1
|
Marchitelli R, Paillère Martinot ML, Trouvé A, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Garavan H, Gowland P, Heinz A, Brühl R, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Hohmann S, Holz N, Vaidya N, Fröhner JH, Smolka MN, Walter H, Whelan R, Schumann G, Martinot JL, Artiges E. Coupled changes between ruminating thoughts and resting-state brain networks during the transition into adulthood. Mol Psychiatry 2024:10.1038/s41380-024-02610-9. [PMID: 38956372 DOI: 10.1038/s41380-024-02610-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 05/03/2024] [Accepted: 05/13/2024] [Indexed: 07/04/2024]
Abstract
Perseverative negative thoughts, known as rumination, might arise from emotional challenges and preclude mental health when transitioning into adulthood. Due to its multifaceted nature, rumination can take several ruminative response styles, that diverge in manifestations, severity, and mental health outcomes. Still, prospective ruminative phenotypes remain elusive insofar. Longitudinal study designs are ideal for stratifying ruminative response styles, especially with resting-state functional MRI whose setup naturally elicits people's ruminative traits. Here, we considered self-rated questionnaires on rumination and psychopathology, along with resting-state functional MRI data in 595 individuals assessed at age 18 and 22 from the IMAGEN cohort. We conducted independent component analysis to characterize eight single static resting-state functional networks in each subject and session and furthermore conducted a dynamic analysis, tackling the time variations of functional networks during the entire scanning time. We then investigated their longitudinal mediation role between changes in three ruminative response styles (reflective pondering, brooding, and depressive rumination) and changes in internalizing and co-morbid externalizing symptoms. Four static and two dynamic networks longitudinally differentiated these ruminative styles and showed complemental sensitivity to internalizing and co-morbid externalizing symptoms. Among these networks, the right frontoparietal network covaried with all ruminative styles but did not play any mediation role towards psychopathology. The default mode, the salience, and the limbic networks prospectively stratified these ruminative styles, suggesting that maladaptive ruminative styles are associated with altered corticolimbic function. For static measures, only the salience network played a longitudinal causal role between brooding rumination and internalizing symptoms. Dynamic measures highlighted the default-mode mediation role between the other ruminative styles and co-morbid externalizing symptoms. In conclusion, we identified the ruminative styles' psychometric and neural outcome specificities, supporting their translation into applied research on young adult mental healthcare.
Collapse
Affiliation(s)
- Rocco Marchitelli
- Ecole Normale Supérieure Paris-Saclay, University Paris-Saclay, University Paris-City, INSERM U1299 "Developmental Trajectories & Psychiatry, Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Ecole Normale Supérieure Paris-Saclay, University Paris-Saclay, University Paris-City, INSERM U1299 "Developmental Trajectories & Psychiatry, Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
- AP-HP Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Alain Trouvé
- Ecole Normale Supérieure Paris-Saclay, University Paris-Saclay, University Paris-City, INSERM U1299 "Developmental Trajectories & Psychiatry, Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, and German Center for Mental Health (DZPG) partner site Mannheim-Heidelberg-Ulm, Heidelberg University, Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, 68131, Mannheim, Germany
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, 05405, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Berlin, Germany
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, and German Center for Mental Health (DZPG) partner site Mannheim-Heidelberg-Ulm, Heidelberg University, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Tomáš Paus
- Department of Psychiatry and Neuroscience, Faculty of Medicine, CHU Sainte-Justine Research Center, Population Neuroscience Laboratory, University of Montreal, Montreal, QC, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry, Center for Psychosocial Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, and German Center for Mental Health (DZPG) partner site Mannheim-Heidelberg-Ulm, Heidelberg University, Mannheim, Germany
| | - Nathalie Holz
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, and German Center for Mental Health (DZPG) partner site Mannheim-Heidelberg-Ulm, Heidelberg University, Mannheim, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Psychotherapy, Medical Faculty, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Psychotherapy, Medical Faculty, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), ISTBI Fudan University, Shanghai, China
- Department of Psychiatry and Neuroscience, Charité University Medicine, Berlin, Germany
| | - Jean-Luc Martinot
- Ecole Normale Supérieure Paris-Saclay, University Paris-Saclay, University Paris-City, INSERM U1299 "Developmental Trajectories & Psychiatry, Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France.
- Department of Psychiatry, Lab-D-PSY, EPS Barthélémy Durand, Etampes, France.
| | - Eric Artiges
- Ecole Normale Supérieure Paris-Saclay, University Paris-Saclay, University Paris-City, INSERM U1299 "Developmental Trajectories & Psychiatry, Centre Borelli CNRS UMR9010, Gif-sur-Yvette, France
- Department of Psychiatry, Lab-D-PSY, EPS Barthélémy Durand, Etampes, France
| |
Collapse
|
2
|
Kuang LD, Li HQ, Zhang J, Gui Y, Zhang J. Dynamic functional network connectivity analysis in schizophrenia based on a spatiotemporal CPD framework. J Neural Eng 2024; 21:016032. [PMID: 38335544 DOI: 10.1088/1741-2552/ad27ee] [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: 09/12/2023] [Accepted: 02/09/2024] [Indexed: 02/12/2024]
Abstract
Objective.Dynamic functional network connectivity (dFNC), based on data-driven group independent component (IC) analysis, is an important avenue for investigating underlying patterns of certain brain diseases such as schizophrenia. Canonical polyadic decomposition (CPD) of a higher-way dynamic functional connectivity tensor, can offer an innovative spatiotemporal framework to accurately characterize potential dynamic spatial and temporal fluctuations. Since multi-subject dFNC data from sliding-window analysis are also naturally a higher-order tensor, we propose an innovative sparse and low-rank CPD (SLRCPD) for the three-way dFNC tensor to excavate significant dynamic spatiotemporal aberrant changes in schizophrenia.Approach.The proposed SLRCPD approach imposes two constraints. First, the L1regularization on spatial modules is applied to extract sparse but significant dynamic connectivity and avoid overfitting the model. Second, low-rank constraint is added on time-varying weights to enhance the temporal state clustering quality. Shared dynamic spatial modules, group-specific dynamic spatial modules and time-varying weights can be extracted by SLRCPD. The strength of connections within- and between-IC networks and connection contribution are proposed to inspect the spatial modules. K-means clustering and classification are further conducted to explore temporal group difference.Main results.82 subject resting-state functional magnetic resonance imaging (fMRI) dataset and opening Center for Biomedical Research Excellence (COBRE) schizophrenia dataset both containing schizophrenia patients (SZs) and healthy controls (HCs) were utilized in our work. Three typical dFNC patterns between different brain functional regions were obtained. Compared to the spatial modules of HCs, the aberrant connections among auditory network, somatomotor, visual, cognitive control and cerebellar networks in 82 subject dataset and COBRE dataset were detected. Four temporal states reveal significant differences between SZs and HCs for these two datasets. Additionally, the accuracy values for SZs and HCs classification based on time-varying weights are larger than 0.96.Significance.This study significantly excavates spatio-temporal patterns for schizophrenia disease.
Collapse
Affiliation(s)
- Li-Dan Kuang
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - He-Qiang Li
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - Jianming Zhang
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - Yan Gui
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| | - Jin Zhang
- School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha, People's Republic of China
| |
Collapse
|
3
|
Wang Y, Yang Z, Zheng X, Liang X, Chen J, He T, Zhu Y, Wu L, Huang M, Zhang N, Zhou F. Temporal and topological properties of dynamic networks reflect disability in patients with neuromyelitis optica spectrum disorders. Sci Rep 2024; 14:4199. [PMID: 38378887 PMCID: PMC10879085 DOI: 10.1038/s41598-024-54518-7] [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: 08/20/2023] [Accepted: 02/13/2024] [Indexed: 02/22/2024] Open
Abstract
Approximately 36% of patients with neuromyelitis optica spectrum disorders (NMOSD) suffer from severe visual and motor disability (blindness or light perception or unable to walk) with abnormalities of whole-brain functional networks. However, it remains unclear how whole-brain functional networks and their dynamic properties are related to clinical disability in patients with NMOSD. Our study recruited 30 NMOSD patients (37.70 ± 11.99 years) and 45 healthy controls (HC, 41.84 ± 11.23 years). The independent component analysis, sliding-window approach and graph theory analysis were used to explore the static strength, time-varying and topological properties of large-scale functional networks and their associations with disability in NMOSD. Compared to HC, NMOSD patients showed significant alterations in dynamic networks rather than static networks. Specifically, NMOSD patients showed increased occurrence (fractional occupancy; P < 0.001) and more dwell times of the low-connectivity state (P < 0.001) with fewer transitions (P = 0.028) between states than HC, and higher fractional occupancy, increased dwell times of the low-connectivity state and lower transitions were related to more severe disability. Moreover, NMOSD patients exhibited altered small-worldness, decreased degree centrality and reduced clustering coefficients of hub nodes in dynamic networks, related to clinical disability. NMOSD patients exhibited higher occurrence and more dwell time in low-connectivity states, along with fewer transitions between states and decreased topological organizations, revealing the disrupted communication and coordination among brain networks over time. Our findings could provide new perspective to help us better understand the neuropathological mechanism of the clinical disability in NMOSD.
Collapse
Affiliation(s)
- Yao Wang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Ziwei Yang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Xiumei Zheng
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Xiao Liang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Jin Chen
- Department of Neurology, The First Affiliated Hospital of Nanchang University, Nanchang, 330006, Jiangxi Province, China
| | - Ting He
- Department of Radiology, Pingxiang People's Hospital, Pingxiang, 337055, Jiangxi Province, China
| | - Yanyan Zhu
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Lin Wu
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Muhua Huang
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China
| | - Ningnannan Zhang
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin, 300052, China.
| | - Fuqing Zhou
- Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
- Clinical Research Center for Medical Imaging in Jiangxi Province, Nanchang, 330006, Jiangxi Province, China.
| |
Collapse
|
4
|
Xu Z, Chang Y, Guo F, Wang C, Chai N, Zheng M, Fang P, Zhu Y. The restoration ability of a short nap after sleep deprivation on the brain cognitive function: A dynamic functional connectivity analysis. CNS Neurosci Ther 2024; 30:e14413. [PMID: 37605612 PMCID: PMC10848048 DOI: 10.1111/cns.14413] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 04/07/2023] [Accepted: 08/05/2023] [Indexed: 08/23/2023] Open
Abstract
AIMS The brain function impairment induced by sleep deprivation (SD) is temporary and can be fully reversed with sufficient sleep. However, in many cases, long-duration recovery sleep is not feasible. Thus, this study aimed to investigate whether a short nap after SD is sufficient to restore brain function. METHODS The data of 38 subjects, including resting state functional magnetic resonance imaging data collected at three timepoints (before SD, after 30 h of SD, and after a short nap following SD) and psychomotor vigilance task (PVT) data, were collected. Dynamic functional connectivity (DFC) analysis was used to evaluate changes in brain states among three timepoints, and four DFC states were distinguished across the three timepoints. RESULTS Before SD, state 2 (a resting-like FC matrix) was dominant (48.26%). However, after 30 h SD, the proportion of state 2 dramatically decreased, and state 3 (still resting-like, but FCs were weakened) became dominant (40.92%). The increased proportion of state 3 positively correlated with a larger PVT "lapse" time. After a nap, the proportions of states 2 and 3 significantly increased and decreased, respectively, and the change in proportion of state 2 negatively correlated with the change in PVT "lapse" time. CONCLUSIONS Taken together, the results indicated that, after a nap, the cognitive function impairment caused by SD may be reversed to some extent. Additionally, DFC differed among timepoints, which was also associated with the extent of cognitive function impairment after SD (state 3) and the extent of recovery therefrom after a nap (state 2).
Collapse
Affiliation(s)
- Ziliang Xu
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Yingjuan Chang
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Fan Guo
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Chen Wang
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Na Chai
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Minwen Zheng
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| | - Peng Fang
- Department of Military Medical PsychologyFourth Military Medical UniversityXi'anChina
| | - Yuanqiang Zhu
- Department of Radiology, Xijing HospitalFourth Military Medical UniversityXi'anChina
| |
Collapse
|
5
|
Miao J, Tantawi M, Alizadeh M, Thalheimer S, Vedaei F, Romo V, Mohamed FB, Wu C. Characteristic dynamic functional connectivity during sevoflurane-induced general anesthesia. Sci Rep 2023; 13:21014. [PMID: 38030651 PMCID: PMC10687074 DOI: 10.1038/s41598-023-43832-1] [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: 03/03/2023] [Accepted: 09/28/2023] [Indexed: 12/01/2023] Open
Abstract
General anesthesia (GA) during surgery is commonly maintained by inhalational sevoflurane. Previous resting state functional MRI (rs-fMRI) studies have demonstrated suppressed functional connectivity (FC) of the entire brain networks, especially the default mode networks, transitioning from the awake to GA condition. However, accuracy and reliability were limited by previous administration methods (e.g. face mask) and short rs-fMRI scans. Therefore, in this study, a clinical scenario of epilepsy patients undergoing laser interstitial thermal therapy was leveraged to acquire 15 min of rs-fMRI while under general endotracheal anesthesia to maximize the accuracy of sevoflurane level. Nine recruited patients had fMRI acquired during awake and under GA, of which seven were included in both static and dynamic FC analyses. Group independent component analysis and a sliding-window method followed by k-means clustering were applied to identify four dynamic brain states, which characterized subtypes of FC patterns. Our results showed that a low-FC brain state was characteristic of the GA condition as a single featuring state during the entire rs-fMRI session; In contrast, the awake condition exhibited frequent fluctuations between three distinct brain states, one of which was a highly synchronized brain state not seen in GA. In conclusion, our study revealed remarkable dynamic connectivity changes from awake to GA condition and demonstrated the advantages of dynamic FC analysis for future studies in the assessments of the effects of GA on brain functional activities.
Collapse
Affiliation(s)
- Jingya Miao
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA.
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA.
| | - Mohamed Tantawi
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Mahdi Alizadeh
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Sara Thalheimer
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
| | - Faezeh Vedaei
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Victor Romo
- Department of Anesthesia, Thomas Jefferson University, Philadelphia, PA, USA
| | - Feroze B Mohamed
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| | - Chengyuan Wu
- Department of Neurosurgery and Radiology, Thomas Jefferson University, Philadelphia, PA, USA
- Integrated Magnetic Resonance Imaging Center, Thomas Jefferson University, Philadelphia, PA, USA
| |
Collapse
|
6
|
Byun JI, Jahng GH, Ryu CW, Park S, Lee KH, Hong SO, Jung KY, Shin WC. Altered intrinsic brain functional network dynamics in moderate-to-severe obstructive sleep apnea. Sleep Med 2023; 101:550-557. [PMID: 36577226 DOI: 10.1016/j.sleep.2022.12.003] [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: 04/07/2022] [Revised: 12/04/2022] [Accepted: 12/05/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVES Obstructive sleep apnea (OSA) can affect temporal fluctuations in brain activity during rest. Dynamic functional connectivity (dFC) captures the fluctuations in FC during the resting state. This study aimed to investigate differences in dFC between moderate-to-severe OSA patients and healthy controls using resting-state functional magnetic resonance imaging (fMRI) and sliding-window analysis. METHODS Thirty-seven consecutive patients with moderate-to-severe OSA and 16 age- and sex-matched controls underwent resting-state fMRI in the morning following overnight polysomnography. The dynamics of aberrant FC between the groups and the correlation between the dynamics and clinical variables were evaluated. RESULTS dFC analysis revealed two distinct connectivity states: hypoconnected (State I) and hyperconnected (State II). In OSA patients, State I occurred 34% more often than in the controls and the occurrence of State II was proportionally reduced. The time in State I positively correlated with the Pittsburg Sleep Quality Index score in the OSA patients. CONCLUSIONS This study showed dFC alterations in moderate-to-severe OSA patients, which may serve as a novel physiological biomarker for OSA.
Collapse
Affiliation(s)
- Jung-Ick Byun
- Department of Neurology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Republic of Korea.
| | - Geon-Ho Jahng
- Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Republic of Korea
| | - Chang-Woo Ryu
- Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Republic of Korea
| | - Soonchan Park
- Department of Radiology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Republic of Korea
| | - Kun Hee Lee
- Department of Otorhinolaryngology-Head and Neck Surgery, Kyung Hee University College of Medicine, Seoul, Republic of Korea
| | - Sung Ok Hong
- Department of Oral and Maxillofacial Surgery, Kyung Hee University College of Dentistry, Kyung Hee University Hospital at Gangdong, Seoul, Republic of Korea
| | - Ki-Young Jung
- Department of Neurology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Won Chul Shin
- Department of Neurology, Kyung Hee University Hospital at Gangdong, Kyung Hee University College of Medicine, Seoul, Republic of Korea; Department of Medicine, AgeTech-service Convergence Major, Kyung Hee University, Seoul, Republic of Korea.
| |
Collapse
|
7
|
van den Berg M, Adhikari MH, Verschuuren M, Pintelon I, Vasilkovska T, Van Audekerke J, Missault S, Heymans L, Ponsaerts P, De Vos WH, Van der Linden A, Keliris GA, Verhoye M. Altered basal forebrain function during whole-brain network activity at pre- and early-plaque stages of Alzheimer's disease in TgF344-AD rats. Alzheimers Res Ther 2022; 14:148. [PMID: 36217211 PMCID: PMC9549630 DOI: 10.1186/s13195-022-01089-2] [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: 06/24/2022] [Accepted: 09/22/2022] [Indexed: 11/10/2022]
Abstract
BACKGROUND Imbalanced synaptic transmission appears to be an early driver in Alzheimer's disease (AD) leading to brain network alterations. Early detection of altered synaptic transmission and insight into mechanisms causing early synaptic alterations would be valuable treatment strategies. This study aimed to investigate how whole-brain networks are influenced at pre- and early-plague stages of AD and if these manifestations are associated with concomitant cellular and synaptic deficits. METHODS: To this end, we used an established AD rat model (TgF344-AD) and employed resting state functional MRI and quasi-periodic pattern (QPP) analysis, a method to detect recurrent spatiotemporal motifs of brain activity, in parallel with state-of-the-art immunohistochemistry in selected brain regions. RESULTS At the pre-plaque stage, QPPs in TgF344-AD rats showed decreased activity of the basal forebrain (BFB) and the default mode-like network. Histological analyses revealed increased astrocyte abundance restricted to the BFB, in the absence of amyloid plaques, tauopathy, and alterations in a number of cholinergic, gaba-ergic, and glutamatergic synapses. During the early-plaque stage, when mild amyloid-beta (Aβ) accumulation was observed in the cortex and hippocampus, QPPs in the TgF344-AD rats normalized suggesting the activation of compensatory mechanisms during this early disease progression period. Interestingly, astrogliosis observed in the BFB at the pre-plaque stage was absent at the early-plaque stage. Moreover, altered excitatory/inhibitory balance was observed in cortical regions belonging to the default mode-like network. In wild-type rats, at both time points, peak activity in the BFB preceded peak activity in other brain regions-indicating its modulatory role during QPPs. However, this pattern was eliminated in TgF344-AD suggesting that alterations in BFB-directed neuromodulation have a pronounced impact in network function in AD. CONCLUSIONS This study demonstrates the value of rsfMRI and advanced network analysis methods to detect early alterations in BFB function in AD, which could aid early diagnosis and intervention in AD. Restoring the global synaptic transmission, possibly by modulating astrogliosis in the BFB, might be a promising therapeutic strategy to restore brain network function and delay the onset of symptoms in AD.
Collapse
Affiliation(s)
- Monica van den Berg
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mohit H. Adhikari
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Marlies Verschuuren
- grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Laboratory of Cell Biology and Histology, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,Antwerp Centre for Advanced Microscopy, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | - Isabel Pintelon
- grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Laboratory of Cell Biology and Histology, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,Antwerp Centre for Advanced Microscopy, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | - Tamara Vasilkovska
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Johan Van Audekerke
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Stephan Missault
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Loran Heymans
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Peter Ponsaerts
- grid.5284.b0000 0001 0790 3681Laboratory of Experimental Hematology, Vaccine and Infectious Disease Institute (Vaxinfectio), University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | - Winnok H. De Vos
- grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Laboratory of Cell Biology and Histology, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,Antwerp Centre for Advanced Microscopy, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | - Annemie Van der Linden
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Georgios A. Keliris
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium ,grid.511960.aInstitute of Computer Science, Foundation for Research & Technology - Hellas, Heraklion, Crete, Greece
| | - Marleen Verhoye
- grid.5284.b0000 0001 0790 3681Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1 2610 Wilrijk, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681µNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| |
Collapse
|
8
|
Rao B, Wang S, Yu M, Chen L, Miao G, Zhou X, Zhou H, Liao W, Xu H. Suboptimal states and frontoparietal network-centered incomplete compensation revealed by dynamic functional network connectivity in patients with post-stroke cognitive impairment. Front Aging Neurosci 2022; 14:893297. [PMID: 36003999 PMCID: PMC9393744 DOI: 10.3389/fnagi.2022.893297] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundNeural reorganization occurs after a stroke, and dynamic functional network connectivity (dFNC) pattern is associated with cognition. We hypothesized that dFNC alterations resulted from neural reorganization in post-stroke cognitive impairment (PSCI) patients, and specific dFNC patterns characterized different pathological types of PSCI.MethodsResting-state fMRI data were collected from 16 PSCI patients with hemorrhagic stroke (hPSCI group), 21 PSCI patients with ischemic stroke (iPSCI group), and 21 healthy controls (HC). We performed the dFNC analysis for the dynamic connectivity states, together with their topological and temporal features.ResultsWe identified 10 resting-state networks (RSNs), and the dFNCs could be clustered into four reoccurring states (modular, regional, sparse, and strong). Compared with HC, the hPSCI and iPSCI patients showed lower standard deviation (SD) and coefficient of variation (CV) in the regional and modular states, respectively (p < 0.05). Reduced connectivities within the primary network (visual, auditory, and sensorimotor networks) and between the primary and high-order cognitive control domains were observed (p < 0.01).ConclusionThe transition trend to suboptimal states may play a compensatory role in patients with PSCI through redundancy networks. The reduced exploratory capacity (SD and CV) in different suboptimal states characterized cognitive impairment and pathological types of PSCI. The functional disconnection between the primary and high-order cognitive control network and the frontoparietal network centered (FPN-centered) incomplete compensation may be the pathological mechanism of PSCI. These results emphasize the flexibility of neural reorganization during self-repair.
Collapse
Affiliation(s)
- Bo Rao
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Sirui Wang
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Minhua Yu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Linglong Chen
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Guofu Miao
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Xiaoli Zhou
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Hong Zhou
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Weijing Liao
- Department of Rehabilitation Medicine, Zhongnan Hospital of Wuhan University, Wuhan, China
- *Correspondence: Weijing Liao,
| | - Haibo Xu
- Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan, China
- Haibo Xu,
| |
Collapse
|
9
|
Li Z, Zhao L, Ji J, Ma B, Zhao Z, Wu M, Zheng W, Zhang Z. Temporal Grading Index of Functional Network Topology Predicts Pain Perception of Patients With Chronic Back Pain. Front Neurol 2022; 13:899254. [PMID: 35756935 PMCID: PMC9226296 DOI: 10.3389/fneur.2022.899254] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022] Open
Abstract
Chronic back pain (CBP) is a maladaptive health problem affecting the brain function and behavior of the patient. Accumulating evidence has shown that CBP may alter the organization of functional brain networks; however, whether the severity of CBP is associated with changes in dynamics of functional network topology remains unclear. Here, we generated dynamic functional networks based on resting-state functional magnetic resonance imaging (rs-fMRI) of 34 patients with CBP and 34 age-matched healthy controls (HC) in the OpenPain database via a sliding window approach, and extracted nodal degree, clustering coefficient (CC), and participation coefficient (PC) of all windows as features to characterize changes of network topology at temporal scale. A novel feature, named temporal grading index (TGI), was proposed to quantify the temporal deviation of each network property of a patient with CBP to the normal oscillation of the HCs. The TGI of the three features achieved outstanding performance in predicting pain intensity on three commonly used regression models (i.e., SVR, Lasso, and elastic net) through a 5-fold cross-validation strategy, with the minimum mean square error of 0.25 ± 0.05; and the TGI was not related to depression symptoms of the patients. Furthermore, compared to the HCs, brain regions that contributed most to prediction showed significantly higher CC and lower PC across time windows in the CBP cohort. These results highlighted spatiotemporal changes in functional network topology in patients with CBP, which might serve as a valuable biomarker for assessing the sensation of pain in the brain and may facilitate the development of CBP management/therapy approaches.
Collapse
Affiliation(s)
- Zhonghua Li
- Department of Rehabilitation Medicine, Gansu Provincial Hospital of TCM, Lanzhou, China
| | - Leilei Zhao
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Jing Ji
- Department of Rehabilitation Medicine, Gansu Provincial Hospital of TCM, Lanzhou, China
| | - Ben Ma
- Department of Rehabilitation Medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Zhiyong Zhao
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Miao Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China
| | - Weihao Zheng
- Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China
| | - Zhe Zhang
- Institute of Brain Science, Hangzhou Normal University, Hangzhou, China.,School of Physics, Hangzhou Normal University, Hangzhou, China
| |
Collapse
|
10
|
Chen Z, Zhang R, Huo H, Liu P, Zhang C, Feng T. Functional connectome of human cerebellum. Neuroimage 2022; 251:119015. [DOI: 10.1016/j.neuroimage.2022.119015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2021] [Revised: 01/26/2022] [Accepted: 02/17/2022] [Indexed: 10/19/2022] Open
|
11
|
Chen J, Fan Y, Wei W, Wang L, Wang X, Fan F, Jia Z, Li M, Wang J, Zou Q, Chen B, Lv Y. Repetitive transcranial magnetic stimulation modulates cortical-subcortical connectivity in sensorimotor network. Eur J Neurosci 2021; 55:227-243. [PMID: 34905661 DOI: 10.1111/ejn.15571] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 11/30/2022]
Abstract
Repetitive transcranial magnetic stimulation (rTMS) holds the ability to modulate the connectivity within the stimulated network. However, whether and how the rTMS targeted over the primary motor cortex (M1) could affect the connectivity within the sensorimotor network (SMN) is not fully elucidated. Hence, in this study, we investigated the after-effects of rTMS over left M1 at different frequencies on connectivity within SMN. Forty-five healthy participants were recruited and randomly divided into three groups according to rTMS frequencies (high-frequency [HF], 3 Hz; low-frequency [LF], 1 Hz; and SHAM). Participants received 1-Hz, 3-Hz or sham stimulation and underwent two functional magnetic resonance imaging (fMRI) scanning sessions before and after rTMS intervention. Using resting-state functional connectivity (FC) approach, we found that high- and low-frequency rTMS had opposing effects on FC within the SMN, especially for connectivity with subcortical regions (i.e., putamen, thalamus and cerebellum). Specifically, the reductions in connectivity between cortical and subcortical regions within cortico-basal ganglia thalamo-cortical circuits and the cognitive loop of cerebellum, and increased connectivity between cortical and subdivisions within the sensorimotor loop of cerebellum were observed after high-frequency rTMS intervention, whereas the thalamus and cognitive cerebellum subdivisions exhibited increased connectivity, and sensorimotor cerebellum subdivisions showed decreased connectivity with stimulated target after low-frequency stimulation. Collectively, these findings demonstrated the alterations of connectivity within SMN after rTMS intervention at different frequencies and may help to understand the mechanisms of rTMS treatment for movement disorders associated with deficits in subcortical regions such as Parkinson's disease, Huntington's disease and Tourette's syndrome.
Collapse
Affiliation(s)
- Jing Chen
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Yanzi Fan
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Wei Wei
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Luoyu Wang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| | - Xiaoyu Wang
- Department of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Fengmei Fan
- Beijing Huilongguan Hospital, Peking University Huilongguan Clinical Medical School, Beijing, China
| | - Zejuan Jia
- Shijiazhuang Hospital of Traditional Chinese Medicine, Shijiazhuang, China
| | - Mengting Li
- School of Teacher Education, Zhejiang Normal University, Jinhua, China
| | - Jinhui Wang
- Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, China
| | - Qihong Zou
- Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Bing Chen
- School of Education, Hangzhou Normal University, Hangzhou, China
| | - Yating Lv
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.,Institute of Psychological Science, Hangzhou Normal University, Hangzhou, China.,Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, China
| |
Collapse
|