while neighboring areas (frontal pole, Broca's region, area 8, and motoric areas) were separable. Comparisons with functional imaging studies revealed specific functional profiles of the DLPFC areas. Our results indicate that the new areas do not follow a simple organizational gradient assumption in the DLPFC. Instead, they are more similar to those of the ventrolateral prefrontal cortex (Broca's areas 44, 45) and frontopolar areas (Fp1, Fp2) than to the more posterior areas. Within the DLPFC, the cytoarchitectonic similarities between areas do not seem to follow a simple anterior-to-posterior gradient either, but cluster along other principles. The new maps are part of the publicly available Julich Brain Atlas and provide a microstructural reference for existing and future imaging studies. Thus, our study represents a further step toward deciphering the structural-functional organization of the human prefrontal cortex.
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Affiliation(s)
- Ariane Bruno
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Kimberley Lothmann
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Sebastian Bludau
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Hartmut Mohlberg
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty and University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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Cao Z, Xiao X, Xie C, Wei L, Yang Y, Zhu C. Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility. Front Psychiatry 2024; 15:1341908. [PMID: 38419897 PMCID: PMC10899497 DOI: 10.3389/fpsyt.2024.1341908] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 01/24/2024] [Indexed: 03/02/2024] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person's brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model's stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications.
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Affiliation(s)
- Zhengcao Cao
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- School of Arts and Communication, Beijing Normal University, Beijing, China
| | - Xiang Xiao
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Cong Xie
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Lijiang Wei
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Yihong Yang
- Neuroimaging Research Branch, National Institute on Drug Abuse, National Institutes of Health, Baltimore, MD, United States
| | - Chaozhe Zhu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
- Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, Beijing, China
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Bastuji H, Cadic-Melchior A, Ruelle-Le Glaunec L, Magnin M, Garcia-Larrea L. Functional connectivity between medial pulvinar and cortical networks as a predictor of arousal to noxious stimuli during sleep. Eur J Neurosci 2024; 59:570-583. [PMID: 36889675 DOI: 10.1111/ejn.15958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/21/2023] [Accepted: 03/04/2023] [Indexed: 03/10/2023]
Abstract
The interruption of sleep by a nociceptive stimulus is favoured by an increase in the pre-stimulus functional connectivity between sensory and higher level cortical areas. In addition, stimuli inducing arousal also trigger a widespread electroencephalographic (EEG) response reflecting the coordinated activation of a large cortical network. Because functional connectivity between distant cortical areas is thought to be underpinned by trans-thalamic connections involving associative thalamic nuclei, we investigated the possible involvement of one principal associative thalamic nucleus, the medial pulvinar (PuM), in the sleeper's responsiveness to nociceptive stimuli. Intra-cortical and intra-thalamic signals were analysed in 440 intracranial electroencephalographic (iEEG) segments during nocturnal sleep in eight epileptic patients receiving laser nociceptive stimuli. The spectral coherence between the PuM and 10 cortical regions grouped in networks was computed during 5 s before and 1 s after the nociceptive stimulus and contrasted according to the presence or absence of an arousal EEG response. Pre- and post-stimulus phase coherence between the PuM and all cortical networks was significantly increased in instances of arousal, both during N2 and paradoxical (rapid eye movement [REM]) sleep. Thalamo-cortical enhancement in coherence involved both sensory and higher level cortical networks and predominated in the pre-stimulus period. The association between pre-stimulus widespread increase in thalamo-cortical coherence and subsequent arousal suggests that the probability of sleep interruption by a noxious stimulus increases when it occurs during phases of enhanced trans-thalamic transfer of information between cortical areas.
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Affiliation(s)
- Hélène Bastuji
- Central Integration of Pain (NeuroPain) Lab, Lyon Neuroscience Research Center, INSERM U1028, CNRS, UMR5292, Université Claude Bernard, Bron, France
- Centre du Sommeil, Hospices Civils de Lyon, Bron, France
| | - Andéol Cadic-Melchior
- Central Integration of Pain (NeuroPain) Lab, Lyon Neuroscience Research Center, INSERM U1028, CNRS, UMR5292, Université Claude Bernard, Bron, France
| | - Lucien Ruelle-Le Glaunec
- Central Integration of Pain (NeuroPain) Lab, Lyon Neuroscience Research Center, INSERM U1028, CNRS, UMR5292, Université Claude Bernard, Bron, France
| | - Michel Magnin
- Central Integration of Pain (NeuroPain) Lab, Lyon Neuroscience Research Center, INSERM U1028, CNRS, UMR5292, Université Claude Bernard, Bron, France
| | - Luis Garcia-Larrea
- Central Integration of Pain (NeuroPain) Lab, Lyon Neuroscience Research Center, INSERM U1028, CNRS, UMR5292, Université Claude Bernard, Bron, France
- Centre d'évaluation et de traitement de la douleur, Hôpital Neurologique, Lyon, France
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Chibaatar E, Watanabe K, Quinn PM, Okamoto N, Shinkai T, Natsuyama T, Hayasaki G, Ikenouchi A, Kakeda S, Yoshimura R. Triple network connectivity changes in patients with major depressive disorder versus healthy controls via structural network imaging after electroconvulsive therapy treatment. J Affect Disord 2023; 340:923-929. [PMID: 37598718 DOI: 10.1016/j.jad.2023.08.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 07/06/2023] [Accepted: 08/03/2023] [Indexed: 08/22/2023]
Abstract
OBJECTIVE To investigate the effect of electroconvulsive treatment (ECT) on dynamic structural network connectivity in major depressive disorder (MDD), based on the triple-network model. METHODS Twenty-one first-episode, drug-naïve patients with MDD and 21 age- and sex-matched healthy subjects were recruited. Bilateral electrical stimulation was performed thrice a week for a total of 4-5 weeks in the MDD group. MRI data were obtained, and triple-network structural connectivity was evaluated using source-based morphometry (SBM) analysis. A paired t-test was used to analyze structural connectivity differences between pre- and post-ECT MDD groups, one-way analysis was used to calculate three intrinsic network differences between HCs, pre- and post-ECT groups, and partial least squares structural equation modelling was used to investigate dynamic structural network connectivity (dSNC) across groups. RESULTS Pre-ECT patients with MDD exhibited significantly lower salience network (SN) structural connectivity (p = 0.010) than the healthy control (HC) group and after ECT therapy SN structural connectivity was significantly elevated (p = 0.002) in post-ECT group compared with pre-ECT. PLS-SEM analysis conducted on inter-network connectivity in the triple-network model indicated a significant difference between SN and central executive network (CEN) in all three groups. The HC and post-ECT MDD groups showed notable direct connectivity between the SN and default mode network (DMN), while the pre-ECT MDD group showed consequential pathological connectivity between the CEN and DMN. A mediation analysis revealed a significant indirect effect of the SN on the DMN through the CEN (β = 0.363, p = 0.008) only in the pre-ECT MDD group. CONCLUSIONS ECT may be an effective and minimally invasive treatment for addressing structural changes in the SN and direct communication abnormalities between the three core brain networks in patients with MDD, with possible beneficial correction of indirect connections.
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Affiliation(s)
- Enkmurun Chibaatar
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Keita Watanabe
- Department of Radiology, Kyoto Prefectural University of Medicine, Kyoto, Japan
| | - Patrick M Quinn
- Wakamatsu Hospital, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Naomichi Okamoto
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Takahiro Shinkai
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Tomoya Natsuyama
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Gaku Hayasaki
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Atsuko Ikenouchi
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan
| | - Shingo Kakeda
- Department of Radiology, Graduate School of Medicine, Hirosaki University, Hirosaki, Japan
| | - Reiji Yoshimura
- Department of Psychiatry, University of Occupational and Environmental Health, Kitakyushu, Japan.
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Langerbeck M, Baggio T, Messina I, Bhat S, Grecucci A. Borderline shades: Morphometric features predict borderline personality traits but not histrionic traits. Neuroimage Clin 2023; 40:103530. [PMID: 37879232 PMCID: PMC10618757 DOI: 10.1016/j.nicl.2023.103530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 10/09/2023] [Accepted: 10/12/2023] [Indexed: 10/27/2023]
Abstract
Borderline personality disorder (BPD) is one of the most diagnosed disorders in clinical settings. Besides the fully diagnosed disorder, borderline personality traits (BPT) are quite common in the general population. Prior studies have investigated the neural correlates of BPD but not of BPT. This paper investigates the neural correlates of BPT in a subclinical population using a supervised machine learning method known as Kernel Ridge Regression (KRR) to build predictive models. Additionally, we want to determine whether the same brain areas involved in BPD are also involved in subclinical BPT. Recent attempts to characterize the specific role of resting state-derived macro networks in BPD have highlighted the role of the default mode network. However, it is not known if this extends to the subclinical population. Finally, we wanted to test the hypothesis that the same circuitry that predicts BPT can also predict histrionic personality traits. Histrionic personality is sometimes considered a milder form of BPD, and making a differential diagnosis between the two may be difficult. For the first time KRR was applied to structural images of 135 individuals to predict BPT, based on the whole brain, on a circuit previously found to correctly classify BPD, and on the five macro-networks. At a whole brain level, results show that frontal and parietal regions, as well as the Heschl's area, the thalamus, the cingulum, and the insula, are able to predict borderline traits. BPT predictions increase when considering only the regions limited to the brain circuit derived from a study on BPD, confirming a certain overlap in brain structure between subclinical and clinical samples. Of all the five macro networks, only the DMN successfully predicts BPD, confirming previous observations on its role in the BPD. Histrionic traits could not be predicted by the BPT circuit. The results have implications for the diagnosis of BPD and a dimensional model of personality.
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Affiliation(s)
- Miriam Langerbeck
- Faculty of Psychology and Neuroscience (FPN), Maastricht University, Netherlands
| | - Teresa Baggio
- Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Italy.
| | - Irene Messina
- Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Italy; Universitas Mercatorum, Rome, Italy.
| | - Salil Bhat
- Department of Cognitive Neuroscience, Faculty of Psychology and Cognitive Neuroscience (FPN), Maastricht University, Netherlands.
| | - Alessandro Grecucci
- Department of Psychology and Cognitive Sciences (DiPSCo), University of Trento, Italy; Centre for Medical Sciences (CISMed), University of Trento, Italy.
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10
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Lew BJ, McCusker MC, O'Neill J, Bares SH, Wilson TW, Doucet GE. Resting state network connectivity alterations in HIV: Parallels with aging. Hum Brain Mapp 2023; 44:4679-4691. [PMID: 37417797 PMCID: PMC10400792 DOI: 10.1002/hbm.26409] [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: 09/29/2022] [Revised: 05/10/2023] [Accepted: 06/12/2023] [Indexed: 07/08/2023] Open
Abstract
The increasing incidence of age-related comorbidities in people with HIV (PWH) has led to accelerated aging theories. Functional neuroimaging research, including functional connectivity (FC) using resting-state functional magnetic resonance imaging (rs-fMRI), has identified neural aberrations related to HIV infection. Yet little is known about the relationship between aging and resting-state FC in PWH. This study included 86 virally suppressed PWH and 99 demographically matched controls spanning 22-72 years old who underwent rs-fMRI. The independent and interactive effects of HIV and aging on FC were investigated both within- and between-network using a 7-network atlas. The relationship between HIV-related cognitive deficits and FC was also examined. We also conducted network-based statistical analyses using a brain anatomical atlas (n = 512 regions) to ensure similar results across independent approaches. We found independent effects of age and HIV in between-network FC. The age-related increases in FC were widespread, while PWH displayed further increases above and beyond aging, particularly between-network FC of the default-mode and executive control networks. The results were overall similar using the regional approach. Since both HIV infection and aging are associated with independent increases in between-network FC, HIV infection may be associated with a reorganization of the major brain networks and their functional interactions in a manner similar to aging.
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Affiliation(s)
- Brandon J. Lew
- Institute for Human NeuroscienceBoys Town National Research HospitalOmahaNebraskaUSA
- College of MedicineUniversity of Nebraska Medical Center (UNMC)OmahaNebraskaUSA
| | - Marie C. McCusker
- Institute for Human NeuroscienceBoys Town National Research HospitalOmahaNebraskaUSA
- Interdepartmental Neuroscience ProgramYale University School of MedicineNew HavenConnecticutUSA
| | - Jennifer O'Neill
- Department of Internal Medicine, Division of Infectious DiseasesUNMCOmahaNebraskaUSA
| | - Sara H. Bares
- Department of Internal Medicine, Division of Infectious DiseasesUNMCOmahaNebraskaUSA
| | - Tony W. Wilson
- Institute for Human NeuroscienceBoys Town National Research HospitalOmahaNebraskaUSA
- College of MedicineUniversity of Nebraska Medical Center (UNMC)OmahaNebraskaUSA
- Department of Pharmacology & NeuroscienceCreighton UniversityOmahaNebraskaUSA
| | - Gaelle E. Doucet
- Institute for Human NeuroscienceBoys Town National Research HospitalOmahaNebraskaUSA
- Department of Pharmacology & NeuroscienceCreighton UniversityOmahaNebraskaUSA
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11
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Wu D, Schaper FLWVJ, Jin G, Qi L, Du J, Wang X, Wang Y, Xu C, Wang X, Yu T, Fox MD, Ren L. Human anterior thalamic stimulation evoked cortical potentials align with intrinsic functional connectivity. Neuroimage 2023:120243. [PMID: 37353098 DOI: 10.1016/j.neuroimage.2023.120243] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 06/05/2023] [Accepted: 06/20/2023] [Indexed: 06/25/2023] Open
Abstract
Characterizing human thalamocortical network is fundamental for understanding a vast array of human behaviors since the thalamus plays a central role in cortico-subcortical communication. Over the past few decades, advances in functional magnetic resonance imaging have allowed for spatial mapping of intrinsic resting-state functional connectivity (RSFC) between both cortical regions and in cortico-subcortical networks. Despite these advances, identifying the electrophysiological basis of human thalamocortical network architecture remains challenging. By leveraging stereoelectroencephalography electrodes temporarily implanted into distributed cortical regions and the anterior nucleus of the thalamus (ANT) of 10 patients with refractory focal epilepsy, we tested whether ANT stimulation evoked cortical potentials align with RSFC from the stimulation site, derived from a normative functional connectome (n=1000). Our study identifies spatial convergence of ANT stimulation evoked cortical potentials and normative RSFC. Other than connections to the Papez circuit, the ANT was found to be closely connected to several distinct higher-order association cortices, including the precuneus, angular gyrus, dorsal lateral prefrontal cortex, and anterior insula. Remarkably, we found that the spatial distribution and magnitude of cortical-evoked responses to single-pulse electrical stimulation of the ANT aligned with the spatial pattern and strength of normative RSFC of the stimulation site. The present study provides electrophysiological evidence that stimulation evoked electrical activity flows along intrinsic brain networks connected on a thalamocortical level.
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Affiliation(s)
- Di Wu
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Clinical Research Center of Epilepsy, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; National Center for Neurological Disorders, Beijing 100053, China
| | - Frederic L W V J Schaper
- Center of Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States
| | - Guangyuan Jin
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Clinical Research Center of Epilepsy, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; National Center for Neurological Disorders, Beijing 100053, China
| | - Lei Qi
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Clinical Research Center of Epilepsy, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; National Center for Neurological Disorders, Beijing 100053, China
| | - Jialin Du
- Department of Pharmacy Phase I Clinical Trial Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xiaopeng Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Clinical Research Center of Epilepsy, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; National Center for Neurological Disorders, Beijing 100053, China
| | - Yuke Wang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Cuiping Xu
- National Center for Neurological Disorders, Beijing 100053, China; Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Xueyuan Wang
- National Center for Neurological Disorders, Beijing 100053, China; Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Tao Yu
- National Center for Neurological Disorders, Beijing 100053, China; Institute of Functional Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Michael D Fox
- Center of Brain Circuit Therapeutics, Departments of Neurology, Psychiatry, and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, United States; Berenson-Allen Center for Non-invasive Brain Stimulation, Department of Neurology, Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA 02115, United States; Martinos Center for Biomedical Imaging, Departments of Neurology and Radiology, Harvard Medical School and Massachusetts General Hospital, Boston, MA 02115, United States; Havard Medical School, Boston, MA 02115, USA
| | - Liankun Ren
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Clinical Research Center of Epilepsy, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; National Center for Neurological Disorders, Beijing 100053, China; Chinese Institute for Brain Research, Beijing 102206, China.
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12
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Labache L, Ge T, Yeo BTT, Holmes AJ. Language network lateralization is reflected throughout the macroscale functional organization of cortex. Nat Commun 2023; 14:3405. [PMID: 37296118 PMCID: PMC10256741 DOI: 10.1038/s41467-023-39131-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 05/30/2023] [Indexed: 06/12/2023] Open
Abstract
Hemispheric specialization is a fundamental feature of human brain organization. However, it is not yet clear to what extent the lateralization of specific cognitive processes may be evident throughout the broad functional architecture of cortex. While the majority of people exhibit left-hemispheric language dominance, a substantial minority of the population shows reverse lateralization. Using twin and family data from the Human Connectome Project, we provide evidence that atypical language dominance is associated with global shifts in cortical organization. Individuals with atypical language organization exhibit corresponding hemispheric differences in the macroscale functional gradients that situate discrete large-scale networks along a continuous spectrum, extending from unimodal through association territories. Analyses reveal that both language lateralization and gradient asymmetries are, in part, driven by genetic factors. These findings pave the way for a deeper understanding of the origins and relationships linking population-level variability in hemispheric specialization and global properties of cortical organization.
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Affiliation(s)
- Loïc Labache
- Department of Psychology, Yale University, New Haven, CT, 06520, US.
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, 02114, US
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, 02114, US
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, 02142, US
| | - B T Thomas Yeo
- Department of Electrical and Computer Engineering, Centre for Sleep and Cognition, National University of Singapore, Singapore, SG, 119077, Singapore
- Department of Electrical and Computer Engineering, Centre for Translational Magnetic Resonance Research, National University of Singapore, Singapore, SG, 119077, Singapore
- N.1 Institute for Health, National University of Singapore, Singapore, SG, 119077, Singapore
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, 02129, US
- National University of Singapore Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, SG, 119077, Singapore
| | - Avram J Holmes
- Department of Psychology, Yale University, New Haven, CT, 06520, US.
- Department of Psychiatry, Yale University, New Haven, CT, 06520, US.
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, US.
- Department of Psychiatry, Brain Health Institute, Rutgers University, Piscataway, NJ, 08854, US.
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13
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Kruse JA, Martin CS, Hamlin N, Slattery E, Moriarty EM, Horne LK, Ozkalp-Poincloux B, Camarda A, White SF, Oleson J, Cassotti M, Doucet GE. Changes of creative ability and underlying brain network connectivity throughout the lifespan. Brain Cogn 2023; 168:105975. [PMID: 37031635 PMCID: PMC10175225 DOI: 10.1016/j.bandc.2023.105975] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/30/2023] [Accepted: 03/31/2023] [Indexed: 04/11/2023]
Abstract
Creativity, or divergent thinking, is essential to and supported by cognitive functions necessary for everyday tasks. The current study investigates divergent thinking and its neural mechanisms from adolescence to late adulthood. To do this, 180 healthy participants completed a creativity task called the egg task including 86 adolescents (mean age (SD) = 13.62 (1.98)), 52 young adults (24.92 (3.60), and 42 older adults (62.84 (7.02)). Additionally, a subsample of 111 participants completed a resting-state fMRI scan. After investigating the impact of age on different divergent thinking metrics, we investigated the impact of age on the association between divergent thinking and resting-state functional connectivity within and between major resting-state brain networks associated with creative thinking: the DMN, ECN, and SN. Adolescents tended to be less creative than both young and older adults in divergent thinking scores related to expansion creativity, and not in persistent creativity, while young and older adults performed relatively similar. We found that adolescents' functional integrity of the executive control network (ECN) was positively associated with expansion creativity, which was significantly different from the negative association in both the young and older adults. These results suggest that creative performance and supporting brain networks change throughout the lifespan.
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Affiliation(s)
- Jordanna A Kruse
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Casey S Martin
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Noah Hamlin
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Emma Slattery
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Eibhlis M Moriarty
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | - Lucy K Horne
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA
| | | | - Anaelle Camarda
- Institut Supérieur Maria Montessori, France; Université Paris Cité and Université Gustave Eiffel, LaPEA, Boulogne-Billancourt, France
| | - Stuart F White
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA; Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, NE, USA
| | | | | | - Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, NE, USA; Department of Pharmacology and Neuroscience, Creighton University School of Medicine, Omaha, NE, USA.
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14
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Rakesh G, Logue MW, Clarke-Rubright E, Haswell CC, Thompson PM, De Bellis MD, Morey RA, Sun D. Network Centrality and Modularity of Structural Covariance Networks in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study. Brain Connect 2023; 13:211-225. [PMID: 36511392 PMCID: PMC10325816 DOI: 10.1089/brain.2022.0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Introduction: Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCNs) are represented as graphs with brain regions as nodes and correlations between nodes as edges. Methods: We built SCNs for PTSD and control groups using 148 CT and SA measures that were harmonized for site in n = 3439 subjects from Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA)-Psychiatric Genomics Consortium (PGC) PTSD. We compared centrality between PTSD and controls as well as interactions of diagnostic group with age, sex, and comorbid major depressive disorder (MDD) status. We investigated associations between network modularity and diagnostic grouping. Results: Nodes with higher CT-based centrality in PTSD compared with controls included the left inferior frontal sulcus, left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. Children (<10 years) and adolescents (10-21) with PTSD showed greater centrality in frontotemporal areas compared with young (22-39) and middle-aged adults (40-59) with PTSD, who showed higher centrality in occipital areas. The PTSD diagnostic group interactions with sex and comorbid MDD showed altered centrality in occipital regions, along with greater visual network (VN) modularity in PTSD subjects compared with controls. Conclusion: Structural covariance in PTSD is associated with centrality differences in occipital areas and VN modularity differences in a large well-powered sample. In the context of extensive structural covariance remodeling taking place before and during adolescence, the present findings suggest a process of cortical remodeling that commences with trauma and/or the onset of PTSD but may also predate these events. Impact statement Centrality is a graph theory measure that offers insights into a node's relationship with all other nodes in the brain. Centrality pinpoints the drivers of brain communication within networks and nodes and may be a promising target for treatments such as neuromodulation. Modularity can pinpoint modules that exist within larger networks and quantify the connections between these modules. Centrality and modularity complement functional and structural connectivity measurements within specific brain networks.
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Affiliation(s)
- Gopalkumar Rakesh
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina, USA
| | - Mark W. Logue
- National Center for PTSD, VA Boston Healthcare System, Boston, Massachusetts, USA
- Biomedical Genetics, Boston University, Boston, Massachusetts, USA
| | - Emily Clarke-Rubright
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina, USA
| | - Courtney C. Haswell
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina, USA
| | - Paul M. Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of University of Southern California, Marina del Rey, California, USA
| | - Michael D. De Bellis
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina, USA
| | - Rajendra A. Morey
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina, USA
| | - Delin Sun
- Duke-UNC Brain Imaging and Analysis Center, Duke University, Durham, North Carolina, USA
- Mid-Atlantic Mental Illness Research, Education and Clinical Center, Durham VA Medical Center, Durham, North Carolina, USA
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15
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Son JJ, Schantell M, Picci G, Wang YP, Stephen JM, Calhoun VD, Doucet GE, Taylor BK, Wilson TW. Altered longitudinal trajectory of default mode network connectivity in healthy youth with subclinical depressive and posttraumatic stress symptoms. Dev Cogn Neurosci 2023; 60:101216. [PMID: 36857850 PMCID: PMC9986502 DOI: 10.1016/j.dcn.2023.101216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/08/2023] [Accepted: 02/14/2023] [Indexed: 02/19/2023] Open
Abstract
The default mode network (DMN) plays a crucial role in internal self-processing, rumination, and social functions. Disruptions to DMN connectivity have been linked with early adversity and the emergence of psychopathology in adolescence and early adulthood. Herein, we investigate how subclinical psychiatric symptoms can impact DMN functional connectivity during the pubertal transition. Resting-state fMRI data were collected annually from 190 typically-developing youth (9-15 years-old) at three timepoints and within-network DMN connectivity was computed. We used latent growth curve modeling to determine how self-reported depressive and posttraumatic stress symptoms predicted rates of change in DMN connectivity over the three-year period. In the baseline model without predictors, we found no systematic changes in DMN connectivity over time. However, significant modulation emerged after adding psychopathology predictors; greater depressive symptomatology was associated with significant decreases in connectivity over time, whereas posttraumatic stress symptoms were associated with significant increases in connectivity over time. Follow-up analyses revealed that these effects were driven by connectivity changes involving the dorsal medial prefrontal cortex subnetwork. In conclusion, these data suggest that subclinical depressive and posttraumatic symptoms alter the trajectory of DMN connectivity, which may indicate that this network is a nexus of clinical significance in mental health disorders.
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Affiliation(s)
- Jake J Son
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Mikki Schantell
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA
| | - Giorgia Picci
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA
| | - Yu-Ping Wang
- Department of Biomedical Engineering, Tulane University, New Orleans, LA, USA
| | | | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of technology, and Emory University, Atlanta, GA, USA
| | - Gaelle E Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Brittany K Taylor
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA
| | - Tony W Wilson
- Institute for Human Neuroscience, Boys Town National Research Hospital, Boys Town, NE, USA; Center for Pediatric Brain Health, Boys Town National Research Hospital, Boys Town, NE, USA; College of Medicine, University of Nebraska Medical Center (UNMC), Omaha, NE, USA; Department of Pharmacology & Neuroscience, Creighton University, Omaha, NE, USA.
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16
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Karavallil Achuthan S, Coburn KL, Beckerson ME, Kana RK. Amplitude of low frequency fluctuations during resting state fMRI in autistic children. Autism Res 2023; 16:84-98. [PMID: 36349875 DOI: 10.1002/aur.2846] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 10/25/2022] [Indexed: 11/11/2022]
Abstract
Resting state fMRI (rs-fMRI) provides an excellent platform for examining the amplitude of low frequency fluctuations (ALFF) and fractional amplitude of low frequency fluctuations (fALFF), which are key indices of brain functioning. However, ALFF and fALFF have been used only sporadically to study autism. rs-fMRI data from 69 children (40 autistic, mean age = 8.47 ± 2.20 years; age range: 5.2 to 13.2; and 29 non-autistic, mean age = 9.02 ± 1.97 years; age range 5.9 to 12.9) were obtained from the Autism Brain Imaging Data Exchange (ABIDE II). ALFF and fALFF were measured using CONN connectivity toolbox and SPM12, at whole-brain & network-levels. A two-sampled t-test and a 2 Group (autistic, non-autistic) × 7 Networks ANOVA were conducted to test group differences in ALFF and fALFF. The whole-brain analysis identified significantly reduced ALFF values for autistic participants in left parietal opercular cortex, precuneus, and right insula. At the network level, there was a significant effect of diagnostic group and brain network on ALFF values, and only significant effect of network, not group, on fALFF values. Regression analyses indicated a significant effect of age on ALFF values of certain networks in autistic participants. Such intrinsically different network-level responses in autistic participants may have implications for task-level recruitment and synchronization of brain areas, which may in turn impact optimal cognitive functioning. Moreover, differences in low frequency fluctuations of key networks, such as the DMN and SN, may underlie alterations in brain responses in autism that are frequently reported in the literature.
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Affiliation(s)
- Smitha Karavallil Achuthan
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Kelly L Coburn
- Department of Speech-Language Pathology & Audiology, Towson University, Towson, Maryland, USA
| | - Meagan E Beckerson
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
| | - Rajesh K Kana
- Department of Psychology & The Center for Innovative Research in Autism, University of Alabama, Tuscaloosa, Alabama, USA
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17
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Caria A, Grecucci A. Neuroanatomical predictors of real‐time
fMRI
‐based anterior insula regulation. A supervised machine learning study. Psychophysiology 2022; 60:e14237. [PMID: 36523140 DOI: 10.1111/psyp.14237] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 10/18/2022] [Accepted: 11/30/2022] [Indexed: 12/23/2022]
Abstract
Increasing evidence showed that learned control of metabolic activity in selected brain regions can support emotion regulation. Notably, a number of studies demonstrated that neurofeedback-based regulation of fMRI activity in several emotion-related areas leads to modifications of emotional behavior along with changes of neural activity in local and distributed networks, in both healthy individuals and individuals with emotional disorders. However, the current understanding of the neural mechanisms underlying self-regulation of the emotional brain, as well as their relationship with other emotion regulation strategies, is still limited. In this study, we attempted to delineate neuroanatomical regions mediating real-time fMRI-based emotion regulation by exploring whole brain GM and WM features predictive of self-regulation of anterior insula (AI) activity, a neuromodulation procedure that can successfully support emotional brain regulation in healthy individuals and patients. To this aim, we employed a multivariate kernel ridge regression model to assess brain volumetric features, at regional and network level, predictive of real-time fMRI-based AI regulation. Our results showed that several GM regions including fronto-occipital and medial temporal areas and the basal ganglia as well as WM regions including the fronto-occipital fasciculus, tapetum and fornix significantly predicted learned AI regulation. Remarkably, we observed a substantial contribution of the cerebellum in relation to both the most effective regulation run and average neurofeedback performance. Overall, our findings highlighted specific neurostructural features contributing to individual differences of AI-guided emotion regulation. Notably, such neuroanatomical topography partially overlaps with the neurofunctional network associated with cognitive emotion regulation strategies, suggesting common neural mechanisms.
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Affiliation(s)
- Andrea Caria
- Department of Psychology and Cognitive Science University of Trento Rovereto Italy
| | - Alessandro Grecucci
- Department of Psychology and Cognitive Science University of Trento Rovereto Italy
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18
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Ulrich M, Niemann F, Grön G. Role of the right anterior insula for the emergence of flow-A combined task-based fMRI activation and connectivity study. Front Hum Neurosci 2022; 16:1067968. [PMID: 36569474 PMCID: PMC9772033 DOI: 10.3389/fnhum.2022.1067968] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
The emergence of flow is a situation of high salience because externally oriented attention on the task and access to resources for goal-directed behavior are enhanced, while internally oriented or self-related cognition is decreased. The right anterior insula has been reported as a causal out-flow hub of the salience resting-state network, orchestrating the engagement of the central executive network (CEN) and the disengagement of the default-mode network (DMN) during a functional challenge. In the present study, we employed a combined task-based activation and connectivity analysis to investigate the role of the right anterior insula during the emergence of flow. A sample of 41 healthy male subjects was confronted with a functional challenge that permitted the emergence of flow during BOLD-based functional magnetic resonance imaging. Comparing connectivity changes in the right anterior insula during the flow condition against connectivity changes associated with control conditions of boredom and overload, relatively increased couplings were observed with the left and right dorsolateral prefrontal cortex. Activation data for these regions did, however, not show the flow-typical inverted U-shaped (invU) response pattern. Relatively decreased functional couplings encompassed ventral aspects of the striatum, but neither the amygdala nor the medial prefrontal cortex (MPFC). For the ventral striatum, activation data were consistent with the flow-typical U-shaped activation pattern, which supports the notion that under the high salience of autotelic situations, the anterior insula is much less positively coupled with the ventral striatum than under boundary conditions of boredom and overload. Taken together, present functional connectivity results were in alignment with the assumed role of the right anterior insula under conditions of different salience. However, this particular region does not appear to mediate the most typical flow-associated activation patterns.
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Affiliation(s)
- Martin Ulrich
- Section Neuropsychology and Functional Imaging, Department of Psychiatry, Ulm University, Ulm, Germany,*Correspondence: Martin Ulrich,
| | - Filip Niemann
- Cognition, Aging, and Brain Stimulation Lab, Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Georg Grön
- Section Neuropsychology and Functional Imaging, Department of Psychiatry, Ulm University, Ulm, Germany
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19
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Ferreira LK, Lindberg O, Santillo AF, Wahlund LO. Functional connectivity in behavioral variant frontotemporal dementia. Brain Behav 2022; 12:e2790. [PMID: 36306386 PMCID: PMC9759144 DOI: 10.1002/brb3.2790] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 09/13/2022] [Accepted: 09/24/2022] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Functional connectivity (FC)-which reflects relationships between neural activity in different brain regions-has been used to explore the functional architecture of the brain in neurodegenerative disorders. Although an increasing number of studies have explored FC changes in behavioral variant frontotemporal dementia (bvFTD), there is no focused, in-depth review about FC in bvFTD. METHODS Comprehensive literature search and narrative review to summarize the current field of FC in bvFTD. RESULTS (1) Decreased FC within the salience network (SN) is the most consistent finding in bvFTD; (2) FC changes extend beyond the SN and affect the interplay between networks; (3) results within the Default Mode Network are mixed; (4) the brain as a network is less interconnected and less efficient in bvFTD; (5) symptoms, functional impairment, and cognition are associated with FC; and (6) the functional architecture resembles patterns of neuropathological spread. CONCLUSIONS FC has potential as a biomarker, and future studies are expected to advance the field with multicentric initiatives, longitudinal designs, and methodological advances.
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Affiliation(s)
- Luiz Kobuti Ferreira
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.,Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, & Stockholm Health Care Services, Stockholm, Sweden
| | - Olof Lindberg
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Alexander F Santillo
- Clinical Memory Research Unit and Psychiatry, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | - Lars-Olof Wahlund
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
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20
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Effect of group-based vs individualized stimulation site selection on reliability of network-targeted TMS. Neuroimage 2022; 264:119714. [PMID: 36309331 DOI: 10.1016/j.neuroimage.2022.119714] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 09/23/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) is a widely used technique for the noninvasive assessment and manipulation of brain activity and behavior. Although extensively used for research and clinical purposes, recent studies have questioned the reliability of TMS findings because of the high inter-individual variability that has been observed. OBJECTIVE In this study, we compared the efficacy and reliability of different targeting scenarios on the TMS-evoked response. METHODS 24 subjects underwent a single pulse stimulation protocol over two parietal nodes belonging to the Dorsal Attention (DAN) and Default Mode (DMN) Networks respectively. Across visits, the stimulated target for both networks was chosen either based on group-derived networks' maps or personalized network topography based on individual anatomy and functional profile. All stimulation visits were conducted twice, one month apart, during concomitant electroencephalography recording. RESULTS At the network level, we did not observe significant differences in the TMS-evoked response between targeting conditions. However, reliable patterns of activity were observed- for both networks tested- following the individualized targeting approach. When the same analyses were carried out at the electrode space level, evidence of reliable patterns was observed following the individualized stimulation of the DAN, but not of the DMN. CONCLUSIONS Our findings suggest that individualization of stimulation sites might ensure reliability of the evoked TMS-response across visits. Furthermore, individualized stimulation sites appear to be of foremost importance in highly variable, high order task-positive networks, such as the DAN.
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21
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Unraveling the functional attributes of the language connectome: crucial subnetworks, flexibility and variability. Neuroimage 2022; 263:119672. [PMID: 36209795 DOI: 10.1016/j.neuroimage.2022.119672] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 10/04/2022] [Accepted: 10/05/2022] [Indexed: 11/23/2022] Open
Abstract
Language processing is a highly integrative function, intertwining linguistic operations (processing the language code intentionally used for communication) and extra-linguistic processes (e.g., attention monitoring, predictive inference, long-term memory). This synergetic cognitive architecture requires a distributed and specialized neural substrate. Brain systems have mainly been examined at rest. However, task-related functional connectivity provides additional and valuable information about how information is processed when various cognitive states are involved. We gathered thirteen language fMRI tasks in a unique database of one hundred and fifty neurotypical adults (InLang [Interactive networks of Language] database), providing the opportunity to assess language features across a wide range of linguistic processes. Using this database, we applied network theory as a computational tool to model the task-related functional connectome of language (LANG atlas). The organization of this data-driven neurocognitive atlas of language was examined at multiple levels, uncovering its major components (or crucial subnetworks), and its anatomical and functional correlates. In addition, we estimated its reconfiguration as a function of linguistic demand (flexibility) or several factors such as age or gender (variability). We observed that several discrete networks could be specifically shaped to promote key functional features of language: coding-decoding (Net1), control-executive (Net2), abstract-knowledge (Net3), and sensorimotor (Net4) functions. The architecture of these systems and the functional connectivity of the pivotal brain regions varied according to the nature of the linguistic process, gender, or age. By accounting for the multifaceted nature of language and modulating factors, this study can contribute to enriching and refining existing neurocognitive models of language. The LANG atlas can also be considered a reference for comparative or clinical studies involving various patients and conditions.
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22
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Liu T, Shi Z, Zhang J, Wang K, Li Y, Pei G, Wang L, Wu J, Yan T. Individual functional parcellation revealed compensation of dynamic limbic network organization in healthy ageing. Hum Brain Mapp 2022; 44:744-761. [PMID: 36214186 PMCID: PMC9842897 DOI: 10.1002/hbm.26096] [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: 06/28/2022] [Revised: 09/01/2022] [Accepted: 09/19/2022] [Indexed: 01/25/2023] Open
Abstract
Using group-level functional parcellations and constant-length sliding window analysis, dynamic functional connectivity studies have revealed network-specific impairment and compensation in healthy ageing. However, functional parcellation and dynamic time windows vary across individuals; individual-level ageing-related brain dynamics are uncertain. Here, we performed individual parcellation and individual-length sliding window clustering to characterize ageing-related dynamic network changes. Healthy participants (n = 637, 18-88 years) from the Cambridge Centre for Ageing and Neuroscience dataset were included. An individual seven-network parcellation, varied from group-level parcellation, was mapped for each participant. For each network, strong and weak cognitive brain states were revealed by individual-length sliding window clustering and canonical correlation analysis. The results showed negative linear correlations between age and change ratios of sizes in the default mode, frontoparietal, and salience networks and a positive linear correlation between age and change ratios of size in the limbic network (LN). With increasing age, the occurrence and dwell time of strong states showed inverted U-shaped patterns or a linear decreasing pattern in most networks but showed a linear increasing pattern in the LN. Overall, this study reveals a compensative increase in emotional networks (i.e., the LN) and a decline in cognitive and primary sensory networks in healthy ageing. These findings may provide insights into network-specific and individual-level targeting during neuromodulation in ageing and ageing-related diseases.
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Affiliation(s)
- Tiantian Liu
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Zhongyan Shi
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Jian Zhang
- Intelligent Robotics Institute, School of Mechatronical EngineeringBeijing Institute of TechnologyBeijingChina
| | - Kexin Wang
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Yuanhao Li
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Guangying Pei
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Li Wang
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
| | - Jinglong Wu
- School of Medical TechnologyBeijing Institute of TechnologyBeijingChina
| | - Tianyi Yan
- School of Life ScienceBeijing Institute of TechnologyBeijingChina
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23
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Morand A, Segobin S, Lecouvey G, Gonneaud J, Eustache F, Rauchs G, Desgranges B. Alterations in resting-state functional connectivity associated to the age-related decline in time-based prospective memory. Cereb Cortex 2022; 33:4374-4383. [PMID: 36130116 DOI: 10.1093/cercor/bhac349] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Revised: 07/29/2022] [Accepted: 07/30/2022] [Indexed: 11/12/2022] Open
Abstract
Time-based prospective memory (TBPM) is defined as the ability to remember to perform intended actions at a specific time in the future. TBPM is impaired in aging, and this decline has been associated with white-matter alterations within the superior fronto-occipital fasciculus. In the present study, we used resting-state functional magnetic resonance imaging from 22 healthy young (26 ± 5.2 years) and 23 older (63 ± 6.1 years) participants to investigate how age-related alterations in resting-state functional connectivity are related to TBPM performance, and whether these alterations are associated with the white-matter disruptions we have previously observed with diffusion tensor imaging. Whole-brain analyses revealed lower resting-state functional connectivity in older participants compared with younger ones, which in turn correlated with TBPM performance. These correlations were mainly located in the salience network and the parietal part of the frontoparietal network. Our findings suggest that resting-state functional connectivity alterations contribute to the age-related decline in TBPM.
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Affiliation(s)
- Alexandrine Morand
- Normandie Universite, UNICAEN, PSL Universite Paris, EPHE, Inserm, U1077, CHU de Caen, NIMH, GIP Cyceron, Pole des Formations et de Recherche en Sante, 2 rue des Rochambelles, F-14032 Caen Cedex CS 14032, France
- Normandie Universite, UNICAEN, Inserm, U1237, PHIND, Institut Blood and Brain @Caen-Normandie, GIP Cyceron, Bd Henri Becquerel, BP 5229, 14074 Caen Cedex 5, France
| | - Shailendra Segobin
- Normandie Universite, UNICAEN, PSL Universite Paris, EPHE, Inserm, U1077, CHU de Caen, NIMH, GIP Cyceron, Pole des Formations et de Recherche en Sante, 2 rue des Rochambelles, F-14032 Caen Cedex CS 14032, France
| | - Grégory Lecouvey
- Normandie Universite, UNICAEN, PSL Universite Paris, EPHE, Inserm, U1077, CHU de Caen, NIMH, GIP Cyceron, Pole des Formations et de Recherche en Sante, 2 rue des Rochambelles, F-14032 Caen Cedex CS 14032, France
| | - Julie Gonneaud
- Normandie Universite, UNICAEN, Inserm, U1237, PHIND, Institut Blood and Brain @Caen-Normandie, GIP Cyceron, Bd Henri Becquerel, BP 5229, 14074 Caen Cedex 5, France
| | - Francis Eustache
- Normandie Universite, UNICAEN, PSL Universite Paris, EPHE, Inserm, U1077, CHU de Caen, NIMH, GIP Cyceron, Pole des Formations et de Recherche en Sante, 2 rue des Rochambelles, F-14032 Caen Cedex CS 14032, France
| | - Géraldine Rauchs
- Normandie Universite, UNICAEN, PSL Universite Paris, EPHE, Inserm, U1077, CHU de Caen, NIMH, GIP Cyceron, Pole des Formations et de Recherche en Sante, 2 rue des Rochambelles, F-14032 Caen Cedex CS 14032, France
- Normandie Universite, UNICAEN, Inserm, U1237, PHIND, Institut Blood and Brain @Caen-Normandie, GIP Cyceron, Bd Henri Becquerel, BP 5229, 14074 Caen Cedex 5, France
| | - Béatrice Desgranges
- Normandie Universite, UNICAEN, PSL Universite Paris, EPHE, Inserm, U1077, CHU de Caen, NIMH, GIP Cyceron, Pole des Formations et de Recherche en Sante, 2 rue des Rochambelles, F-14032 Caen Cedex CS 14032, France
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24
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Ulrich M, Heckel K, Kölle M, Grön G. Methylphenidate Differentially Affects Intrinsic Functional Connectivity of the Salience Network in Adult ADHD Treatment Responders and Non-Responders. BIOLOGY 2022; 11:biology11091320. [PMID: 36138799 PMCID: PMC9495306 DOI: 10.3390/biology11091320] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 09/01/2022] [Accepted: 09/02/2022] [Indexed: 11/16/2022]
Abstract
Positron emission tomography (PET) studies have shown involvement of the striatum when treating adult attention-deficit/hyperactivity disorder (ADHD) with methylphenidate (MPH). Results from resting-state functional magnetic resonance imaging (rs-fMRI) for the same issue were less unequivocal. Here, a new analytical framework was set up to investigate medication effects using seed-based rs-fMRI analysis to infer brain regions with alterations in intrinsic functional connectivity (IFC) corresponding with ADHD symptom reduction. In a within-subjects study design, 53 stimulant-naïve adult ADHD patients were investigated before and after 6 weeks of MPH treatment, using two major clinical symptom scales and rs-fMRI. The same data were acquired in a sample of 50 age- and sex-matched healthy controls at baseline. A consensual atlas provided seeds for five predefined major resting-state networks. In order to avoid biasing of medication effects due to putative treatment failure, the entire ADHD sample was first categorized into treatment Responders (N = 36) and Non-Responders (N = 17) using machine learning-based classification with the clinical scales as primary data. Imaging data revealed medication effects only in Responders. In that group, IFC of bilateral putamen changed significantly with medication and approached almost normal levels of IFC. Present results align well with results from previous PET studies, with seed-based rs-fMRI as an entirely different neuroimaging method.
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Affiliation(s)
- Martin Ulrich
- Section Neuropsychology and Functional Imaging, Department of Psychiatry, Ulm University, 89075 Ulm, Germany
- Correspondence:
| | - Katharina Heckel
- Section Neuropsychology and Functional Imaging, Department of Psychiatry, Ulm University, 89075 Ulm, Germany
| | - Markus Kölle
- Department of Psychiatry and Psychotherapy, Bonn University, 53127 Bonn, Germany
| | - Georg Grön
- Section Neuropsychology and Functional Imaging, Department of Psychiatry, Ulm University, 89075 Ulm, Germany
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25
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Makowski C, Wang H, Chen CH. Clinical opportunity awaits at the intersection of genomics and brain imaging. J Psychiatry Neurosci 2022; 47:E293-E298. [PMID: 35948342 PMCID: PMC9377545 DOI: 10.1503/jpn.220075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
| | | | - Chi-Hua Chen
- From the Center for Multimodal Imaging and Genetics, Department of Radiology, University of California San Diego, San Diego, Cali., USA
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26
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Fede SJ, Kisner MA, Manuweera T, Kerich M, Momenan R. Compounding Vulnerability in the Neurocircuitry of Addiction: Longitudinal Functional Connectivity Changes in Alcohol Use Disorder. Alcohol Alcohol 2022; 57:712-721. [PMID: 35760068 DOI: 10.1093/alcalc/agac028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 05/16/2022] [Accepted: 05/21/2022] [Indexed: 11/14/2022] Open
Abstract
AIMS The addiction neurocircuitry model describes the role of several brain circuits (drug reward, negative emotionality and craving/executive control) in alcohol use and subsequent development of alcohol use disorder (AUD). Human studies examining longitudinal change using resting-state functional magnetic resonance imaging (rs-fMRI) are needed to understand how functional changes to these circuits are caused by or contribute to continued AUD. METHODS In order to characterize how intrinsic functional connectivity changes with sustained AUD, we analyzed rs-fMRI data from individuals with (n = 18; treatment seeking and non-treatment seeking) and without (n = 21) AUD collected on multiple visits as part of various research studies at the NIAAA intramural program from 2012 to 2020. RESULTS Results of the seed correlation analysis showed that individuals with AUD had an increase in functional connectivity over time between emotionality and craving neurocircuits, and a decrease between executive control and reward networks. Post hoc investigations of AUD severity and alcohol consumption between scans revealed an additive effect of these AUD features in many of the circuits, such that more alcohol consumption or more severe AUD was associated with more pronounced changes to synchronicity. CONCLUSIONS These findings suggest an increased concordance of networks underlying emotionality and compulsions toward drinking while also a reduction in control network connectivity, consistent with the addiction neurocircuitry model. Further, they suggest a compounding effect of continued heavy drinking on these vulnerabilities in neurocircuitry. More longitudinal research is necessary to understand the trajectories of individuals with AUD not adequately represented in this study, as well as whether this can inform effective harm reduction strategies.
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Affiliation(s)
- Samantha J Fede
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 10 Center Drive, MSC 1108, Bethesda, MD 20892, USA.,Department of Psychological Sciences, Auburn University, 226 Thach Hall, Auburn, AL 36849, USA
| | - Mallory A Kisner
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 10 Center Drive, MSC 1108, Bethesda, MD 20892, USA
| | - Thushini Manuweera
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 10 Center Drive, MSC 1108, Bethesda, MD 20892, USA
| | - Mike Kerich
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 10 Center Drive, MSC 1108, Bethesda, MD 20892, USA
| | - Reza Momenan
- Clinical NeuroImaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, 10 Center Drive, MSC 1108, Bethesda, MD 20892, USA
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Mancuso L, Cavuoti-Cabanillas S, Liloia D, Manuello J, Buzi G, Cauda F, Costa T. Tasks activating the default mode network map multiple functional systems. Brain Struct Funct 2022; 227:1711-1734. [PMID: 35179638 PMCID: PMC9098625 DOI: 10.1007/s00429-022-02467-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/31/2022] [Indexed: 12/30/2022]
Abstract
Recent developments in network neuroscience suggest reconsidering what we thought we knew about the default mode network (DMN). Although this network has always been seen as unitary and associated with the resting state, a new deconstructive line of research is pointing out that the DMN could be divided into multiple subsystems supporting different functions. By now, it is well known that the DMN is not only deactivated by tasks, but also involved in affective, mnestic, and social paradigms, among others. Nonetheless, it is starting to become clear that the array of activities in which it is involved, might also be extended to more extrinsic functions. The present meta-analytic study is meant to push this boundary a bit further. The BrainMap database was searched for all experimental paradigms activating the DMN, and their activation likelihood estimation maps were then computed. An additional map of task-induced deactivations was also created. A multidimensional scaling indicated that such maps could be arranged along an anatomo-psychological gradient, which goes from midline core activations, associated with the most internal functions, to that of lateral cortices, involved in more external tasks. Further multivariate investigations suggested that such extrinsic mode is especially related to reward, semantic, and emotional functions. However, an important finding was that the various activation maps were often different from the canonical representation of the resting-state DMN, sometimes overlapping with it only in some peripheral nodes, and including external regions such as the insula. Altogether, our findings suggest that the intrinsic-extrinsic opposition may be better understood in the form of a continuous scale, rather than a dichotomy.
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Affiliation(s)
- Lorenzo Mancuso
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
| | | | - Donato Liloia
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Jordi Manuello
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Giulia Buzi
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
| | - Franco Cauda
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy
| | - Tommaso Costa
- FOCUS Lab Department of Psychology, University of Turin, Via Giuseppe Verdi 10, 10124, Turin, Italy.
- GCS-fMRI, Koelliker Hospital and Department of Psychology, University of Turin, Turin, Italy.
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28
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Haas SS, Myoraku A, Watson K, Robakis T, Frangou S, Abbasi F, Rasgon N. Lower functional hippocampal connectivity in healthy adults is jointly associated with higher levels of leptin and insulin resistance. Eur Psychiatry 2022; 65:e29. [PMID: 35492025 PMCID: PMC9158395 DOI: 10.1192/j.eurpsy.2022.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Background Metabolic dysregulation is currently considered a major risk factor for hippocampal pathology. The aim of the present study was to characterize the influence of key metabolic drivers on functional connectivity of the hippocampus in healthy adults. Methods Insulin resistance was directly quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test and fasting levels of insulin, glucose, leptin, and cortisol, and measurements of body mass index and waist circumference were obtained in a sample of healthy cognitively intact adults (n = 104). Resting-state neuroimaging data were also acquired for the quantification of hippocampal functional cohesiveness and integration with the major resting-state networks (RSNs). Data-driven analysis using unsupervised machine learning (k-means clustering) was then employed to identify clusters of individuals based on their metabolic and functional connectivity profiles. Results K-means clustering identified two clusters of increasing metabolic deviance evidenced by cluster differences in the plasma levels of leptin (40.36 (29.97) vs. 27.59 (25.58) μg/L) and the degree of insulin resistance (SSPG concentration: 161.63 (65.27) vs. 125.72 (66.81) mg/dL). Individuals in the cluster with higher metabolic deviance showed lower functional cohesiveness within each hippocampus and lower integration of posterior and anterior components of the left and right hippocampus with the major RSNs. The two clusters did not differ in general intellectual ability or episodic memory. Conclusions We identified two clusters of individuals differentiated by abnormalities in insulin resistance, leptin levels, and hippocampal connectivity, with one of the clusters showing greater deviance. These findings support the link between metabolic dysregulation and hippocampal function even in nonclinical samples.
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Affiliation(s)
- Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison Myoraku
- Department of Psychiatry, Stanford University School of Medicine
| | - Kathleen Watson
- Department of Psychiatry, Stanford University School of Medicine
| | - Thalia Robakis
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.,Department of Psychiatry, Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Fahim Abbasi
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Natalie Rasgon
- Department of Psychiatry, Stanford University School of Medicine
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29
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Investigating Large-Scale Network with Unified Granger Causality Analysis. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022. [DOI: 10.1155/2022/6962359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
As the concept of integrating global neuron coupling effect is increasingly accepted, investigating causal connection increasingly requires the intervention of large-scale analysis. In this study, a large-scale brain network analysis was carried out by a description length guided framework, which involves a unified Granger causality analysis (uGCA) method and now integrates the concept of large-scale analysis. This will be helpful to make a more comprehensive determination for causal connection among the global brain regions. Distinct from the conventional GCA, which involves a two-stage scheme consisting of Akaike information criterion or Bayesian information criterion (AIC/BIC) and
-test to obtain a causal effect, a unified guided framework can ensure more reliable results while eliminating some confounding influences among network nodes. Then, we performed large-scale network simulation experiments involving 13 nodes; it was found that our proposal was more accurate and robust in guiding the causal connection investigation of large-scale networks. When it comes to the resting-state fMRI datasets, we studied a 90-node network selected from the Anatomical Automatic Labeling (AAL) template. Then, combining a K-means clustering method, we found that most brain nodes in the connection network obtained by uGCA methods were gathered into the corresponding functional brain regions and functionally related regions cooperated with each other. Compared to conventional GCA, their results were more consistent with clinical and anatomical priors. Moreover, in studies of several large-scale functional networks involving default mode network (DMN), dorsal attention network (DAN), and frontoparietal control network (FCN), the uGCA method more clearly revealed their empirical cooperation. As a brain with numerous nodes and massive connections, a unified large-scale analysis method is of great significance for the integration of causal connections in the whole brain network in the future.
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Salman MS, Wager TD, Damaraju E, Abrol A, Vergara VM, Fu Z, Calhoun VD. An Approach to Automatically Label and Order Brain Activity/Component Maps. Brain Connect 2022; 12:85-95. [PMID: 34039009 PMCID: PMC8867103 DOI: 10.1089/brain.2020.0950] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Background: Functional magnetic resonance imaging (fMRI) is a brain imaging technique that provides detailed insights into brain function and its disruption in various brain disorders. The data-driven analysis of fMRI brain activity maps involves several postprocessing steps, the first of which is identifying whether the estimated brain network maps capture signals of interest, for example, intrinsic connectivity networks (ICNs), or artifacts. This is followed by linking the ICNs to standardized anatomical and functional parcellations. Optionally, as in the study of functional network connectivity (FNC), rearranging the connectivity graph is also necessary to facilitate interpretation. Methods: Here we develop a novel and efficient method (Autolabeler) for implementing and integrating all of these processes in a fully automated manner. The Autolabeler method is pretrained on a cross-validated elastic-net regularized general linear model from the noisecloud toolbox to separate neuroscientifically meaningful ICNs from artifacts. It is capable of automatically labeling activity maps with labels from several well-known anatomical and functional parcellations. Subsequently, this method also maximizes the modularity within functional domains to generate a more systematically structured FNC matrix for post hoc network analyses. Results: Results show that our pretrained model achieves 86% accuracy at classifying ICNs from artifacts in an independent validation data set. The automatic anatomical and functional labels also have a high degree of similarity with manual labels selected by human raters. Discussion: At a time of ever-increasing rates of generating brain imaging data and analyzing brain activity, the proposed Autolabeler method is intended to automate such analyses for faster and more reproducible research. Impact statement Our proposed method is capable of implementing and integrating some of the crucial tasks in functional magnetic resonance imaging (fMRI) studies. It is the first to incorporate such tasks without the need for expert intervention. We develop an open-source toolbox for the proposed method that can function as stand-alone software and additionally provides seamless integration with the widely used group independent component analysis for fMRI toolbox (GIFT). This integration can aid investigators to conduct fMRI studies in an end-to-end automated manner.
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Affiliation(s)
- Mustafa S. Salman
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, and Emory University, Atlanta, Georgia, USA.,School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA.,Address correspondence to: Mustafa S. Salman, TReNDS Center, Georgia State University, 55 Park Pl NE, 18th floor, Atlanta, GA 30303, USA
| | - Tor D. Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hannover, New Hampshire, USA
| | - Eswar Damaraju
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, and Emory University, Atlanta, Georgia, USA
| | - Anees Abrol
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, and Emory University, Atlanta, Georgia, USA
| | - Victor M. Vergara
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, and Emory University, Atlanta, Georgia, USA
| | - Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, and Emory University, Atlanta, Georgia, USA
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, Georgia State University, and Emory University, Atlanta, Georgia, USA.,School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, Georgia, USA
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31
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Chen KT, Ho TY, Siow TY, Yeh YC, Huang SY. OUP accepted manuscript. Cereb Cortex Commun 2022; 3:tgac008. [PMID: 35281215 PMCID: PMC8914218 DOI: 10.1093/texcom/tgac008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2022] [Accepted: 02/08/2022] [Indexed: 11/12/2022] Open
Affiliation(s)
- Ko-Ting Chen
- Department of Neurosurgery, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
- School of Medicine, Chang Gung University, Taoyuan 33302, Taiwan
- Neuroscience Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Tsung-Ying Ho
- Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital at Linkou, Chang Gung University, Taoyuan 333, Taiwan
| | - Tiing-Yee Siow
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Yu-Chiang Yeh
- Department of Neurosurgery, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Sheng-Yao Huang
- Corresponding author: Molecular Medicine Research Center, Chang Gung University, Taoyuan, Taiwan.
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32
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Daviddi S, Pedale T, Serra L, Macrì S, Campolongo P, Santangelo V. Altered Hippocampal Resting-state Functional Connectivity in Highly Superior Autobiographical Memory. Neuroscience 2022; 480:1-8. [PMID: 34774712 DOI: 10.1016/j.neuroscience.2021.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 10/21/2021] [Accepted: 11/02/2021] [Indexed: 10/19/2022]
Abstract
Individuals with Highly Superior Autobiographical Memory (HSAM) provide the opportunity to investigate the neurobiological substrates of enhanced memory performance. While previous studies started to assess the neural correlates of memory retrieval in HSAM, here we assessed for the first time the intrinsic connectivity of a core memory region, the hippocampus, with the whole brain, in 8 HSAM subjects (HSAMs) and 21 controls during resting-state functional neuroimaging. We found in HSAMs vs. controls disrupted hippocampal resting-state functional connectivity (rsFC) with high-level control regions belonging to the saliency network (the anterior cingulate cortex and the left and right insulae), and to the ventral fronto-parietal attentional network (the temporo-parietal junction and the inferior frontal gyrus), also involved with salience detection. Conversely, HSAMs showed enhanced hippocampal rsFC with sensory regions along the fusiform gyrus and the inferior temporal cortex. This altered pattern of hippocampal rsFC might be interpreted as a reduced capability of HSAMs to discriminate and select salient information, with a subsequent increase in the probability to encode and consolidate sensory information irrespective of their task-relevancy. Ultimately, these findings provide evidence that HSAM might be paradoxically enabled by an altered hippocampal rsFC that bypasses regions involved with salience detection in favor of specialized sensory regions.
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Affiliation(s)
- Sarah Daviddi
- Department of Philosophy, Social Sciences & Education, University of Perugia, Piazza G. Ermini 1, 06123 Perugia, Italy
| | - Tiziana Pedale
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Via Ardeatina 306, 00179 Rome, Italy
| | - Laura Serra
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Via Ardeatina 306, 00179 Rome, Italy
| | - Simone Macrì
- Centre for Behavioral Sciences and Mental Health, Istituto Superiore di Sanità, Viale Regina Elena, 299 00161 Rome, Italy
| | - Patrizia Campolongo
- Department of Physiology and Pharmacology, Sapienza University of Rome, P.le A. Moro 5, 00185 Rome, Italy; CERC, Fondazione Santa Lucia, IRCCS, Via del Fosso di Fiorano 64, 00143 Rome, Italy
| | - Valerio Santangelo
- Department of Philosophy, Social Sciences & Education, University of Perugia, Piazza G. Ermini 1, 06123 Perugia, Italy; Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Via Ardeatina 306, 00179 Rome, Italy.
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33
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Missing links: The functional unification of language and memory (L∪M). Neurosci Biobehav Rev 2021; 133:104489. [PMID: 34929226 DOI: 10.1016/j.neubiorev.2021.12.012] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 11/14/2021] [Accepted: 12/07/2021] [Indexed: 10/19/2022]
Abstract
The field of neurocognition is currently undergoing a significant change of perspective. Traditional neurocognitive models evolved into an integrative and dynamic vision of cognitive functioning. Dynamic integration assumes an interaction between cognitive domains traditionally considered to be distinct. Language and declarative memory are regarded as separate functions supported by different neural systems. However, they also share anatomical structures (notably, the inferior frontal gyrus, the supplementary motor area, the superior and middle temporal gyrus, and the hippocampal complex) and cognitive processes (such as semantic and working memory) that merge to endorse our quintessential daily lives. We propose a new model, "L∪M" (i.e., Language/union/Memory), that considers these two functions interactively. We fractionated language and declarative memory into three fundamental dimensions or systems ("Receiver-Transmitter", "Controller-Manager" and "Transformer-Associative" Systems), that communicate reciprocally. We formalized their interactions at the brain level with a connectivity-based approach. This new taxonomy overcomes the modular view of cognitive functioning and reconciles functional specialization with plasticity in neurological disorders.
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34
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Using Brain Imaging to Improve Spatial Targeting of Transcranial Magnetic Stimulation for Depression. Biol Psychiatry 2021; 90:689-700. [PMID: 32800379 DOI: 10.1016/j.biopsych.2020.05.033] [Citation(s) in RCA: 125] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 05/29/2020] [Accepted: 05/29/2020] [Indexed: 01/18/2023]
Abstract
Transcranial magnetic stimulation (TMS) is an effective treatment for depression but is limited in that the optimal therapeutic target remains unknown. Early TMS trials lacked a focal target and thus positioned the TMS coil over the prefrontal cortex using scalp measurements. Over time, it became clear that this method leads to variation in the stimulation site and that this could contribute to heterogeneity in antidepressant response. Newer methods allow for precise positioning of the TMS coil over a specific brain location, but leveraging these precise methods requires a more precise therapeutic target. We review how neuroimaging is being used to identify a more focal therapeutic target for depression. We highlight recent studies showing that more effective TMS targets in the frontal cortex are functionally connected to deep limbic regions such as the subgenual cingulate cortex. We review how connectivity might be used to identify an optimal TMS target for use in all patients and potentially even a personalized target for each individual patient. We address the clinical implications of this emerging field and highlight critical questions for future research.
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35
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Doucet GE, Baker S, Wilson TW, Kurz MJ. Weaker Connectivity of the Cortical Networks Is Linked with the Uncharacteristic Gait in Youth with Cerebral Palsy. Brain Sci 2021; 11:brainsci11081065. [PMID: 34439684 PMCID: PMC8391166 DOI: 10.3390/brainsci11081065] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 08/10/2021] [Accepted: 08/11/2021] [Indexed: 11/16/2022] Open
Abstract
Cerebral palsy (CP) is the most prevalent pediatric neurologic impairment and is associated with major mobility deficiencies. This has led to extensive investigations of the sensorimotor network, with far less research focusing on other major networks. The aim of this study was to investigate the functional connectivity (FC) of the main sensory networks (i.e., visual and auditory) and the sensorimotor network, and to link FC to the gait biomechanics of youth with CP. Using resting-state functional magnetic resonance imaging, we first identified the sensorimotor, visual and auditory networks in youth with CP and neurotypical controls. Our analysis revealed reduced FC among the networks in the youth with CP relative to the controls. Notably, the visual network showed lower FC with both the sensorimotor and auditory networks. Furthermore, higher FC between the visual and sensorimotor cortices was associated with larger step length (r = 0.74, pFDR = 0.04) in youth with CP. These results confirm that CP is associated with functional brain abnormalities beyond the sensorimotor network, suggesting abnormal functional integration of the brain’s motor and primary sensory systems. The significant association between abnormal visuo-motor FC and gait could indicate a link with visuomotor disorders in this patient population.
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36
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Aue T, Dricu M, Singh L, Moser DA, Raviteja K. Enhanced Sensitivity to Optimistic Cues is Manifested in Brain Structure: A Voxel-Based Morphometry Study. Soc Cogn Affect Neurosci 2021; 16:1170-1181. [PMID: 34128051 PMCID: PMC8599192 DOI: 10.1093/scan/nsab075] [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: 01/28/2021] [Revised: 04/25/2021] [Accepted: 06/14/2021] [Indexed: 01/07/2023] Open
Abstract
Recent research shows that congruent outcomes are more rapidly (and incongruent less rapidly) detected when individuals receive optimistic rather than pessimistic cues, an effect that was termed optimism robustness. In the current voxel-based morphometry study, we examined whether optimism robustness has a counterpart in brain structure. The participants' task was to detect two different letters (symbolizing monetary gain or loss) in a visual search matrix. Prior to each onset of the search matrix, two different verbal cues informed our participants about a high probability to gain (optimistic expectancy) or lose (pessimistic expectancy) money. The target presented was either congruent or incongruent with these induced expectancies. Optimism robustness revealed in the participants' reaction times correlated positively with gray matter volume (GMV) in brain regions involved in selective attention (medial visual association area, intraparietal sulcus), emphasizing the strong intertwinement of optimistic expectancies and attention deployment. In addition, GMV in the primary visual cortex diminished with increasing optimism robustness, in line with the interpretation of optimism robustness arising from a global, context-oriented perception. Future studies should address the malleability of these structural correlates of optimism robustness. Our results may assist in the identification of treatment targets in depression.
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Affiliation(s)
- Tatjana Aue
- Institute of Psychology, University of Bern, Bern, Switzerland
| | - Mihai Dricu
- Institute of Psychology, University of Bern, Bern, Switzerland
| | - Laura Singh
- Institute of Psychology, University of Bern, Bern, Switzerland
| | - Dominik A Moser
- Institute of Psychology, University of Bern, Bern, Switzerland
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37
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Intracortical Functional Connectivity Predicts Arousal to Noxious Stimuli during Sleep in Humans. J Neurosci 2021; 41:5115-5123. [PMID: 33931551 DOI: 10.1523/jneurosci.2935-20.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 04/13/2021] [Accepted: 04/15/2021] [Indexed: 11/21/2022] Open
Abstract
Nociceptive stimuli disrupt sleep, but may, or may not, entail an arousal. While arousal reactions go along with the activation of a widespread cortical network, the factors enabling such activation remain unknown. Here we used intracranial EEG in humans to test the relation between the cortical activity immediately preceding a noxious stimulus and the capacity of such a stimulus to trigger arousal. Intracranial EEG signals were analyzed during all-night sleep in 14 epileptic patients (4 women), who received laser stimuli slightly above their individual pain threshold. During 5 s preceding each stimulus, the functional correlation (spectral phase-coherence) between the main spinothalamic sensory area (posterior insula) and 12 other brain regions, grouped in four networks, as well as their spectral contents, were contrasted according to the presence of a stimulus-induced arousal, and then fed into a logistic regression model to assess their predictive value. Enhanced prestimulus phase-coherence between the sensory posterior insula and neocortical and limbic areas increased significantly the probability of arousal to nociceptive stimuli, in both slow-wave (N2) and rapid eye movements/paradoxical sleep. Furthermore, during N2 sleep, arousal was facilitated by stimulus delivery in periods of attenuated slow-wave activity. Together, these data indicate that sleep micro-states with enhanced interareal communication facilitate information transfer from sensory to higher-order cortical areas, and hence physiological arousal.SIGNIFICANCE STATEMENT Sleep is commonly subdivided into stages based on specific electrophysiological characteristics; however, within each single sleep stage, the functional state of the brain is continuously changing. Here we show that the probability for a phasic noxious stimulus to entail an arousal is modulated by the prestimulus interareal phase-coherence between sensory and higher-level cortical areas. Fluctuations in interareal communication immediately before the noxious stimulus may determine the responsiveness to incoming input by facilitating or preventing the transfer of noxious information from sensory to multiple higher-level cortical networks.
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38
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Moser DA, Dricu M, Kotikalapudi R, Doucet GE, Aue T. Reduced network integration in default mode and executive networks is associated with social and personal optimism biases. Hum Brain Mapp 2021; 42:2893-2906. [PMID: 33755272 PMCID: PMC8127148 DOI: 10.1002/hbm.25411] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 01/19/2021] [Accepted: 02/08/2021] [Indexed: 12/17/2022] Open
Abstract
An optimism bias refers to the belief in good things happening to oneself in the future with a higher likelihood than is justified. Social optimism biases extend this concept to groups that one identifies with. Previous literature has found that both personal and social optimism biases are linked to brain structure and task-related brain function. Less is known about whether optimism biases are also expressed in resting-state functional connectivity (RSFC). Forty-two participants completed questionnaires on dispositional personal optimism (which is not necessarily unjustified) and comparative optimism (i.e., whether we see our own future as being rosier than a comparison person's future) and underwent a resting-state functional magnetic resonance imaging scan. They further undertook an imaginative soccer task in order to assess both their personal and social optimism bias. We tested associations of these data with RSFC within and between 13 networks, using sparse canonical correlation analyses (sCCAs). We found that the primary sCCA component was positively connected to personal and social optimism bias and negatively connected to dispositional personal pessimism. This component was associated with (a) reduced integration of the default mode network, (b) reduced integration of the central executive and salience networks, and (c) reduced segregation between the default mode network and the central executive network. Our finding that optimism biases are linked to RSFC indicates that they may be rooted in neurobiology that exists outside of concurrent tasks. This poses questions as to what the limits of the malleability of such biases may be.
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Affiliation(s)
- Dominik Andreas Moser
- Institute of Psychology, University of Bern, Bern, Switzerland.,Child and Adolescent Psychiatry, University Hospital Lausanne, Lausanne, Switzerland
| | - Mihai Dricu
- Institute of Psychology, University of Bern, Bern, Switzerland
| | | | - Gaelle Eve Doucet
- Institute for Human Neuroscience, Boys Town National Research Hospital, Omaha, Nebraska, USA
| | - Tatjana Aue
- Institute of Psychology, University of Bern, Bern, Switzerland
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39
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Pongpipat EE, Kennedy KM, Foster CM, Boylan MA, Rodrigue KM. Functional Connectivity Within and Between n-Back Modulated Regions: An Adult Lifespan Psychophysiological Interaction Investigation. Brain Connect 2021; 11:103-118. [PMID: 33317393 PMCID: PMC7984940 DOI: 10.1089/brain.2020.0791] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction: Working memory (WM) and its blood-oxygen-level-dependent-related parametric modulation under load decrease with age. Functional connectivity (FC) generally increases with WM load; however, how aging impacts connectivity and whether this is load-dependent, region-dependent, or associated with cognitive performance is unclear. Methods: This study examines these questions in 170 healthy adults (meanage = 52.99 ± 19.18) who completed functional magnetic resonance imaging scanning during an n-back task (0-, 2-, 3-, and 4-back). The FC was estimated by utilizing a modified generalized psychophysiological interaction approach with seeds from fronto-parietal (FP) and default mode (DM) regions that modulated to n-back difficulty. The FC analyses focused on both connectivity during WM engagement (task vs. control) and connectivity in response to increased WM load (linear slope across conditions). Each analysis utilized within- and between-region FC, predicted by age (linear or quadratic), and its associations with in- and out-of-scanner task performance. Results: Engaging in WM either generally (task vs. control) or as a function of difficulty strengthened integration within- and between-FP and DM regions. Notably, these task-sensitive functional connections were robust to the effects of age. Stronger negative FC between FP and DM regions was also associated with better WM performance in an age-dependent manner, occurring selectively in middle-aged and older adults. Discussion: These results suggest that FC is critical for engaging in cognitively demanding tasks, and its lack of sensitivity to healthy aging may provide a means to maintain cognition across the adult lifespan. Thus, this study highlights the contribution of maintenance in brain function to support working memory processing with aging.
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Affiliation(s)
- Ekarin E. Pongpipat
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas at Dallas, Dallas, Texas, USA
| | - Kristen M. Kennedy
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas at Dallas, Dallas, Texas, USA
| | - Chris M. Foster
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas at Dallas, Dallas, Texas, USA
| | - Maria A. Boylan
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas at Dallas, Dallas, Texas, USA
| | - Karen M. Rodrigue
- Center for Vital Longevity, School of Behavioral and Brain Science, The University of Texas at Dallas, Dallas, Texas, USA
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40
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Muller AM, Meyerhoff DJ. Maladaptive brain organization at 1 month into abstinence as an indicator for future relapse in patients with alcohol use disorder. Eur J Neurosci 2021; 53:2923-2938. [PMID: 33630358 PMCID: PMC8252378 DOI: 10.1111/ejn.15161] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 02/22/2021] [Accepted: 02/23/2021] [Indexed: 12/11/2022]
Abstract
Abstinence is a lifelong endeavor, and the risk of a relapse is always present for patients with Alcohol Use Disorder (AUD). The aim of the study was to better understand specific characteristics of the intrinsic whole-brain-network architecture of 34 AUD patients that may support abstinence or relapse. We used Graph Theory Analysis (GTA) of resting-state fMRI data from treatment seekers at 1 month of abstinence and their follow-up data as abstainers or relapsers 3 months later, together with data from 30 light/non-drinking controls scanned at the same interval. We determined the group-specific intrinsic community configurations at both timepoints as well as the corresponding modularity Q, a GTA measure that quantifies how well individual network communities are separated from each other. Both AUD groups at both timepoints had community configurations significantly different from those of controls, but the three groups did not significantly differ in their Q values. However, relapsers showed a maladaptive community configuration at baseline, which became more similar to the controls' community organization after the relapsers had started consuming alcohol again during the study interval. Additionally, successful recovery from AUD was not associated with re-gaining the intrinsic brain organization found in light/non-drinkers, but with a re-configuration resulting in a new brain organization distinctly different from that of healthy controls. Resting-state fMRI provides useful measures reflecting neuroplastic adaptations related to AUD treatment outcome.
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Affiliation(s)
- Angela M Muller
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Dieter J Meyerhoff
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
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41
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Deep Learning-based Classification of Resting-state fMRI Independent-component Analysis. Neuroinformatics 2021; 19:619-637. [PMID: 33543442 DOI: 10.1007/s12021-021-09514-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/17/2021] [Indexed: 12/12/2022]
Abstract
Functional connectivity analyses of fMRI data have shown that the activity of the brain at rest is spatially organized into resting-state networks (RSNs). RSNs appear as groups of anatomically distant but functionally tightly connected brain regions. Inter-RSN intrinsic connectivity analyses may provide an optimal spatial level of integration to analyze the variability of the functional connectome. Here we propose a deep learning approach to enable the automated classification of individual independent-component (IC) decompositions into a set of predefined RSNs. Two databases were used in this work, BIL&GIN and MRi-Share, with 427 and 1811 participants, respectively. We trained a multilayer perceptron (MLP) to classify each IC as one of 45 RSNs, using the IC classification of 282 participants in BIL&GIN for training and a 5-dimensional parameter grid search for hyperparameter optimization. It reached an accuracy of 92 %. Predictions for the remaining individuals in BIL&GIN were tested against the original classification and demonstrated good spatial overlap between the cortical RSNs. As a first application, we created an RSN atlas based on MRi-Share. This atlas defined a brain parcellation in 29 RSNs covering 96 % of the gray matter. Second, we proposed an individual-based analysis of the subdivision of the default-mode network into 4 networks. Minimal overlap between RSNs was found except in the angular gyrus and potentially in the precuneus. We thus provide the community with an individual IC classifier that can be used to analyze one dataset or to statistically compare different datasets for RSN spatial definitions.
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42
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Cash RFH, Cocchi L, Lv J, Wu Y, Fitzgerald PB, Zalesky A. Personalized connectivity-guided DLPFC-TMS for depression: Advancing computational feasibility, precision and reproducibility. Hum Brain Mapp 2021; 42:4155-4172. [PMID: 33544411 PMCID: PMC8357003 DOI: 10.1002/hbm.25330] [Citation(s) in RCA: 80] [Impact Index Per Article: 26.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 11/16/2020] [Accepted: 12/13/2020] [Indexed: 01/18/2023] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for refractory depression, however, therapeutic outcomes vary. Mounting evidence suggests that clinical response relates to functional connectivity with the subgenual cingulate cortex (SGC) at the precise DLPFC stimulation site. Critically, SGC-related network architecture shows considerable interindividual variation across the spatial extent of the DLPFC, indicating that connectivity-based target personalization could potentially be necessary to improve treatment outcomes. However, to date accurate personalization has not appeared feasible, with recent work indicating that the intraindividual reproducibility of optimal targets is limited to 3.5 cm. Here we developed reliable and accurate methodologies to compute individualized connectivity-guided stimulation targets. In resting-state functional MRI scans acquired across 1,000 healthy adults, we demonstrate that, using this approach, personalized targets can be reliably and robustly pinpointed, with a median accuracy of ~2 mm between scans repeated across separate days. These targets remained highly stable, even after 1 year, with a median intraindividual distance between coordinates of only 2.7 mm. Interindividual spatial variation in personalized targets exceeded intraindividual variation by a factor of up to 6.85, suggesting that personalized targets did not trivially converge to a group-average site. Moreover, personalized targets were heritable, suggesting that connectivity-guided rTMS personalization is stable over time and under genetic control. This computational framework provides capacity for personalized connectivity-guided TMS targets to be robustly computed with high precision and has the flexibly to advance research in other basic research and clinical applications.
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Affiliation(s)
- Robin F H Cash
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia.,Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
| | - Luca Cocchi
- Clinical Brain Networks Group, QIMR Berghofer, Brisbane, Queensland, Australia
| | - Jinglei Lv
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia.,Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia.,School of Biomedical Engineering, The University of Sydney, Camperdown, New South Wales, Australia
| | - Yumeng Wu
- Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
| | - Paul B Fitzgerald
- Epworth Centre for Innovation and Mental Health, Epworth Healthcare and the Monash University Central Clinical School, Camberwell, Victoria, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia.,Department of Biomedical Engineering, The University of Melbourne, Melbourne, Victoria, Australia
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43
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Doucet GE, Labache L, Thompson PM, Joliot M, Frangou S. Atlas55+: Brain Functional Atlas of Resting-State Networks for Late Adulthood. Cereb Cortex 2021; 31:1719-1731. [PMID: 33188411 PMCID: PMC7869083 DOI: 10.1093/cercor/bhaa321] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Revised: 09/21/2020] [Accepted: 10/09/2020] [Indexed: 11/14/2022] Open
Abstract
Currently, several human brain functional atlases are used to define the spatial constituents of the resting-state networks (RSNs). However, the only brain atlases available are derived from samples of young adults. As brain networks are continuously reconfigured throughout life, the lack of brain atlases derived from older populations may influence RSN results in late adulthood. To address this gap, the aim of the study was to construct a reliable brain atlas derived only from older participants. We leveraged resting-state functional magnetic resonance imaging data from three cohorts of healthy older adults (total N = 563; age = 55-95 years) and a younger-adult cohort (N = 128; age = 18-35 years). We identified the major RSNs and their subdivisions across all older-adult cohorts. We demonstrated high spatial reproducibility of these RSNs with an average spatial overlap of 67%. Importantly, the RSNs derived from the older-adult cohorts were spatially different from those derived from the younger-adult cohort (P = 2.3 × 10-3). Lastly, we constructed a novel brain atlas, called Atlas55+, which includes the consensus of the major RSNs and their subdivisions across the older-adult cohorts. Thus, Atlas55+ provides a reliable age-appropriate template for RSNs in late adulthood and is publicly available. Our results confirm the need for age-appropriate functional atlases for studies investigating aging-related brain mechanisms.
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Affiliation(s)
- Gaelle E Doucet
- Boys Town National Research Hospital, Omaha, NE 68131, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Loic Labache
- GIN, UMR5293, CEA, CNRS, Bordeaux University, Bordeaux 33000, France
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA 90033, USA
| | - Marc Joliot
- GIN, UMR5293, CEA, CNRS, Bordeaux University, Bordeaux 33000, France
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Centre for Brain Health, University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
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44
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Effects of a Motor Imagery Task on Functional Brain Network Community Structure in Older Adults: Data from the Brain Networks and Mobility Function (B-NET) Study. Brain Sci 2021; 11:brainsci11010118. [PMID: 33477358 PMCID: PMC7830141 DOI: 10.3390/brainsci11010118] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Revised: 01/11/2021] [Accepted: 01/15/2021] [Indexed: 11/17/2022] Open
Abstract
Elucidating the neural correlates of mobility is critical given the increasing population of older adults and age-associated mobility disability. In the current study, we applied graph theory to cross-sectional data to characterize functional brain networks generated from functional magnetic resonance imaging data both at rest and during a motor imagery (MI) task. Our MI task is derived from the Mobility Assessment Tool–short form (MAT-sf), which predicts performance on a 400 m walk, and the Short Physical Performance Battery (SPPB). Participants (n = 157) were from the Brain Networks and Mobility (B-NET) Study (mean age = 76.1 ± 4.3; % female = 55.4; % African American = 8.3; mean years of education = 15.7 ± 2.5). We used community structure analyses to partition functional brain networks into communities, or subnetworks, of highly interconnected regions. Global brain network community structure decreased during the MI task when compared to the resting state. We also examined the community structure of the default mode network (DMN), sensorimotor network (SMN), and the dorsal attention network (DAN) across the study population. The DMN and SMN exhibited a task-driven decline in consistency across the group when comparing the MI task to the resting state. The DAN, however, displayed an increase in consistency during the MI task. To our knowledge, this is the first study to use graph theory and network community structure to characterize the effects of a MI task, such as the MAT-sf, on overall brain network organization in older adults.
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Individual-fMRI-approaches reveal cerebellum and visual communities to be functionally connected in obsessive compulsive disorder. Sci Rep 2021; 11:1354. [PMID: 33446780 PMCID: PMC7809273 DOI: 10.1038/s41598-020-80346-6] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 12/11/2020] [Indexed: 01/29/2023] Open
Abstract
There is significant interest in understanding the pathophysiology of Obsessive-Compulsive Disorder (OCD) using resting-state fMRI (rsfMRI). Previous studies acknowledge abnormalities within and beyond the fronto-striato-limbic circuit in OCD that require further clarifications. However, limited information could be inferred from the conventional way of investigating the functional connectivity differences between OCD and healthy controls. Here, we identified altered brain organization in patients with OCD by applying individual-based approaches to maximize the identification of underlying network-based features specific to the OCD group. rsfMRI of 20 patients with OCD and 22 controls were preprocessed, and individual-fMRI-subspace was derived for each subject within each group. We evaluated group differences in functional connectivity using individual-fMRI-subspace and established its advantage over conventional-fMRI methodology. We applied prediction-based approaches to highlight the group differences by evaluating the differences in functional connections that predicted the clinical scores (namely, the Obsessive-Compulsive Inventory-Revised (OCI-R) and Hamilton Anxiety Rating Scale). Then, we explored the brain network organization of both groups by estimating the subject-specific communities within each group. Lastly, we evaluated associations between the inter-individual variation of nodes in the communities to clinical measures using linear regression. Functional connectivity analysis using individual-fMRI-subspace detected 83 connections that were different between OCD and control groups, compared to none found using conventional-fMRI methodology. Connectome-based prediction analysis did not show significant overlap between the two groups in the functional connections that predicted the clinical scores. This suggests that the functional architecture in patients with OCD may be different compared to controls. Seven communities were found in both groups. Interestingly, within the OCD group but not controls, we observed functional connectivity between cerebellar and visual regions, and lack of connectivity between striato-limbic and frontal areas. Inter-individual variations in the community-size of these two communities were also associated with the OCI-R score (p < .005). Due to our small sample size, we further validated our results by (i) accounting for head motion, (ii) applying global signal regression (GSR) in data processing, and (iii) using an alternate atlas for parcellation. While the main results were consistently observed with accounting for head motion and using another atlas, the key findings were not reproduced with GSR application. The study demonstrated the existence of disconnectedness in fronto-striato-limbic community and connectedness between cerebellar and visual areas in OCD patients, which was also related to the clinical symptomatology of OCD.
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Person-based similarity in brain structure and functional connectivity in bipolar disorder. J Affect Disord 2020; 276:38-44. [PMID: 32697714 PMCID: PMC7568424 DOI: 10.1016/j.jad.2020.06.041] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 05/26/2020] [Accepted: 06/16/2020] [Indexed: 11/22/2022]
Abstract
BACKGROUND Bipolar disorder shows significant variability in clinical presentation. Here we adopt a personalized approach to quantify the brain structural and functional similarity of each individual patient to other patients and to healthy individuals. METHODS Brain morphometric and resting-state functional connectivity measures from two independent samples of patients with bipolar disorder and healthy individuals (total number of participants=215) were modeled as single vectors to generated individualized morphometric and connectivity profiles. These profiles were then used to compute a person-based similarity indices which quantified the similarity in neuroimaging profiles amongst patients and between patients and health individuals. RESULTS The morphometric and connectivity profiles of patients showed within-diagnosis similarity which was comparable to that observed in healthy individuals. They also showed minimal deviance from those of healthy individuals; the correlation between the profiles of patients and healthy individuals was high (range: 0.71-0.94, p<10-5). The degree of similarity between imaging profiles was associated with IQ (for cortical thickness) and age (functional integration) rather than clinical variables. Patients who were prescribed lithium, compared to those who were not, showed greater similarity to healthy individuals in terms of network integration (t = 2.2, p = 0.03). LIMITATIONS We focused on patients with Bipolar disorder, type I only. CONCLUSIONS High inter-individual similarity in neuroimaging profiles was observed amongst patients with bipolar disorder and between patients and healthy individuals. We infer that brain alterations associated with bipolar disorder may be nested within the normal biological diversity consistent with the high prevalence of mood symptoms in the general population.
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Doucet GE, Janiri D, Howard R, O'Brien M, Andrews-Hanna JR, Frangou S. Transdiagnostic and disease-specific abnormalities in the default-mode network hubs in psychiatric disorders: A meta-analysis of resting-state functional imaging studies. Eur Psychiatry 2020; 63:e57. [PMID: 32466812 PMCID: PMC7355168 DOI: 10.1192/j.eurpsy.2020.57] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Background. The default mode network (DMN) dysfunction has emerged as a consistent biological correlate of multiple psychiatric disorders. Specifically, there is evidence of alterations in DMN cohesiveness in schizophrenia, mood and anxiety disorders. The aim of this study was to synthesize at a fine spatial resolution the intra-network functional connectivity of the DMN in adults diagnosed with schizophrenia, mood and anxiety disorders, capitalizing on powerful meta-analytic tools provided by activation likelihood estimation. Methods. Results from 70 whole-brain resting-state functional magnetic resonance imaging articles published during the last 15 years were included comprising observations from 2,789 patients and 3,002 healthy controls. Results. Specific regional changes in DMN cohesiveness located in the anteromedial and posteromedial cortex emerged as shared and trans-diagnostic brain phenotypes. Disease-specific dysconnectivity was also identified. Unmedicated patients showed more DMN functional alterations, highlighting the importance of interventions targeting the functional integration of the DMN. Conclusion. This study highlights functional alteration in the major hubs of the DMN, suggesting common abnormalities in self-referential mental activity across psychiatric disorders.
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Affiliation(s)
- Gaelle E Doucet
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Brain Architecture, Imaging and Cognition Lab, Boys Town National Research Hospital, Omaha, Nebraska, USA
| | - Delfina Janiri
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
| | - Rebecca Howard
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Madeline O'Brien
- Graduate School of Biomedical Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Jessica R Andrews-Hanna
- Department of Psychology, University of Arizona, Tucson, Arizona, USA.,Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, Arizona, USA.,Cognitive Science, University of Arizona, Tucson, Arizona, USA
| | - Sophia Frangou
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Centre for Brain Health, University of British Columbia, Vancouver, British Columbia, Canada
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Topological Data Analysis Reveals Robust Alterations in the Whole-Brain and Frontal Lobe Functional Connectomes in Attention-Deficit/Hyperactivity Disorder. eNeuro 2020; 7:ENEURO.0543-19.2020. [PMID: 32317343 PMCID: PMC7221355 DOI: 10.1523/eneuro.0543-19.2020] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 03/04/2020] [Accepted: 04/02/2020] [Indexed: 11/21/2022] Open
Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a developmental disorder characterized by difficulty to control the own behavior. Neuroimaging studies have related ADHD with the interplay of fronto-parietal attention systems with the default mode network (DMN; Castellanos and Aoki, 2016). However, some results have been inconsistent, potentially due to methodological differences in the analytical strategies when defining the brain functional network, i.e., the functional connectivity threshold and/or the brain parcellation scheme. Here, we make use of topological data analysis (TDA) to explore the brain connectome as a function of the filtration value (i.e., the connectivity threshold), instead of using a static connectivity threshold. Specifically, we characterized the transition from all nodes being isolated to being connected into a single component as a function of the filtration value. We explored the utility of such a method to identify differences between 81 children with ADHD (45 male, age: 7.26–17.61 years old) and 96 typically developing children (TDC; 59 male, age: 7.17–17.96 years old), using a public dataset of resting state (rs)fMRI in human subjects. Results were highly congruent when using four different brain segmentations (atlases), and exhibited significant differences for the brain topology of children with ADHD, both at the whole-brain network and the functional subnetwork levels, particularly involving the frontal lobe and the DMN. Therefore, this is a solid approach that complements connectomics-related methods and may contribute to identify the neurophysio-pathology of ADHD.
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Singh L, Schüpbach L, Moser DA, Wiest R, Hermans EJ, Aue T. The effect of optimistic expectancies on attention bias: Neural and behavioral correlates. Sci Rep 2020; 10:6495. [PMID: 32300214 PMCID: PMC7162893 DOI: 10.1038/s41598-020-61440-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 02/26/2020] [Indexed: 12/12/2022] Open
Abstract
Optimism bias and positive attention bias are important features of healthy information processing. Recent findings suggest dynamic bidirectional optimism-attention interactions, but the underlying neural mechanisms remain to be identified. The current functional magnetic resonance imaging (fMRI) study, therefore, investigated the neural mechanisms underlying causal effects of optimistic expectancies on attention. We hypothesized that expectancies guide attention to confirmatory evidence in the environment, with enhanced salience and executive control network (SN/ECN) activity for unexpected information. Moreover, based on previous findings, we anticipated optimistic expectancies to more strongly impact attention and SN/ECN activity than pessimistic expectancies. Expectancies were induced with visual cues in 50 participants; subsequent attention to reward and punishment was assessed in a visual search task. As hypothesized, cues shortened reaction times to expected information, and unexpected information enhanced SN/ECN activity. Notably, these effects were stronger for optimistic than pessimistic expectancy cues. Our findings suggest that optimistic expectancies involve particularly strong predictions of reward, causing automatic guidance of attention to reward and great surprise about unexpected punishment. Such great surprise may be counteracted by visual avoidance of the punishing evidence, as revealed by prior evidence, thereby reducing the need to update (over)optimistic reward expectancies.
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Affiliation(s)
- Laura Singh
- Department of Psychology, University of Bern, 3012, Bern, Switzerland.
| | - Laurent Schüpbach
- Department of Psychology, University of Bern, 3012, Bern, Switzerland
| | - Dominik A Moser
- Department of Psychology, University of Bern, 3012, Bern, Switzerland
| | - Roland Wiest
- Institute of Diagnostic and Interventional Neuroradiology, University Hospital, Inselspital, University of Bern, 3010, Bern, Switzerland
| | - Erno J Hermans
- Donders Institute for Brain, Cognition and Behaviour, Radboud University Medical Center, 6500 HB, Nijmegen, The Netherlands
| | - Tatjana Aue
- Department of Psychology, University of Bern, 3012, Bern, Switzerland.
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Functional connections between and within brain subnetworks under resting-state. Sci Rep 2020; 10:3438. [PMID: 32103058 PMCID: PMC7044315 DOI: 10.1038/s41598-020-60406-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2019] [Accepted: 02/10/2020] [Indexed: 11/24/2022] Open
Abstract
The focus of this paper is on the functional role of brain regions focusing on their modular architecture and individual variability. Our main assumption is that the more variable anti-correlation patterns reflect random connections, while the more conserved ones play a functional role. Within this framework, we expanded on previous results using a different database and a different methodological approach. Aiming to identify the role of specific functional connections within a global network organization which includes subnetworks, we found that the fronto-parietal module acts as the main source of anti-correlations. In addition, the pre-frontal regions (namely: frontal middle, frontal middle orbital, frontal inferior triangular) and the parietal inferior region are highly conserved and, at the same time, act as highly connected nodes, thus confirming their importance in functional modulation.
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