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Zhang Y, Guo L, Gu Z, Yang Q, Han S, Zhang H. Short-Term Restriction of Physical and Social Activities Effects on Brain Structure and Connectivity. Brain Sci 2024; 15:7. [PMID: 39851375 PMCID: PMC11764288 DOI: 10.3390/brainsci15010007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2024] [Revised: 12/10/2024] [Accepted: 12/19/2024] [Indexed: 01/26/2025] Open
Abstract
BACKGROUND Prolonged confinement in enclosed environments has raised concerns about its effects on both physical and mental health. Although increased rates of depression or anxiety during COVID-19 lockdowns have been reported, the effects of short-term restrictions on social activities and physical on brain function and structure remain poorly known. METHODS This study explored longitudinal changes in brain gray matter volume (GMV) and functional connectivity (FC) immediately after and four months following a short-term lockdown in comparison to pre-lockdown conditions. MRI data were collected from 20 participants before the lockdown, from 29 participants (14 original, 15 new) two months post-lockdown, and from 27 out of the 29 participants four months post-lifting of the lockdown. RESULTS Results showed significant GMV reductions in the right gyrus rectus and cuneus post-lockdown, with further reductions observed four months after lifting the restrictions, affecting additional brain regions. Longitudinal FC trajectories revealed decreased connectivity between the default mode network (DMN) and sensorimotor/attention networks post-lockdown, and recovery after four months post-lifting of the lockdown. CONCLUSIONS The observed plasticity in brain FC indicates substantial recovery potential with the potential long-term effect of structural changes. Our findings offer insights into the effects of isolation on the human brain, potentially informing rehabilitation mechanisms and interventions for individuals in similar conditions.
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Affiliation(s)
- Yajuan Zhang
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China; (Y.Z.); (L.G.); (Z.G.); (S.H.)
| | - Lianghu Guo
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China; (Y.Z.); (L.G.); (Z.G.); (S.H.)
| | - Zhuoyang Gu
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China; (Y.Z.); (L.G.); (Z.G.); (S.H.)
| | - Qing Yang
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China; (Y.Z.); (L.G.); (Z.G.); (S.H.)
| | - Siyan Han
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China; (Y.Z.); (L.G.); (Z.G.); (S.H.)
| | - Han Zhang
- School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices, ShanghaiTech University, Shanghai 201210, China; (Y.Z.); (L.G.); (Z.G.); (S.H.)
- Shanghai Clinical Research and Trial Center, Shanghai 201210, China
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Fu L, Aximu R, Zhao G, Chen Y, Sun Z, Xue H, Wang S, Zhang N, Zhang Z, Lei M, Zhai Y, Xu J, Sun J, Ma J, Liu F. Mapping the landscape: a bibliometric analysis of resting-state fMRI research on schizophrenia over the past 25 years. SCHIZOPHRENIA (HEIDELBERG, GERMANY) 2024; 10:35. [PMID: 38490990 PMCID: PMC10942978 DOI: 10.1038/s41537-024-00456-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2023] [Accepted: 03/05/2024] [Indexed: 03/18/2024]
Abstract
Schizophrenia, a multifaceted mental disorder characterized by disturbances in thought, perception, and emotion, has been extensively investigated through resting-state fMRI, uncovering changes in spontaneous brain activity among those affected. However, a bibliometric examination regarding publication trends in resting-state fMRI studies related to schizophrenia is lacking. This study obtained relevant publications from the Web of Science Core Collection spanning the period from 1998 to 2022. Data extracted from these publications included information on countries/regions, institutions, authors, journals, and keywords. The collected data underwent analysis and visualization using VOSviewer software. The primary analyses included examination of international and institutional collaborations, authorship patterns, co-citation analyses of authors and journals, as well as exploration of keyword co-occurrence and temporal trend networks. A total of 859 publications were retrieved, indicating an overall growth trend from 1998 to 2022. China and the United States emerged as the leading contributors in both publication outputs and citations, with Central South University and the University of New Mexico being identified as the most productive institutions. Vince D. Calhoun had the highest number of publications and citation counts, while Karl J. Friston was recognized as the most influential author based on co-citations. Key journals such as Neuroimage, Schizophrenia Research, Schizophrenia Bulletin, and Biological Psychiatry played pivotal roles in advancing this field. Recent popular keywords included support vector machine, antipsychotic medication, transcranial magnetic stimulation, and related terms. This study systematically synthesizes the historical development, current status, and future trends in resting-state fMRI research in schizophrenia, offering valuable insights for future research directions.
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Affiliation(s)
- Linhan Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300070, China
| | - Remilai Aximu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
- School of Medical Imaging, Tianjin Medical University, Tianjin, 300070, China
| | - Guoshu Zhao
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
- School of Medicine, Nankai University, Tianjin, 300071, China
| | - Yayuan Chen
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zuhao Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Shaoying Wang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Nannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Zhihui Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Minghuan Lei
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Ying Zhai
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jinglei Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China
| | - Jie Sun
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Juanwei Ma
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
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Cattarinussi G, Gugliotta AA, Sambataro F. The Risk for Schizophrenia-Bipolar Spectrum: Does the Apple Fall Close to the Tree? A Narrative Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6540. [PMID: 37569080 PMCID: PMC10418911 DOI: 10.3390/ijerph20156540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2023] [Revised: 07/24/2023] [Accepted: 08/04/2023] [Indexed: 08/13/2023]
Abstract
Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share clinical features and several risk genes. Important information about their genetic underpinnings arises from intermediate phenotypes (IPs), quantifiable biological traits that are more prevalent in unaffected relatives (RELs) of patients compared to the general population and co-segregate with the disorders. Within IPs, neuropsychological functions and neuroimaging measures have the potential to provide useful insight into the pathophysiology of SCZ and BD. In this context, the present narrative review provides a comprehensive overview of the available evidence on deficits in neuropsychological functions and neuroimaging alterations in unaffected relatives of SCZ (SCZ-RELs) and BD (BD-RELs). Overall, deficits in cognitive functions including intelligence, memory, attention, executive functions, and social cognition could be considered IPs for SCZ. Although the picture for cognitive alterations in BD-RELs is less defined, BD-RELs seem to present worse performances compared to controls in executive functioning, including adaptable thinking, planning, self-monitoring, self-control, and working memory. Among neuroimaging markers, SCZ-RELs appear to be characterized by structural and functional alterations in the cortico-striatal-thalamic network, while BD risk seems to be associated with abnormalities in the prefrontal, temporal, thalamic, and limbic regions. In conclusion, SCZ-RELs and BD-RELs present a pattern of cognitive and neuroimaging alterations that lie between patients and healthy individuals. Similar abnormalities in SCZ-RELs and BD-RELs may be the phenotypic expression of the shared genetic mechanisms underlying both disorders, while the specificities in neuropsychological and neuroimaging profiles may be associated with the differential symptom expression in the two disorders.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
| | - Alessio A. Gugliotta
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, 35131 Padova, Italy; (G.C.); (A.A.G.)
- Padova Neuroscience Center, University of Padova, 35131 Padova, Italy
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Tavakoli H, Rostami R, Nazem-Zadeh MR. Assessments of variability in cortical and subcortical measurements and within-network connectivity of the brain using test-retest data. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083532 DOI: 10.1109/embc40787.2023.10340571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
The evaluation and diagnosis of structural changes in brain caused by disease or treatment over time has become one of the important applications of medical imaging methods, in particular MRI, and it is growing. It is critical to evaluate the reliability of the changes in measurements observed in an individual patient for any clinical decision-making. In this paper, we calculated the repeatability coefficient (RC) as a measure of uncertainty for MRI measurements of subcortical volumes and cortical thickness, and within-network connectivity using test-retest data of 20 healthy subjects. We also evaluated changes in 13 patients who received 20 sessions of transcranial magnetic stimulation as a treatment. The most reliable measure seems to be in the thickness of the left occipital with RC% of 3.5 and the least reliable measure is the brain connectivity within visual network using Yeo's atlas with RC% of 29.4. The most sensitive measure to the percentage of true changes in treated patients is the connectivity within subcortical network of AAL with 76.9%.Clinical Relevance- The results of this study can be useful for evaluating changes in the gray matter structures or functional connectivity of the brain due to a neurological disease such as Alzheimer's or Parkinson's. Also, the obtained results can be used to evaluate the changes caused by any intervention or treatment that may have any positive or negative effect on the brain.
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