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Tao Q, Dang J, Guo H, Zhang M, Niu X, Kang Y, Sun J, Ma L, Wei Y, Wang W, Wen B, Cheng J, Han S, Zhang Y. Abnormalities in static and dynamic intrinsic neural activity and neurotransmitters in first-episode OCD. J Affect Disord 2024; 363:609-618. [PMID: 39029696 DOI: 10.1016/j.jad.2024.07.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Revised: 06/29/2024] [Accepted: 07/16/2024] [Indexed: 07/21/2024]
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) is a disabling disorder in which the temporal variability of regional brain connectivity is not well understood. The aim of this study was to investigate alterations in static and dynamic intrinsic neural activity (INA) in first-episode OCD and whether these changes have the potential to reflect neurotransmitters. METHODS A total of 95 first-episode OCD patients and 106 matched healthy controls (HCs) were included in this study. Based on resting-state functional magnetic resonance imaging (rs-fMRI), the static and dynamic local connectivity coherence (calculated by static and dynamic regional homogeneity, sReHo and dReHo) were compared between the two groups. Furthermore, correlations between abnormal INA and PET- and SPECT-derived maps were performed to examine specific neurotransmitter system changes underlying INA abnormalities in OCD. RESULTS Compared with HCs, OCD showed decreased sReHo and dReHo values in left superior, middle temporal gyrus (STG/MTG), left Heschl gyrus (HES), left putamen, left insula, bilateral paracentral lobular (PCL), right postcentral gyrus (PoCG), right precentral gyrus (PreCG), left precuneus and right supplementary motor area (SMA). Decreased dReHo values were also found in left PoCG, left PreCG, left SMA and left middle cingulate cortex (MCC). Meanwhile, alterations in INA present in brain regions were correlated with dopamine system (D2, FDOPA), norepinephrine transporter (NAT) and the vesicular acetylcholine transporter (VAChT) maps. CONCLUSION Static and dynamic INA abnormalities exist in first-episode OCD, having the potential to reveal the molecular characteristics. The results help to further understand the pathophysiological mechanism and provide alternative therapeutic targets of OCD.
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Affiliation(s)
- Qiuying Tao
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Huirong Guo
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, China
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Yimeng Kang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Jieping Sun
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Longyao Ma
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Baohong Wen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China.
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, China; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging, China; Henan Engineering Technology Research Center for detection and application of brain function, China; Henan Engineering Research Center of medical imaging intelligent diagnosis and treatment, China; Henan key laboratory of imaging intelligence research, China; Henan Engineering Research Center of Brain Function Development and Application, China.
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Zheng C, Cao Y, Li Y, Ye Z, Jia X, Li M, Yu Y, Liu W. Long-term table tennis training alters dynamic functional connectivity and white matter microstructure in large scale brain regions. Brain Res 2024; 1838:148889. [PMID: 38552934 DOI: 10.1016/j.brainres.2024.148889] [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: 01/03/2024] [Revised: 03/22/2024] [Accepted: 03/26/2024] [Indexed: 05/12/2024]
Abstract
Table tennis training has been employed as an exercise treatment to enhance cognitive brain functioning in patients with mental illnesses. However, research on its underlying mechanisms remains limited. In this study, we investigated functional and structural changes in large-scale brain regions between 20 table tennis players (TTPs) and 21 healthy controls (HCs) using 7-Tesla magnetic resonance imaging (MRI) techniques. Compared with those of HCs, TTPs exhibited significantly greater fractional anisotropy (FA) and axial diffusivity (AD) values in multiple fiber tracts. We used the locations with the most significant structural changes in white matter as the seed areas and then compared static and dynamic functional connectivity (sFC and dFC). Brodmann 11, located in the orbitofrontal cortex, showed altered dFC values to large-scale brain regions, such as the occipital lobe, thalamus, and cerebellar hemispheres, in TTPs. Brodmann 48, located in the temporal lobe, showed altered dFC to the parietal lobe, frontal lobe, cerebellum, and occipital lobe. Furthermore, the AD values of the forceps minor (Fmi) and right anterior thalamic radiations (ATRs) were negatively correlated with useful field of view (UFOV) test scores in TTPs. Our results suggest that table tennis players exhibit a unique pattern of dynamic neural activity, this provides evidence for potential mechanisms through which table tennis interventions can enhance attention and other cognitive functions.
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Affiliation(s)
- Chanying Zheng
- Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China; Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuting Cao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Yuyang Li
- Interdisciplinary Institute of Neuroscience and Technology, Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, China
| | | | - Xize Jia
- School of Psychology, Zhejiang Normal University, Jinhua, China
| | - Mengting Li
- School of Psychology, Zhejiang Normal University, Jinhua, China.
| | - Yang Yu
- Psychiatry Department, the Second Affiliated Hospital Zhejiang University School of Medicine, Zhejiang, Hangzhou, China.
| | - Wenming Liu
- Department of Sport Science, College of Education, Zhejiang University, Hangzhou, China.
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Cui W, Chen B, He J, Fan G, Wang S. Dynamic functional network connectivity in children with profound bilateral congenital sensorineural hearing loss. Pediatr Radiol 2024; 54:1738-1747. [PMID: 39134864 DOI: 10.1007/s00247-024-06022-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 07/30/2024] [Accepted: 07/31/2024] [Indexed: 09/07/2024]
Abstract
BACKGROUND Functional magnetic resonance imaging (fMRI) studies have revealed extensive functional reorganization in patients with sensorineural hearing loss (SNHL). However, almost no study focuses on the dynamic functional connectivity after hearing loss. OBJECTIVE This study aimed to investigate dynamic functional connectivity changes in children with profound bilateral congenital SNHL under the age of 3 years. MATERIALS AND METHODS Thirty-two children with profound bilateral congenital SNHL and 24 children with normal hearing were recruited for the present study. Independent component analysis identified 18 independent components composing five resting-state networks. A sliding window approach was used to acquire dynamic functional matrices. Three states were identified using the k-means algorithm. Then, the differences in temporal properties and the variance of network efficiency between groups were compared. RESULTS The children with SNHL showed longer mean dwell time and decreased functional connectivity between the auditory network and sensorimotor network in state 3 (P < 0.05), which was characterized by relatively stronger functional connectivity between high-order resting-state networks and motion and perception networks. There was no difference in the variance of network efficiency. CONCLUSIONS These results indicated the functional reorganization due to hearing loss. This study also provided new perspectives for understanding the state-dependent connectivity patterns in children with SNHL.
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Affiliation(s)
- Wenzhuo Cui
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Boyu Chen
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Jiachuan He
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Guoguang Fan
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China
| | - Shanshan Wang
- Department of Radiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, Liaoning, PR China.
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Jing Y, Liu Y, Zhou Y, Li M, Gao Y, Zhang B, Li J. Inflammation-related abnormal dynamic brain activity correlates with cognitive impairment in first-episode, drug-naïve major depressive disorder. J Affect Disord 2024; 366:217-225. [PMID: 39197551 DOI: 10.1016/j.jad.2024.08.165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2024] [Revised: 07/22/2024] [Accepted: 08/23/2024] [Indexed: 09/01/2024]
Abstract
BACKGROUND Cognitive impairment is common in major depressive disorder (MDD) and potentially linked to inflammation-induced alterations in brain function. However, the relationship between inflammation, dynamic brain activity, and cognitive impairment in MDD remains unclear. METHODS Fifty-seven first-episode, drug-naïve MDD patients and sixty healthy controls underwent fMRI scanning. Dynamic amplitude of low-frequency fluctuations (dALFF) and dynamic functional connectivity (dFC) were measured using the sliding window method. Plasma IL - 6 levels and cognitive function were assessed using enzyme-linked immunosorbent assay (ELISA) and the Repeated Battery for Assessment of Neuropsychological Status (RBANS), respectively. RESULTS MDD patients exhibited decreased dALFF in the bilateral inferior temporal gyrus (ITG), right inferior frontal gyrus, opercular part (IFGoperc), and bilateral middle occipital gyrus (MOG). Regions of dALFF associated with IL-6 included right ITG (r = -0.400/p = 0.003), left ITG (r = -0.381/p = 0.004), right IFGoperc (r = -0.342/p = 0.011), and right MOG (r = -0.327/p = 0.016). Furthermore, IL-6-related abnormal dALFF (including right ITG: r = 0.309/p = 0.023, left ITG: r = 0.276/p = 0.044) was associated with attention impairment. These associations were absent entirely in MDD patients without suicidal ideation. Additionally, IL-6 levels were correlated with dFC of specific brain regions. LIMITATIONS Small sample size and cross-sectional study design. CONCLUSIONS Inflammation-related dALFF was associated with attention impairment in MDD patients, with variations observed among MDD subgroups. These findings contribute to the understanding of the intricate relationship between inflammation, dynamic brain activity and cognitive impairments in MDD.
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Affiliation(s)
- Yifan Jing
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yuan Liu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Yuwen Zhou
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Meijuan Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Ying Gao
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Bin Zhang
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China
| | - Jie Li
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin 300222, China.
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Ma L, Tao Q, Dang J, Sun J, Niu X, Zhang M, Kang Y, Wang W, Cheng J, Han S, Zhang Y. Altered local intrinsic neural activity and molecular architecture in internet use disorders. Brain Res Bull 2024; 216:111052. [PMID: 39173776 DOI: 10.1016/j.brainresbull.2024.111052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2024] [Revised: 07/20/2024] [Accepted: 08/17/2024] [Indexed: 08/24/2024]
Abstract
BACKGROUND Internet gaming disorder (IGD) is mainly characterized by its core dysfunction in higher-order brain cortices involved in inhibitory control, whose neurobiological basis remains unclear. Then, we will investigate local intrinsic neural activity (INA) alterations in IGD, ascertain whether these potential alterations are related to clinical characteristics, and further explore the underlying molecular architecture. METHOD In this study, we performed the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo) derived from resting-state functional magnetic resonance imaging (rs-fMRI) to explore the impact of IGD on local INA. Correlation analysis revealed the relationship between ReHo and fALFF in terms of group differences and clinical characteristics. Moreover, correlations between fALFF, ReHo, and PET- and SPECT-driven maps were investigated to elucidate the specific molecular architecture alternations in IGD. Finally, receiver operating characteristic curve (ROC) analysis was used to show the potential abilities of fALFF and ReHo in distinguishing individuals with IGD (IGDs) from healthy controls (HCs). RESULT Compared with HCs, IGDs revealed increased ReHo and fALFF in the prefrontal cortex. Significantly decreased ReHo was observed in the temporal lobe, occipital lobe, and cerebellum. In addition, the ReHo values in the cerebellum_7b_R were positively correlated with internet addiction severity. ROC curve analysis showed that ReHo and fALFF-altered brain regions could effectively distinguish IGDs from HCs. More importantly, cross-modal correlations revealed local INA changes in brain regions associated with the monoamine neurotransmitter system and the less studied cholinergic/GABAergic system. CONCLUSION These results suggest that local functional impairments are shown in the audiovisual and inhibitory control circuits in IGDs. This may be associated with underlying neurotransmitter system alterations. Therefore, this study provides the possibility of GABAergic receptor agonists and cholinergic receptor inhibitors for the treatment of IGD.
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Affiliation(s)
- Longyao Ma
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Qiuying Tao
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Jinghan Dang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Jieping Sun
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Xiaoyu Niu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Mengzhe Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Yimeng Kang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University; Zhengzhou Key Laboratory of brain function and cognitive magnetic resonance imaging.
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Fu Z, Sui J, Iraji A, Liu J, Calhoun VD. Cognitive and psychiatric relevance of dynamic functional connectivity states in a large (N > 10,000) children population. Mol Psychiatry 2024:10.1038/s41380-024-02683-6. [PMID: 39085394 DOI: 10.1038/s41380-024-02683-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 07/16/2024] [Accepted: 07/24/2024] [Indexed: 08/02/2024]
Abstract
Children's brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9~11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state with the most within-network synchrony and the anticorrelations between networks, especially between the sensory networks and between the cerebellum and other networks, was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a DFC state showing integration of sensory networks and antagonism between default-mode and sensorimotor networks but weak segregation of the cerebellum. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.
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Affiliation(s)
- Zening Fu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA.
- Department of Computer Science, Georgia State University, Atlanta, GA, USA.
| | - Jing Sui
- IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Jingyu Liu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Computer Science, Georgia State University, Atlanta, GA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- Department of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA, USA
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Asendorf AL, Theis H, Tittgemeyer M, Timmermann L, Fink GR, Drzezga A, Eggers C, Ruppert‐Junck MC, Pedrosa DJ, Hoenig MC, van Eimeren T. Dynamic properties in functional connectivity changes and striatal dopamine deficiency in Parkinson's disease. Hum Brain Mapp 2024; 45:e26776. [PMID: 38958131 PMCID: PMC11220510 DOI: 10.1002/hbm.26776] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 06/14/2024] [Accepted: 06/19/2024] [Indexed: 07/04/2024] Open
Abstract
Recent studies in Parkinson's disease (PD) patients reported disruptions in dynamic functional connectivity (dFC, i.e., a characterization of spontaneous fluctuations in functional connectivity over time). Here, we assessed whether the integrity of striatal dopamine terminals directly modulates dFC metrics in two separate PD cohorts, indexing dopamine-related changes in large-scale brain network dynamics and its implications in clinical features. We pooled data from two disease-control cohorts reflecting early PD. From the Parkinson's Progression Marker Initiative (PPMI) cohort, resting-state functional magnetic resonance imaging (rsfMRI) and dopamine transporter (DaT) single-photon emission computed tomography (SPECT) were available for 63 PD patients and 16 age- and sex-matched healthy controls. From the clinical research group 219 (KFO) cohort, rsfMRI imaging was available for 52 PD patients and 17 age- and sex-matched healthy controls. A subset of 41 PD patients and 13 healthy control subjects additionally underwent 18F-DOPA-positron emission tomography (PET) imaging. The striatal synthesis capacity of 18F-DOPA PET and dopamine terminal quantity of DaT SPECT images were extracted for the putamen and the caudate. After rsfMRI pre-processing, an independent component analysis was performed on both cohorts simultaneously. Based on the derived components, an individual sliding window approach (44 s window) and a subsequent k-means clustering were conducted separately for each cohort to derive dFC states (reemerging intra- and interindividual connectivity patterns). From these states, we derived temporal metrics, such as average dwell time per state, state attendance, and number of transitions and compared them between groups and cohorts. Further, we correlated these with the respective measures for local dopaminergic impairment and clinical severity. The cohorts did not differ regarding age and sex. Between cohorts, PD groups differed regarding disease duration, education, cognitive scores and L-dopa equivalent daily dose. In both cohorts, the dFC analysis resulted in three distinct states, varying in connectivity patterns and strength. In the PPMI cohort, PD patients showed a lower state attendance for the globally integrated (GI) state and a lower number of transitions than controls. Significantly, worse motor scores (Unified Parkinson's Disease Rating Scale Part III) and dopaminergic impairment in the putamen and the caudate were associated with low average dwell time in the GI state and a low total number of transitions. These results were not observed in the KFO cohort: No group differences in dFC measures or associations between dFC variables and dopamine synthesis capacity were observed. Notably, worse motor performance was associated with a low number of bidirectional transitions between the GI and the lesser connected (LC) state across the PD groups of both cohorts. Hence, in early PD, relative preservation of motor performance may be linked to a more dynamic engagement of an interconnected brain state. Specifically, those large-scale network dynamics seem to relate to striatal dopamine availability. Notably, most of these results were obtained only for one cohort, suggesting that dFC is impacted by certain cohort features like educational level, or disease severity. As we could not pinpoint these features with the data at hand, we suspect that other, in our case untracked, demographical features drive connectivity dynamics in PD. PRACTITIONER POINTS: Exploring dopamine's role in brain network dynamics in two Parkinson's disease (PD) cohorts, we unraveled PD-specific changes in dynamic functional connectivity. Results in the Parkinson's Progression Marker Initiative (PPMI) and the KFO cohort suggest motor performance may be linked to a more dynamic engagement and disengagement of an interconnected brain state. Results only in the PPMI cohort suggest striatal dopamine availability influences large-scale network dynamics that are relevant in motor control.
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Affiliation(s)
- Adrian L. Asendorf
- Department of Nuclear MedicineUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
| | - Hendrik Theis
- Department of Nuclear MedicineUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
- Department of NeurologyUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
| | - Marc Tittgemeyer
- Max Planck Institute for Metabolism Research, Translational Neurocircuitry GroupCologneGermany
- University of Cologne, Cologne Excellence Cluster on Cellular Stress Responses in Aging‐Associated Diseases (CECAD)CologneGermany
| | | | - Gereon R. Fink
- Department of NeurologyUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
- Research Centre Juelich, Institute of Neuroscience and Medicine III, Cognitive NeuroscienceJuelichGermany
| | - Alexander Drzezga
- Department of Nuclear MedicineUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
| | - Carsten Eggers
- Department of NeurologyMarburgGermany
- Department of NeurologyUniversity of Duisburg‐Essen, Knappschaftskrankenhaus BottropBottropGermany
| | | | - David J. Pedrosa
- Universities of Marburg and Gießen, Center for Mind, Brain, and Behavior‐CMBBMarburgGermany
| | - Merle C. Hoenig
- Department of Nuclear MedicineUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
- Research Center Juelich, Institute of Neuroscience and Medicine II, Molecular Organization of the BrainJuelichGermany
| | - Thilo van Eimeren
- Department of Nuclear MedicineUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
- Department of NeurologyUniversity of Cologne, Faculty of Medicine and University Hospital CologneCologneGermany
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Blair DS, Miller RL, Calhoun VD. A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. ENTROPY (BASEL, SWITZERLAND) 2024; 26:545. [PMID: 39056908 PMCID: PMC11275472 DOI: 10.3390/e26070545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/07/2024] [Accepted: 06/19/2024] [Indexed: 07/28/2024]
Abstract
Over the past decade and a half, dynamic functional imaging has revealed low-dimensional brain connectivity measures, identified potential common human spatial connectivity states, tracked the transition patterns of these states, and demonstrated meaningful transition alterations in disorders and over the course of development. Recently, researchers have begun to analyze these data from the perspective of dynamic systems and information theory in the hopes of understanding how these dynamics support less easily quantified processes, such as information processing, cortical hierarchy, and consciousness. Little attention has been paid to the effects of psychiatric disease on these measures, however. We begin to rectify this by examining the complexity of subject trajectories in state space through the lens of information theory. Specifically, we identify a basis for the dynamic functional connectivity state space and track subject trajectories through this space over the course of the scan. The dynamic complexity of these trajectories is assessed along each dimension of the proposed basis space. Using these estimates, we demonstrate that schizophrenia patients display substantially simpler trajectories than demographically matched healthy controls and that this drop in complexity concentrates along specific dimensions. We also demonstrate that entropy generation in at least one of these dimensions is linked to cognitive performance. Overall, the results suggest great value in applying dynamic systems theory to problems of neuroimaging and reveal a substantial drop in the complexity of schizophrenia patients' brain function.
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Affiliation(s)
- David Sutherland Blair
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory University, Atlanta, GA 30303, USA (V.D.C.)
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Wiafe SL, Asante NO, Calhoun VD, Faghiri A. Studying time-resolved functional connectivity via communication theory: on the complementary nature of phase synchronization and sliding window Pearson correlation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.12.598720. [PMID: 38915498 PMCID: PMC11195172 DOI: 10.1101/2024.06.12.598720] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Time-resolved functional connectivity (trFC) assesses the time-resolved coupling between brain regions using functional magnetic resonance imaging (fMRI) data. This study aims to compare two techniques used to estimate trFC, to investigate their similarities and differences when applied to fMRI data. These techniques are the sliding window Pearson correlation (SWPC), an amplitude-based approach, and phase synchronization (PS), a phase-based technique. To accomplish our objective, we used resting-state fMRI data from the Human Connectome Project (HCP) with 827 subjects (repetition time: 0.7s) and the Function Biomedical Informatics Research Network (fBIRN) with 311 subjects (repetition time: 2s), which included 151 schizophrenia patients and 160 controls. Our simulations reveal distinct strengths in two connectivity methods: SWPC captures high-magnitude, low-frequency connectivity, while PS detects low-magnitude, high-frequency connectivity. Stronger correlations between SWPC and PS align with pronounced fMRI oscillations. For fMRI data, higher correlations between SWPC and PS occur with matched frequencies and smaller SWPC window sizes (~30s), but larger windows (~88s) sacrifice clinically relevant information. Both methods identify a schizophrenia-associated brain network state but show different patterns: SWPC highlights low anti-correlations between visual, subcortical, auditory, and sensory-motor networks, while PS shows reduced positive synchronization among these networks. In sum, our findings underscore the complementary nature of SWPC and PS, elucidating their respective strengths and limitations without implying the superiority of one over the other.
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Affiliation(s)
- Sir-Lord Wiafe
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Nana O. Asante
- ETH Zürich, Zürich, Rämistrasse 101, Switzerland
- Ashesi University, 1 University Avenue Berekuso, Ghana
| | - Vince D. Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
| | - Ashkan Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA 30303, USA
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Zhu QQ, Tian S, Zhang L, Ding HY, Gao YX, Tang Y, Yang X, Zhu Y, Qi M. Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease. Eur J Neurosci 2024; 59:2391-2402. [PMID: 38314647 DOI: 10.1111/ejn.16267] [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: 03/31/2023] [Revised: 01/12/2024] [Accepted: 01/14/2024] [Indexed: 02/06/2024]
Abstract
The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.
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Affiliation(s)
- Qin-Qin Zhu
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Shui Tian
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ling Zhang
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Hong-Yuan Ding
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ya-Xin Gao
- Rehabilitation Center, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Suzhou, China
| | - Yin Tang
- Department of Medical imaging, Jingjiang People's Hospital, Jingjiang, China
| | - Xi Yang
- School of Rehabilitation Medicine, Nanjing Medical University, Nanjing, China
| | - Yi Zhu
- Rehabilitation Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Ming Qi
- Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Ye B, Wu Y, Cao M, Xu C, Zhou C, Zhang X. Altered patterns of dynamic functional connectivity of brain networks in deficit and non-deficit schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-024-01803-1. [PMID: 38662092 DOI: 10.1007/s00406-024-01803-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 03/19/2024] [Indexed: 04/26/2024]
Abstract
This study aims to investigate the altered patterns of dynamic functional network connectivity (dFNC) between deficit schizophrenia (DS) and non-deficit schizophrenia (NDS), and further explore the associations with cognitive impairments. 70 DS, 91 NDS, and 120 matched healthy controls (HCs) were enrolled. The independent component analysis was used to segment the whole brain. The fMRI brain atlas was used to identify functional networks, and the dynamic functional connectivity (FC) of each network was detected. Correlation analysis was used to explore the associations between altered dFNC and cognitive functions. Four dynamic states were identified. Compared to NDS, DS showed increased FC between sensorimotor network and default mode network in state 1 and decreased FC within auditory network in state 4. Additionally, DS had a longer mean dwell time of state 2 and a shorter one in state 3 compared to NDS. Correlation analysis showed that fraction time and mean dwell time of states were correlated with cognitive impairments in DS. This study demonstrates the distinctive altered patterns of dFNC between DS and NDS patients. The associations with impaired cognition provide specific neuroimaging evidence for the pathogenesis of DS.
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Affiliation(s)
- Biying Ye
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Yiqiao Wu
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Mingjun Cao
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Chanhuan Xu
- Department of Fourth Clinical Medical College, Nanjing Medical University, Nanjing, China
| | - Chao Zhou
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No.264 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
| | - Xiangrong Zhang
- Department of Geriatric Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, No.264 Guangzhou Road, Nanjing, 210029, Jiangsu, China.
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Seidel M, Geisler D, King JA, Winter M, Poller NW, Arold D, Gramatke K, Roessner V, Ehrlich S. Dynamic Changes in Local Brain Connectivity and Activity: A Longitudinal Study in Adolescent Anorexia Nervosa. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:447-458. [PMID: 38301885 DOI: 10.1016/j.bpsc.2024.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 12/21/2023] [Accepted: 01/22/2024] [Indexed: 02/03/2024]
Abstract
BACKGROUND Resting-state functional connectivity analysis has been used to study disruptions in neural circuitries underlying eating disorder symptoms. Research has shown resting-state functional connectivity to be altered during the acute phase of anorexia nervosa (AN), but little is known about the biological mechanisms underlying neural changes associated with weight restoration. The goal of the current study was to investigate longitudinal changes in regional homogeneity (ReHo) among neighboring voxels, degree centrality (DC) (a voxelwise whole brain correlation coefficient), voxel-mirrored homotopic connectivity (VMHC) (measuring the synchronization between hemispheres), and the fractional amplitude of low-frequency fluctuations associated with weight gain during AN treatment. METHODS Resting-state functional connectivity data were acquired and analyzed from a sample of 174 female volunteers: 87 underweight patients with AN that were scanned before treatment and again after at least 12% body mass index increase, as well as 87 age-matched healthy control participants. RESULTS Longitudinal changes in ReHo, DC, VMHC, and the fractional amplitude of low-frequency fluctuations were observed in most regions identified to differ between patients with AN before treatment and healthy control participants. However, the degree of normalization varied for each parameter, ranging from 9% of all clusters in DC to 66% in VMHC. Longitudinal changes in ReHo and VMHC showed a linear association weight gain. CONCLUSIONS Resting-state functional magnetic resonance imaging measures, including ReHo, DC, VMHC, and the fractional amplitude of low-frequency fluctuations, show varying degrees of recovery after short-term weight restoration. Although only some of these changes were related to weight gain, our results provide an overall positive message, suggesting that weight restoration is associated with changes in functional brain measures that point toward normalization.
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Affiliation(s)
- Maria Seidel
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany.
| | - Daniel Geisler
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Joseph A King
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Marie Winter
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Nico W Poller
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Dominic Arold
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Katrin Gramatke
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Veit Roessner
- Department of Child and Adolescent Psychiatry and Psychotherapy, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany; Eating Disorder Research and Treatment Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
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Khan AF, Muhammad F, Mohammadi E, O'Neal C, Haynes G, Hameed S, Walker B, Rohan ML, Yabluchanskiy A, Smith ZA. Beyond the aging spine - a systematic review of functional changes in the human brain in cervical spondylotic myelopathy. GeroScience 2024; 46:1421-1450. [PMID: 37801201 PMCID: PMC10828266 DOI: 10.1007/s11357-023-00954-8] [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: 07/21/2023] [Accepted: 08/31/2023] [Indexed: 10/07/2023] Open
Abstract
Cervical Spondylotic Myelopathy (CSM) is a degenerative condition that leads to loss of cervical spinal cord integrity, typically affecting the aged population. Emerging fMRI-based evidence suggests that the brain is also affected by CSM. This systematic review aimed to understand the usefulness of brain fMRI in CSM. A comprehensive literature search was conducted until March 2023 according to PRISMA guidelines. The inclusion criteria included original research articles in English, primarily studying the human brain's functional changes in CSM using fMRI with at least 5 participants. The extracted data from each study included demographics, disease severity, MRI machine characteristics, affected brain areas, functional changes, and clinical utilities. A total of 30 studies met the inclusion criteria. Among the fMRI methods, resting-state fMRI was the most widely used experimental paradigm, followed by motor tasks. The brain areas associated with motor control were most affected in CSM, followed by the superior frontal gyrus and occipital cortex. Functional changes in the brain were correlated to clinical metrics showing clinical utility. However, the evidence that a specific fMRI metric correlating with a clinical metric was "very low" to "insufficient" due to a low number of studies and negative results. In conclusion, fMRI can potentially facilitate the diagnosis of CSM by quantitatively interrogating the functional changes of the brain, particularly areas of the brain associated with motor control. However, this field is in its early stages, and more studies are needed to establish the usefulness of brain fMRI in CSM.
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Affiliation(s)
- Ali Fahim Khan
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA.
| | - Fauziyya Muhammad
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA
| | - Esmaeil Mohammadi
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA
| | - Christen O'Neal
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA
| | - Grace Haynes
- Stephenson School of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | - Sanaa Hameed
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA
| | - Brynden Walker
- College of Arts and Sciences, University of Oklahoma, Norman, OK, USA
| | | | - Andriy Yabluchanskiy
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Zachary Adam Smith
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, 1000 N Lincoln Blvd, Suite 4000, Oklahoma City, OK, 73104, USA
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Cheng X, Chen J, Zhang X, Wang T, Sun J, Zhou Y, Yang R, Xiao Y, Chen A, Song Z, Chen P, Yang C, QiuxiaWu, Lin T, Chen Y, Cao L, Wei X. Characterizing the temporal dynamics of intrinsic brain activities in depressed adolescents with prior suicide attempts. Eur Child Adolesc Psychiatry 2024; 33:1179-1191. [PMID: 37284850 PMCID: PMC11032277 DOI: 10.1007/s00787-023-02242-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 05/24/2023] [Indexed: 06/08/2023]
Abstract
Converging evidence has revealed disturbances in the corticostriatolimic system are associated with suicidal behaviors in adults with major depressive disorder. However, the neurobiological mechanism that confers suicidal vulnerability in depressed adolescents is largely unknown. A total of 86 depressed adolescents with and without prior suicide attempts (SA) and 47 healthy controls underwent resting-state functional imaging (R-fMRI) scans. The dynamic amplitude of low-frequency fluctuations (dALFF) was measured using sliding window approach. We identified SA-related alterations in dALFF variability primarily in the left middle temporal gyrus, inferior frontal gyrus, middle frontal gyrus (MFG), superior frontal gyrus (SFG), right SFG, supplementary motor area (SMA) and insula in depressed adolescents. Notably, dALFF variability in the left MFG and SMA was higher in depressed adolescents with recurrent suicide attempts than in those with a single suicide attempt. Moreover, dALFF variability was capable of generating better diagnostic and prediction models for suicidality than static ALFF. Our findings suggest that alterations in brain dynamics in regions involved in emotional processing, decision-making and response inhibition are associated with an increased risk of suicidal behaviors in depressed adolescents. Furthermore, dALFF variability could serve as a sensitive biomarker for revealing the neurobiological mechanisms underlying suicidal vulnerability.
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Affiliation(s)
- Xiaofang Cheng
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Jianshan Chen
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Xiaofei Zhang
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Ting Wang
- The Second Affiliated Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Yuexiu district, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Jiaqi Sun
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Yanling Zhou
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Ruilan Yang
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Yeyu Xiao
- Guangzhou Integrated Traditional Chinese and Western Medicine, Guangzhou, 510800, Guangdong, People's Republic of China
| | - Amei Chen
- The Second Affiliated Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Yuexiu district, Guangzhou, 510180, Guangdong, People's Republic of China
| | - Ziyi Song
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Pinrui Chen
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Chanjuan Yang
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - QiuxiaWu
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Taifeng Lin
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Yingmei Chen
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China
| | - Liping Cao
- The Affiliated Brain Hospital of Guangzhou Medical University, 36 Mingxin Road, liwan district, Guangzhou, 510370, Guangdong, People's Republic of China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, 510370, Guangdong, People's Republic of China.
| | - Xinhua Wei
- The Second Affiliated Hospital, School of Medicine, South China University of Technology, 1 Panfu Road, Yuexiu district, Guangzhou, 510180, Guangdong, People's Republic of China.
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15
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Xin X, Yu J, Gao X. The brain entropy dynamics in resting state. Front Neurosci 2024; 18:1352409. [PMID: 38595975 PMCID: PMC11002175 DOI: 10.3389/fnins.2024.1352409] [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: 12/08/2023] [Accepted: 03/08/2024] [Indexed: 04/11/2024] Open
Abstract
As a novel measure for irregularity and complexity of the spontaneous fluctuations of brain activities, brain entropy (BEN) has attracted much attention in resting-state functional magnetic resonance imaging (rs-fMRI) studies during the last decade. Previous studies have shown its associations with cognitive and mental functions. While most previous research assumes BEN is approximately stationary during scan sessions, the brain, even at its resting state, is a highly dynamic system. Such dynamics could be characterized by a series of reoccurring whole-brain patterns related to cognitive and mental processes. The present study aims to explore the time-varying feature of BEN and its potential links with general cognitive ability. We adopted a sliding window approach to derive the dynamical brain entropy (dBEN) of the whole-brain functional networks from the HCP (Human Connectome Project) rs-fMRI dataset that includes 812 young healthy adults. The dBEN was further clustered into 4 reoccurring BEN states by the k-means clustering method. The fraction window (FW) and mean dwell time (MDT) of one BEN state, characterized by the extremely low overall BEN, were found to be negatively correlated with general cognitive abilities (i.e., cognitive flexibility, inhibitory control, and processing speed). Another BEN state, characterized by intermediate overall BEN and low within-state BEN located in DMN, ECN, and part of SAN, its FW, and MDT were positively correlated with the above cognitive abilities. The results of our study advance our understanding of the underlying mechanism of BEN dynamics and provide a potential framework for future investigations in clinical populations.
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Affiliation(s)
- Xiaoyang Xin
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
- Preschool College, Luoyang Normal University, Luoyang, China
| | - Jiaqian Yu
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
| | - Xiaoqing Gao
- Center for Psychological Sciences, Zhejiang University, Hangzhou, China
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16
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Han M, He C, Li T, Li Q, Chu T, Li J, Wang P. Altered dynamic and static brain activity and functional connectivity in COVID-19 patients: a preliminary study. Neuroreport 2024; 35:306-315. [PMID: 38305116 DOI: 10.1097/wnr.0000000000002009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
This study aimed to investigate the effects of COVID-19 on brain functional activity through resting-state functional MRI (rs-fMRI). fMRI scans were conducted on a cohort of 42 confirmed COVID-19-positive patients and 46 healthy controls (HCs) to assess brain functional activity. A combination of dynamic and static amplitude of low-frequency fluctuations (dALFF/sALFF) and dynamic and static functional connectivity (dFC/sFC) was used for evaluation. Abnormal brain regions identified were then used as feature inputs in the model to evaluate support vector machine (SVM) capability in recognizing COVID-19 patients. Moreover, the random forest (RF) model was employed to verify the stability of SVM diagnoses for COVID-19 patients. Compared to HCs, COVID-19 patients exhibited a decrease in sALFF in the right lingual gyrus and the left medial occipital gyrus and an increase in dALFF in the right straight gyrus. Moreover, there was a decline in sFC between both lingual gyri and the right superior occipital gyrus and a reduction in dFC with the precentral gyrus. The dynamic and static combined ALFF and FC could distinguish between COVID-19 patients and the HCs with an accuracy of 0.885, a specificity of 0.818, a sensitivity of 0.933 and an area under the curve of 0.909. The combination of dynamic and static ALFF and FC can provide information for detecting brain functional abnormalities in COVID-19 patients.
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Affiliation(s)
- Mingxing Han
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
| | - Chunni He
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
| | - Tianping Li
- Department of Radiology, The Second Hospital of Jiaxing, Jiaxing, People's Republic of China
| | - Qinglong Li
- Department of Magenetic Resonance Imaging (MRI), Henan Provincial Hospital of Traditional Chinese Medicine (The Second Affiliated Hospital of Henan University of Traditional Chinese Medicine), Zhengzhou
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Qingdao University, Yantai, People's Republic of China
| | - Jun Li
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
| | - Peiyuan Wang
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
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Zheng R, Bu C, Chen Y, Wei Y, Zhou B, Jiang Y, Zhu C, Wang K, Wang C, Li S, Han S, Zhang Y, Cheng J. Decreased intrinsic neural timescale in treatment-naïve adolescent depression. J Affect Disord 2024; 348:389-397. [PMID: 38160888 DOI: 10.1016/j.jad.2023.12.048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Revised: 11/25/2023] [Accepted: 12/23/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND Major depressive disorder (MDD) is mainly characterized by its core dysfunction in higher-order brain cortices involved in emotional and cognitive processes, whose neurobiological basis remains unclear. In this study, we applied a relatively new developed resting-state functional magnetic resonance imaging (rs-fMRI) method of intrinsic neural timescale (INT), which reflects how long neural information is stored in a local brain area and reflects an ability of information integration, to investigate the local intrinsic neural dynamics using univariate and multivariate analyses in adolescent depression. METHOD Based on the rs-fMRI data of sixty-six treatment-naïve adolescents with MDD and fifty-two well-matched healthy controls (HCs), we calculated an INT by assessing the magnitude of autocorrelation of the resting-state brain activity, and then compared the difference of INT between the two groups. Correlation between abnormal INT and clinical features was performed. We also utilized multivariate pattern analysis to determine whether INT could differentiate MDD patients from HCs at the individual level. RESULT Compared with HCs, patients with MDD showed shorter INT widely distributed in cortical and partial subcortical regions. Interestingly, the decreased INT in the left hippocampus was related to disease severity of MDD. Furthermore, INT can distinguish MDD patients from HCs with the most discriminative regions located in the dorsolateral prefrontal cortex, angular, middle occipital gyrus, and cerebellar posterior lobe. CONCLUSION Our research aids in advancing understanding the brain abnormalities of treatment-naïve adolescents with MDD from the perspective of the local neural dynamics, highlighting the significant role of INT in understanding neurophysiological mechanisms. This study shows that the altered intrinsic timescales of local neural signals widely distributed in higher-order brain cortices regions may be the neurodynamic basis of cognitive and emotional disturbances in MDD patients, and provides preliminary support for the suggestion that these could be used to aid the identification of MDD patients in clinical practice.
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Affiliation(s)
- Ruiping Zheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Chunxiao Bu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Yuan Chen
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Bingqian Zhou
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Yu Jiang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Chendi Zhu
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Henan University of Chinese Medicine, PR China
| | - Kefan Wang
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Shuying Li
- Department of Psychiatry, the First Affiliated Hospital of Zhengzhou University, PR China
| | - Shaoqiang Han
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China.
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China.
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, the First Affiliated Hospital of Zhengzhou University, PR China.
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Yi X, Wang X, Fu Y, Luo Y, Wang J, Han Z, Kuang Y, Chen X, Chen BT. Altered brain activity and cognitive impairment in patients with psoriasis. J Eur Acad Dermatol Venereol 2024; 38:557-567. [PMID: 38059666 DOI: 10.1111/jdv.19685] [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: 05/14/2023] [Accepted: 10/25/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Patients with psoriasis may have cognitive impairment. However, there is limited information regarding intrinsic brain activity and cognitive function in patients with psoriasis. OBJECTIVES This study aim to assess alterations of intrinsic brain activity and its association with cognitive function in patients with psoriasis. METHODS A total of 222 patients with psoriasis aged 18-70 years and 144 age and gender-matched healthy controls (HCs) were enrolled into this study. All subjects underwent brain resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing. The rs-fMRI data were analysed for both intrinsic brain activity as indicated by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC). Correlative analysis of brain activity with cognitive assessment was performed. RESULTS Compared with the HCs, patients with psoriasis had worse cognitive performance in the Trail Making Test, Digit Span Test and Stroop Color-Word Test (p < 0.05). Patients with psoriasis showed decreased ALFF in the left superior frontal gyrus, the left medial superior frontal gyrus and the right precuneus gyrus; as well as enhanced ALFF in the left paracentral lobule (pFWE < 0.05). Significant correlations were noted between the altered ALFF in the four brain regions and cognitive assessment (p < 0.05). Moreover, patients with psoriasis had increased FC between the four brain regions with altered ALFF (seeds) and the left prefrontal gyrus, the left anterior cingulate gyrus, left superior parietal lobule and default mode network (DMN) regions such as the right precuneus gyrus, left inferior parietal lobule, right angular gyrus and bilateral inferior temporal gyrus (pFWE < 0.05). CONCLUSIONS Patients with psoriasis had altered brain activity and connectivity in the key brain areas within the DMN-prefrontal circuit. These brain changes may be the underlying neural correlates for cognitive functioning in patients with psoriasis.
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Affiliation(s)
- Xiaoping Yi
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xueying Wang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
| | - Yan Fu
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
| | - Yan Luo
- Department of Dermatology, People's Hospital of Jiangxi Province, Nanchang, Jiangxi, China
| | - Jing Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Zaide Han
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yehong Kuang
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiang Chen
- National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Xiangya Hospital, Changsha, Hunan, China
- National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Central South University, Changsha, Hunan, China
- Hunan Key Laboratory of Skin Cancer and Psoriasis, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Hunan Engineering Research Center of Skin Health and Disease, Xiangya Hospital, Central South University, Changsha, Hunan, China
- Department of Dermatology, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Bihong T Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, Duarte, California, USA
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Huang W, Fang X, Li S, Mao R, Ye C, Liu W, Deng Y, Lin G. Abnormal characteristic static and dynamic functional network connectivity in idiopathic normal pressure hydrocephalus. CNS Neurosci Ther 2024; 30:e14178. [PMID: 36949617 PMCID: PMC10915979 DOI: 10.1111/cns.14178] [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: 11/22/2022] [Revised: 03/02/2023] [Accepted: 03/03/2023] [Indexed: 03/24/2023] Open
Abstract
AIMS Idiopathic Normal pressure hydrocephalus (iNPH) is a neurodegenerative disease characterized by gait disturbance, dementia, and urinary dysfunction. The neural network mechanisms underlying this phenomenon is currently unknown. METHODS To investigate the resting-state functional connectivity (rs-FC) abnormalities of iNPH-related brain connectivity from static and dynamic perspectives and the correlation of these abnormalities with clinical symptoms before and 3-month after shunt. We investigated both static and dynamic functional network connectivity (sFNC and dFNC, respectively) in 33 iNPH patients and 23 healthy controls (HCs). RESULTS The sFNC and dFNC of networks were generally decreased in iNPH patients. The reduction in sFNC within the default mode network (DMN) and between the somatomotor network (SMN) and visual network (VN) were related to symptoms. The temporal properties of dFNC and its temporal variability in state-4 were sensitive to the identification of iNPH and were correlated with symptoms. The temporal variability in the dorsal attention network (DAN) increased, and the average instantaneous FC was altered among networks in iNPH. These features were partially associated with clinical symptoms. CONCLUSION The dFNC may be a more sensitive biomarker for altered network function in iNPH, providing us with extra information on the mechanisms of iNPH.
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Affiliation(s)
- Wenjun Huang
- Department of RadiologyHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Xuhao Fang
- Department of NeurosurgeryHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Shihong Li
- Department of RadiologyHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Renling Mao
- Department of NeurosurgeryHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Chuntao Ye
- Department of RadiologyHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Wei Liu
- Department of RadiologyHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Yao Deng
- Department of NeurosurgeryHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
| | - Guangwu Lin
- Department of RadiologyHuadong Hospital Affiliated to Fudan UniversityShanghaiChina
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Sun H, Yan R, Hua L, Xia Y, Chen Z, Huang Y, Wang X, Xia Q, Yao Z, Lu Q. Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder. J Psychiatr Res 2024; 171:60-68. [PMID: 38244334 DOI: 10.1016/j.jpsychires.2024.01.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Revised: 01/10/2024] [Accepted: 01/15/2024] [Indexed: 01/22/2024]
Abstract
OBJECTIVE Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) in the early stage, which may lead to inappropriate treatment. This study aimed to characterize the alterations of spontaneous neuronal activity in patients with depressive episodes whose diagnosis transferred from MDD to BD. METHODS 532 patients with MDD and 132 healthy controls (HCs) were recruited over 10 years. During the follow-up period, 75 participants with MDD transferred to BD (tBD), and 157 participants remained with the diagnosis of unipolar depression (UD). After excluding participants with poor image quality and excessive head movement, 68 participants with the diagnosis of tBD, 150 participants with the diagnosis of UD, and 130 HCs were finally included in the analysis. The dynamic amplitude of low-frequency fluctuations (dALFF) of spontaneous neuronal activity was evaluated in tBD, UD and HC using functional magnetic resonance imaging at study inclusion. Receiver operating characteristic (ROC) analysis was performed to evaluate sensitivity and specificity of the conversion prediction from MDD to BD based on dALFF. RESULTS Compared to HC, tBD exhibited elevated dALFF at left premotor cortex (PMC_L), right lateral temporal cortex (LTC_R) and right early auditory cortex (EAC_R), and UD showed reduced dALFF at PMC_L, left paracentral lobule (PCL_L), bilateral medial prefrontal cortex (mPFC), right orbital frontal cortex (OFC_R), right dorsolateral prefrontal cortex (DLPFC_R), right posterior cingulate cortex (PCC_R) and elevated dALFF at LTC_R. Furthermore, tBD exhibited elevated dALFF at PMC_L, PCL_L, bilateral mPFC, bilateral OFC, DLPFC_R, PCC_R and LTC_R than UD. In addition, ROC analysis based on dALFF in differential areas obtained an area under the curve (AUC) of 72.7%. CONCLUSIONS The study demonstrated the temporal dynamic abnormalities of tBD and UD in the critical regions of the somatomotor network (SMN), default mode network (DMN), and central executive network (CEN). The differential abnormal patterns of temporal dynamics between the two diseases have the potential to predict the diagnosis transition from MDD to BD.
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Affiliation(s)
- Hao Sun
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Rui Yan
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Lingling Hua
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Yi Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Zhilu Chen
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Yinghong Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Xiaoqin Wang
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Qiudong Xia
- Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China
| | - Zhijian Yao
- Nanjing Brain Hospital, Clinical Teaching Hospital of Medical School, Nanjing University, Nanjing, China; Department of Psychiatry, The Affiliated Brain Hospital of Nanjing Medical University, 249 Guangzhou Road, Nanjing, 210029, China; School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, 210096, China.
| | - Qing Lu
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing, 210096, China; Child Development and Learning Science, Key Laboratory of Ministry of Education, Nanjing, 210096, China.
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21
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Ding J, Chen Q, Liu Y, Tang Z, Feng C, Wang M, Ding Z. Dynamic analysis of amplitude of low-frequency fluctuation in children with growth hormone deficiency. Behav Brain Res 2024; 459:114769. [PMID: 37984523 DOI: 10.1016/j.bbr.2023.114769] [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: 08/20/2023] [Revised: 11/11/2023] [Accepted: 11/17/2023] [Indexed: 11/22/2023]
Abstract
OBJECTIVE Growth hormone (GH) affects brain activities and promotes growth and development. GH is a peptide hormone secreted by the anterior pituitary gland and is tied to behavior and cognitive function. Growth hormone deficiency (GHD) is the most common type of pathological short stature in children. Existing studies provide evidence that GHD may impact functional brain activities. The aim of this study was to investigate dynamic local brain activity in GHD children. METHOD In this study, we combined amplitude of low-frequency fluctuations (ALFF) and sliding-window techniques to examine the local brain activity of children with GHD. The resting-state functional magnetic resonance imaging (fMRI) data were collected from 26 children with GHD and 15 age- and sex-matched healthy controls (HC). RESULT Our results showed significant abnormal temporal variability of dynamic ALFF in widespread regions in children with GHD, primarily in the frontal gyrus, temporal gyrus, and parietal lobule. CONCLUSION The dALFF can capture dynamic changes in brain spontaneous activity, which are related to behavior and cognition. Based on this dynamic local brain activity, the results of this study provide a better understanding of the pathophysiological mechanism in children with GHD.
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Affiliation(s)
- Jurong Ding
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, PR China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, PR China.
| | - Qiang Chen
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, PR China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, PR China
| | - Yihong Liu
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, PR China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, PR China
| | - Zhiling Tang
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, PR China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, PR China
| | - Chenyu Feng
- School of Automation and Information Engineering, Sichuan University of Science and Engineering, Zigong, PR China; Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong, PR China
| | - Mei Wang
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, PR China
| | - Zhongxiang Ding
- Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, PR China.
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22
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Luo L, Liao Y, Jia F, Ning G, Liu J, Li X, Chen X, Ma X, He X, Fu C, Cai X, Qu H. Altered dynamic functional and effective connectivity in drug-naive children with Tourette syndrome. Transl Psychiatry 2024; 14:48. [PMID: 38253543 PMCID: PMC10803732 DOI: 10.1038/s41398-024-02779-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 01/08/2024] [Accepted: 01/12/2024] [Indexed: 01/24/2024] Open
Abstract
Tourette syndrome (TS) is a developmental neuropsychiatric disorder characterized by repetitive, stereotyped, involuntary tics, the neurological basis of which remains unclear. Although traditional resting-state MRI (rfMRI) studies have identified abnormal static functional connectivity (FC) in patients with TS, dynamic FC (dFC) remains relatively unexplored. The rfMRI data of 54 children with TS and 46 typically developing children (TDC) were analyzed using group independent component analysis to obtain independent components (ICs), and a sliding-window approach to generate dFC matrices. All dFC matrices were clustered into two reoccurring states, the state transition metrics were obtained. We conducted Granger causality and nodal topological analyses to further investigate the brain regions that may play the most important roles in driving whole-brain switching between different states. We found that children with TS spent more time in state 2 (PFDR < 0.001), a state characterized by strong connectivity between ICs, and switched more quickly between states (PFDR = 0.025) than TDC. The default mode network (DMN) may play an important role in abnormal state transitions because the FC that changed the most between the two states was between the DMN and other networks. Additionally, the DMN had increased degree centrality, efficiency and altered causal influence on other networks. Certain alterations related to executive function (r = -0.309, P < 0.05) and tic symptom ratings (r = 0.282; 0.413, P < 0.05) may represent important aspects of the pathophysiology of TS. These findings facilitate our understanding of the neural basis for the clinical presentation of TS.
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Affiliation(s)
- Lekai Luo
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Yi Liao
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Fenglin Jia
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Gang Ning
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Jing Liu
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Xuesheng Li
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Xijian Chen
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Xinmao Ma
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Xuejia He
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Chuan Fu
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China
| | - Xiaotang Cai
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China.
- Department of Rehabilitation, West China Second University Hospital, Chengdu, 610021, Sichuan, PR China.
| | - Haibo Qu
- Department of Radiology, West China Second University Hospital, Sichuan University, Chengdu, 610021, Sichuan, PR China.
- Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, 610021, Sichuan, PR China.
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Cai S, Liang Y, Wang Y, Fan Z, Qi Z, Liu Y, Chen F, Jiang C, Shi Z, Wang L, Zhang L. Shared and malignancy-specific functional plasticity of dynamic brain properties for patients with left frontal glioma. Cereb Cortex 2024; 34:bhad445. [PMID: 38011109 DOI: 10.1093/cercor/bhad445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 11/01/2023] [Accepted: 11/02/2023] [Indexed: 11/29/2023] Open
Abstract
The time-varying brain activity may parallel the disease progression of cerebral glioma. Assessment of brain dynamics would better characterize the pathological profile of glioma and the relevant functional remodeling. This study aims to investigate the dynamic properties of functional networks based on sliding-window approach for patients with left frontal glioma. The generalized functional plasticity due to glioma was characterized by reduced dynamic amplitude of low-frequency fluctuation of somatosensory networks, reduced dynamic functional connectivity between homotopic regions mainly involving dorsal attention network and subcortical nuclei, and enhanced subcortical dynamic functional connectivity. Malignancy-specific functional remodeling featured a chaotic modification of dynamic amplitude of low-frequency fluctuation and dynamic functional connectivity for low-grade gliomas, and attenuated dynamic functional connectivity of the intrahemispheric cortico-subcortical connections and reduced dynamic amplitude of low-frequency fluctuation of the bilateral caudate for high-grade gliomas. Network dynamic activity was clustered into four distinct configuration states. The occurrence and dwell time of the weakly connected state were reduced in patients' brains. Support vector machine model combined with predictive dynamic features achieved an averaged accuracy of 87.9% in distinguishing low- and high-grade gliomas. In conclusion, dynamic network properties are highly predictive of the malignant grade of gliomas, thus could serve as new biomarkers for disease characterization.
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Affiliation(s)
- Siqi Cai
- Paul. C. Lauterbur Research Centers for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yuchao Liang
- Department of Neurosurgery, Beijing Tiantan Hospital of Capital Medical University, Beijing 10070, China
| | - Yinyan Wang
- Department of Neurosurgery, Beijing Tiantan Hospital of Capital Medical University, Beijing 10070, China
| | - Zhen Fan
- Department of Neurosurgery, Huashan Hospital of Fudan University, Shanghai 200040, China
| | - Zengxin Qi
- Department of Neurosurgery, Huashan Hospital of Fudan University, Shanghai 200040, China
| | - Yufei Liu
- Department of Neurosurgery, Shenzhen Second People's Hospital, Shenzhen, Guangdong 518025, China
| | - Fanfan Chen
- Department of Neurosurgery, Shenzhen Second People's Hospital, Shenzhen, Guangdong 518025, China
| | - Chunxiang Jiang
- Paul. C. Lauterbur Research Centers for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
| | - Zhifeng Shi
- Department of Neurosurgery, Huashan Hospital of Fudan University, Shanghai 200040, China
| | - Lei Wang
- Department of Neurosurgery, Beijing Tiantan Hospital of Capital Medical University, Beijing 10070, China
| | - Lijuan Zhang
- Paul. C. Lauterbur Research Centers for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong 518055, China
- University of Chinese Academy of Sciences, Beijing 100049, China
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Fu Z, Sui J, Iraji A, Liu J, Calhoun V. Cognitive and Psychiatric Relevance of Dynamic Functional Connectivity States in a Large (N>10,000) Children Population. RESEARCH SQUARE 2024:rs.3.rs-3586731. [PMID: 38260417 PMCID: PMC10802706 DOI: 10.21203/rs.3.rs-3586731/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Children's brains dynamically adapt to the stimuli from the internal state and the external environment, allowing for changes in cognitive and mental behavior. In this work, we performed a large-scale analysis of dynamic functional connectivity (DFC) in children aged 9 ~ 11 years, investigating how brain dynamics relate to cognitive performance and mental health at an early age. A hybrid independent component analysis framework was applied to the Adolescent Brain Cognitive Development (ABCD) data containing 10,988 children. We combined a sliding-window approach with k-means clustering to identify five brain states with distinct DFC patterns. Interestingly, the occurrence of a strongly connected state was negatively correlated with cognitive performance and positively correlated with dimensional psychopathology in children. Meanwhile, opposite relationships were observed for a sparsely connected state. The composite cognitive score and the ADHD score were the most significantly correlated with the DFC states. The mediation analysis further showed that attention problems mediated the effect of DFC states on cognitive performance. This investigation unveils the neurological underpinnings of DFC states, which suggests that tracking the transient dynamic connectivity may help to characterize cognitive and mental problems in children and guide people to provide early intervention to buffer adverse influences.
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Affiliation(s)
- Zening Fu
- Georgia Institute of Technology, Emory University and Georgia State University
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Xiong X, Dai L, Chen W, Lu J, Hu C, Zhao H, Ke J. Dynamics and concordance alterations of regional brain function indices in vestibular migraine: a resting-state fMRI study. J Headache Pain 2024; 25:1. [PMID: 38178029 PMCID: PMC10768112 DOI: 10.1186/s10194-023-01705-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 12/12/2023] [Indexed: 01/06/2024] Open
Abstract
BACKGROUND Prior MRI studies on vestibular migraine (VM) have revealed abnormalities in static regional intrinsic brain activity (iBA) and dynamic functional connectivity between brain regions or networks. However, the temporal variation and concordance of regional iBA measures remain to be explored. METHODS 57 VM patients during the interictal period were compared to 88 healthy controls (HC) in this resting-state functional magnetic resonance imaging (fMRI) study. The dynamics and concordance of regional iBA indices, including amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo), were examined by utilizing sliding time-window analysis. Partial correlation analyses were performed between clinical parameters and resting-state fMRI indices in brain areas showing significant group differences. RESULTS The VM group showed increased ALFF and ReHo dynamics, as well as increased temporal concordance between ALFF and ReHo in the bilateral paracentral lobule and supplementary motor area relative to the HC group. We also found decreased ReHo dynamics in the right temporal pole, and decreased ALFF dynamics in the right cerebellum posterior lobe, bilateral angular gyrus and middle occipital gyrus (MOG) in the VM group compared with the HC group. Moreover, a positive correlation was observed between ALFF dynamics in the left MOG and vertigo disease duration across all VM patients. CONCLUSION Temporal dynamics and concordance of regional iBA indices were altered in the motor cortex, cerebellum, occipital and temporoparietal cortex, which may contribute to disrupted multisensory processing and vestibular control in patients with VM. ALFF dynamics in the left MOG may be useful biomarker for evaluating vertigo burden in this disorder.
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Affiliation(s)
- Xing Xiong
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
- Institute of Medical imaging, Soochow University, Soochow, Jiangsu Province, People's Republic of China
| | - Lingling Dai
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
- Institute of Medical imaging, Soochow University, Soochow, Jiangsu Province, People's Republic of China
| | - Wen Chen
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
- Institute of Medical imaging, Soochow University, Soochow, Jiangsu Province, People's Republic of China
| | - Jiajie Lu
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
| | - Chunhong Hu
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China
- Institute of Medical imaging, Soochow University, Soochow, Jiangsu Province, People's Republic of China
| | - Hongru Zhao
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
| | - Jun Ke
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, Jiangsu, China.
- Institute of Medical imaging, Soochow University, Soochow, Jiangsu Province, People's Republic of China.
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Wang HY, Zhang L, Guan BY, Wang SY, Zhang CH, Ni MF, Miao YW, Zhang BW. Resting-state cortico-limbic functional connectivity pattern in panic disorder: Relationships with emotion regulation strategy use and symptom severity. J Psychiatr Res 2024; 169:97-104. [PMID: 38007890 DOI: 10.1016/j.jpsychires.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 11/10/2023] [Accepted: 11/15/2023] [Indexed: 11/28/2023]
Abstract
Cognitive reappraisal is an effective emotion regulation strategy involving prefrontal cortex (PFC) control of the amygdala. Its aberrant functioning is closely associated with panic disorder (PD). However, the resting-state functional connectivity (rsFC) between the PFC, implicated in cognitive reappraisal, and the amygdala in PD has not been studied. Thus, this study aims to investigate the rsFC patterns and their association with cognitive reappraisal and PD. This study involved 51 participants, including 26 untreated patients with PD and 25 healthy controls (HC). We evaluated the habit of cognitive reappraisal assessment and the severity of PD using neuropsychological and clinical measures. Resting-state fMRI was utilized to evaluate the rsFC pattern between the PFC, engaged in cognitive reappraisal, and the amygdala. Mediation analysis was performed to explore the role of this rsFC in the relationship between cognitive reappraisal and PD severity. PD patients showed reduced rsFC between the PFC and the amygdala compared to HC. This weakened rsFC was associated with the severity of PD symptoms. Moreover, cognitive reappraisal was negatively correlated with PD severity, and mediation analysis indicated that the rsFC of the PFC-amygdala played a mediating role in this association. Abnormal PFC-amygdala rsFC may play a pivotal role in PD development and/or manifestation and mediate the association between cognitive reappraisal and PD severity, potentially serving as a clinical indicator for monitoring and intervention.
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Affiliation(s)
- Hai-Yang Wang
- Department of Neurology, Jining No. 1 People's Hospital, Shandong First Medical University, Jining, 272000, China
| | - Lin Zhang
- Medical Equipment Department, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Bei-Yan Guan
- Department of Neurology and Psychiatry, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Shi-Yao Wang
- Department of Neurology and Psychiatry, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China
| | - Cui-Hong Zhang
- Department of Neurology, Huizhou Third People's Hospital, Guangzhou Medical University, Huizhou, 516000, China
| | - Ming-Fei Ni
- Department of Radiology, First Affiliate Hospital of Dalian Medical University, Dalian, 116011, China
| | - Yan-Wei Miao
- Department of Radiology, First Affiliate Hospital of Dalian Medical University, Dalian, 116011, China
| | - Bing-Wei Zhang
- Department of Neurology and Psychiatry, First Affiliated Hospital of Dalian Medical University, Dalian, 116011, China; Department of Psychology, Dalian Medical University, Dalian, 116044, China.
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Cattarinussi G, Di Giorgio A, Moretti F, Bondi E, Sambataro F. Dynamic functional connectivity in schizophrenia and bipolar disorder: A review of the evidence and associations with psychopathological features. Prog Neuropsychopharmacol Biol Psychiatry 2023; 127:110827. [PMID: 37473954 DOI: 10.1016/j.pnpbp.2023.110827] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 06/05/2023] [Accepted: 07/10/2023] [Indexed: 07/22/2023]
Abstract
Alterations of functional network connectivity have been implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BD). Recent studies also suggest that the temporal dynamics of functional connectivity (dFC) can be altered in these disorders. Here, we summarized the existing literature on dFC in SCZ and BD, and their association with psychopathological and cognitive features. We systematically searched PubMed, Web of Science, and Scopus for studies investigating dFC in SCZ and BD and identified 77 studies. Our findings support a general model of dysconnectivity of dFC in SCZ, whereas a heterogeneous picture arose in BD. Although dFC alterations are more severe and widespread in SCZ compared to BD, dysfunctions of a triple network system underlying goal-directed behavior and sensory-motor networks were present in both disorders. Furthermore, in SCZ, positive and negative symptoms were associated with abnormal dFC. Implications for understanding the pathophysiology of disorders, the role of neurotransmitters, and treatments on dFC are discussed. The lack of standards for dFC metrics, replication studies, and the use of small samples represent major limitations for the field.
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Affiliation(s)
- Giulia Cattarinussi
- Department of Neuroscience (DNS), University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy
| | - Annabella Di Giorgio
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Federica Moretti
- Department of Medicine and Surgery, University of Milan Bicocca, Milan, Italy
| | - Emi Bondi
- Department of Mental Health and Addictions, ASST Papa Giovanni XXIII, Bergamo, Italy
| | - Fabio Sambataro
- Department of Neuroscience (DNS), University of Padova, Italy; Padova Neuroscience Center, University of Padova, Italy.
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Buciuman MO, Oeztuerk OF, Popovic D, Enrico P, Ruef A, Bieler N, Sarisik E, Weiske J, Dong MS, Dwyer DB, Kambeitz-Ilankovic L, Haas SS, Stainton A, Ruhrmann S, Chisholm K, Kambeitz J, Riecher-Rössler A, Upthegrove R, Schultze-Lutter F, Salokangas RKR, Hietala J, Pantelis C, Lencer R, Meisenzahl E, Wood SJ, Brambilla P, Borgwardt S, Falkai P, Antonucci LA, Bertolino A, Liddle P, Koutsouleris N. Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2023; 8:1207-1217. [PMID: 37343661 DOI: 10.1016/j.bpsc.2023.06.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Revised: 06/01/2023] [Accepted: 06/03/2023] [Indexed: 06/23/2023]
Abstract
BACKGROUND Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level. METHODS Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up. RESULTS Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%. CONCLUSIONS We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.
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Affiliation(s)
- Madalina-Octavia Buciuman
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Oemer Faruk Oeztuerk
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - David Popovic
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Paolo Enrico
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Anne Ruef
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Nadia Bieler
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Elif Sarisik
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; International Max Planck Research School for Translational Psychiatry, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Johanna Weiske
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Mark Sen Dong
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany
| | - Dominic B Dwyer
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Orygen, the National Centre of Excellence for Youth Mental Health, Melbourne, Victoria, Australia
| | - Lana Kambeitz-Ilankovic
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | - Shalaila S Haas
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Alexandra Stainton
- Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia
| | - Stephan Ruhrmann
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | | | - Joseph Kambeitz
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital of Cologne, University of Cologne, Cologne, Germany
| | | | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, United Kingdom
| | - Frauke Schultze-Lutter
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität, Düsseldorf, Germany; Department of Psychology, Faculty of Psychology, Airlangga University, Surabaya, Indonesia; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland
| | | | - Jarmo Hietala
- Department of Psychiatry, University of Turku, Turku, Finland
| | - Christos Pantelis
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, University of Melbourne, Carlton South, Melbourne, Victoria, Australia; NorthWestern Mental Health, Royal Melbourne Hospital, Parkville, Melbourne, Victoria, Australia
| | - Rebekka Lencer
- Department of Psychiatry and Psychotherapy, University of Münster, Münster, Germany
| | - Eva Meisenzahl
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität, Düsseldorf, Germany
| | - Stephen J Wood
- Orygen, the National Centre of Excellence for Youth Mental Health, Melbourne, Victoria, Australia; Centre for Youth Mental Health, University of Melbourne, Melbourne, Victoria, Australia; School of Psychology, University of Birmingham, Birmingham, United Kingdom
| | - Paolo Brambilla
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione Istituto di Ricovero e Cura a Carattere Scientifico Ca' Granda Ospedale Maggiore Policlinico, University of Milan, Milan, Italy
| | - Stefan Borgwardt
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lüebeck, Germany
| | - Peter Falkai
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany
| | - Linda A Antonucci
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Sciences, Neuroscience and Sense Organs, University of Bari "Aldo Moro", Bari, Italy; Department of Translational Biomedicine and Neuroscience (DiBraiN) - University of Bari "Aldo Moro," Bari, Italy
| | - Peter Liddle
- Division of Mental Health and Clinical Neuroscience, Institute of Mental Health, School of Medicine, University of Nottingham, Nottingham, United Kingdom
| | - Nikolaos Koutsouleris
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilian University, Munich, Germany; Max Planck Institute for Psychiatry, Munich, Germany; Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom.
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29
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Kang Y, Zhang Y, Huang K, Wang Z. Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia. Brain Imaging Behav 2023; 17:584-594. [PMID: 37382826 DOI: 10.1007/s11682-023-00786-2] [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] [Accepted: 06/11/2023] [Indexed: 06/30/2023]
Abstract
Alterations in dynamic intrinsic brain activity and signaling of neurotransmitters, such as dopamine, have been independently detected in schizophrenia patients. Yet, it remains unclear whether the dopamine genetic risk variants have association with brain intrinsic activity. We aimed to investigate the schizophrenia-specific dynamic amplitude of low frequency fluctuation (dALFF) altered pattern, and its association with dopamine genetic risk score in first-episode drug-naïve schizophrenia (FES). Fifty-two FES and 51 healthy controls were included. A sliding-window method based on the dALFF was adopted to estimate the dynamic alterations in intrinsic brain activity. Subjects were genotyped, and a genetic risk score (GRS), which combined the additive effects of ten risk genotypes from five dopamine-related genes, was calculated. We used the voxel-wise correlation analysis to explore the association of dopamine-GRS with dALFF. FES showed significantly increased dALFF left medial prefrontal cortex and significantly decreased dALFF in the right posterior cingulate cortex compared with healthy controls. Greater dopamine GRS in FES was associated with higher dALFF in the left middle frontal gyrus and left inferior parietal gyrus. Our findings indicate that cumulative dopamine genetic risk is associated with a known imaging phenotype for schizophrenia.
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Affiliation(s)
- Yafei Kang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Youming Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Kexin Huang
- West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Zhenhong Wang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China.
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30
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Yang W, Niu H, Jin Y, Cui J, Li M, Qiu Y, Lu D, Li G, Li J. Altered dynamic functional connectivity of the thalamus subregions in patients with schizophrenia. J Psychiatr Res 2023; 167:86-92. [PMID: 37862908 DOI: 10.1016/j.jpsychires.2023.09.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 06/05/2023] [Accepted: 09/27/2023] [Indexed: 10/22/2023]
Abstract
BACKGROUND Previous neuroimaging studies indicated that patients with schizophrenia showed impaired thalamus and thalamo-cortical circuits. However, the dynamic functional connectivity (dFC) patterns of the thalamus remain unclear. In this study, we explored the dFC of the thalamus in SZ patients and whether clinical features are correlated with altered dFC. METHODS Forty-three patients with schizophrenia and 31 healthy controls underwent 3.0 T rs-fMRI. Based on the human Brainnetome atlas, the thalamus is divided into 8 subregions. Subsequently, we performed flexible least squares method to calculate the dFC of each thalamus subregions. RESULTS Compared with healthy controls, patients with schizophrenia exhibited increased dFC between the thalamus and cerebellar, visual-related cortex, sensorimotor-related cortex, and frontal lobe. In addition, we found that the dFC of the thalamus and the right fusiform gyrus was negatively associated with age of onset. CONCLUSIONS Our findings demonstrated that the dFC of specific thalamus sub-regions is altered in patients with schizophrenia. Our results further suggested the dysconnectivity of thalamus plays an important role in the pathophysiology of schizophrenia.
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Affiliation(s)
- Weiliang Yang
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Huiming Niu
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Yiqiong Jin
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Jie Cui
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Meijuan Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Yuying Qiu
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China
| | - Duihong Lu
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Gang Li
- The Third People's Hospital of Tianshui, Tianshui, 741000, China
| | - Jie Li
- Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China.
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Bu C, Ren H, Lv Q, Bu H, Gao X, Zheng R, Huang H, Wang W, Wei Y, Cheng J, Zhang Y. Alteration of static and dynamic intrinsic brain activity induced by short-term spinal cord stimulation in postherpetic neuralgia patients. Front Neurosci 2023; 17:1254514. [PMID: 37877014 PMCID: PMC10590878 DOI: 10.3389/fnins.2023.1254514] [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: 07/07/2023] [Accepted: 09/21/2023] [Indexed: 10/26/2023] Open
Abstract
Introduction Short-term spinal cord stimulation (stSCS) is an effective treatment for postherpetic neuralgia (PHN). However, how exactly stSCS affects time-dynamic intrinsic brain activity in PHN patients is not clear. The purpose of this study was to examine the static and dynamic variability of neural activity in PHN patients after stSCS. Methods In this study, 10 patients with PHN underwent resting-state functional magnetic resonance imaging (rs-fMRI) at baseline and after SCS. The amplitude of low-frequency fluctuations (ALFF) and dynamic ALFF (dALFF) were used to investigate the static and dynamic variability of neural activity in PHN patients after stSCS. We additionally examined the associations between clinical parameters and functional changes in the brain. Results There was a significant increase in dALFF in the left precuneus and right superior parietal gyrus, and a decrease in dALFF in the left inferior temporal gyrus, right gyrus rectus, left superior temporal gyrus, right orbitofrontal cortex, and left orbitofrontal cortex. There was significantly increased ALFF in the right inferior temporal gyrus, and decreased ALFF in the right lingual gyrus, left superior parietal gyrus, right superior parietal gyrus, and left precuneus. Furthermore, Pittsburgh sleep quality index scores were positively associated with dALFF changes in the left superior temporal gyrus and left orbitofrontal cortex. Hospital anxiety and depression scale scores and continuous pain scores exhibited significant negative correlation with dALFF changes in the right superior parietal gyrus. Conclusion This study indicated that stSCS is able to cause dALFF changes in PHN patients, thus stSCS might alter brain functions to relieve pain, sleep, and mood symptoms. The findings provide new insights into the mechanisms of stSCS efficacy in the treatment of patients with PHN.
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Affiliation(s)
- Chunxiao Bu
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huan Ren
- Department of Pain Medicine, Peking University Shenzhen Hospital, Shenzhen, China
| | - Qingqing Lv
- Department of Radiology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huilian Bu
- Department of Pain Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xinyu Gao
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Ruiping Zheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Huiyu Huang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Weijian Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yarui Wei
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yong Zhang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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32
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Luo L, Li Q, Wang Y, He N, Wang Y, You W, Zhang Q, Long F, Chen L, Zhao Y, Yao L, Sweeney JA, Gong Q, Li F. Shared and Disorder-Specific Alterations of Brain Temporal Dynamics in Obsessive-Compulsive Disorder and Schizophrenia. Schizophr Bull 2023; 49:1387-1398. [PMID: 37030006 PMCID: PMC10483459 DOI: 10.1093/schbul/sbad042] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/10/2023]
Abstract
BACKGROUND Obsessive-compulsive disorder (OCD) and schizophrenia have distinct but also overlapping symptoms. Few studies have examined the shared and disorder-specific disturbances in dynamic brain function in the 2 disorders. STUDY DESIGN Resting-state functional magnetic resonance imaging data of 31 patients with OCD and 49 patients with schizophrenia, all untreated, and 45 healthy controls (HCs) were analyzed using spatial group independent component (IC) analysis. Time-varying degree centrality patterns across the whole brain were clustered into 3 reoccurring states, and state transition metrics were obtained. We further explored regional temporal variability of degree centrality for each IC across all time windows. STUDY RESULTS Patients with OCD and patients with schizophrenia both showed decreased occurrence of a state having the highest centrality in the sensorimotor and auditory networks. Additionally, patients with OCD and patients with schizophrenia both exhibited reduced dynamics of degree centrality in the superior frontal gyrus than controls, while dynamic degree centrality of the cerebellum was lower in patients with schizophrenia than with OCD and HCs. Altered dynamics of degree centrality nominally correlated with symptom severity in both patient groups. CONCLUSIONS Our study provides evidence of transdiagnostic and clinically relevant functional brain abnormalities across OCD and schizophrenia in neocortex, as well as functional dynamic alterations in the cerebellum specific to schizophrenia. These findings add to the recognition of overlap in neocortical alterations in the 2 disorders, and indicate that cerebellar alterations in schizophrenia may be specifically important in schizophrenia pathophysiology via impact on cerebellar thalamocortical circuitry.
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Affiliation(s)
- Lekai Luo
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
- Department of Radiology, West China Second Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Qian Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Yaxuan Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Ning He
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Yuxia Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Wanfang You
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Qian Zhang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Fenghua Long
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Lizhou Chen
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Youjin Zhao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Li Yao
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - John A Sweeney
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
- Department of Psychiatry and Behavioral Neuroscience, University of Cincinnati, Cincinnati, OH
| | - Qiyong Gong
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
| | - Fei Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, Sichuan, P.R. China
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Duda M, Faghiri A, Belger A, Bustillo JR, Ford JM, Mathalon DH, Mueller BA, Pearlson GD, Potkin SG, Preda A, Sui J, Van Erp TGM, Calhoun VD. Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.05.547840. [PMID: 37461731 PMCID: PMC10350020 DOI: 10.1101/2023.07.05.547840] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/25/2023]
Abstract
Schizophrenia (SZ) is a complex psychiatric disorder that is currently defined by symptomatic and behavioral, rather than biological, criteria. Neuroimaging is an appealing avenue for SZ biomarker development, as several neuroimaging-based studies comparing individuals with SZ to healthy controls (HC) have shown measurable group differences in brain structure, as well as functional brain alterations in both static and dynamic functional network connectivity (sFNC and dFNC, respectively). The recently proposed filter-banked connectivity (FBC) method extends the standard dFNC sliding-window approach to estimate FNC within an arbitrary number of distinct frequency bands. The initial implementation used a set of filters spanning the full connectivity spectral range, providing a unified approach to examine both sFNC and dFNC in a single analysis. Initial FBC results found that individuals with SZ spend more time in a less structured, more disconnected low-frequency (i.e., static) FNC state than HC, as well as preferential SZ occupancy in high-frequency connectivity states, suggesting a frequency-specific component underpinning the functional dysconnectivity observed in SZ. Building on these findings, we sought to link such frequency-specific patterns of FNC to covarying data-driven structural brain networks in the context of SZ. Specifically, we employ a multi-set canonical correlation analysis + joint independent components analysis (mCCA + jICA) data fusion framework to study the connection between grey matter volume (GMV) maps and FBC states across the full connectivity frequency spectrum. Our multimodal analysis identified two joint sources that captured co-varying patterns of frequency-specific functional connectivity and alterations in GMV with significant group differences in loading parameters between the SZ group and HC. The first joint source linked frequency-modulated connections between the subcortical and sensorimotor networks and GMV alterations in the frontal and temporal lobes, while the second joint source identified a relationship between low-frequency cerebellar-sensorimotor connectivity and structural changes in both the cerebellum and motor cortex. Together, these results show a strong connection between cortico-subcortical functional connectivity at both high and low frequencies and alterations in cortical GMV that may be relevant to the pathogenesis and pathophysiology of SZ.
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Affiliation(s)
- Marlena Duda
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Ashkan Faghiri
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | - Aysenil Belger
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Juan R Bustillo
- Department of Psychiatry and Behavioral Sciences, University of New Mexico, Albuquerque, NM, USA
| | - Judith M Ford
- Mental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco, California, USA
- Department of Psychiatry and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
| | - Daniel H Mathalon
- Mental Health Service, San Francisco Veterans Affairs Healthcare System, San Francisco, California, USA
- Department of Psychiatry and Weill Institute for Neurosciences, University of California San Francisco, San Francisco, California, USA
| | - Bryon A Mueller
- Department of Psychiatry and Behavioral Sciences, University of Minnesota, Minneapolis, Minnesota, USA
| | - Godfrey D Pearlson
- Departments of Psychiatry and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Steven G Potkin
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, California, USA
| | - Jing Sui
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
- IDG/McGovern Institute for Brain Research, State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Theo G M Van Erp
- Clinical Translational Neuroscience Laboratory, Department of Psychiatry and Human Behavior, University of California Irvine, Irvine, CA, USA
- Center for the Neurobiology of Learning and Memory, University of California Irvine, Irvine, CA, USA
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
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Yu R, Han B, Wu X, Wei G, Zhang J, Ding M, Wen X. Dual-functional network regulation underlies the central executive system in working memory. Neuroscience 2023:S0306-4522(23)00245-2. [PMID: 37286158 DOI: 10.1016/j.neuroscience.2023.05.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 04/24/2023] [Accepted: 05/27/2023] [Indexed: 06/09/2023]
Abstract
The frontoparietal network (FPN) and cingulo-opercular network (CON) may exert top-down regulation corresponding to the central executive system (CES) in working memory (WM); however, contributions and regulatory mechanisms remain unclear. We examined network interaction mechanisms underpinning the CES by depicting CON- and FPN-mediated whole-brain information flow in WM. We used datasets from participants performing verbal and spatial working memory tasks, divided into encoding, maintenance, and probe stages. We used general linear models to obtain task-activated CON and FPN nodes to define regions of interest (ROI); an online meta-analysis defined alternative ROIs for validation. We calculated whole-brain functional connectivity (FC) maps seeded by CON and FPN nodes at each stage using beta sequence analysis. We used Granger causality analysis to obtain the connectivity maps and assess task-level information flow patterns. For verbal working memory, the CON functionally connected positively and negatively to task-dependent and task-independent networks, respectively, at all stages. FPN FC patterns were similar only in the encoding and maintenance stages. The CON elicited stronger task-level outputs. Main effects were: stable CON→FPN, CON→DMN, CON→visual areas, FPN→visual areas, and phonological areas→FPN. The CON and FPN both up-regulated task-dependent and down-regulated task-independent networks during encoding and probing. Task-level output was slightly stronger for the CON. CON→FPN, CON→DMN, visual areas→CON, and visual areas→FPN showed consistent effects. The CON and FPN might together underlie the CES's neural basis and achieve top-down regulation through information interaction with other large-scale functional networks, and the CON may be a higher-level regulatory core in WM.
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Affiliation(s)
- Renshu Yu
- Department of Psychology, Renmin University of China, Beijing, China, 100872; Laboratory of the Department of Psychology, Renmin University of China, Beijing, China, 100872
| | - Bukui Han
- Department of Psychology, Renmin University of China, Beijing, China, 100872; Laboratory of the Department of Psychology, Renmin University of China, Beijing, China, 100872
| | - Xia Wu
- School of Artificial Intelligence, Beijing Normal University, Beijing, China, 100093
| | - Guodong Wei
- Department of Psychology, Renmin University of China, Beijing, China, 100872; Laboratory of the Department of Psychology, Renmin University of China, Beijing, China, 100872
| | - Junhui Zhang
- Department of Psychology, Renmin University of China, Beijing, China, 100872; Laboratory of the Department of Psychology, Renmin University of China, Beijing, China, 100872
| | - Mingzhou Ding
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville FL, USA, 32611
| | - Xiaotong Wen
- Department of Psychology, Renmin University of China, Beijing, China, 100872; Laboratory of the Department of Psychology, Renmin University of China, Beijing, China, 100872; Interdisciplinary Platform of Philosophy and Cognitive Science, Renmin University of China, China, 100872.
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Rokham H, Falakshahi H, Fu Z, Pearlson G, Calhoun VD. Evaluation of boundaries between mood and psychosis disorder using dynamic functional network connectivity (dFNC) via deep learning classification. Hum Brain Mapp 2023; 44:3180-3195. [PMID: 36919656 PMCID: PMC10171526 DOI: 10.1002/hbm.26273] [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: 07/07/2022] [Revised: 02/20/2023] [Accepted: 02/27/2023] [Indexed: 03/16/2023] Open
Abstract
The validity and reliability of diagnoses in psychiatry is a challenging topic in mental health. The current mental health categorization is based primarily on symptoms and clinical course and is not biologically validated. Among multiple ongoing efforts, neurological observations alongside clinical evaluations are considered to be potential solutions to address diagnostic problems. The Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) has published multiple papers attempting to reclassify psychotic illnesses based on biological rather than symptomatic measures. However, the effort to investigate the relationship between this new categorization approach and other neuroimaging techniques, including resting-state fMRI data, is still limited. This study focused on investigating the relationship between different psychotic disorders categorization methods and resting-state fMRI-based measures called dynamic functional network connectivity (dFNC) using state-of-the-art artificial intelligence (AI) approaches. We applied our method to 613 subjects, including individuals with psychosis and healthy controls, which were classified using both the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) and the B-SNIP biomarker-based (Biotype) approach. Statistical group differences and cross-validated classifiers were performed within each framework to assess how different categories. Results highlight interesting differences in occupancy in both DSM-IV and Biotype categorizations compared to healthy individuals, which are distributed across specific transient connectivity states. Biotypes tended to show less distinctiveness in occupancy level and included fewer cellwise differences. Classification accuracy obtained by DSM-IV and Biotype categories were both well above chance. Results provided new insights and highlighted the benefits of both DSM-IV and biology-based categories while also emphasizing the importance of future work in this direction, including employing further data types.
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Affiliation(s)
- Hooman Rokham
- Department of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
| | - Haleh Falakshahi
- Department of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
| | - Zening Fu
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
| | - Godfrey Pearlson
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Department of NeuroscienceYale UniversityNew HavenConnecticutUSA
- Olin Neuropsychiatry Research CenterHartford HospitalHartfordConnecticutUSA
| | - Vince D. Calhoun
- Department of Electrical and Computer EngineeringGeorgia Institute of TechnologyAtlantaGeorgiaUSA
- Tri‐institutional Center of Translational Research in Neuroimaging and Data Science (TReNDS), Georgia Institute of Technology, and Emory UniversityGeorgia State UniversityAtlantaGeorgiaUSA
- Department of PsychiatryYale UniversityNew HavenConnecticutUSA
- Department of Computer ScienceGeorgia State UniversityAtlantaGeorgiaUSA
- Department of PsychologyGeorgia State UniversityAtlantaGeorgiaUSA
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Wu X, Wang L, Jiang H, Fu Y, Wang T, Ma Z, Wu X, Wang Y, Fan F, Song Y, Lv Y. Frequency-dependent and time-variant alterations of neural activity in post-stroke depression: A resting-state fMRI study. Neuroimage Clin 2023; 38:103445. [PMID: 37269698 PMCID: PMC10244813 DOI: 10.1016/j.nicl.2023.103445] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 05/23/2023] [Accepted: 05/24/2023] [Indexed: 06/05/2023]
Abstract
BACKGROUND Post-stroke depression (PSD) is one of the most frequent psychiatric disorders after stroke. However, the underlying brain mechanism of PSD remains unclarified. Using the amplitude of low-frequency fluctuation (ALFF) approach, we aimed to investigate the abnormalities of neural activity in PSD patients, and further explored the frequency and time properties of ALFF changes in PSD. METHODS Resting-state fMRI data and clinical data were collected from 39 PSD patients (PSD), 82 S patients without depression (Stroke), and 74 age- and sex-matched healthy controls (HC). ALFF across three frequency bands (ALFF-Classic: 0.01-0.08 Hz; ALFF-Slow4: 0.027-0.073 Hz; ALFF-Slow5: 0.01-0.027 Hz) and dynamic ALFF (dALFF) were computed and compared among three groups. Ridge regression analyses and spearman's correlation analyses were further applied to explore the relationship between PSD-specific alterations and depression severity in PSD. RESULTS We found that PSD-specific alterations of ALFF were frequency-dependent and time-variant. Specially, compared to both Stroke and HC groups, PSD exhibited increased ALFF in the contralesional dorsolateral prefrontal cortex (DLPFC) and insula in all three frequency bands. Increased ALFF in ipsilesional DLPFC were observed in both slow-4 and classic frequency bands which were positively correlated with depression scales in PSD, while increased ALFF in the bilateral hippocampus and contralesional rolandic operculum were only found in slow-5 frequency band. These PSD-specific alterations in different frequency bands could predict depression severity. Moreover, decreased dALFF in contralesional superior temporal gyrus were observed in PSD group. LIMITATIONS Longitudinal studies are required to explore the alterations of ALFF in PSD as the disease progress. CONCLUSIONS The frequency-dependent and time-variant properties of ALFF could reflect the PSD-specific alterations in complementary ways, which may assist to elucidate underlying neural mechanisms and be helpful for early diagnosis and interventions for the disease.
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Affiliation(s)
- Xiumei Wu
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Luoyu Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Department of Radiology, Affiliated Hangzhou First People's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Haibo Jiang
- Department of Neurology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - Yanhui Fu
- Department of Neurology, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Tiantian Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Zhenqiang Ma
- Department of Neurology, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Xiaoyan Wu
- Department of Image, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Yiying Wang
- Department of Ultrasonics, Anshan Changda Hospital, Anshan, Liaoning, China
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China.
| | - Yulin Song
- Department of Neurology, Anshan Changda Hospital, Anshan, Liaoning, China.
| | - Yating Lv
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China.
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Dai YR, Wu YK, Chen X, Zeng YW, Li K, Li JT, Su YA, Zhu LL, Yan CG, Si TM. Eight-week antidepressant treatment changes intrinsic functional brain topology in first-episode drug-naïve patients with major depressive disorder. J Affect Disord 2023; 329:225-234. [PMID: 36858265 DOI: 10.1016/j.jad.2023.02.126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/20/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023]
Abstract
BACKGROUND A recent study revealed disrupted topological organization of whole-brain networks in patients with major depressive disorder (MDD); however, these results were mostly driven by recurrent MDD patients, rather than first-episode drug-naïve (FEDN) patients. Furthermore, few longitudinal studies have explored the effects of antidepressant therapy on the topological organization of whole-brain networks. METHODS We collected clinical and neuroimaging data from 159 FEDN MDD patients and 152 normal controls (NCs). A total of 115 MDD patients completed an eight-week antidepressant treatment procedure. Topological features of brain networks were calculated using graph theory-based methods and compared between FEDN MDD patients and NCs, as well as before and after treatment. RESULTS Decreased global efficiency, local efficiency, small-worldness, and modularity were found in pretreatment FEDN MDD patients compared with NCs. Nodal degrees, betweenness, and efficiency decreased in several networks compared with NCs. After antidepressant treatment, the global efficiency increased, while the local efficiency, the clustering coefficient of the network, the path length, and the normalized characteristic path length decreased. Moreover, the reduction rate of the normalized characteristic path length was positively correlated with the reduction rate of retardation factor scores. LIMITATIONS The interaction effects of groups and time on the topological features were not explored because of absence of the eighth-week data of NC group. CONCLUSIONS The topological architecture of functional brain networks is disrupted in FEDN MDD patients. After antidepressant therapy, the global efficiency shifted toward recovery, but the local efficiency deteriorated, suggesting a correlation between recovery of retardation symptoms and global efficiency.
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Affiliation(s)
- You-Ran Dai
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yan-Kun Wu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Xiao Chen
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Ya-Wei Zeng
- PLA Strategic support Force Characteristic Medical Center, Beijing 100101, China
| | - Ke Li
- PLA Strategic support Force Characteristic Medical Center, Beijing 100101, China
| | - Ji-Tao Li
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Yun-Ai Su
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China
| | - Lin-Lin Zhu
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
| | - Chao-Gan Yan
- CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, China
| | - Tian-Mei Si
- Peking University Sixth Hospital, Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing 100191, China.
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Xu L, Wei H, Sun Z, Chu T, Li M, Liu R, Jiang L, Liang Z. Dynamic alterations of spontaneous neural activity in post-stroke aphasia: a resting-state functional magnetic resonance imaging study. Front Neurosci 2023; 17:1177930. [PMID: 37250389 PMCID: PMC10213748 DOI: 10.3389/fnins.2023.1177930] [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: 03/02/2023] [Accepted: 04/20/2023] [Indexed: 05/31/2023] Open
Abstract
Background and purpose The dynamic alterations in spontaneous neural activity of the brain during the acute phase of post-stroke aphasia (PSA) remain unclear. Therefore, in this study, dynamic amplitude of low-frequency fluctuation (dALFF) was applied to explore abnormal temporal variability in local functional activity of the brain during acute PSA. Materials and methods Resting-state functional magnetic resonance imaging (rs-fMRI) data from 26 patients with PSA and 25 healthy controls (HCs) were acquired. The sliding window method was used to assess dALFF, with the k-means clustering method used to identify dALFF states. The two-sample t-test was applied to compare differences in dALFF variability and state metrics between the PSA and HC groups. Results (1) In the PSA group, greater variance of dALFF in the cerebellar network (CBN) and left fronto-temporo-parietal network (FTPN) was observed. (2) Three dALFF states were identified among all subjects. States 1 and 2 were identified in the PSA patients, and the two dALFF states shared a similar proportion. Moreover, the number of transitions between the two dALFF states was higher in the patients compared with that in HCs. Conclusion The results of this study provide valuable insights into brain dysfunction that occurs during the acute phase (6.00 ± 3.52 days) of PSA. The observed increase in variability of local functional activities in CBN and left FTPN may be related to the spontaneous functional recovery of language during acute PSA, and it also suggests that cerebellum plays an important role in language.
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Affiliation(s)
- Luyao Xu
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Hongchun Wei
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Zhongwen Sun
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Min Li
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Ruhui Liu
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Li Jiang
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
| | - Zhigang Liang
- Department of Neurology, Yantai Yuhuangding Hospital Affiliated to Qingdao University, Yantai, Shandong, China
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Zhu Z, Wang S, Lee T, Zhang R. Habenula functional connectivity variability increases with disease severity in individuals with major depression. J Affect Disord 2023; 333:216-224. [PMID: 37088249 DOI: 10.1016/j.jad.2023.04.082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 03/23/2023] [Accepted: 04/18/2023] [Indexed: 04/25/2023]
Abstract
BACKGROUND Increasing evidence has suggested the significant relationships between major depressive disorder (MDD) and the neural abnormalities of the Habenula (Hb). Yet, previous research on the relationships between Hb and MDD mainly focuses on the static descriptions of their functional connectivity. However, recent work suggests that the connectivity patterns are indeed dynamic, though related analysis and interpretation remain scarce. METHODS Using seed-based resting-state fMRI, the static (sFC) and dynamic functional connectivity (dFC) between the Hb and whole-brain were calculated, including 51 clinical participants (MDDs) and 45 healthy controls (HCs). Association between the aberrant connectivity patterns and depressive symptomatology was also analyzed. RESULTS Compared with the HCs, MDDs exhibited increased sFC from the left Hb to the right inferior temporal gyrus and left superior frontal gyrus (SFG), while sFC to the right calcarine gyrus decreased. Notably, we observed that dFC between the left Hb and the right supplementary motor area, right postcentral gyrus (PoCG), left inferior frontal gyrus as well as left occipital gyrus was weak in MDDs. Furthermore, sFC between the Hb and SFG correlated positively with the measured attention-related cognitive deficits. Importantly, there was a positive correlation between dFC between the Hb and PoCG and depressive severity. CONCLUSIONS The findings indicate that the anomalous neural circuitry of Hb may underpin impaired attention disengagement, emotional modulation and motor inhibition associated with depressive symptoms such as rumination disposition and psychomotor retardation. This may open new avenues for studying the neuropathology mechanisms and guiding new treatment strategies for MDD.
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Affiliation(s)
- Ziqing Zhu
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China
| | - Sibin Wang
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Tatia Lee
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, China; Center for Brain Science and Brain-Inspired Intelligence, Guangdong-Hong Kong-Macao Greater Bay Area, China.
| | - Ruibin Zhang
- Cognitive Control and Brain Healthy Laboratory, Department of Psychology, School of Public Health, Southern Medical University, Guangzhou, China; State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Hong Kong, China; Center for Brain Science and Brain-Inspired Intelligence, Guangdong-Hong Kong-Macao Greater Bay Area, China; Department of Psychiatry, Zhujiang Hospital, Southern Medical University, Guangzhou, China.
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Ji J, Liu YY, Wu GW, Hu YL, Liang CH, Wang XD. Changes in dynamic and static brain fluctuation distinguish minimal hepatic encephalopathy and cirrhosis patients and predict the severity of liver damage. Front Neurosci 2023; 17:1077808. [PMID: 37056312 PMCID: PMC10086246 DOI: 10.3389/fnins.2023.1077808] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 03/13/2023] [Indexed: 03/30/2023] Open
Abstract
PurposeMinimal hepatic encephalopathy (MHE) is characterized by mild neuropsychological and neurophysiological alterations that are not detectable by routine clinical examination. Abnormal brain activity (in terms of the amplitude of low-frequency fluctuation (ALFF) has been observed in MHE patients. However, little is known concerning temporal dynamics of intrinsic brain activity. The present study aimed to investigate the abnormal dynamics of brain activity (dynamic ALFF; dALFF) and static measures [static ALFF; (sALFF)] in MHE patients and to strive for a reliable imaging neuromarkers for distinguishing MHE patients from cirrhosis patients. In addition, the present study also investigated whether intrinsic brain activity predicted the severity of liver damage.MethodsThirty-four cirrhosis patients with MHE, 28 cirrhosis patients without MHE, and 33 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state magnetic resonance imaging (rs-fMRI). dALFF was estimated by combining the ALFF method with the sliding-window method, in which temporal variability was quantized over the whole-scan timepoints and then compared among the three groups. Additionally, dALFF, sALFF and both two features were utilized as classification features in a support vector machine (SVM) to distinguish MHE patients from cirrhosis patients. The severity of liver damage was reflected by the Child–Pugh score. dALFF, sALFF and both two features were used to predict Child–Pugh scores in MHE patients using a general linear model.ResultsCompared with HCs, MHE patients showed significantly increased dALFF in the left inferior occipital gyrus, right middle occipital gyrus, and right insula; increased dALFF was also observed in the right posterior lobe of the cerebellum (CPL) and right thalamus. Compared with HCs, noMHE patients exhibited decreased dALFF in the right precuneus. In contrast, compared with noMHE patients, MHE patients showed increased dALFF in the right precuneus, right superior frontal gyrus, and right superior occipital gyrus. Furthermore, the increased dALFF values in the left precuneus were positively associated with poor digit-symbol test (DST) scores (r = 0.356, p = 0.038); however, dALFF in the right inferior temporal gyrus (ITG) was negatively associated with the number connection test–A (NCT-A) scores (r = -0.784, p = 0.000). A significant positive correlation was found between dALFF in the left inferior occipital gyrus (IOG) and high blood ammonia levels (r = 0.424, p = 0.012). Notably, dALFF values yielded a higher classification accuracy than sALFF values in distinguishing MHE patients from cirrhosis patients. Importantly, the dALFF values predicted the Child–Pugh score (r = 0.140, p = 0.030), whereas sALFF values did not in the current dataset. Combining two features had high accuracy in classification in distinguishing MHE patients from cirrhotic patients and yielded prediction in the severity of liver damage.ConclusionThese findings suggest that combining dALFF and sALFF features is a useful neuromarkers for distinguishing MHE patients from cirrhosis patients and highlights the important role of dALFF feature in predicting the severity of liver damage in MHE.
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Affiliation(s)
- Jiang Ji
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
- Department of Radiology, The First Affiliated Hospital of Xinxiang Medical College, Xinxiang, China
| | - Yi-yang Liu
- Department of Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Guo-Wei Wu
- Chinese Institute for Brain Research, Beijing, China
| | - Yan-Long Hu
- Department of Radiology, The First Affiliated Hospital of Xinxiang Medical College, Xinxiang, China
| | - Chang-Hua Liang
- Department of Radiology, The First Affiliated Hospital of Xinxiang Medical College, Xinxiang, China
- *Correspondence: Chang-Hua Liang,
| | - Xiao-dong Wang
- Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, China
- Xiao-dong Wang,
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Zhang S, Goodale SE, Gold BP, Morgan VL, Englot DJ, Chang C. Vigilance associates with the low-dimensional structure of fMRI data. Neuroimage 2023; 267:119818. [PMID: 36535323 PMCID: PMC10074161 DOI: 10.1016/j.neuroimage.2022.119818] [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: 08/21/2022] [Revised: 11/24/2022] [Accepted: 12/15/2022] [Indexed: 12/23/2022] Open
Abstract
The human brain exhibits rich dynamics that reflect ongoing functional states. Patterns in fMRI data, detected in a data-driven manner, have uncovered recurring configurations that relate to individual and group differences in behavioral, cognitive, and clinical traits. However, resolving the neural and physiological processes that underlie such measurements is challenging, particularly without external measurements of brain state. A growing body of work points to underlying changes in vigilance as one driver of time-windowed fMRI connectivity states, calculated on the order of tens of seconds. Here we examine the degree to which the low-dimensional spatial structure of instantaneous fMRI activity is associated with vigilance levels, by testing whether vigilance-state detection can be carried out in an unsupervised manner based on individual BOLD time frames. To investigate this question, we first reduce the spatial dimensionality of fMRI data, and apply Gaussian Mixture Modeling to cluster the resulting low-dimensional data without any a priori vigilance information. Our analysis includes long-duration task and resting-state scans that are conducive to shifts in vigilance. We observe a close alignment between low-dimensional fMRI states (data-driven clusters) and measurements of vigilance derived from concurrent electroencephalography (EEG) and behavior. Whole-brain coactivation analysis revealed cortical anti-correlation patterns that resided primarily during higher behavioral- and EEG-defined levels of vigilance, while cortical activity was more often spatially uniform in states corresponding to lower vigilance. Overall, these findings indicate that vigilance states may be detected in the low-dimensional structure of fMRI data, even within individual time frames.
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Affiliation(s)
- Shengchao Zhang
- Department of Electrical and Computer Engineering, Vanderbilt University, 400 24th Avenue S., Nashville, TN 37212, USA.
| | - Sarah E Goodale
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Benjamin P Gold
- Department of Electrical and Computer Engineering, Vanderbilt University, 400 24th Avenue S., Nashville, TN 37212, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Victoria L Morgan
- Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Dario J Englot
- Department of Electrical and Computer Engineering, Vanderbilt University, 400 24th Avenue S., Nashville, TN 37212, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Neurological Surgery, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Catie Chang
- Department of Electrical and Computer Engineering, Vanderbilt University, 400 24th Avenue S., Nashville, TN 37212, USA; Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, USA; Department of Computer Science, Vanderbilt University, Nashville, TN, USA; Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, USA.
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Alaçam D, Miller R, Agcaoglu O, Preda A, Ford J, Calhoun V. A method for capturing dynamic spectral coupling in resting fMRI reveals domain-specific patterns in schizophrenia. Front Neurosci 2023; 17:1078995. [PMID: 37179560 PMCID: PMC10174238 DOI: 10.3389/fnins.2023.1078995] [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: 10/24/2022] [Accepted: 04/03/2023] [Indexed: 05/15/2023] Open
Abstract
Introduction Resting-state functional magnetic resonance imaging (rs-fMRI) is a powerful tool for assessing functional brain connectivity. Recent studies have focused on shorter-term connectivity and dynamics in the resting state. However, most of the prior work evaluates changes in time-series correlations. In this study, we propose a framework that focuses on time-resolved spectral coupling (assessed via the correlation between power spectra of the windowed time courses) among different brain circuits determined via independent component analysis (ICA). Methods Motivated by earlier work suggesting significant spectral differences in people with schizophrenia, we developed an approach to evaluate time-resolved spectral coupling (trSC). To do this, we first calculated the correlation between the power spectra of windowed time-courses pairs of brain components. Then, we subgrouped each correlation map into four subgroups based on the connectivity strength utilizing quartiles and clustering techniques. Lastly, we examined clinical group differences by regression analysis for each averaged count and average cluster size matrices in each quartile. We evaluated the method by applying it to resting-state data collected from 151 (114 males, 37 females) people with schizophrenia (SZ) and 163 (117 males, 46 females) healthy controls (HC). Results Our proposed approach enables us to observe the change of connectivity strength within each quartile for different subgroups. People with schizophrenia showed highly modularized and significant differences in multiple network domains, whereas males and females showed less modular differences. Both cell count and average cluster size analysis for subgroups indicate a higher connectivity rate in the fourth quartile for the visual network in the control group. This indicates increased trSC in visual networks in the controls. In other words, this shows that the visual networks in people with schizophrenia have less mutually consistent spectra. It is also the case that the visual networks are less spectrally correlated on short timescales with networks of all other functional domains. Conclusions The results of this study reveal significant differences in the degree to which spectral power profiles are coupled over time. Importantly, there are significant but distinct differences both between males and females and between people with schizophrenia and controls. We observed a more significant coupling rate in the visual network for the healthy controls and males in the upper quartile. Fluctuations over time are complex, and focusing on only time-resolved coupling among time-courses is likely to miss important information. Also, people with schizophrenia are known to have impairments in visual processing but the underlying reasons for the impairment are still unknown. Therefore, the trSC approach can be a useful tool to explore the reasons for the impairments.
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Affiliation(s)
- Deniz Alaçam
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
- Department of Mathematics, Bursa Uludag University, Bursa, Türkiye
- *Correspondence: Deniz Alaçam
| | - Robyn Miller
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Oktay Agcaoglu
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
| | - Adrian Preda
- Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, United States
| | - Judith Ford
- San Francisco VA Medical Center, University of California, San Francisco, San Francisco, CA, United States
- Department of Psychiatry, University of California, San Francisco, San Francisco, CA, United States
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, Atlanta, GA, United States
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Altered time-varying local spontaneous brain activity pattern in patients with high myopia: a dynamic amplitude of low-frequency fluctuations study. Neuroradiology 2023; 65:157-166. [PMID: 35953566 DOI: 10.1007/s00234-022-03033-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 07/29/2022] [Indexed: 01/10/2023]
Abstract
PURPOSE To investigate the abnormal time-varying local spontaneous brain activity in patients with high myopia (HM) on the basis of the dynamic amplitude of low-frequency fluctuations (dALFF) approach. METHODS Age and gender matching were performed based on resting-state functional magnetic resonance imaging data from 86 HM patients and 87 healthy controls (HCs). Local spontaneous brain activities were evaluated using the time-varying dALFF method. Support vector machine combined with the radial basis function kernel was used for pattern classification analysis. RESULTS Inter-group comparison between HCs and HM patients has demonstrated that dALFF variability in the left inferior frontal gyrus (orbital part), left lingual gyrus, right anterior cingulate and paracingulate gyri, and right calcarine fissure and surrounding cortex was decreased in HM patients, while increased in the left thalamus, left paracentral lobule, and left inferior parietal (except supramarginal and angular gyri). Pattern classification between HM patients and HCs displayed a classification accuracy of 85.5%. CONCLUSION In this study, the findings mentioned above have suggested the association between local brain activities of HM patients and abnormal variability in brain regions performing visual sensorimotor and attentional control functions. Several useful information has been provided to elucidate the mechanism-related alterations of the myopic nervous system. In addition, the significant role of abnormal dALFF variability has been highlighted to achieve an in-depth comprehension of the pathological alterations and neuroimaging mechanisms in the field of HM.
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Wang M, Tang X, Li B, Wan T, Zhu X, Zhu Y, Lai X, He Y, Xia G. Dynamic local metrics changes in patients with toothache: A resting-state functional magnetic resonance imaging study. Front Neurol 2022; 13:1077432. [PMID: 36578304 PMCID: PMC9790921 DOI: 10.3389/fneur.2022.1077432] [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: 10/23/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
Objective To study the dynamic changes of local metrics in patients with toothache (TA, Toothache) in the resting state, in order to further understand the changes of central neural mechanism in patients with dental pain and its effect on cognition and emotion. Methods Thirty patients with TA and thirty matched healthy (HC) control volunteers were recruited, and resting-state functional magnetic resonance (rs-MRI) scans were performed on all subjects, and data were analyzed to compare group differences in three dynamic local indices: dynamic regional homogeneity (dReHO), dynamic low-frequency fluctuation amplitude (dALFF) and dynamic fractional low-frequency fluctuation amplitude (dfALFF). In addition, the association between dynamic local metrics in different brain regions of TA patients and scores on the Visual Analog Scale (VAS) and the Hospital Anxiety and Depression Scale (HADS) was investigated by Pearson correlation analysis. Results In this study, we found that The local metrics of TA patients changed with time Compared with the HC group, TA patients showed increased dReHo values in the left superior temporal gyrus, middle frontal gyrus, precentral gyrus, precuneus, angular gyrus, right superior frontal gyrus, middle temporal gyrus, postcentral gyrus and middle frontal gyrus, increased dALFF values in the right superior frontal gyrus, and increased dfALFF values in the right middle temporal gyrus, middle frontal gyrus and right superior occipital gyrus (p < 0.01, cluster level P < 0.05). Pearson correlation analysis showed that dReHo values of left precuneus and left angular gyrus were positively correlated with VAS scores in TA group. dReHo value of right posterior central gyrus was positively correlated with HADS score (P < 0.05). Conclusion There are differences in the patterns of neural activity changes in resting-state brain areas of TA patients, and the brain areas that undergo abnormal changes are mainly pain processing brain areas, emotion processing brain areas and pain cognitive modulation brain areas, which help to reveal their underlying neuropathological mechanisms. In the hope of further understanding its effects on cognition and emotion.
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Affiliation(s)
- Mengting Wang
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xin Tang
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Bin Li
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Tianyi Wan
- Medical Imaging Center, Jiangxi Provincial People's Hospital, Nanchang, China
| | - Xuechao Zhu
- Medical Imaging Center, Jiangxi Cancer Hospital, Nanchang, China
| | - Yuping Zhu
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Xunfu Lai
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China
| | - Yulin He
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China,*Correspondence: Yulin He
| | - Guojin Xia
- Medical Imaging Center, The First Affiliated Hospital of Nanchang University, Nanchang, China,Guojin Xia
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Cheng B, Wang X, Roberts N, Zhou Y, Wang S, Deng P, Meng Y, Deng W, Wang J. Abnormal dynamics of resting-state functional activity and couplings in postpartum depression with and without anxiety. Cereb Cortex 2022; 32:5597-5608. [PMID: 35174863 DOI: 10.1093/cercor/bhac038] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 01/18/2022] [Accepted: 01/19/2022] [Indexed: 02/05/2023] Open
Abstract
Postpartum depression (PPD) and PPD comorbid with anxiety (PPD-A) are highly prevalent and severe mental health problems in postnatal women. PPD and PPD-A share similar pathopsychological features, leading to ongoing debates regarding the diagnostic and neurobiological uniqueness. This paper aims to delineate common and disorder-specific neural underpinnings and potential treatment targets for PPD and PPD-A by characterizing functional dynamics with resting-state functional magnetic resonance imaging in 138 participants (45 first-episode, treatment-naïve PPD; 31 PDD-A patients; and 62 healthy postnatal women [HPW]). PPD-A group showed specifically increased dynamic amplitude of low-frequency fluctuation in the subgenual anterior cingulate cortex (sgACC) and increased dynamic functional connectivity (dFC) between the sgACC and superior temporal sulcus. PPD group exhibited specifically increased static FC (sFC) between the sgACC and ventral anterior insula. Common disrupted sFC between the sgACC and middle temporal gyrus was found in both PPD and PPD-A patients. Interestingly, dynamic changes in dFC between the sgACC and superior temporal gyrus could differentiate PPD, PPD-A, and HPW. Our study presents initial evidence on specifically abnormal functional dynamics of limbic, emotion regulation, and social cognition systems in patients with PDD and PPD-A, which may facilitate understanding neurophysiological mechanisms, diagnosis, and treatment for PPD and PPD-A.
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Affiliation(s)
- Bochao Cheng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu 610041, China
| | - Xiuli Wang
- Department of Psychiatry, The Fourth People's Hospital of Chengdu, University of Electronic Science and Technology of China, Chengdu 610041, China
| | - Neil Roberts
- Edinburgh Imaging facility, The Queen's Medical Research Institute (QMRI), School of Clinical Sciences, University of Edinburgh, Edinburgh EH16 4TJ, United Kingdom
| | - Yushan Zhou
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu 610041, China.,Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Song Wang
- Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Pengcheng Deng
- Department of Radiology, West China Second University Hospital of Sichuan University, Chengdu 610041, China
| | - Yajing Meng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wei Deng
- Department of Psychiatry, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China
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Luo L, You W, DelBello MP, Gong Q, Li F. Recent advances in psychoradiology. Phys Med Biol 2022; 67. [PMID: 36279868 DOI: 10.1088/1361-6560/ac9d1e] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 10/24/2022] [Indexed: 11/24/2022]
Abstract
Abstract
Psychiatry, as a field, lacks objective markers for diagnosis, progression, treatment planning, and prognosis, in part due to difficulties studying the brain in vivo, and diagnoses are based on self-reported symptoms and observation of patient behavior and cognition. Rapid advances in brain imaging techniques allow clinical investigators to noninvasively quantify brain features at the structural, functional, and molecular levels. Psychoradiology is an emerging discipline at the intersection of psychiatry and radiology. Psychoradiology applies medical imaging technologies to psychiatry and promises not only to improve insight into structural and functional brain abnormalities in patients with psychiatric disorders but also to have potential clinical utility. We searched for representative studies related to recent advances in psychoradiology through May 1, 2022, and conducted a selective review of 165 references, including 75 research articles. We summarize the novel dynamic imaging processing methods to model brain networks and present imaging genetics studies that reveal the relationship between various neuroimaging endophenotypes and genetic markers in psychiatric disorders. Furthermore, we survey recent advances in psychoradiology, with a focus on future psychiatric diagnostic approaches with dimensional analysis and a shift from group-level to individualized analysis. Finally, we examine the application of machine learning in psychoradiology studies and the potential of a novel option for brain stimulation treatment based on psychoradiological findings in precision medicine. Here, we provide a summary of recent advances in psychoradiology research, and we hope this review will help guide the practice of psychoradiology in the scientific and clinical fields.
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Chen W, Wang H, Sun T, Wu Q, Han W, Li Q, Liu Y, Zhou Y, He X. Dynamic changes in fractional amplitude of low-frequency fluctuations in patients with chronic insomnia. Front Neurosci 2022; 16:1050240. [PMID: 36523433 PMCID: PMC9744813 DOI: 10.3389/fnins.2022.1050240] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 11/11/2022] [Indexed: 12/12/2023] Open
Abstract
BACKGROUND Previous neuroimaging studies have mostly focused on changes in static functional connectivity in patients with chronic insomnia (CI) . Features of dynamic brain activity in patients with CI have rarely been described in detail. The present study investigated changes in dynamic intrinsic brain activity in patients with CI by dynamic fractional amplitude of low-frequency fluctuation (dfALFF) analysis. MATERIALS AND METHODS A total of 30 patients with CI and 27 healthy controls (HCs) were enrolled. We compared dfALFF between these two groups, and examined the correlation between changes in dfALFF and clinical symptoms of CI. Multivariate pattern analysis was performed to differentiate patients with CI from HCs. RESULTS Compared with HC subjects, patients with CI showed significantly increased dfALFF in the left insula, right superior temporal gyrus, left parahippocampal gyrus, right amygdala, and bilateral posterior lobes of the cerebellum. Moreover, dfALFF values in the left insula and left parahippocampal gyrus showed a positive correlation with Pittsburgh Sleep Quality Index scores. A logistic regression model was constructed that had 96.7% sensitivity, 80.0% specificity, and 83.0% overall accuracy for distinguishing patients with CI from HCs. CONCLUSION Dynamic local brain activity showed increased instability in patients with CI. The variability in dfALFF in the limbic system and brain areas related to sleep/wakefulness was associated with insomnia symptoms. These findings may provide insight into the neuropathologic basis of CI.
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Affiliation(s)
- Wei Chen
- Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China
| | - Hui Wang
- School of Future Technology, Xi’an Jiaotong University, Xi’an, China
- Department of Medical Imaging, The First Affiliated Hospital of Xi ‘an Jiaotong University, Xi’an, China
| | - Tianze Sun
- Department of Medical Imaging, The First Affiliated Hospital of Xi ‘an Jiaotong University, Xi’an, China
| | - Qi Wu
- Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China
| | - Wenxuan Han
- Department of Medical Imaging, The First Affiliated Hospital of Xi ‘an Jiaotong University, Xi’an, China
| | - Qian Li
- Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China
| | - Yong Liu
- Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China
| | - Yuanping Zhou
- Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China
| | - Xiuyong He
- Department of Medical Imaging Center, Ankang Hospital of Traditional Chinese Medicine, Ankang, China
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Yue J, Zhao N, Qiao Y, Feng Z, Hu Y, Ge Q, Zhang T, Zhang Z, Wang J, Zang Y. Higher reliability and validity of Wavelet-ALFF of resting-state fMRI: From multicenter database and application to rTMS modulation. Hum Brain Mapp 2022; 44:1105-1117. [PMID: 36394386 PMCID: PMC9875929 DOI: 10.1002/hbm.26142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 09/26/2022] [Accepted: 10/15/2022] [Indexed: 11/18/2022] Open
Abstract
Amplitude of low-frequency fluctuation (ALFF) has been widely used for localization of abnormal activity at the single-voxel level in resting-state fMRI (RS-fMRI) studies. However, previous ALFF studies were based on fast Fourier transform (FFT-ALFF). Our recent study found that ALFF based on wavelet transform (Wavelet-ALFF) showed better sensitivity and reproducibility than FFT-ALFF. The current study aimed to test the reliability and validity of Wavelet-ALFF, and apply Wavelet-ALFF to investigate the modulation effect of repetitive transcranial magnetic stimulation (rTMS). The reliability and validity were assessed on multicenter RS-fMRI datasets under eyes closed (EC) and eyes open (EO) conditions (248 healthy participants in total). We then detected the sensitivity of Wavelet-ALFF using a rTMS modulation dataset (24 healthy participants). For each dataset, Wavelet-ALFF based on five mother wavelets (i.e., db2, bior4.4, morl, meyr and sym3) and FFT-ALFF were calculated in the conventional band and five frequency sub-bands. The results showed that the reliability of both inter-scanner and intra-scanner was higher with Wavelet-ALFF than with FFT-ALFF across multiple frequency bands, especially db2-ALFF in the higher frequency band slow-2 (0.1992-0.25 Hz). In terms of validity, the multicenter ECEO datasets showed that the effect sizes of Wavelet-ALFF with all mother wavelets (especially for db2-ALFF) were larger than those of FFT-ALFF across multiple frequency bands. Furthermore, Wavelet-ALFF detected a larger modulation effect than FFT-ALFF. Collectively, Wavelet db2-ALFF showed the best reliability and validity, suggesting that db2-ALFF may offer a powerful metric for inspecting regional spontaneous brain activities in future studies.
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Affiliation(s)
- Juan Yue
- TMS Center, Hangzhou Normal University Affiliated Deqing HospitalHuzhouChina,Center for Cognition and Brain DisordersThe Affiliated Hospital of Hangzhou Normal UniversityHangzhouChina,Institute of Psychological SciencesHangzhou Normal UniversityHangzhouChina,Zhejiang Key Laboratory for Research in Assessment of Cognitive ImpairmentsHangzhouChina
| | - Na Zhao
- Center for Cognition and Brain DisordersThe Affiliated Hospital of Hangzhou Normal UniversityHangzhouChina,Institute of Psychological SciencesHangzhou Normal UniversityHangzhouChina,Zhejiang Key Laboratory for Research in Assessment of Cognitive ImpairmentsHangzhouChina,Unit of Psychiatry, Department of Public Health and Medicinal Administration, & Institute of Translational Medicine, Faculty of Health SciencesUniversity of MacauMacao SARChina,Centre for Cognitive and Brain SciencesUniversity of MacauMacao SARChina
| | - Yang Qiao
- Center for Cognition and Brain DisordersThe Affiliated Hospital of Hangzhou Normal UniversityHangzhouChina,Institute of Psychological SciencesHangzhou Normal UniversityHangzhouChina,Zhejiang Key Laboratory for Research in Assessment of Cognitive ImpairmentsHangzhouChina,Centre for Cognitive and Brain SciencesUniversity of MacauMacao SARChina,Faculty of Health SciencesUniversity of MacauMacao SARChina
| | - Zi‐Jian Feng
- TMS Center, Hangzhou Normal University Affiliated Deqing HospitalHuzhouChina
| | - Yun‐Song Hu
- Center for Cognition and Brain DisordersThe Affiliated Hospital of Hangzhou Normal UniversityHangzhouChina,Institute of Psychological SciencesHangzhou Normal UniversityHangzhouChina,Zhejiang Key Laboratory for Research in Assessment of Cognitive ImpairmentsHangzhouChina
| | - Qiu Ge
- Center for Cognition and Brain DisordersThe Affiliated Hospital of Hangzhou Normal UniversityHangzhouChina,Institute of Psychological SciencesHangzhou Normal UniversityHangzhouChina,Zhejiang Key Laboratory for Research in Assessment of Cognitive ImpairmentsHangzhouChina
| | | | - Zhu‐Qian Zhang
- School of MedicineHangzhou Normal UniversityHangzhouChina
| | - Jue Wang
- Institute of sports medicine and healthChengdu Sport UniversityChengduChina
| | - Yu‐Feng Zang
- Center for Cognition and Brain DisordersThe Affiliated Hospital of Hangzhou Normal UniversityHangzhouChina,Institute of Psychological SciencesHangzhou Normal UniversityHangzhouChina,Zhejiang Key Laboratory for Research in Assessment of Cognitive ImpairmentsHangzhouChina
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Li H, Li L, Li K, Li P, Xie W, Zeng Y, Kong L, Long T, Huang L, Liu X, Shu Y, Zeng L, Peng D. Abnormal dynamic functional network connectivity in male obstructive sleep apnea with mild cognitive impairment: A data-driven functional magnetic resonance imaging study. Front Aging Neurosci 2022; 14:977917. [DOI: 10.3389/fnagi.2022.977917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 09/26/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveThe purpose of this study was to investigate the dynamic functional network connectivity (FNC) and its relationship with cognitive function in obstructive sleep apnea (OSA) patients from normal cognition (OSA-NC) to mild cognitive impairment (OSA-MCI).Materials and methodsEighty-two male OSA patients and 48 male healthy controls (HC) were included in this study. OSA patients were classified to OSA-MCI (n = 41) and OSA-NC (n = 41) based on cognitive assessments. The independent component analysis was used to determine resting-state functional networks. Then, a sliding-window approach was used to construct the dynamic FNC, and differences in temporal properties of dynamic FNC and functional connectivity strength were compared between OSA patients and the HC. Furthermore, the relationship between temporal properties and clinical assessments were analyzed in OSA patients.ResultsTwo different connectivity states were identified, namely, State I with stronger connectivity and lower frequency, and State II with lower connectivity and relatively higher frequency. Compared to HC, OSA patients had a longer mean dwell time and higher fractional window in stronger connectivity State I, and opposite result were found in State II, which was mainly reflected in OSA-MCI patients. The number of transitions was an increasing trend and positively correlated with cognitive assessment in OSA-MCI patients. Compared with HC, OSA patients showed extensive abnormal functional connectivity in stronger connected State I and less reduced functional connectivity in lower connected State II, which were mainly located in the salience network, default mode network, and executive control network.ConclusionOur study found that OSA patients showed abnormal dynamic FNC properties, which was a continuous trend from HC, and OSA-NC to OSA-MCI, and OSA patients showed abnormal dynamic functional connectivity strength. The number of transformations was associated with cognitive impairment in OSA-MCI patients, which may provide new insights into the neural mechanisms in OSA patients.
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Electroconvulsive therapy changes temporal dynamics of intrinsic brain activity in depressed patients. Psychiatry Res 2022; 316:114732. [PMID: 35926361 DOI: 10.1016/j.psychres.2022.114732] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Revised: 07/14/2022] [Accepted: 07/16/2022] [Indexed: 11/24/2022]
Abstract
Electroconvulsive therapy (ECT) has been demonstrated to be effective in treating depressed patients. Previous neuroimaging studies have focused mainly on alterations in static brain activity and connectivity to study the effects of ECT in depressed patients. However, it remains unclear whether the temporal dynamics of brain activity are associated with mechanisms of ECT in depressed patients. We measured the dynamics of spontaneous brain activity using dynamic amplitude of low-frequency fluctuation (dALFF) in healthy controls (n = 40) and patients diagnosed with unipolar depression (UD, n = 36) or bipolar disorder (BD, n = 9) before and after ECT. Furthermore, the temporal variability of intrinsic brain activity (iBA) was quantified as the variance of dALFF across sliding window. In addition, correlation analysis was performed to investigate the relationships among dALFF, depressive symptoms, and cognitive function in depressed patients. We lack second resting-state functional magnetic resonance imaging (rs-fMRI) data for healthy controls. After ECT, patients showed decreased brain dynamics (less temporal variability) in the right dorsal anterior cingulate cortex (dACC) and the right precuneus, whereas they showed increased brain dynamics in the bilateral superior medial frontal cortex (mSFC). No significant correlation was found between the dALFF and clinical variables in depressed patients. Our findings suggest that right dACC, right precuneus, and bilateral mSFC play an important role in response to ECT depressed patients from the perspective of dynamic local brain activity, indicating that the dALFF variability may be useful in further understanding the mechanisms of ECT's antidepressant effects.
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