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Lou W, Li X, Jin R, Peng W. Time-varying phase synchronization of resting-state functional magnetic resonance imaging reveals a shift toward self-referential processes during sustained pain. Pain 2024; 165:1493-1504. [PMID: 38193830 DOI: 10.1097/j.pain.0000000000003152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Accepted: 11/20/2023] [Indexed: 01/10/2024]
Abstract
ABSTRACT Growing evidence has suggested that time-varying functional connectivity between different brain regions might underlie the dynamic experience of pain. This study used a novel, data-driven framework to characterize the dynamic interactions of large-scale brain networks during sustained pain by estimating recurrent patterns of phase-synchronization. Resting-state functional magnetic resonance imaging signals were collected from 50 healthy participants before (once) and after (twice) the onset of sustained pain that was induced by topical application of capsaicin cream. We first decoded the instantaneous phase of neural activity and then applied leading eigenvector dynamic analysis on the time-varying phase-synchronization. We identified 3 recurrent brain states that show distinctive phase-synchronization. The presence of state 1, characterized by phase-synchronization between the default mode network and auditory, visual, and sensorimotor networks, together with transitions towards this brain state, increased during sustained pain. These changes can account for the perceived pain intensity and reported unpleasantness induced by capsaicin application. In contrast, state 3, characterized by phase-synchronization between the cognitive control network and sensory networks, decreased after the onset of sustained pain. These results are indicative of a shift toward internally directed self-referential processes (state 1) and away from externally directed cognitive control processes (state 3) during sustained pain.
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Affiliation(s)
- Wutao Lou
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Hong Kong, China
| | - Xiaoyun Li
- School of Psychology, Shenzhen University, Shenzhen, Guangdong, China
| | - Richu Jin
- Research Institute of Trustworthy Autonomous Systems, Southern University of Science and Technology, Shenzhen, China
- Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Weiwei Peng
- School of Psychology, Shenzhen University, Shenzhen, Guangdong, China
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2
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van der Horn HJ, de Koning ME, Visser K, Kok MGJ, Spikman JM, Scheenen ME, Renken RJ, Calhoun VD, Vergara VM, Cabral J, Mayer AR, van der Naalt J. Dynamic phase-locking states and personality in sub-acute mild traumatic brain injury: An exploratory study. PLoS One 2023; 18:e0295984. [PMID: 38100479 PMCID: PMC10723684 DOI: 10.1371/journal.pone.0295984] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023] Open
Abstract
Research has shown that maladaptive personality characteristics, such as Neuroticism, are associated with poor outcome after mild traumatic brain injury (mTBI). The current exploratory study investigated the neural underpinnings of this process using dynamic functional network connectivity (dFNC) analyses of resting-state (rs) fMRI, and diffusion MRI (dMRI). Twenty-seven mTBI patients and 21 healthy controls (HC) were included. After measuring the Big Five personality dimensions, principal component analysis (PCA) was used to obtain a superordinate factor representing emotional instability, consisting of high Neuroticism, moderate Openness, and low Extraversion, Agreeableness, and Conscientiousness. Persistent symptoms were measured using the head injury symptom checklist at six months post-injury; symptom severity (i.e., sum of all items) was used for further analyses. For patients, brain MRI was performed in the sub-acute phase (~1 month) post-injury. Following parcellation of rs-fMRI using independent component analysis, leading eigenvector dynamic analysis (LEiDA) was performed to compute dynamic phase-locking brain states. Main patterns of brain diffusion were computed using tract-based spatial statistics followed by PCA. No differences in phase-locking state measures were found between patients and HC. Regarding dMRI, a trend significant decrease in fractional anisotropy was found in patients relative to HC, particularly in the fornix, genu of the corpus callosum, anterior and posterior corona radiata. Visiting one specific phase-locking state was associated with lower symptom severity after mTBI. This state was characterized by two clearly delineated communities (each community consisting of areas with synchronized phases): one representing an executive/saliency system, with a strong contribution of the insulae and basal ganglia; the other representing the canonical default mode network. In patients who scored high on emotional instability, this relationship was even more pronounced. Dynamic phase-locking states were not related to findings on dMRI. Altogether, our results provide preliminary evidence for the coupling between personality and dFNC in the development of long-term symptoms after mTBI.
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Affiliation(s)
- Harm J. van der Horn
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- The Mind Research Network/Lovelace Biomedical Research Institute, Pete & Nancy Domenici Hall, Albuquerque, NM, United States of America
| | | | - Koen Visser
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Marius G. J. Kok
- Department of Radiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Jacoba M. Spikman
- Department of Neuropsychology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Myrthe E. Scheenen
- Department of Neuropsychology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Remco J. Renken
- Department of Neuroscience, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Vince D. Calhoun
- Tri-institutional Center for Translational Research (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States of America
| | - Victor M. Vergara
- Tri-institutional Center for Translational Research (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States of America
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
| | - Andrew R. Mayer
- The Mind Research Network/Lovelace Biomedical Research Institute, Pete & Nancy Domenici Hall, Albuquerque, NM, United States of America
- Department of Neurology, University of New Mexico School of Medicine, Albuquerque, NM, United States of America
- Department of Psychiatry, University of New Mexico School of Medicine, Albuquerque, NM, United States of America
- Department of Psychology, University of New Mexico School of Medicine, Albuquerque, NM, United States of America
| | - Joukje van der Naalt
- Department of Neurology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
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Alonso S, Tyborowska A, Ikani N, Mocking RJT, Figueroa CA, Schene AH, Deco G, Kringelbach ML, Cabral J, Ruhé HG. Depression recurrence is accompanied by longer periods in default mode and more frequent attentional and reward processing dynamic brain-states during resting-state activity. Hum Brain Mapp 2023; 44:5770-5783. [PMID: 37672593 PMCID: PMC10619399 DOI: 10.1002/hbm.26475] [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: 08/11/2022] [Revised: 07/15/2023] [Accepted: 08/16/2023] [Indexed: 09/08/2023] Open
Abstract
Recurrence in major depressive disorder (MDD) is common, but neurobiological models capturing vulnerability for recurrences are scarce. Disturbances in multiple resting-state networks have been linked to MDD, but most approaches focus on stable (vs. dynamic) network characteristics. We investigated how the brain's dynamical repertoire changes after patients transition from remission to recurrence of a new depressive episode. Sixty two drug-free, MDD-patients with ≥2 episodes underwent a baseline resting-state fMRI scan when in remission. Over 30-months follow-up, 11 patients with a recurrence and 17 matched-remitted MDD-patients without a recurrence underwent a second fMRI scan. Recurrent patterns of functional connectivity were characterized by applying Leading Eigenvector Dynamics Analysis (LEiDA). Differences between baseline and follow-up were identified for the 11 non-remitted patients, while data from the 17 matched-remitted patients was used as a validation dataset. After the transition into a depressive state, basal ganglia-anterior cingulate cortex (ACC) and visuo-attentional networks were detected significantly more often, whereas default mode network activity was found to have a longer duration. Additionally, the fMRI signal in the basal ganglia-ACC areas underlying the reward network, were significantly less synchronized with the rest of the brain after recurrence (compared to a state of remission). No significant changes were observed in the matched-remitted patients who were scanned twice while in remission. These findings characterize changes that may be associated with the transition from remission to recurrence and provide initial evidence of altered dynamical exploration of the brain's repertoire of functional networks when a recurrent depressive episode occurs.
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Affiliation(s)
- Sonsoles Alonso
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University Medical Center GroningenUniversity of GroningenGroningenthe Netherlands
- Department of Clinical Medicine, Center for Functionally Integrative NeuroscienceAarhus UniversityAarhusDenmark
| | - Anna Tyborowska
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
| | - Nessa Ikani
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Depression Expertise CenterProPersona Mental Health CareNijmegenthe Netherlands
- Overwaal Centre of Expertise for Anxiety Disorders, OCD and PTSDPro Persona Mental Health CareNijmegenthe Netherlands
| | - Roel J. T. Mocking
- Department of PsychiatryAmsterdam UMC, Location AMCAmsterdamthe Netherlands
| | - Caroline A. Figueroa
- Department of PsychiatryUniversity Medical Centre UtrechtUtrechtthe Netherlands
- School of Social WelfareUniversity of CaliforniaBerkeleyCaliforniaUSA
| | - Aart H. Schene
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
| | - Gustavo Deco
- Department of Information and Communication Technologies, Center for Brain and Cognition, Computational Neuroscience GroupUniversitat Pompeu FabraBarcelonaSpain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA)BarcelonaSpain
| | - Morten L. Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre CollegeUniversity of OxfordOxfordUK
- Center for Music in the BrainAarhus UniversityAarhusDenmark
- Department of PsychiatryUniversity of OxfordOxfordUK
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre CollegeUniversity of OxfordOxfordUK
- Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
| | - Henricus G. Ruhé
- Department of PsychiatryRadboud University Medical CentreNijmegenthe Netherlands
- Donders Institute for Brain, Cognition and BehaviorRadboud UniversityNijmegenthe Netherlands
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Zhang Y, Wang F, Sui J. Decoding individual differences in self-prioritization from the resting-state functional connectome. Neuroimage 2023; 276:120205. [PMID: 37253415 DOI: 10.1016/j.neuroimage.2023.120205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/23/2023] [Accepted: 05/27/2023] [Indexed: 06/01/2023] Open
Abstract
Although the self has traditionally been viewed as a higher-order mental function by most theoretical frameworks, recent research advocates a fundamental self hypothesis, viewing the self as a baseline function of the brain embedded within its spontaneous activities, which dynamically regulates cognitive processing and subsequently guides behavior. Understanding this fundamental self hypothesis can reveal where self-biased behaviors emerge and to what extent brain signals at rest can predict such biased behaviors. To test this hypothesis, we investigated the association between spontaneous neural connectivity and robust self-bias in a perceptual matching task using resting-state functional magnetic resonance imaging (fMRI) in 348 young participants. By decoding whole-brain connectivity patterns, the support vector regression model produced the best predictions of the magnitude of self-bias in behavior, which was evaluated via a nested cross-validation procedure. The out-of-sample generalizability was further authenticated using an external dataset of older adults. The functional connectivity results demonstrated that self-biased behavior was associated with distinct connections between the default mode, cognitive control, and salience networks. Consensus network and computational lesion analyses further revealed contributing regions distributed across six networks, extending to additional nodes, such as the thalamus, whose role in self-related processing remained unclear. These results provide evidence that self-biased behavior derives from spontaneous neural connectivity, supporting the fundamental self hypothesis. Thus, we propose an integrated neural network model of this fundamental self that synthesizes previous theoretical models and portrays the brain mechanisms by which the self emerges at rest internally and regulates responses to the external environment.
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Affiliation(s)
- Yongfa Zhang
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China
| | - Fei Wang
- Department of Psychology, School of Social Sciences, Tsinghua University, Beijing 100084, China; Laboratory of Brain and Intelligence, Tsinghua University, Beijing 100084, China; The Centre for Positive Psychology Research, Tsinghua University, Beijing 100084, China.
| | - Jie Sui
- School of Psychology, University of Aberdeen, Aberdeen AB24 3FX, Scotland, Great Britain
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5
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Eraifej J, Cabral J, Fernandes HM, Kahan J, He S, Mancini L, Thornton J, White M, Yousry T, Zrinzo L, Akram H, Limousin P, Foltynie T, Aziz TZ, Deco G, Kringelbach M, Green AL. Modulation of limbic resting-state networks by subthalamic nucleus deep brain stimulation. Netw Neurosci 2023; 7:478-495. [PMID: 37397890 PMCID: PMC10312264 DOI: 10.1162/netn_a_00297] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 11/29/2022] [Indexed: 09/03/2023] Open
Abstract
Beyond the established effects of subthalamic nucleus deep brain stimulation (STN-DBS) in reducing motor symptoms in Parkinson's disease, recent evidence has highlighted the effect on non-motor symptoms. However, the impact of STN-DBS on disseminated networks remains unclear. This study aimed to perform a quantitative evaluation of network-specific modulation induced by STN-DBS using Leading Eigenvector Dynamics Analysis (LEiDA). We calculated the occupancy of resting-state networks (RSNs) in functional MRI data from 10 patients with Parkinson's disease implanted with STN-DBS and statistically compared between ON and OFF conditions. STN-DBS was found to specifically modulate the occupancy of networks overlapping with limbic RSNs. STN-DBS significantly increased the occupancy of an orbitofrontal limbic subsystem with respect to both DBS OFF (p = 0.0057) and 49 age-matched healthy controls (p = 0.0033). Occupancy of a diffuse limbic RSN was increased with STN-DBS OFF when compared with healthy controls (p = 0.021), but not when STN-DBS was ON, which indicates rebalancing of this network. These results highlight the modulatory effect of STN-DBS on components of the limbic system, particularly within the orbitofrontal cortex, a structure associated with reward processing. These results reinforce the value of quantitative biomarkers of RSN activity in evaluating the disseminated impact of brain stimulation techniques and the personalization of therapeutic strategies.
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Affiliation(s)
- John Eraifej
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Henrique M. Fernandes
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Joshua Kahan
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Shenghong He
- MRC Brain Network Dynamics Unit, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - John Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Mark White
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Tarek Yousry
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, University College London, London, United Kingdom
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, United Kingdom
| | - Ludvic Zrinzo
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Harith Akram
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Patricia Limousin
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tom Foltynie
- Sobell Department for Motor Neurosciences and Movement Disorders, UCL Institute of Neurology, London, United Kingdom
| | - Tipu Z. Aziz
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Universitat Pompeu Fabra, Barcelona, Spain
- Institució Catalana de la Recerca i Estudis Avançats, Barcelona, Spain
- Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Morten Kringelbach
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Alexander L. Green
- Oxford Functional Neurosurgery Group, Nuffield Department of Surgical Sciences, University of Oxford, Oxford, United Kingdom
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6
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Kurtin DL, Scott G, Hebron H, Skeldon AC, Violante IR. Task-based differences in brain state dynamics and their relation to cognitive ability. Neuroimage 2023; 271:119945. [PMID: 36870433 DOI: 10.1016/j.neuroimage.2023.119945] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 02/06/2023] [Accepted: 02/14/2023] [Indexed: 03/06/2023] Open
Abstract
Transient patterns of interregional connectivity form and dissipate in response to varying cognitive demands. Yet, it is not clear how different cognitive demands influence brain state dynamics, and whether these dynamics relate to general cognitive ability. Here, using functional magnetic resonance imaging (fMRI) data, we characterised shared, recurrent, global brain states in 187 participants across the working memory, emotion, language, and relation tasks from the Human Connectome Project. Brain states were determined using Leading Eigenvector Dynamics Analysis (LEiDA). In addition to the LEiDA-based metrics of brain state lifetimes and probabilities, we also computed information-theoretic measures of Block Decomposition Method of complexity, Lempel-Ziv complexity and transition entropy. Information theoretic metrics are notable in their ability to compute relationships amongst sequences of states over time, compared to lifetime and probability, which capture the behaviour of each state in isolation. We then related task-based brain state metrics to fluid intelligence. We observed that brain states exhibited stable topology across a range of numbers of clusters (K = 2:15). Most metrics of brain state dynamics, including state lifetime, probability, and all information theoretic metrics, reliably differed between tasks. However, relationships between state dynamic metrics and cognitive abilities varied according to the task, the metric, and the value of K, indicating that there are contextual relationships between task-dependant state dynamics and trait cognitive ability. This study provides evidence that the brain reconfigures across time in response to cognitive demands, and that there are contextual, rather than generalisable, relationships amongst task, state dynamics, and cognitive ability.
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Affiliation(s)
- Danielle L Kurtin
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK.
| | - Gregory Scott
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK; Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Henry Hebron
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK; UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK
| | - Anne C Skeldon
- UK Dementia Research Institute, Care Research and Technology Centre at Imperial College, London and the University of Surrey, Guildford, UK; Department of Mathematics, Faculty of Engineering and Physical Sciences, University of Surrey, Guildford, UK
| | - Ines R Violante
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
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7
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Wang C, Yang L, Lin Y, Wang C, Tian P. Alteration of resting-state network dynamics in autism spectrum disorder based on leading eigenvector dynamics analysis. Front Integr Neurosci 2023; 16:922577. [PMID: 36743477 PMCID: PMC9892631 DOI: 10.3389/fnint.2022.922577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 12/23/2022] [Indexed: 01/20/2023] Open
Abstract
Background Neurobiological models to explain the vulnerability of autism spectrum disorders (ASDs) are scarce, and previous resting-state functional magnetic resonance imaging (rs-fMRI) studies mostly examined static functional connectivity (FC). Given that FC constantly evolves, it is critical to probe FC dynamic differences in ASD patients. Methods We characterized recurring phase-locking (PL) states during rest in 45 ASD patients and 47 age- and sex-matched healthy controls (HCs) using Leading Eigenvector Dynamics Analysis (LEiDA) and probed the organization of PL states across different fine grain sizes. Results Our results identified five different groups of discrete resting-state functional networks, which can be defined as recurrent PL state overtimes. Specifically, ASD patients showed an increased probability of three PL states, consisting of the visual network (VIS), frontoparietal control network (FPN), default mode network (DMN), and ventral attention network (VAN). Correspondingly, ASD patients also showed a decreased probability of two PL states, consisting of the subcortical network (SUB), somatomotor network (SMN), FPN, and VAN. Conclusion Our findings suggested that the temporal reorganization of brain discrete networks was closely linked to sensory to cognitive systems of the brain. Our study provides new insights into the dynamics of brain networks and contributes to a deeper understanding of the neurological mechanisms of ASD.
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Affiliation(s)
- Chaoyan Wang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Lu Yang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yanan Lin
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Caihong Wang
- Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Peichao Tian
- Department of Pediatrics, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China,*Correspondence: Peichao Tian,
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8
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Marschall TM, Koops S, Brederoo SG, Cabral J, Ćurčić-Blake B, Sommer IEC. Time varying dynamics of hallucinations in clinical and non-clinical voice-hearers. Neuroimage Clin 2023; 37:103351. [PMID: 36805417 PMCID: PMC9969260 DOI: 10.1016/j.nicl.2023.103351] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 01/24/2023] [Accepted: 02/12/2023] [Indexed: 02/16/2023]
Abstract
Auditory verbal hallucinations (AVH) are frequently associated with psychotic disorders, yet also occur in non-clinical voice-hearers. AVH in this group are similar to those within clinical voice-hearers in terms of several phenomenological aspects, but non-clinical voice-hearers report to have more control over their AVH and attribute less emotional valence to them. These dissimilarities may stem from differences on the neurobiological level, as it is still under debate whether the mechanisms involved in AVH are the same in clinical and non-clinical voice-hearers. In this study, 21 clinical and 21 non-clinical voice-hearers indicated the onset and offsets of AVH during an fMRI scan. Using a method called leading eigenvector dynamics analysis (LEiDA), we examined time-varying dynamics of functional connectivity involved in AVH with a sub-second temporal resolution. We assessed differences between groups, and between hallucination and rest periods in dwell time, switching frequency, probability of occurrence, and transition probabilities of nine recurrent states of functional connectivity with a permutation ANOVA. Deviations in dwell times, switching frequencies, and switch probabilities in the hallucination period indicated more erratic dynamics during this condition regardless of their clinical status. Post-hoc analyses of the dwell times exhibited the most distinct differences between the rest and hallucination condition for the non-clinical sample, suggesting stronger differences between the two conditions in this group. Overall, these findings suggest that the neurobiological mechanisms involved in AVH are similar in clinical and non-clinical individuals.
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Affiliation(s)
- Theresa M Marschall
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands.
| | - Sanne Koops
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| | - Sanne G Brederoo
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| | - Joana Cabral
- Centre for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, UK; Life and Health Sciences Research Institute, School of Medicine, University of Minho, Braga, Portugal
| | - Branislava Ćurčić-Blake
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
| | - Iris E C Sommer
- University of Groningen, Department of Psychiatry, University Medical Center Groningen, Groningen, The Netherlands
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9
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Caetano I, Ferreira S, Coelho A, Amorim L, Castanho TC, Portugal-Nunes C, Soares JM, Gonçalves N, Sousa R, Reis J, Lima C, Marques P, Moreira PS, Rodrigues AJ, Santos NC, Morgado P, Magalhães R, Picó-Pérez M, Cabral J, Sousa N. Perceived stress modulates the activity between the amygdala and the cortex. Mol Psychiatry 2022; 27:4939-4947. [PMID: 36117211 DOI: 10.1038/s41380-022-01780-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/01/2022] [Revised: 08/31/2022] [Accepted: 09/02/2022] [Indexed: 01/14/2023]
Abstract
The significant link between stress and psychiatric disorders has prompted research on stress's impact on the brain. Interestingly, previous studies on healthy subjects have demonstrated an association between perceived stress and amygdala volume, although the mechanisms by which perceived stress can affect brain function remain unknown. To better understand what this association entails at a functional level, herein, we explore the association of perceived stress, measured by the PSS10 questionnaire, with disseminated functional connectivity between brain areas. Using resting-state fMRI from 252 healthy subjects spanning a broad age range, we performed both a seed-based amygdala connectivity analysis (static connectivity, with spatial resolution but no temporal definition) and a whole-brain data-driven approach to detect altered patterns of phase interactions between brain areas (dynamic connectivity with spatiotemporal information). Results show that increased perceived stress is directly associated with increased amygdala connectivity with frontal cortical regions, which is driven by a reduced occurrence of an activity pattern where the signals in the amygdala and the hippocampus evolve in opposite directions with respect to the rest of the brain. Overall, these results not only reinforce the pathological effect of in-phase synchronicity between subcortical and cortical brain areas but also demonstrate the protective effect of counterbalanced (i.e., phase-shifted) activity between brain subsystems, which are otherwise missed with correlation-based functional connectivity analysis.
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Affiliation(s)
- Inês Caetano
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Sónia Ferreira
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Ana Coelho
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Liliana Amorim
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal.,Association P5 Digital Medical Center (ACMP5), 4710-057, Braga, Portugal
| | - Teresa Costa Castanho
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal.,Association P5 Digital Medical Center (ACMP5), 4710-057, Braga, Portugal
| | - Carlos Portugal-Nunes
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal.,CECAV-Veterinary and Animal Science Research Centre, Quinta de Prados, 5000-801, Vila Real, Portugal
| | - José Miguel Soares
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Nuno Gonçalves
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Rui Sousa
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal.,Departamento de Psiquiatria e Saúde Mental, Centro Hospitalar Tondela-Viseu, 3500-228, Viseu, Portugal
| | - Joana Reis
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Catarina Lima
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Paulo Marques
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Pedro Silva Moreira
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Ana João Rodrigues
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Nadine Correia Santos
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Pedro Morgado
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Ricardo Magalhães
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Maria Picó-Pérez
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal.,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal.,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal
| | - Nuno Sousa
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, 4710-057, Braga, Portugal. .,ICVS/3B's, PT Government Associate Laboratory, 4710-057, Braga/Guimarães, Portugal. .,Clinical Academic Center-Braga (2CA), 4710-243, Braga, Portugal. .,Association P5 Digital Medical Center (ACMP5), 4710-057, Braga, Portugal.
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10
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Olsen AS, Lykkebo-Valløe A, Ozenne B, Madsen MK, Stenbæk DS, Armand S, Mørup M, Ganz M, Knudsen GM, Fisher PM. Psilocybin modulation of time-varying functional connectivity is associated with plasma psilocin and subjective effects. Neuroimage 2022; 264:119716. [PMID: 36341951 DOI: 10.1016/j.neuroimage.2022.119716] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 10/11/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Psilocin, the neuroactive metabolite of psilocybin, is a serotonergic psychedelic that induces an acute altered state of consciousness, evokes lasting changes in mood and personality in healthy individuals, and has potential as an antidepressant treatment. Examining the acute effects of psilocin on resting-state time-varying functional connectivity implicates network-level connectivity motifs that may underlie acute and lasting behavioral and clinical effects. AIM Evaluate the association between resting-state time-varying functional connectivity (tvFC) characteristics and plasma psilocin level (PPL) and subjective drug intensity (SDI) before and right after intake of a psychedelic dose of psilocybin in healthy humans. METHODS Fifteen healthy individuals completed the study. Before and at multiple time points after psilocybin intake, we acquired 10-minute resting-state blood-oxygen-level-dependent functional magnetic resonance imaging scans. Leading Eigenvector Dynamics Analysis (LEiDA) and diametrical clustering were applied to estimate discrete, sequentially active brain states. We evaluated associations between the fractional occurrence of brain states during a scan session and PPL and SDI using linear mixed-effects models. We examined associations between brain state dwell time and PPL and SDI using frailty Cox proportional hazards survival analysis. RESULTS Fractional occurrences for two brain states characterized by lateral frontoparietal and medial fronto-parietal-cingulate coherence were statistically significantly negatively associated with PPL and SDI. Dwell time for these brain states was negatively associated with SDI and, to a lesser extent, PPL. Conversely, fractional occurrence and dwell time of a fully connected brain state partly associated with motion was positively associated with PPL and SDI. CONCLUSION Our findings suggest that the acute perceptual psychedelic effects induced by psilocybin may stem from drug-level associated decreases in the occurrence and duration of lateral and medial frontoparietal connectivity motifs. We apply and argue for a modified approach to modeling eigenvectors produced by LEiDA that more fully acknowledges their underlying structure. Together these findings contribute to a more comprehensive neurobiological framework underlying acute effects of serotonergic psychedelics.
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Affiliation(s)
- Anders S Olsen
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark; Department of Applied Mathematics and Computer Science, DTU Compute, Kgs. Lyngby, Denmark
| | - Anders Lykkebo-Valløe
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Brice Ozenne
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark; Department of Public Health, Section of Biostatistics, University of Copenhagen, Copenhagen, Denmark
| | - Martin K Madsen
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Dea S Stenbæk
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark; Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Sophia Armand
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | - Morten Mørup
- Department of Applied Mathematics and Computer Science, DTU Compute, Kgs. Lyngby, Denmark
| | - Melanie Ganz
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark; Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Gitte M Knudsen
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark; Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Patrick M Fisher
- Neurobiology Research Unit and NeuroPharm, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark.
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11
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Cahart MS, Dell’Acqua F, Giampietro V, Cabral J, Timmers M, Streffer J, Einstein S, Zelaya F, Williams SCR, O’Daly O. Test-retest reliability of time-varying patterns of brain activity across single band and multiband resting-state functional magnetic resonance imaging in healthy older adults. Front Hum Neurosci 2022; 16:980280. [PMID: 36438643 PMCID: PMC9685802 DOI: 10.3389/fnhum.2022.980280] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Accepted: 10/25/2022] [Indexed: 12/23/2023] Open
Abstract
Leading Eigenvector Dynamics Analysis (LEiDA) is an analytic approach that characterizes brain activity recorded with functional Magnetic Resonance Imaging (fMRI) as a succession of discrete phase-locking patterns, or states, that consistently recur over time across all participants. LEiDA allows for the extraction of three state-related measures which have previously been key to gaining a better understanding of brain dynamics in both healthy and clinical populations: the probability of occurrence of a given state, its lifetime and the probability of switching from one state to another. The degree to which test-retest reliability of the LEiDA measures may be affected by increasing MRI multiband (MB) factors in comparison with single band sequences is yet to be established. In this study, 24 healthy older adults were scanned over three sessions, on weeks 0, 1, and 4. On each visit, they underwent a conventional single band resting-state fMRI (rs-fMRI) scan and three different MB rs-fMRI scans, with MB factors of 4, with and without in-plane acceleration, and 6 without in-plane acceleration. We found test-retest reliability scores to be significantly higher with MB factor 4 with and without in-plane acceleration for most cortical networks. These findings will inform the choice of acquisition parameters for future studies and clinical trials.
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Affiliation(s)
- Marie-Stephanie Cahart
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Flavio Dell’Acqua
- NatBrainLab, Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Vincent Giampietro
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Joana Cabral
- Life and Health Sciences Research Institute, University of Minho, Braga, Portugal
| | - Maarten Timmers
- Janssen Research and Development, A Division of Janssen Pharmaceutica NV, Beerse, Belgium
| | - Johannes Streffer
- AC Immune SA, Lausanne, Switzerland
- Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | | | - Fernando Zelaya
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Steven C. R. Williams
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Owen O’Daly
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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12
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Fasano MC, Cabral J, Stevner A, Vuust P, Cantou P, Brattico E, Kringelbach ML. The early adolescent brain on music: Analysis of functional dynamics reveals engagement of orbitofrontal cortex reward system. Hum Brain Mapp 2022; 44:429-446. [PMID: 36069619 PMCID: PMC9842905 DOI: 10.1002/hbm.26060] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/19/2022] [Accepted: 08/07/2022] [Indexed: 01/25/2023] Open
Abstract
Music listening plays a pivotal role for children and adolescents, yet it remains unclear how music modulates brain activity at the level of functional networks in this young population. Analysing the dynamics of brain networks occurring and dissolving over time in response to music can provide a better understanding of the neural underpinning of music listening. We collected functional magnetic resonance imaging (fMRI) data from 17 preadolescents aged 10-11 years while listening to two similar music pieces separated by periods without music. We subsequently tracked the occurrence of functional brain networks over the recording time using a recent method that detects recurrent patterns of phase-locking in the fMRI signals: the leading eigenvector dynamics analysis (LEiDA). The probabilities of occurrence and switching profiles of different functional networks were compared between periods of music and no music. Our results showed significantly increased occurrence of a specific functional network during the two music pieces compared to no music, involving the medial orbitofrontal and ventromedial prefrontal cortices-a brain subsystem associated to reward processing. Moreover, the higher the musical reward sensitivity of the preadolescents, the more this network was preceded by a pattern involving the insula. Our findings highlight the involvement of a brain subsystem associated with hedonic and emotional processing during music listening in the early adolescent brain. These results offer novel insight into the neural underpinnings of musical reward in early adolescence, improving our understanding of the important role and the potential benefits of music at this delicate age.
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Affiliation(s)
- Maria Celeste Fasano
- Department of Psychology and Behavioural SciencesAarhus UniversityAarhusDenmark,Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark,Centre for Eudaimonia and Human FlourishingLinacre College, University of OxfordOxfordUK
| | - Joana Cabral
- Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark,Centre for Eudaimonia and Human FlourishingLinacre College, University of OxfordOxfordUK,Life and Health Sciences Research Institute (ICVS), School of MedicineUniversity of MinhoBragaPortugal
| | - Angus Stevner
- Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark
| | - Peter Vuust
- Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark
| | - Pauline Cantou
- Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark
| | - Elvira Brattico
- Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark,Department of PsychologyEducational Sciences, Communication, University of BariBariItaly
| | - Morten L. Kringelbach
- Center for Music in the Brain, Department of Clinical MedicineAarhus University & The Royal Academy of Music Aarhus/AalborgAarhusDenmark,Centre for Eudaimonia and Human FlourishingLinacre College, University of OxfordOxfordUK,Department of PsychiatryUniversity of OxfordOxfordUK
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13
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Farinha M, Amado C, Morgado P, Cabral J. Increased Excursions to Functional Networks in Schizophrenia in the Absence of Task. Front Neurosci 2022; 16:821179. [PMID: 35360175 PMCID: PMC8963765 DOI: 10.3389/fnins.2022.821179] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/10/2022] [Indexed: 01/10/2023] Open
Abstract
Schizophrenia is a chronic psychotic disorder characterized by the disruption of thought processes, perception, cognition, and behaviors, for which there is still a lack of objective and quantitative biomarkers in brain activity. Using functional magnetic resonance imaging (fMRI) data from an open-source database, this study investigated differences between the dynamic exploration of resting-state networks in 71 schizophrenia patients and 74 healthy controls. Focusing on recurrent states of phase coherence in fMRI signals, brain activity was examined for intergroup differences through the lens of dynamical systems theory. Results showed reduced fractional occupancy and dwell time of a globally synchronized state in schizophrenia. Conversely, patients exhibited increased fractional occupancy, dwell time and limiting probability of being in states during which canonical functional networks—i.e., Limbic, Dorsal Attention and Somatomotor—synchronized in anti-phase with respect to the rest of the brain. In terms of state-to-state transitions, patients exhibited increased probability of switching to Limbic, Somatomotor and Visual networks, and reduced probability of remaining in states related to the Default Mode network, the Orbitofrontal network and the globally synchronized state. All results revealed medium to large effect sizes. Combined, these findings expose pronounced differences in the temporal expression of resting-state networks in schizophrenia patients, which may relate to the pathophysiology of this disorder. Overall, these results reinforce the utility of dynamical systems theory to extend current knowledge regarding disrupted brain dynamics in psychiatric disorders.
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Affiliation(s)
- Miguel Farinha
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Centro Clínico Académico Hospital de Braga, Braga, Portugal
- *Correspondence: Miguel Farinha
| | - Conceição Amado
- Department of Mathematics and CEMAT, Instituto Superior Tècnico, University of Lisbon, Lisbon, Portugal
| | - Pedro Morgado
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Centro Clínico Académico Hospital de Braga, Braga, Portugal
| | - Joana Cabral
- Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Braga, Portugal
- ICVS/3B's—PT Government Associate Laboratory, Braga/Guimarães, Portugal
- Center for Eudaimonia and Human Flourishing, Linacre College, University of Oxford, Oxford, United Kingdom
- Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
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14
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Suo X, Guo L, Fu D, Ding H, Li Y, Qin W. A Comparative Study of Diffusion Fiber Reconstruction Models for Pyramidal Tract Branches. Front Neurosci 2021; 15:777377. [PMID: 34955727 PMCID: PMC8698251 DOI: 10.3389/fnins.2021.777377] [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: 09/15/2021] [Accepted: 11/02/2021] [Indexed: 11/13/2022] Open
Abstract
Currently, comparative studies evaluating the quantification accuracy of pyramidal tracts (PT) and PT branches that were tracked based on four mainstream diffusion models are deficient. The present study aims to evaluate four mainstream models using the high-quality Human Connectome Project (HCP) dataset. Diffusion tensor imaging (DTI), diffusion spectral imaging (DSI), generalized Q-space sampling imaging (GQI), and Q-ball imaging (QBI) were used to construct the PT and PT branches in 50 healthy volunteers from the HCP. False and true PT fibers were identified based on anatomic information. One-way repeated measure analysis of variance and post hoc paired-sample t-test were performed to identify the best PT and PT branch quantification model. The number, percentage, and density of true fibers of PT obtained based on GQI and QBI were significantly larger than those based on DTI and DSI (all p < 0.0005, Bonferroni corrected), whereas false fibers yielded the opposite results (all p < 0.0005, Bonferroni corrected). More trunk branches (PTtrunk) were present in the four diffusion models compared with the upper limb (PTUlimb), lower limb (PTLlimb), and cranial (PTcranial) branches. In addition, significantly more true fibers were obtained in PTtrunk, PTUlimb, and PTLlimb based on the GQI and QBI compared with DTI and DSI (all p < 0.0005, Bonferroni corrected). Finally, GQI-based group probabilistic maps showed that the four PT branches exhibited relatively unique spatial distributions. Therefore, the GQI and QBI represent better diffusion models for the PT and PT branches. The group probabilistic maps of PT branches have been shared with the public to facilitate more precise studies on the plasticity of and the damage to the motor pathway.
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Affiliation(s)
- Xinjun Suo
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Lining Guo
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Dianxun Fu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
| | - Hao Ding
- Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China.,School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Yihong Li
- School of Medical Imaging, Tianjin Medical University, Tianjin, China
| | - Wen Qin
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China.,Tianjin Key Lab of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, China
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15
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Yao W, Chen H, Sheng X, Zhao H, Xu Y, Bai F. Core-Centered Connection Abnormalities Associated with Pathological Features Mediate the Progress of Cognitive Impairments in Alzheimer's Disease Spectrum Patients. J Alzheimers Dis 2021; 82:1499-1511. [PMID: 34180417 DOI: 10.3233/jad-210481] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Abnormal default mode network (DMN) was associated with the progress of Alzheimer's disease (AD). Rather than treat the DMN as a unitary network, it can be further divided into three subsystems with different functions. OBJECTIVE It remains unclear the interactions of DMN subsystems associated with the progress of cognitive impairments and AD pathological features. METHODS This study has recruited 187 participants, including test data and verification data. Firstly, an imaging analysis approach was utilized to investigate disease-related differences in the interactions of DMN subsystems in test data (n = 149), including 42 cognitively normal subjects, 43 early mild cognitive impairment (EMCI), 32 late mild cognitive impairment (LMCI), and 32 AD patients. Brain-behavior-pathological relationships regarding to the interactions among DMN subsystems were then further examined. Secondly, DMN subsystems abnormalities for classifying AD spectrum population in the independent verification data (n = 38). RESULTS This study found that the impaired cognition relates to disturbances in the interactions between DMN subsystems but preferentially in core subsystem, and the abnormal regulatory processes of core subsystem were significantly associated with the levels of cerebrospinal fluid Aβ and tau in AD-spectrum patients. Meantime, the nonlinear relationship between dysfunctional core subsystem and impaired cognition was observed as one progresses through the stages of MCI to AD. Importantly, this classification presented a higher sensitivity and specificity dependent on the core-centered connection abnormalities. CONCLUSION The abnormal interaction patterns of DMN subsystems at an early stage of AD appeared and presented as core-centered connection abnormalities, which were the potential neuroimaging features for monitoring the development of AD.
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Affiliation(s)
- Weina Yao
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Haifeng Chen
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Xiaoning Sheng
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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16
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Hypostability in the default mode network and hyperstability in the frontoparietal control network of dynamic functional architecture during rumination. Neuroimage 2021; 241:118427. [PMID: 34311069 DOI: 10.1016/j.neuroimage.2021.118427] [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: 02/08/2021] [Revised: 06/19/2021] [Accepted: 07/22/2021] [Indexed: 11/22/2022] Open
Abstract
The neural underpinnings of rumination can be characterized by its specific dynamic nature. Temporal stability is the stable and consistent representation of information by a distributed neural activity and connectivity pattern across brain regions. Although stability is a key feature of the brain's functional architecture, its profiles supporting rumination remain elusive. We characterized the stability of the whole-brain functional architecture during an induced, continuous rumination state and compared it with a well-constrained distraction state as the control condition in a group of healthy participants (N = 40). We further examined the relationship between stability in regions showing a significant effect on the rumination vs. distraction contrast and rumination traits. The variability of dynamic functional connectivities (FCs) among these regions was also explored to determine the potential coupling regions that drove the altered stability pattern during rumination. The results showed that rumination was characterized by a similar but altered stability profile compared with distraction and resting states. Comparison between rumination and distraction revealed that key regions of the default mode network (DMN), such as the medial prefrontal cortex (MPFC) and bilateral parahippocampal gyrus (PHG), which showed decreased stability while frontoparietal control network (FPCN) regions, including the inferior parietal lobule (IPL) and dorsal lateral prefrontal cortex (DLPFC), showed significantly enhanced stability in rumination compared with distraction. Additionally, stability in the MPFC and IPL was related to individual differences in rumination traits. Exploratory analysis of the variation in dynamic FCs suggested that higher stability in the IPL may be related to its less variable FCs with the PHG. Together, these findings implicated that rumination may be supported by the dissociated dynamic nature of hypostability in the DMN and hyperstability in the FPCN.
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Larabi DI, Marsman JBC, Aleman A, Tijms BM, Opmeer EM, Pijnenborg GHM, van der Meer L, van Tol MJ, Ćurčić-Blake B. Insight does not come at random: Individual gray matter networks relate to clinical and cognitive insight in schizophrenia. Prog Neuropsychopharmacol Biol Psychiatry 2021; 109:110251. [PMID: 33493651 DOI: 10.1016/j.pnpbp.2021.110251] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/11/2020] [Accepted: 01/13/2021] [Indexed: 12/28/2022]
Abstract
BACKGROUND Impaired clinical and cognitive insight are prevalent in schizophrenia and relate to poorer outcome. Good insight has been suggested to depend on social cognitive and metacognitive abilities requiring global integration of brain signals. Impaired insight has been related to numerous focal gray matter (GM) abnormalities distributed across the brain suggesting dysconnectivity at the global level. In this study, we test whether global integration deficiencies reflected in gray matter network connectivity underlie individual variations in insight. METHODS We used graph theory to examine whether individual GM-network metrics relate to insight in patients with a psychotic disorder (n = 114). Clinical insight was measured with the Schedule for the Assessment of Insight-Expanded and item G12 of the Positive and Negative Syndrome Scale, and cognitive insight with the Beck Cognitive Insight Scale. Individual GM-similarity networks were created from GM-segmentations of T1-weighted MRI-scans. Graph metrics were calculated using the Brain Connectivity Toolbox. RESULTS Networks of schizophrenia patients with poorer clinical insight showed less segregation (i.e. clustering coefficient) into specialized subnetworks at the global level. Schizophrenia patients with poorer cognitive insight showed both less segregation and higher connectedness (i.e. lower path length) of their brain networks, making their network topology more "random". CONCLUSIONS Our findings suggest less segregated processing of information in patients with poorer cognitive and clinical insight, in addition to higher connectedness in patients with poorer cognitive insight. The ability to take a critical perspective on one's symptoms (clinical insight) or views (cognitive insight) might depend especially on segregated specialized processing within distinct subnetworks.
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Affiliation(s)
- Daouia I Larabi
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands; Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Wilhelm-Johnen-Straße, 52428 Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Gurlittstraße 55, 40223 Düsseldorf, Germany.
| | - Jan-Bernard C Marsman
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands
| | - André Aleman
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands; Department of Clinical and Developmental Neuropsychology, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, the Netherlands
| | - Betty M Tijms
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center, PO Box 7057, 1007 MB Amsterdam, the Netherlands
| | - Esther M Opmeer
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands; Department of Health and Welfare, University of Applied Sciences Windesheim, Campus 2, 8017 CA Zwolle, the Netherlands
| | - Gerdina H M Pijnenborg
- Department of Clinical and Developmental Neuropsychology, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, the Netherlands; Department of Psychotic Disorders, GGZ Drenthe, Dennenweg 9, 9404 LA Assen, the Netherlands
| | - Lisette van der Meer
- Department of Clinical and Developmental Neuropsychology, University of Groningen, Grote Kruisstraat 2/1, 9712 TS Groningen, the Netherlands; Department of Psychiatric Rehabilitation, Lentis Psychiatric Institute, Lagerhout E35, 9741 KE Zuidlaren, the Netherlands; Rob Giel Research Center, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, the Netherlands
| | - Marie-José van Tol
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands
| | - Branislava Ćurčić-Blake
- Department of Biomedical Sciences of Cells and Systems, Cognitive Neuroscience Center, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 2, 9713 AW Groningen, the Netherlands
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Wei XY, Chen H, Guo C, Tan WL, Zhan SH. The Instant and Sustained Effect of Electroacupuncture in Postgraduate Students with Depression: An fMRI Study. Neuropsychiatr Dis Treat 2021; 17:873-883. [PMID: 33776442 PMCID: PMC7989050 DOI: 10.2147/ndt.s307083] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 03/08/2021] [Indexed: 12/24/2022] Open
Abstract
OBJECTION This study was a primary study to evaluate the instant and sustained effect of electroacupuncture (EA) at GV20 (Baihui) in postgraduate students with mild depression by using a special flexible head coil. METHODS A total of 20 postgraduate students with mild depression underwent EA stimulation at GV20 and 3 phases of resting-state functional magnetic resonance imaging (rs-fMRI) scanning. Phase I: Preparation (before needle insertion); Phase II: during EA; Phase III: 15 minutes after needle removal. The Rs-fMRI data were processed using DPABI and SPSS 25. RESULTS 1) ReHo values showed significantly differences in the right posterior cingulate cortex, right calcarine gyrus, right angular gyrus, right precuneus, right cuneus, and bilateral postcentral gyri among Phase I, Phase II and Phase III; 2) Relative to the Phase I, increased brain activity in the Phase II was observed in the bilateral postcentral gyri, right calcarine gyrus, right cuneus. Compared with the Phase II, decreased brain activity in the Phase III was observed in the right precuneus, right posterior cingulate cortex, right angular gyrus. Relative to the Phase I, Significantly increased brain activity in the Phase III was observed in the right calcarine gyrus, right cuneus, and bilateral postcentral gyri. While decreased ReHo values were found in the right posterior cingulate cortex, right angular gyrus, right precuneus; and 3) Correlation analysis showed that the ReHo values of multiple brain regions in Phase I and Phase III were significantly correlated with the VAS and HRSD-17 scores. CONCLUSION This study focuses on the instant and sustained effect in postgraduate students with depression. Our study showed that instant effect produced by EA stimulation at GV20 firstly induced changes in somatosensory and visual area, and then, sustained effect (Phase III) have a higher intensity and more extensive than instant effects. Meanwhile, we provide a visualization way to study the instant effects of head acupoints by using a flexible head coil.
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Affiliation(s)
- Xiang-Yu Wei
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Hui Chen
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Cui Guo
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Wen-Li Tan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
| | - Song-Hua Zhan
- Department of Radiology, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201203, People's Republic of China
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Alonso Martínez S, Deco G, Ter Horst GJ, Cabral J. The Dynamics of Functional Brain Networks Associated With Depressive Symptoms in a Nonclinical Sample. Front Neural Circuits 2020; 14:570583. [PMID: 33071760 PMCID: PMC7530893 DOI: 10.3389/fncir.2020.570583] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 08/26/2020] [Indexed: 12/17/2022] Open
Abstract
Brain function depends on the flexible and dynamic coordination of functional subsystems within distributed neural networks operating on multiple scales. Recent progress has been made in the characterization of functional connectivity (FC) at the whole-brain scale from a dynamic, rather than static, perspective, but its validity for cognitive sciences remains under debate. Here, we analyzed brain activity recorded with functional Magnetic Resonance Imaging from 71 healthy participants evaluated for depressive symptoms after a relationship breakup based on the conventional Major Depression Inventory (MDI). We compared both static and dynamic FC patterns between participants reporting high and low depressive symptoms. Between-group differences in static FC were estimated using a standard pipeline for network-based statistic (NBS). Additionally, FC was analyzed from a dynamic perspective by characterizing the occupancy, lifetime, and transition profiles of recurrent FC patterns. Recurrent FC patterns were defined by clustering the BOLD phase-locking patterns obtained using leading eigenvector dynamics analysis (LEiDA). NBS analysis revealed a brain subsystem exhibiting significantly lower within-subsystem correlation values in more depressed participants (high MDI). This subsystem predominantly comprised connections between regions of the default mode network (i.e., precuneus) and regions outside this network. On the other hand, LEiDA results showed that high MDI participants engaged more in a state connecting regions of the default mode, memory retrieval, and frontoparietal network (p-FDR = 0.012); and less in a state connecting mostly the visual and dorsal attention systems (p-FDR = 0.004). Although both our analyses on static and dynamic FC implicate the role of the precuneus in depressive symptoms, only including the temporal evolution of BOLD FC helped to disentangle over time the distinct configurations in which this region plays a role. This finding further indicates that a holistic understanding of brain function can only be gleaned if the temporal dynamics of FC is included.
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Affiliation(s)
- Sonsoles Alonso Martínez
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Gert J Ter Horst
- Cognitive Neuroscience Center, Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, Groningen, Netherlands
| | - Joana Cabral
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom.,Center for Music in the Brain, Aarhus University, Aarhus, Denmark.,Life and Health Sciences Research Institute (ICVS), University of Minho, Minho, Portugal
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