1
|
Sun H, Cui H, Sun Q, Li Y, Bai T, Wang K, Zhang J, Tian Y, Wang J. Individual large-scale functional network mapping for major depressive disorder with electroconvulsive therapy. J Affect Disord 2024; 360:116-125. [PMID: 38821362 DOI: 10.1016/j.jad.2024.05.141] [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: 02/17/2024] [Revised: 05/08/2024] [Accepted: 05/27/2024] [Indexed: 06/02/2024]
Abstract
Personalized functional connectivity mapping has been demonstrated to be promising in identifying underlying neurophysiological basis for brain disorders and treatment effects. Electroconvulsive therapy (ECT) has been proved to be an effective treatment for major depressive disorder (MDD) while its active mechanisms remain unclear. Here, 46 MDD patients before and after ECT as well as 46 demographically matched healthy controls (HC) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. A spatially regularized form of non-negative matrix factorization (NMF) was used to accurately identify functional networks (FNs) in individuals to map individual-level static and dynamic functional network connectivity (FNC) to reveal the underlying neurophysiological basis of therepetical effects of ECT for MDD. Moreover, these static and dynamic FNCs were used as features to predict the clinical treatment outcomes for MDD patients. We found that ECT could modulate both static and dynamic large-scale FNCs at individual level in MDD patients, and dynamic FNCs were closely associated with depression and anxiety symptoms. Importantly, we found that individual FNCs, particularly the individual dynamic FNCs could better predict the treatment outcomes of ECT suggesting that dynamic functional connectivity analysis may be better to link brain functional characteristics with clinical symptoms and treatment outcomes. Taken together, our findings provide new evidence for the active mechanisms and biomarkers for ECT to improve diagnostic accuracy and to guide individual treatment selection for MDD patients.
Collapse
Affiliation(s)
- Hui Sun
- College of Electrical Engineering, Sichuan University, Chengdu 610065, China
| | - Hongjie Cui
- College of Electrical Engineering, Sichuan University, Chengdu 610065, China
| | - Qinyao Sun
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 625014, China
| | - Yuanyuan Li
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China
| | - Tongjian Bai
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China
| | - Kai Wang
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230022, China
| | - Jiang Zhang
- College of Electrical Engineering, Sichuan University, Chengdu 610065, China.
| | - Yanghua Tian
- Department of Neurology, the First Hospital of Anhui Medical University, Hefei 230022, China; School of Mental Health and Psychological Sciences, Anhui Medical University, Hefei 230022, China.
| | - Jiaojian Wang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming 650500, China.
| |
Collapse
|
2
|
Voits T, DeLuca V, Hao J, Elin K, Abutalebi J, Duñabeitia JA, Berglund G, Gabrielsen A, Rook J, Thomsen H, Waagen P, Rothman J. Degree of multilingual engagement modulates resting state oscillatory activity across the lifespan. Neurobiol Aging 2024; 140:70-80. [PMID: 38735176 DOI: 10.1016/j.neurobiolaging.2024.04.009] [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: 01/05/2024] [Revised: 03/18/2024] [Accepted: 04/19/2024] [Indexed: 05/14/2024]
Abstract
Multilingualism has been demonstrated to lead to a more favorable trajectory of neurocognitive aging, yet our understanding of its effect on neurocognition across the lifespan remains limited. We collected resting state EEG recordings from a sample of multilingual individuals across a wide age range. Additionally, we obtained data on participant multilingual language use patterns alongside other known lifestyle enrichment factors. Language experience was operationalized via a modified multilingual diversity (MLD) score. Generalized additive modeling was employed to examine the effects and interactions of age and MLD on resting state oscillatory power and coherence. The data suggest an independent modulatory effect of individualized multilingual engagement on age-related differences in whole brain resting state power across alpha and theta bands, and an interaction between age and MLD on resting state coherence in alpha, theta, and low beta. These results provide evidence of multilingual engagement as an independent correlational factor related to differences in resting state EEG power, consistent with the claim that multilingualism can serve as a protective factor in neurocognitive aging.
Collapse
Affiliation(s)
- Toms Voits
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden; UiT the Arctic University of Norway, Tromsø, Norway.
| | | | - Jiuzhou Hao
- UiT the Arctic University of Norway, Tromsø, Norway
| | - Kirill Elin
- UiT the Arctic University of Norway, Tromsø, Norway
| | - Jubin Abutalebi
- UiT the Arctic University of Norway, Tromsø, Norway; Centre for Neurolinguistics and Psycholinguistics (CNPL), Vita-Salute San Raffaele University, Milan, Italy
| | - Jon Andoni Duñabeitia
- UiT the Arctic University of Norway, Tromsø, Norway; Universidad Nebrija Research Center in Cognition (CINC), Nebrija University, Madrid, Spain
| | | | | | - Janine Rook
- Department of Applied Linguistics, University of Groningen, Groningen, the Netherlands
| | - Hilde Thomsen
- UiT the Arctic University of Norway, Tromsø, Norway; Université Côte d'Azur, Nice, France
| | | | - Jason Rothman
- UiT the Arctic University of Norway, Tromsø, Norway; Universidad Nebrija Research Center in Cognition (CINC), Nebrija University, Madrid, Spain
| |
Collapse
|
3
|
Karunakaran KD, Pascale M, Ozana N, Potter K, Pachas GN, Evins AE, Gilman JM. Intoxication due to Δ9-tetrahydrocannabinol is characterized by disrupted prefrontal cortex activity. Neuropsychopharmacology 2024; 49:1481-1490. [PMID: 38714786 PMCID: PMC11251178 DOI: 10.1038/s41386-024-01876-5] [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: 01/30/2024] [Revised: 04/08/2024] [Accepted: 04/23/2024] [Indexed: 05/10/2024]
Abstract
Neural states of impairment from intoxicating substances, including cannabis, are poorly understood. Cannabinoid 1 receptors, the main target of Δ9-tetrahydrocannabinol (THC), the primary intoxicating cannabinoid in cannabis, are densely localized within prefrontal cortex; therefore, prefrontal brain regions are key locations to examine brain changes that characterize acute intoxication. We conducted a double-blind, randomized, cross-over study in adults, aged 18-55 years, who use cannabis regularly, to determine the effects of acute intoxication on prefrontal cortex resting-state measures, assessed with portable functional near-infrared spectroscopy. Participants received oral THC (10-80 mg, individually dosed to overcome tolerance and achieve acute intoxication) and identical placebo, randomized for order; 185 adults were randomized and 128 completed both study days and had usable data. THC was associated with expected increases in subjective intoxication ratings (ES = 35.30, p < 0.001) and heart rate (ES = 11.15, p = 0.001). THC was associated with decreased correlations and anticorrelations in static resting-state functional connectivity within the prefrontal cortex relative to placebo, with weakest correlations and anticorrelations among those who reported greater severity of intoxication (RSFC between medial PFC-ventromedial PFC and DEQ scores, r = 0.32, p < 0.001; RSFC between bilateral mPFC and DEQ scores, r = -0.28, p = 0.001). Relative to placebo, THC was associated with increased variability (or reduced stability) in dynamic resting-state functional connectivity of the prefrontal cortex at p = 0.001, consistent across a range of window sizes. Finally, using frequency power spectrum analyses, we observed that relative to placebo, THC was associated with widespread reduced spectral power within the prefrontal cortex across the 0.073-0.1 Hz frequency range at p < 0.039. These neural features suggest a disruptive influence of THC on the neural dynamics of the prefrontal cortex and may underlie cognitive impairing effects of THC that are detectable with portable imaging. This study is registered in Clinicaltrials.gov (NCT03655717).
Collapse
Affiliation(s)
- Keerthana Deepti Karunakaran
- Massachusetts General Hospital (MGH) Department of Psychiatry, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Michael Pascale
- Massachusetts General Hospital (MGH) Department of Psychiatry, Boston, MA, USA
| | - Nisan Ozana
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
- Faculty of Engineering and The Gonda Multidisciplinary Brain Research Center, Bar Ilan University, Ramat-Gan, 52900, Israel
| | - Kevin Potter
- Massachusetts General Hospital (MGH) Department of Psychiatry, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Gladys N Pachas
- Massachusetts General Hospital (MGH) Department of Psychiatry, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - A Eden Evins
- Massachusetts General Hospital (MGH) Department of Psychiatry, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Jodi M Gilman
- Massachusetts General Hospital (MGH) Department of Psychiatry, Boston, MA, USA.
- Harvard Medical School, Boston, MA, USA.
- MGH/HST Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA.
| |
Collapse
|
4
|
Yan H, Shan X, Li H, Liu F, Xie G, Li P, Guo W. Cerebellar functional connectivity and its associated genes: A longitudinal study in drug-naive patients with obsessive-compulsive disorder. J Psychiatr Res 2024; 177:378-391. [PMID: 39083996 DOI: 10.1016/j.jpsychires.2024.07.040] [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: 04/12/2024] [Revised: 07/19/2024] [Accepted: 07/27/2024] [Indexed: 08/02/2024]
Abstract
The role of cerebellar-cerebral functional connectivity (CC-FC) in obsessive-compulsive disorder (OCD), its trajectory post-pharmacotherapy, and its potential as a prognostic biomarker and genetic mechanism remain uncertain. To address these gaps, this study included 37 drug-naive OCD patients and 37 healthy controls (HCs). Participants underwent baseline functional magnetic resonance imaging (fMRI), followed by four weeks of paroxetine treatment for patients with OCD, and another fMRI scan post-treatment. We examined seed-based CC-FC differences between the patients and HCs, and pre- and post-treatment patients. Support vector regression (SVR) based on CC-FC was performed to predict treatment response. Correlation analysis explored associations between CC-FC and clinical features, as well as gene profiles. Compared to HCs, drug-naive OCD patients exhibited reduced CC-FC in executive, affective-limbic, and sensorimotor networks, with specific genetic profiles associated with altered CC-FC. Gene enrichment analyses highlighted the involvement of these genes in various biological processes, molecular functions, and pathways. Post-treatment, the patients showed partial clinical improvement and partial restoration of the previously decreased CC-FC. Abnormal CC-FC at baseline correlated negatively with compulsions severity and social functional impairment, while changes in CC-FC correlated with cognitive function changes post-treatment. CC-FC emerged as a potential predictor of symptom severity in patients following paroxetine treatment. This longitudinal resting-state fMRI study underscores the crucial role of CC-FC in the neuropsychological mechanisms of OCD and its pharmacological treatment. Transcriptome-neuroimaging spatial correlation analyses provide insight into the neurobiological mechanisms underlying OCD pathology. Furthermore, SVR analyses hold promise for advancing precision medicine approaches in treating patients with OCD.
Collapse
Affiliation(s)
- Haohao Yan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Xiaoxiao Shan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Huabing Li
- Department of Radiology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, 410011, China
| | - Feng Liu
- Department of Radiology, Tianjin Medical University General Hospital, Tianjin, China
| | - Guojun Xie
- Department of Psychiatry, The Third People's Hospital of Foshan, Foshan, 528000, Guangdong, China
| | - Ping Li
- Department of Psychiatry, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Wenbin Guo
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| |
Collapse
|
5
|
Chen Y, Shen P, He Y, Zeng D, Li Y, Zhang Y, Chen M, Liu C. Bibliometric analysis of functional magnetic resonance imaging studies on chronic pain over the past 20 years. Acta Neurochir (Wien) 2024; 166:307. [PMID: 39060813 DOI: 10.1007/s00701-024-06204-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Accepted: 07/17/2024] [Indexed: 07/28/2024]
Abstract
PURPOSE The utilization of functional magnetic resonance imaging (fMRI) in studying the mechanisms and treatment of chronic pain has gained significant popularity. However, there is currently a dearth of literature conducting bibliometric analysis on fMRI studies focused on chronic pain. METHODS All the literature included in this study was obtained from the Science Citation Index Expanded of Web of Science Core Collection. We used CiteSpace and VOSviewer to analyze publications, authors, countries or regions, institutions, journals, references and keywords. Additionally, we evaluated the timeline and burst analysis of keywords, as well as the timeline and burst analysis of references. The search was conducted from 2004 to 2023 and completed within a single day on October 4th, 2023. RESULTS A total of 1,327 articles were retrieved. The annual publication shows an overall increasing trend. The United States has the highest number of publications and the main contributing institution is Harvard University. The journal PAIN produces the most articles. In recent years, resting-state fMRI, the prefrontal cortex, nucleus accumbens, thalamus, and migraines have been researched hotspots of fMRI studies on chronic pain. CONCLUSIONS This study provides an in-depth perspective on fMRI for chronic pain research, revealing key points, research hotspots and research trends, which offers valuable ideas for future research activities. It concludes with a summary of advances in clinical practice in this area, pointing out the need for critical evaluation of these findings in the light of guidelines and expert recommendations. It is anticipated that further high-quality research outputs will be generated in the future, which will facilitate the utilization of fMRI in clinical decision-making for chronic pain.
Collapse
Affiliation(s)
- Yiming Chen
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Peifeng Shen
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yanan He
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Deyi Zeng
- Department of Radiology, Panyu Health Management Center (Panyu Rehabilitation Hospital), 688 West Yushan Road Shatou Street, Panyu District, Guangzhou, China
| | - Yuanchao Li
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yuting Zhang
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Mengtong Chen
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chunlong Liu
- Clinical Medical College of Acupuncture Moxibustion and Rehabilitation, Guangzhou University of Chinese Medicine, Guangzhou, China.
| |
Collapse
|
6
|
Ying X, Gao Y, Liao L. Brain Responses Difference between Sexes for Strong Desire to Void: A Functional Magnetic Resonance Imaging Study in Adults Based on Graph Theory. J Clin Med 2024; 13:4284. [PMID: 39124552 PMCID: PMC11313296 DOI: 10.3390/jcm13154284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 07/09/2024] [Accepted: 07/17/2024] [Indexed: 08/12/2024] Open
Abstract
Background: The alternations of brain responses to a strong desire to void were unclear, and the gender differences under the strong desire to void remain controversial. The present study aims to identify the functional brain network's topologic property changes evoked by a strong desire to void in healthy male and female adults with synchronous urodynamics using a graph theory analysis. Methods: The bladders of eleven healthy males and eleven females were filled via a catheter using a specific infusion and withdrawal pattern. A resting-state functional magnetic resonance imaging (fMRI) was performed on the enrolled subjects, scanning under both the empty bladder and strong desire to void states. An automated anatomical labeling (AAL) atlas was used to identify the ninety cortical and subcortical regions. Pearson's correlation calculations were performed to establish a brain connection matrix. A paired t-test (p < 0.05) and Bonferroni correction were applied to identify the significant statistical differences in topological properties between the two states, including small-world network property parameters [gamma (γ) and lambda (λ)], characteristic path length (Lp), clustering coefficient (Cp), global efficiency (Eglob), local efficiency (Eloc), and regional nodal efficiency (Enodal). Results: The final data suggested that females and males had different brain response patterns to a strong desire to void, compared with an empty bladder state. Conclusions: More brain regions involving emotion, cognition, and social work were active in females, and males might obtain a better urinary continence via a compensatory mechanism.
Collapse
Affiliation(s)
- Xiaoqian Ying
- Beijing Tsinghua Changgung Hospital, School of Clinical Medicine, Tsinghua University, Beijing 102218, China;
- Rehabilitation School, Capital Medical University, Beijing Boai Hospital, China Rehabilitation Research Center, Beijing 100068, China
| | - Yi Gao
- Department of Neurourology, Beijing Boai Hospital, China Rehabilitation Research Center, Beijing 100068, China
| | - Limin Liao
- Rehabilitation School, Capital Medical University, Beijing Boai Hospital, China Rehabilitation Research Center, Beijing 100068, China
- Department of Urology, Capital Medical University, Beijing 100068, China
| |
Collapse
|
7
|
Hechler A, Kuchling J, Müller-Jensen L, Klag J, Paul F, Prüss H, Finke C. Hippocampal hub failure is linked to long-term memory impairment in anti-NMDA-receptor encephalitis: insights from structural connectome graph theoretical network analysis. J Neurol 2024:10.1007/s00415-024-12545-4. [PMID: 38977462 DOI: 10.1007/s00415-024-12545-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Revised: 06/22/2024] [Accepted: 06/26/2024] [Indexed: 07/10/2024]
Abstract
BACKGROUND Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is characterized by distinct structural and functional brain alterations, predominantly affecting the medial temporal lobes and the hippocampus. Structural connectome analysis with graph-based investigations of network properties allows for an in-depth characterization of global and local network changes and their relationship with clinical deficits in NMDAR encephalitis. METHODS Structural networks from 61 NMDAR encephalitis patients in the post-acute stage (median time from acute hospital discharge: 18 months) and 61 age- and sex-matched healthy controls (HC) were analyzed using diffusion-weighted imaging (DWI)-based probabilistic anatomically constrained tractography and volumetry of a selection of subcortical and white matter brain volumes was performed. We calculated global, modular, and nodal graph measures with special focus on default-mode network, medial temporal lobe, and hippocampus. Pathologically altered metrics were investigated regarding their potential association with clinical course, disease severity, and cognitive outcome. RESULTS Patients with NMDAR encephalitis showed regular global graph metrics, but bilateral reductions of hippocampal node strength (left: p = 0.049; right: p = 0.013) and increased node strength of right precuneus (p = 0.013) compared to HC. Betweenness centrality was decreased for left-sided entorhinal cortex (p = 0.042) and left caudal middle frontal gyrus (p = 0.037). Correlation analyses showed a significant association between reduced left hippocampal node strength and verbal long-term memory impairment (p = 0.021). We found decreased left (p = 0.013) and right (p = 0.001) hippocampal volumes that were associated with hippocampal node strength (left p = 0.009; right p < 0.001). CONCLUSIONS Focal network property changes of the medial temporal lobes indicate hippocampal hub failure that is associated with memory impairment in NMDAR encephalitis at the post-acute stage, while global structural network properties remain unaltered. Graph theory analysis provides new pathophysiological insight into structural network changes and their association with persistent cognitive deficits in NMDAR encephalitis.
Collapse
Affiliation(s)
- André Hechler
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
- TUM-Neuroimaging Center, Technische Universitaet Muenchen, Munich, Germany
| | - Joseph Kuchling
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité, Universitätsmedizin Berlin, Berlin, Germany
| | - Leonie Müller-Jensen
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Johanna Klag
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
| | - Friedemann Paul
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité, Universitätsmedizin Berlin, Berlin, Germany
- Neurocure Cluster of Excellence, NeuroCure Clinical Research Center, Charité, Berlin Institute of Health, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Harald Prüss
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Berlin, Germany
| | - Carsten Finke
- Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany.
- Department of Neurology and Experimental Neurology, Charité, Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Charitéplatz 1, 10117, Berlin, Germany.
| |
Collapse
|
8
|
Wang B, Yuan Y, Yang L, Huang Y, Zhang X, Zhang X, Yan W, Li Y, Li D, Xiang J, Yang J, Liu M. Multi-hierarchy Network Configuration Can Predict Brain States and Performance. J Cogn Neurosci 2024; 36:1695-1714. [PMID: 38579269 DOI: 10.1162/jocn_a_02153] [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] [Indexed: 04/07/2024]
Abstract
The brain is a hierarchical modular organization that varies across functional states. Network configuration can better reveal network organization patterns. However, the multi-hierarchy network configuration remains unknown. Here, we propose an eigenmodal decomposition approach to detect modules at multi-hierarchy, which can identify higher-layer potential submodules and is consistent with the brain hierarchical structure. We defined three metrics: node configuration matrix, combinability, and separability. Node configuration matrix represents network configuration changes between layers. Separability reflects network configuration from global to local, whereas combinability shows network configuration from local to global. First, we created a random network to verify the feasibility of the method. Results show that separability of real networks is larger than that of random networks, whereas combinability is smaller than random networks. Then, we analyzed a large data set incorporating fMRI data from resting and seven distinct tasking conditions. Experiment results demonstrates the high similarity in node configuration matrices for different task conditions, whereas the tasking states have less separability and greater combinability between modules compared with the resting state. Furthermore, the ability of brain network configuration can predict brain states and cognition performance. Crucially, derived from tasks are highlighted with greater power than resting, showing that task-induced attributes have a greater ability to reveal individual differences. Together, our study provides novel perspectives for analyzing the organization structure of complex brain networks at multi-hierarchy, gives new insights to further unravel the working mechanisms of the brain, and adds new evidence for tasking states to better characterize and predict behavioral traits.
Collapse
Affiliation(s)
- Bin Wang
- Taiyuan University of Technology
| | | | - Lan Yang
- Taiyuan University of Technology
| | | | - Xi Zhang
- Taiyuan University of Technology
| | | | | | - Ying Li
- Taiyuan University of Technology
| | | | | | | | | |
Collapse
|
9
|
Lohia K, Soans RS, Saxena R, Mahajan K, Gandhi TK. Distinct rich and diverse clubs regulate coarse and fine binocular disparity processing: Evidence from stereoscopic task-based fMRI. iScience 2024; 27:109831. [PMID: 38784010 PMCID: PMC11111836 DOI: 10.1016/j.isci.2024.109831] [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: 11/09/2023] [Revised: 03/07/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024] Open
Abstract
While cortical regions involved in processing binocular disparities have been studied extensively, little is known on how the human visual system adapts to changing disparity magnitudes. In this paper, we investigate causal mechanisms of coarse and fine binocular disparity processing using fMRI with a clinically validated, custom anaglyph-based stimulus. We make use of Granger causality and graph measures to reveal the existence of distinct rich and diverse clubs across different disparity magnitudes. We demonstrate that Middle Temporal area (MT) plays a specialized role with overlapping rich and diverse characteristics. Next, we show that subtle interhemispheric differences exist across various brain regions, despite an overall right hemisphere dominance. Finally, we pass the graph measures through the decision tree and found that the diverse clubs outperform rich clubs in decoding disparity magnitudes. Our study sets the stage for conducting further investigations on binocular disparity processing, particularly in the context of neuro-ophthalmic disorders with binocular impairments.
Collapse
Affiliation(s)
- Kritika Lohia
- Department of Electrical Engineering, Indian Institute of Technology – Delhi, New Delhi, India
| | - Rijul Saurabh Soans
- Department of Electrical Engineering, Indian Institute of Technology – Delhi, New Delhi, India
- Laboratory of Experimental Ophthalmology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Herbert Wertheim School of Optometry and Vision Science, University of California, Berkeley, Berkeley, CA, USA
| | - Rohit Saxena
- Dr. Rajendra Prasad Centre for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India
| | | | - Tapan K. Gandhi
- Department of Electrical Engineering, Indian Institute of Technology – Delhi, New Delhi, India
| |
Collapse
|
10
|
Echevarria MAN, Batistuzzo MC, Silva RMF, Brunoni AR, Sato JR, Miguel EC, Hoexter MQ, Shavitt RG. Increases in functional connectivity between the default mode network and sensorimotor network correlate with symptomatic improvement after transcranial direct current stimulation for obsessive-compulsive disorder. J Affect Disord 2024; 355:175-183. [PMID: 38548207 DOI: 10.1016/j.jad.2024.03.141] [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: 09/18/2023] [Revised: 03/10/2024] [Accepted: 03/24/2024] [Indexed: 04/04/2024]
Abstract
BACKGROUND Non-invasive neuromodulation is a promising intervention for obsessive-compulsive disorder (OCD), although its neurobiological mechanisms of action are still poorly understood. Recent evidence suggests that abnormalities in the connectivity of the default mode network (DMN) and the supplementary motor area (SMA) with other brain regions and networks are involved in OCD pathophysiology. We examined if transcranial direct current stimulation (tDCS) alters these connectivity patterns and if they correlate with symptom improvement in treatment-resistant OCD. METHODS In 23 patients from a larger clinical trial (comparing active tDCS to sham) who underwent pre- and post-treatment MRI scans, we assessed resting-state functional MRI (rs-fMRI) data. The treatment involved 30-minute daily tDCS sessions for four weeks (weekdays only), with the cathode over the SMA and the anode over the left deltoid. We conducted whole-brain connectivity analysis comparing active tDCS-treated to sham-treated patients. RESULTS We found that active tDCS, but not sham, led to connectivity increasing between the DMN and the bilateral pre/postcentral gyri (p = 0.004, FDR corrected) and temporal-auditory areas plus the SMA (p = 0.028, FDR corrected). Also, symptom improvement was directly associated with connectivity increasing between the left lateral sensorimotor network and the left precuneus (r = 0.589, p = 0.034). LIMITATIONS Limited sample size (23 participants with resting-state neuroimaging), inability to analyze specific OCD symptom dimensions (e.g., harm, sexual/religious, symmetry/checking, cleaning/contamination). CONCLUSIONS These data offer novel information concerning functional connectivity changes associated with non-invasive neuromodulation interventions in OCD and can guide new brain stimulation interventions in the framework of personalized interventions.
Collapse
Affiliation(s)
- M A N Echevarria
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil.
| | - M C Batistuzzo
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil; Department of Methods and Techniques in Psychology, Pontifical Catholic University, São Paulo, SP, Brazil
| | - R M F Silva
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil
| | - A R Brunoni
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil
| | - J R Sato
- Center of Mathematics, Computing and Cognition, Universidade Federal do ABC, SP, Brazil
| | - E C Miguel
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil
| | - M Q Hoexter
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil
| | - R G Shavitt
- LIM-23, Department of Psychiatry, Faculdade de Medicina, Universidade de São Paulo, SP, Brazil
| |
Collapse
|
11
|
Shen F, Zhou H. Advances in the etiology and neuroimaging of children with attention deficit hyperactivity disorder. Front Pediatr 2024; 12:1400468. [PMID: 38915870 PMCID: PMC11194347 DOI: 10.3389/fped.2024.1400468] [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: 03/13/2024] [Accepted: 05/20/2024] [Indexed: 06/26/2024] Open
Abstract
Attention deficit hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder in children, characterized by age-inappropriate inattention, hyperactivity, and impulsivity, which can cause extensive damage to children's academic, occupational, and social skills. This review will present current advancements in the field of attention deficit hyperactivity disorder, including genetics, environmental factors, epigenetics, and neuroimaging features. Simultaneously, we will discuss the highlights of promising directions for further study.
Collapse
Affiliation(s)
| | - Hui Zhou
- Department of Pediatrics, West China Second University Hospital, Sichuan University, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, Chengdu, China
| |
Collapse
|
12
|
Stanford W, Mucha PJ, Dayan E. Age-related differences in network controllability are mitigated by redundancy in large-scale brain networks. Commun Biol 2024; 7:701. [PMID: 38849512 PMCID: PMC11161655 DOI: 10.1038/s42003-024-06392-2] [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] [Received: 03/20/2023] [Accepted: 05/28/2024] [Indexed: 06/09/2024] Open
Abstract
The aging brain undergoes major changes in its topology. The mechanisms by which the brain mitigates age-associated changes in topology to maintain robust control of brain networks are unknown. Here we use diffusion MRI data from cognitively intact participants (n = 480, ages 40-90) to study age-associated differences in the average controllability of structural brain networks, topological features that could mitigate these differences, and the overall effect on cognitive function. We find age-associated declines in average controllability in control hubs and large-scale networks, particularly within the frontoparietal control and default mode networks. Further, we find that redundancy, a hypothesized mechanism of reserve, quantified via the assessment of multi-step paths within networks, mitigates the effects of topological differences on average network controllability. Lastly, we discover that average network controllability, redundancy, and grey matter volume, each uniquely contribute to predictive models of cognitive function. In sum, our results highlight the importance of redundancy for robust control of brain networks and in cognitive function in healthy-aging.
Collapse
Affiliation(s)
- William Stanford
- Biological and Biomedical Sciences Program, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Peter J Mucha
- Department of Mathematics, Dartmouth College, Hanover, NH, USA
| | - Eran Dayan
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| |
Collapse
|
13
|
Huang H, Chen C, Rong B, Zhou Y, Yuan W, Peng Y, Liu Z, Wang G, Wang H. Distinct resting-state functional connectivity of the anterior cingulate cortex subregions in first-episode schizophrenia. Brain Imaging Behav 2024; 18:675-685. [PMID: 38349504 DOI: 10.1007/s11682-024-00863-0] [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: 02/06/2024] [Indexed: 07/04/2024]
Abstract
The anterior cingulate cortex (ACC) is a heterogeneous region of the brain's limbic system that regulates cognitive and emotional processing, and is frequently implicated in schizophrenia. This study aims to characterize resting-state functional connectivity (rsFC) profiles of three subregions of ACC in patients with first-episode schizophrenia and healthy controls. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were collected from 60 first-episode schizophrenia (FES) patients and 60 healthy controls (HC), and the subgenual ACC (sgACC), pregenual ACC (pgACC), and dorsal ACC (dACC) were selected as seed regions from the newest automated anatomical labeling atlas 3 (AAL3). Seed-based rsFC maps for each ACC subregion were generated and compared between the two groups. The results revealed that compared to the HC group, the FES group showed higher rsFC between the pgACC and bilateral lateral orbitofrontal cortex (lOFC), and lower rsFC between the dACC and right posterior OFC (pOFC), the medial prefrontal gyrus (MPFC), and the precuneus cortex (PCu). These findings point to a selective functional dysconnectivity of pgACC and dACC in schizophrenia and provide more accurate information about the functional role of the ACC in this disorder.
Collapse
Affiliation(s)
- Huan Huang
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, China
| | - Cheng Chen
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, China
| | - Bei Rong
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, China
| | - Yuan Zhou
- Institute of Psychology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wei Yuan
- Department of Psychiatry, Yidu People's Hospital, Yidu, 443300, China
| | - Yunlong Peng
- Department of Psychiatry, Yidu People's Hospital, Yidu, 443300, China
| | - Zhongchun Liu
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, China
| | - Gaohua Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, China
- Hubei Institute of Neurology and Psychiatry Research, Wuhan, 430060, China
| | - Huiling Wang
- Department of Psychiatry, Renmin Hospital of Wuhan University, 238 Jiefang Road, Wuhan, 430060, China.
- Hubei Provincial Key Laboratory of Developmentally Originated Disease, Wuhan, 430071, China.
| |
Collapse
|
14
|
Sanda P, Hlinka J, van den Berg M, Skoch A, Bazhenov M, Keliris GA, Krishnan GP. Cholinergic modulation supports dynamic switching of resting state networks through selective DMN suppression. PLoS Comput Biol 2024; 20:e1012099. [PMID: 38843298 PMCID: PMC11185486 DOI: 10.1371/journal.pcbi.1012099] [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: 07/25/2023] [Revised: 06/18/2024] [Accepted: 04/23/2024] [Indexed: 06/19/2024] Open
Abstract
Brain activity during the resting state is widely used to examine brain organization, cognition and alterations in disease states. While it is known that neuromodulation and the state of alertness impact resting-state activity, neural mechanisms behind such modulation of resting-state activity are unknown. In this work, we used a computational model to demonstrate that change in excitability and recurrent connections, due to cholinergic modulation, impacts resting-state activity. The results of such modulation in the model match closely with experimental work on direct cholinergic modulation of Default Mode Network (DMN) in rodents. We further extended our study to the human connectome derived from diffusion-weighted MRI. In human resting-state simulations, an increase in cholinergic input resulted in a brain-wide reduction of functional connectivity. Furthermore, selective cholinergic modulation of DMN closely captured experimentally observed transitions between the baseline resting state and states with suppressed DMN fluctuations associated with attention to external tasks. Our study thus provides insight into potential neural mechanisms for the effects of cholinergic neuromodulation on resting-state activity and its dynamics.
Collapse
Affiliation(s)
- Pavel Sanda
- Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
| | - Jaroslav Hlinka
- Institute of Computer Science of the Czech Academy of Sciences, Prague, Czech Republic
- National Institute of Mental Health, Klecany, Czech Republic
| | - Monica van den Berg
- Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium
- μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Antonin Skoch
- National Institute of Mental Health, Klecany, Czech Republic
- MR Unit, Department of Diagnostic and Interventional Radiology, Institute for Clinical and Experimental Medicine, Prague, Czech Republic
| | - Maxim Bazhenov
- Department of Medicine, University of California San Diego, La Jolla, California, United States of America
| | - Georgios A. Keliris
- Bio-Imaging Lab, University of Antwerp, Antwerp, Belgium
- Institute of Computer Science, Foundation for Research and Technology - Hellas, Heraklion, Crete, Greece
| | - Giri P. Krishnan
- Department of Medicine, University of California San Diego, La Jolla, California, United States of America
- Georgia Institute of Technology, Atlanta, Georgia, United States of America
| |
Collapse
|
15
|
Wang X, Zwosta K, Hennig J, Böhm I, Ehrlich S, Wolfensteller U, Ruge H. The dynamics of functional brain network segregation in feedback-driven learning. Commun Biol 2024; 7:531. [PMID: 38710773 DOI: 10.1038/s42003-024-06210-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 04/17/2024] [Indexed: 05/08/2024] Open
Abstract
Prior evidence suggests that increasingly efficient task performance in human learning is associated with large scale brain network dynamics. However, the specific nature of this general relationship has remained unclear. Here, we characterize performance improvement during feedback-driven stimulus-response (S-R) learning by learning rate as well as S-R habit strength and test whether and how these two behavioral measures are associated with a functional brain state transition from a more integrated to a more segregated brain state across learning. Capitalizing on two separate fMRI studies using similar but not identical experimental designs, we demonstrate for both studies that a higher learning rate is associated with a more rapid brain network segregation. By contrast, S-R habit strength is not reliably related to changes in brain network segregation. Overall, our current study results highlight the utility of dynamic functional brain state analysis. From a broader perspective taking into account previous study results, our findings align with a framework that conceptualizes brain network segregation as a general feature of processing efficiency not only in feedback-driven learning as in the present study but also in other types of learning and in other task domains.
Collapse
Affiliation(s)
- Xiaoyu Wang
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany.
| | - Katharina Zwosta
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Julius Hennig
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Ilka Böhm
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
| | - Stefan Ehrlich
- Translational Developmental Neuroscience Section, Division of Psychological and Social Medicine and Developmental Neurosciences, Faculty of Medicine, TU Dresden, Dresden, Germany
- Eating Disorder Treatment and Research Center, Department of Child and Adolescent Psychiatry, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Uta Wolfensteller
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| | - Hannes Ruge
- Faculty of Psychology, Technische Universität Dresden, Dresden, Germany
| |
Collapse
|
16
|
Guo J, He C, Song H, Gao H, Yao S, Dong SS, Yang TL. Unveiling Promising Neuroimaging Biomarkers for Schizophrenia Through Clinical and Genetic Perspectives. Neurosci Bull 2024:10.1007/s12264-024-01214-1. [PMID: 38703276 DOI: 10.1007/s12264-024-01214-1] [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: 07/14/2023] [Accepted: 01/08/2024] [Indexed: 05/06/2024] Open
Abstract
Schizophrenia is a complex and serious brain disorder. Neuroscientists have become increasingly interested in using magnetic resonance-based brain imaging-derived phenotypes (IDPs) to investigate the etiology of psychiatric disorders. IDPs capture valuable clinical advantages and hold biological significance in identifying brain abnormalities. In this review, we aim to discuss current and prospective approaches to identify potential biomarkers for schizophrenia using clinical multimodal neuroimaging and imaging genetics. We first described IDPs through their phenotypic classification and neuroimaging genomics. Secondly, we discussed the applications of multimodal neuroimaging by clinical evidence in observational studies and randomized controlled trials. Thirdly, considering the genetic evidence of IDPs, we discussed how can utilize neuroimaging data as an intermediate phenotype to make association inferences by polygenic risk scores and Mendelian randomization. Finally, we discussed machine learning as an optimum approach for validating biomarkers. Together, future research efforts focused on neuroimaging biomarkers aim to enhance our understanding of schizophrenia.
Collapse
Affiliation(s)
- Jing Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Changyi He
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Huimiao Song
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Huiwu Gao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China
| | - Shi Yao
- Guangdong Key Laboratory of Age-Related Cardiac and Cerebral Diseases, Affiliated Hospital of Guangdong Medical University, Zhanjiang, 524000, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, 710049, China.
| |
Collapse
|
17
|
Jafari Z, Kolb BE, Mohajerani MH. A systematic review of altered resting-state networks in early deafness and implications for cochlear implantation outcomes. Eur J Neurosci 2024; 59:2596-2615. [PMID: 38441248 DOI: 10.1111/ejn.16295] [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: 10/31/2022] [Revised: 01/29/2024] [Accepted: 02/06/2024] [Indexed: 05/22/2024]
Abstract
Auditory deprivation following congenital/pre-lingual deafness (C/PD) can drastically affect brain development and its functional organisation. This systematic review intends to extend current knowledge of the impact of C/PD and deafness duration on brain resting-state networks (RSNs), review changes in RSNs and spoken language outcomes post-cochlear implant (CI) and draw conclusions for future research. The systematic literature search followed the PRISMA guideline. Two independent reviewers searched four electronic databases using combined keywords: 'auditory deprivation', 'congenital/prelingual deafness', 'resting-state functional connectivity' (RSFC), 'resting-state fMRI' and 'cochlear implant'. Seventeen studies (16 cross-sectional and one longitudinal) met the inclusion criteria. Using the Crowe Critical Appraisal Tool, the publications' quality was rated between 65.0% and 92.5% (mean: 84.10%), ≥80% in 13 out of 17 studies. A few studies were deficient in sampling and/or ethical considerations. According to the findings, early auditory deprivation results in enhanced RSFC between the auditory network and brain networks involved in non-verbal communication, and high levels of spontaneous neural activity in the auditory cortex before CI are evidence of occupied auditory cortical areas with other sensory modalities (cross-modal plasticity) and sub-optimal CI outcomes. Overall, current evidence supports the idea that moreover intramodal and cross-modal plasticity, the entire brain adaptation following auditory deprivation contributes to spoken language development and compensatory behaviours.
Collapse
Affiliation(s)
- Zahra Jafari
- School of Communication Sciences and Disorders (SCSD), Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Psychology and Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada
| | - Bryan E Kolb
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada
| | - Majid H Mohajerani
- Department of Neuroscience, Canadian Centre for Behavioural Neuroscience, University of Lethbridge, Lethbridge, Alberta, Canada
- Douglas Research Centre, Department of Psychiatry, McGill University, Montreal, Québec, Canada
| |
Collapse
|
18
|
Wu K, Li H, Xie Y, Zhang S, Wang X. Fractional amplitude of low-frequency fluctuation alterations in patients with cervical spondylotic myelopathy: a resting-state fMRI study. Neuroradiology 2024; 66:847-854. [PMID: 38530417 DOI: 10.1007/s00234-024-03337-8] [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: 10/17/2023] [Accepted: 03/11/2024] [Indexed: 03/28/2024]
Abstract
PURPOSE We sought to use the fractional amplitude of low-frequency fluctuation (fALFF) method to investigate the changes in spontaneous brain activity in CSM patients and their relationships with clinical features. METHODS We recruited 20 patients with CSM, and 20 healthy controls (HCs) matched for age, sex, and education status. The fALFF method was used to evaluate the altered spontaneous brain activities. The Pearson correlation analysis of fALFF and the clinical features were carried out. RESULTS Compared with HC, CSM group showed increased fALFF values in the left middle frontal gyrus, inferior parietal lobule, and right angular gyrus. Decreased fALFF values were found in the right lingual gyrus, cuneus (P < 0.05). Pearson correlation analysis shows that the fALFF values of all CSM were positively correlated with JOA score in the right angular gyrus (r = 0.518, P < 0.05). CONCLUSION CSM patients have abnormal fALFF distribution in multiple brain regions and might be an appealing alternative approach for further exploration of the pathological and neuropsychological states in CSM.
Collapse
Affiliation(s)
- Kaifu Wu
- Department of Radiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, No. 26, Shengli Street, Wuhan, 430014, China
| | - Han Li
- Department of Radiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, No. 26, Shengli Street, Wuhan, 430014, China
| | - Yuanliang Xie
- Department of Radiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, No. 26, Shengli Street, Wuhan, 430014, China
| | - Shutong Zhang
- Department of Radiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, No. 26, Shengli Street, Wuhan, 430014, China
| | - Xiang Wang
- Department of Radiology, the Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, No. 26, Shengli Street, Wuhan, 430014, China.
| |
Collapse
|
19
|
Hong YN, Hwang H, Hong J, Han DH. Correlations between developmental trajectories of brain functional connectivity, neurocognitive functions, and clinical symptoms in patients with attention-deficit hyperactivity disorder. J Psychiatr Res 2024; 173:347-354. [PMID: 38581903 DOI: 10.1016/j.jpsychires.2024.03.021] [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: 01/13/2024] [Revised: 03/17/2024] [Accepted: 03/19/2024] [Indexed: 04/08/2024]
Abstract
Several studies on attention-deficit hyperactivity disorder (ADHD) have suggested a developmental sequence of brain changes: subcortico-subcortical connectivity in children, evolving to subcortico-cortical in adolescence, and culminating in cortico-cortical connectivity in young adulthood. This study hypothesized that children with ADHD would exhibit decreased functional connectivity (FC) between the cortex and striatum compared to adults with ADHD, who may show increased FC in these regions. Seventy-six patients with ADHD (26 children, 26 adolescents, and 24 adults) and 74 healthy controls (25 children, 24 adolescents, and 25 adults) participated in the study. Resting state magnetic resonance images were acquired using a 3.0 T Philips Achieva scanner. The results indicated a gradual decrease in the number of subcategories representing intelligence quotient deficits in the ADHD group with age. In adulthood, the ADHD group exhibited lower working memory compared to the healthy control group. The number of regions showing decreased FC from the cortex to striatum between the ADHD and control groups reduced with age, while regions with increased FC from the default mode network and attention network in the ADHD group increased with age. In adolescents and adults, working memory was positively associated with brain activity in the postcentral gyrus and negatively correlated with ADHD clinical symptoms. In conclusion, the findings suggest that intelligence deficits in certain IQ subcategories may diminish as individuals with ADHD age. Additionally, the study indicates an increasing anticorrelation between cortical and subcortical regions with age in individuals with ADHD.
Collapse
Affiliation(s)
- Yu Na Hong
- Department of Psychiatry, Chung-Ang University Hospital, Seoul, Republic of Korea.
| | - Hyunchan Hwang
- Department of Psychiatry, Chung-Ang University Hospital, Seoul, Republic of Korea.
| | - Jisun Hong
- Department of Psychiatry, Chung-Ang University Gwang-Myeong Hospital, Gwang-Myeong, Republic of Korea.
| | - Doug Hyun Han
- Department of Psychiatry, Chung-Ang University Hospital, Seoul, Republic of Korea.
| |
Collapse
|
20
|
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.
Collapse
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.
| |
Collapse
|
21
|
Luo W, Liu B, Tang Y, Huang J, Wu J. Rest to Promote Learning: A Brain Default Mode Network Perspective. Behav Sci (Basel) 2024; 14:349. [PMID: 38667145 PMCID: PMC11047624 DOI: 10.3390/bs14040349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 04/13/2024] [Accepted: 04/17/2024] [Indexed: 04/29/2024] Open
Abstract
The brain often switches freely between focused attention and divergent thinking, and the Default Mode Network (DMN) is activated during brain rest. Since its discovery, the DMN, together with its function and characteristics, indicates that learning does not stop when the brain "rests". Therefore, DMN plays an important role in learning. Neural activities such as beta wave rhythm regulation, "subconscious" divergence thinking mode initiation, hippocampal function, and neural replay occur during default mode, all of which explains that "rest" promotes learning. This paper summarized the function and neural mechanism of DMN in learning and proposed that the DMN plays an essential role in learning, which is that it enables rest to promote learning.
Collapse
Affiliation(s)
- Wei Luo
- Department of Applied Psychology, School of Education Sciences, Nanning Normal University, Nanning 530299, China; (W.L.); (Y.T.)
- Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
- Guangxi Education Modernization and Quality Monitoring Research Center, Nanning 530001, China
| | - Biao Liu
- School of Foreign Languages, Nanning Normal University, Nanning 530100, China;
| | - Ying Tang
- Department of Applied Psychology, School of Education Sciences, Nanning Normal University, Nanning 530299, China; (W.L.); (Y.T.)
| | - Jingwen Huang
- Department of Science Research, Guangxi University, Nanning 530004, China;
| | - Ji Wu
- Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| |
Collapse
|
22
|
Fu Z, Batta I, Wu L, Abrol A, Agcaoglu O, Salman MS, Du Y, Iraji A, Shultz S, Sui J, Calhoun VD. Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. Neuroimage 2024; 292:120617. [PMID: 38636639 DOI: 10.1016/j.neuroimage.2024.120617] [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: 01/08/2024] [Revised: 04/03/2024] [Accepted: 04/15/2024] [Indexed: 04/20/2024] Open
Abstract
A primary challenge to the data-driven analysis is the balance between poor generalizability of population-based research and characterizing more subject-, study- and population-specific variability. We previously introduced a fully automated spatially constrained independent component analysis (ICA) framework called NeuroMark and its functional MRI (fMRI) template. NeuroMark has been successfully applied in numerous studies, identifying brain markers reproducible across datasets and disorders. The first NeuroMark template was constructed based on young adult cohorts. We recently expanded on this initiative by creating a standardized normative multi-spatial-scale functional template using over 100,000 subjects, aiming to improve generalizability and comparability across studies involving diverse cohorts. While a unified template across the lifespan is desirable, a comprehensive investigation of the similarities and differences between components from different age populations might help systematically transform our understanding of the human brain by revealing the most well-replicated and variable network features throughout the lifespan. In this work, we introduced two significant expansions of NeuroMark templates first by generating replicable fMRI templates for infants, adolescents, and aging cohorts, and second by incorporating structural MRI (sMRI) and diffusion MRI (dMRI) modalities. Specifically, we built spatiotemporal fMRI templates based on 6,000 resting-state scans from four datasets. This is the first attempt to create robust ICA templates covering dynamic brain development across the lifespan. For the sMRI and dMRI data, we used two large publicly available datasets including more than 30,000 scans to build reliable templates. We employed a spatial similarity analysis to identify replicable templates and investigate the degree to which unique and similar patterns are reflective in different age populations. Our results suggest remarkably high similarity of the resulting adapted components, even across extreme age differences. With the new templates, the NeuroMark framework allows us to perform age-specific adaptations and to capture features adaptable to each modality, therefore facilitating biomarker identification across brain disorders. In sum, the present work demonstrates the generalizability of NeuroMark templates and suggests the potential of new templates to boost accuracy in mental health research and advance our understanding of lifespan and cross-modal alterations.
Collapse
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, Georgia, United States.
| | - Ishaan Batta
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Lei Wu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Anees Abrol
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Oktay Agcaoglu
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Mustafa S Salman
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Yuhui Du
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Armin Iraji
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, Georgia, United States
| | - Sarah Shultz
- Department of Pediatrics, Emory University School of Medicine, Atlanta, Georgia, United States
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - 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, Georgia, United States
| |
Collapse
|
23
|
Liu Y, Wang H, Sha G, Cao Y, Chen Y, Chen Y, Zhang J, Chai C, Fan Q, Xia S. The covariant structural and functional neuro-correlates of cognitive impairments in patients with end-stage renal diseases. Front Neurosci 2024; 18:1374948. [PMID: 38686326 PMCID: PMC11056510 DOI: 10.3389/fnins.2024.1374948] [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: 01/23/2024] [Accepted: 04/03/2024] [Indexed: 05/02/2024] Open
Abstract
Introduction Cognitive impairment (CI) is a common complication of end-stage renal disease (ESRD) that is associated with structural and functional changes in the brain. However, whether a joint structural and functional alteration pattern exists that is related to CI in ESRD is unclear. Methods In this study, instead of looking at brain structure and function separately, we aim to investigate the covariant characteristics of both functional and structural aspects. Specifically, we took the fusion analysis approach, namely, multimodal canonical correlation analysis and joint independent component analysis (mCCA+jICA), to jointly study the discriminative features in gray matter volume (GMV) measured by T1-weighted (T1w) MRI, fractional anisotropy (FA) in white matter measured by diffusion MRI, and the amplitude of low-frequency fluctuation (ALFF) measured by blood oxygenation-level-dependent (BOLD) MRI in 78 ESRD patients versus 64 healthy controls (HCs), followed by a mediation effect analysis to explore the relationship between neuroimaging findings, cognitive impairments and uremic toxins. Results Two joint group-discriminative independent components (ICs) were found to show covariant abnormalities across FA, GMV, and ALFF (all p < 0.05). The most dominant joint IC revealed associative patterns of alterations of GMV (in the precentral gyrus, occipital lobe, temporal lobe, parahippocampal gyrus, and hippocampus), alterations of ALFF (in the precuneus, superior parietal gyrus, and superior occipital gyrus), and of white matter FA (in the corticospinal tract and inferior frontal occipital fasciculus). Another significant IC revealed associative alterations of GMV (in the dorsolateral prefrontal and orbitofrontal cortex) and FA (in the forceps minor). Moreover, the brain changes identified by FA and GMV in the above-mentioned brain regions were found to mediate the negative correlation between serum phosphate and mini-mental state examination (MMSE) scores (all p < 0.05). Conclusion The mCCA+jICA method was demonstrated to be capable of revealing covariant abnormalities across neuronal features of different types in ESRD patients as contrasted to HCs, and joint brain changes may play an important role in mediating the relationship between serum toxins and CIs in ESRD. Our results show the mCCA+jICA fusion analysis approach may provide new insights into similar neurobiological studies.
Collapse
Affiliation(s)
- Yuefan Liu
- Department of Biomedical Engineering, Medical College, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
| | - Huiying Wang
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Guanchen Sha
- Department of Biomedical Engineering, Medical College, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
| | - Yutong Cao
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
- Intelligent Medical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Yongsheng Chen
- Department of Neurology, Wayne State University School of Medicine, Detroit, MI, United States
| | - Yuanyuan Chen
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
- Intelligent Medical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Jingyi Zhang
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Chao Chai
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| | - Qiuyun Fan
- Department of Biomedical Engineering, Medical College, Tianjin University, Tianjin, China
- Tianjin Key Laboratory of Brain Science and Neuroengineering, Tianjin, China
- Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration, Tianjin, China
- Intelligent Medical Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China
| | - Shuang Xia
- Department of Radiology, School of Medicine, Tianjin First Central Hospital, Nankai University, Tianjin, China
| |
Collapse
|
24
|
Ren W, Wang M, Wang Q, Huang Q, Feng S, Tao J, Wen C, Xu M, He J, Yang C, Zhao K, Yu X. Altered functional connectivity in patients with post-stroke fatigue: A resting-state fMRI study. J Affect Disord 2024; 350:468-475. [PMID: 38224743 DOI: 10.1016/j.jad.2024.01.129] [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: 08/12/2023] [Revised: 11/24/2023] [Accepted: 01/12/2024] [Indexed: 01/17/2024]
Abstract
BACKGROUND Post-stroke fatigue (PSF) was a common complication after stroke. This study aimed to explore the neuroimaging mechanism of PSF, which was rarely studied. METHODS Patients with the first episode of ischemic stroke were recruited from the First Affiliated Hospital of Wenzhou Medical University between March 2021 and December 2022. The fatigue severity scale (FSS) was used to assess fatigue symptoms. PSF was diagnosed by a neurologist based on the FSS score and PSF diagnostic criteria. All the patients were scanned by resting-state functional MRI (rs-fMRI). Precuneus, the posterior node of default-mode network (pDMN), was related to fatigue. Therefore, imaging data were further analyzed by the seed-based resting-state functional connectivity (FC) approach, with the left (PCUN.L) and right precuneus (PCUN.R) being the seeds. RESULTS A total of 70 patients with acute ischemic stroke were finally recruited, comprising 40 patients with PSF and 30 patients without PSF. Both the PCUN.L and PCUN.R seeds (pDMN) exhibited decreased FC with the prefrontal lobes located at the anterior part of DMN (aDMN), and the FC values were negatively correlated with FSS scores (both p < 0.001). These two seeds also exhibited increased FC with the right insula, and the FC values were positively correlated with FSS scores (both p < 0.05). CONCLUSION The abnormal FC between the aDMN and pDMN was associated with PSF. Besides, the insula, related to interoception, might also play an important role in PSF.
Collapse
Affiliation(s)
- Wenwei Ren
- Department of Psychiatry, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China; School of Mental Health, Wenzhou Medical University, Wenzhou, China
| | - Mengpu Wang
- School of Mental Health, The Affiliated Wenzhou Kangning Hospital, Wenzhou Medical University, Wenzhou, China; School of Mental Health, Wenzhou Medical University, Wenzhou, China
| | - Qiongzhang Wang
- School of Mental Health, Wenzhou Medical University, Wenzhou, China
| | - Qiqi Huang
- Pediatric nursing unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shengchuang Feng
- Centre for Lifelong Learning and Individualised Cognition, Nanyang Technological University, Singapore
| | - Jiejie Tao
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Caiyun Wen
- Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Minjie Xu
- Lishui Second People's Hospital Affiliated to Wenzhou Medical University, Lishui, China
| | - Jincai He
- Department of Neurology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Chuang Yang
- Department of Psychiatry, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ke Zhao
- School of Mental Health, Wenzhou Medical University, Wenzhou, China; Lishui Second People's Hospital Affiliated to Wenzhou Medical University, Lishui, China; The Affiliated Kangning Hospital of Wenzhou Medical University, Wenzhou, China.
| | - Xin Yu
- School of Mental Health, Wenzhou Medical University, Wenzhou, China; Peking University Institute of Mental Health (Sixth Hospital), Beijing, China; National Clinical Research Center for Mental Disorders and Key Laboratory of Mental Health, Ministry of Health, Peking University, Beijing, China; Beijing Municipal Key Laboratory for Translational Research on Diagnosis and Treatment of Dementia, Beijing, China.
| |
Collapse
|
25
|
Yue M, Peng X, Chunlei G, Yi L, Shanshan G, Jifei S, Qingyan C, Bai Z, Yong L, Zhangjin Z, Peijing R, Jiliang F. Modulating the default mode network: Antidepressant efficacy of transcutaneous electrical cranial-auricular acupoints stimulation targeting the insula. Psychiatry Res Neuroimaging 2024; 339:111787. [PMID: 38295529 DOI: 10.1016/j.pscychresns.2024.111787] [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: 07/31/2023] [Revised: 11/22/2023] [Accepted: 01/08/2024] [Indexed: 02/02/2024]
Abstract
BACKGROUND Transcutaneous electrical cranial-auricular acupoint stimulation (TECAS) is a novel non-invasive therapy for major depressive disorder (MDD) that stimulates acupoints innervated by the trigeminal and auricular vagus nerves. However, there are few neuroimaging studies involving the TECAS for the treatment of MDD. Therefore, this study aimed to investigate the treatment response and neurological effects of TECAS using resting-state functional magnetic resonance imaging (rs-fMRI). METHOD A total of 34 patients with mild-to-moderate MDD and 34 demographically matched healthy controls (HCs) were recruited. After an eight-week treatment the primary outcome was clinical response, defined as a baseline-to-endpoint ≥ 50 % reduction in the 17-item Hamilton Depression Rating Scale (HAMD-17). The low-frequency fluctuations (ALFF) method were used to investigate the brain abnormalities of MDD patients and HCs, and altered brain networks were analyzed between pre- and post-treatment using seed-based functional connectivity (FC) analysis. RESULTS We found no significant differences in terms of gender, age, and years of education between the two groups. After treatment, the response rate was 58.82 %. Compared to HCs, MDD patients showed lower ALFF values in the left insula(t = -4.298,P < 0.005), the insula-based FC revealed in the right middle frontal gyrus (MFG)/ right superior frontal gyrus, orbital part (ORBsupmed) (t = -5.29,P < 0.005) and the right anterior cingulate gyrus (ACC)were decreased (t = -6.08,P < 0.005). Furthermore, Compared to pre-treatment, abnormal FC values in the ACC /orbital superior frontal gyrus (SFG) (t = 3.42,P < 0.005) and left superior frontal gyrus (SFG)/ supplement motor area (SMA) were enhanced (t = 3.34,P < 0.005). CONCLUSION TECAS exhibits antidepressant efficacy, particularly influencing the insula-based functional connections within the Default Mode Network (DMN) related to emotion processing in individuals with MDD.
Collapse
Affiliation(s)
- Ma Yue
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Xu Peng
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China
| | - Guo Chunlei
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Luo Yi
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Gao Shanshan
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Sun Jifei
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Chen Qingyan
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Zhenjun Bai
- College of Traditional Chinese Medicine Health Service, Shanxi Datong University, Datong, 037009, Shanxi Province, China
| | - Liu Yong
- Affiliated Hospital of Traditional Chinese Medicine, Southwest Medical University, 646000, Luzhou, China
| | - Zhang Zhangjin
- Department of Chinese Medicine, the University of Hong Kong-Shenzhen Hospital (HKU-SZH), Shenzhen, China
| | - Rong Peijing
- Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China; Institute of Acupuncture and Moxibustion, China Academy of Chinese Medical Sciences, 100700, Beijing, China
| | - Fang Jiliang
- Guang'anmen Hospital, China Academy of Chinese Medical Sciences, 100053, Beijing, China; Graduate School of China Academy of Chinese Medical Sciences, 100700, Beijing, China.
| |
Collapse
|
26
|
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.
Collapse
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.
| |
Collapse
|
27
|
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.
Collapse
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
| |
Collapse
|
28
|
Morrone JM, Pedlar CR. EEG-based neurophysiological indices for expert psychomotor performance - a review. Brain Cogn 2024; 175:106132. [PMID: 38219415 DOI: 10.1016/j.bandc.2024.106132] [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: 09/06/2023] [Revised: 12/19/2023] [Accepted: 01/06/2024] [Indexed: 01/16/2024]
Abstract
A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).
Collapse
Affiliation(s)
- Jazmin M Morrone
- Faculty of Sport, Allied Health, and Performance Science, St Mary's University, Twickenham, London, UK.
| | - Charles R Pedlar
- Faculty of Sport, Allied Health, and Performance Science, St Mary's University, Twickenham, London, UK; Institute of Sport, Exercise and Health, Division of Surgery and Interventional Science, University College London, UK
| |
Collapse
|
29
|
Clare K, Park K, Pan Y, Lejuez CW, Volkow ND, Du C. Neurovascular effects of cocaine: relevance to addiction. Front Pharmacol 2024; 15:1357422. [PMID: 38455961 PMCID: PMC10917943 DOI: 10.3389/fphar.2024.1357422] [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: 12/18/2023] [Accepted: 01/22/2024] [Indexed: 03/09/2024] Open
Abstract
Cocaine is a highly addictive drug, and its use is associated with adverse medical consequences such as cerebrovascular accidents that result in debilitating neurological complications. Indeed, brain imaging studies have reported severe reductions in cerebral blood flow (CBF) in cocaine misusers when compared to the brains of healthy non-drug using controls. Such CBF deficits are likely to disrupt neuro-vascular interaction and contribute to changes in brain function. This review aims to provide an overview of cocaine-induced CBF changes and its implication to brain function and to cocaine addiction, including its effects on tissue metabolism and neuronal activity. Finally, we discuss implications for future research, including targeted pharmacological interventions and neuromodulation to limit cocaine use and mitigate the negative impacts.
Collapse
Affiliation(s)
- Kevin Clare
- New York Medical College, Valhalla, NY, United States
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
| | - Kicheon Park
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
| | - Yingtian Pan
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
| | - Carl W. Lejuez
- Department of Psychology, Stony Brook University, Stony Brook, NY, United States
| | - Nora D. Volkow
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, United States
| | - Congwu Du
- Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY, United States
| |
Collapse
|
30
|
Bu J, Yin H, Ren N, Zhu H, Xu H, Zhang R, Zhang S. Structural and functional changes in the default mode network in drug-resistant epilepsy. Epilepsy Behav 2024; 151:109593. [PMID: 38157823 DOI: 10.1016/j.yebeh.2023.109593] [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: 08/07/2023] [Revised: 11/25/2023] [Accepted: 12/07/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE To investigate brain network properties and connectivity abnormalities of the default mode network (DMN) in drug-resistant epilepsy (DRE). The study was based on probabilistic fiber tracking and functional connectivity (FC) analysis, to explore the structural and functional connectivity patterns change between frontal lobe epilepsy (FLE) and temporal lobe epilepsy (TLE). METHODS A total of 33 DRE patients (18 TLE and 15 FLE) and 30 healthy controls (HCs) were recruited. The volume fraction of the septal brain region of the DMN in DRE was calculated using FreeSurfer. The FC analysis was performed using Data Processing and Analysis for Brain Imaging in MATLAB. The structural connections between brain regions of the DMN were calculated based on probabilistic fiber tracking. RESULTS The left precuneus (PCUN) volumes in epilepsy groups were lower than that in HCs. Compared with FLE, TLE showed reduced FC between the left hippocampus (HIP) and PCUN/medial frontal gyrus, and between the right inferior parietal lobule (IPL) and right superior temporal gyrus. Compared with HCs, FLE showed increased FCs between the right IPL and occipital lobe, and between the left superior frontal gyrus (SFG) and bilateral superior temporal gyrus. In terms of structural connectivity, TLE exhibited increased connectivity strength between the left SFG and left PCUN, and showed reduced connection strength between the left HIP and left posterior cingulate gyrus/left PCUN, when compared with the FLE. CONCLUSIONS TLE and FLE patients showed structural and functional changes in the DMN. Compared with FLE patients, the TLE patients showed reduced structural and functional connection strengths between the left HIP and PCUN. These alterations in connection strengths holds promise for the identification of TLE and FLE.
Collapse
Affiliation(s)
- Jinxin Bu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Hangxing Yin
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Nanxiao Ren
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Haitao Zhu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Honghao Xu
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China
| | - Rui Zhang
- Department of Functional Neurosurgery, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
| | - Shugang Zhang
- Department of Neurology, Affiliated Nanjing Brain Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu, China.
| |
Collapse
|
31
|
Inderyas M, Thapaliya K, Marshall-Gradisnik S, Barth M, Barnden L. Subcortical and default mode network connectivity is impaired in myalgic encephalomyelitis/chronic fatigue syndrome. Front Neurosci 2024; 17:1318094. [PMID: 38347875 PMCID: PMC10859529 DOI: 10.3389/fnins.2023.1318094] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Accepted: 12/27/2023] [Indexed: 02/15/2024] Open
Abstract
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex chronic condition with core symptoms of fatigue and cognitive dysfunction, suggesting a key role for the central nervous system in the pathophysiology of this disease. Several studies have reported altered functional connectivity (FC) related to motor and cognitive deficits in ME/CFS patients. In this study, we compared functional connectivity differences between 31 ME/CFS and 15 healthy controls (HCs) using 7 Tesla MRI. Functional scans were acquired during a cognitive Stroop color-word task, and blood oxygen level-dependent (BOLD) time series were computed for 27 regions of interest (ROIs) in the cerebellum, brainstem, and salience and default mode networks. A region-based comparison detected reduced FC between the pontine nucleus and cerebellum vermis IX (p = 0.027) for ME/CFS patients compared to HCs. Our ROI-to-voxel analysis found significant impairment of FC within the ponto-cerebellar regions in ME/CFS. Correlation analyses of connectivity with clinical scores in ME/CFS patients detected associations between FC and 'duration of illness' and 'memory scores' in salience network hubs and cerebellum vermis and between FC and 'respiratory rate' within the medulla and the default mode network FC. This novel investigation is the first to report the extensive involvement of aberrant ponto-cerebellar connections consistent with ME/CFS symptomatology. This highlights the involvement of the brainstem and the cerebellum in the pathomechanism of ME/CFS.
Collapse
Affiliation(s)
- Maira Inderyas
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD, Australia
| | - Kiran Thapaliya
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD, Australia
| | - Sonya Marshall-Gradisnik
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD, Australia
| | - Markus Barth
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD, Australia
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia
| | - Leighton Barnden
- National Centre for Neuroimmunology and Emerging Diseases, Menzies Health Institute Queensland, Griffith University, Southport, QLD, Australia
| |
Collapse
|
32
|
Sellers KK, Cohen JL, Khambhati AN, Fan JM, Lee AM, Chang EF, Krystal AD. Closed-loop neurostimulation for the treatment of psychiatric disorders. Neuropsychopharmacology 2024; 49:163-178. [PMID: 37369777 PMCID: PMC10700557 DOI: 10.1038/s41386-023-01631-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/31/2023] [Accepted: 06/02/2023] [Indexed: 06/29/2023]
Abstract
Despite increasing prevalence and huge personal and societal burden, psychiatric diseases still lack treatments which can control symptoms for a large fraction of patients. Increasing insight into the neurobiology underlying these diseases has demonstrated wide-ranging aberrant activity and functioning in multiple brain circuits and networks. Together with varied presentation and symptoms, this makes one-size-fits-all treatment a challenge. There has been a resurgence of interest in the use of neurostimulation as a treatment for psychiatric diseases. Initial studies using continuous open-loop stimulation, in which clinicians adjusted stimulation parameters during patient visits, showed promise but also mixed results. Given the periodic nature and fluctuations of symptoms often observed in psychiatric illnesses, the use of device-driven closed-loop stimulation may provide more effective therapy. The use of a biomarker, which is correlated with specific symptoms, to deliver stimulation only during symptomatic periods allows for the personalized therapy needed for such heterogeneous disorders. Here, we provide the reader with background motivating the use of closed-loop neurostimulation for the treatment of psychiatric disorders. We review foundational studies of open- and closed-loop neurostimulation for neuropsychiatric indications, focusing on deep brain stimulation, and discuss key considerations when designing and implementing closed-loop neurostimulation.
Collapse
Affiliation(s)
- Kristin K Sellers
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joshua L Cohen
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Ankit N Khambhati
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Joline M Fan
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | - A Moses Lee
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA
| | - Edward F Chang
- Department of Neurological Surgery, University of California, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Andrew D Krystal
- Weill Institute for Neurosciences, University of California, San Francisco, CA, USA.
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA.
| |
Collapse
|
33
|
Theiss P, Pucci FG, Slavin KV. Invasive Neuromodulation Techniques for Treatment-Resistant Depression. Curr Top Behav Neurosci 2024; 66:297-311. [PMID: 38082109 DOI: 10.1007/7854_2023_460] [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] [Indexed: 07/26/2024]
Abstract
Surgically implanted neurostimulation devices for the treatment of depression have been studied for the last three decades. While the surgical risk associated with these treatment approaches clearly limits their use to the most severely impacted depressed patients, they offer a unique opportunity to better understand the impact of relatively localized alteration of neural activity in patient groups. As a result, these approaches provide a strict test of the role of individual neural structures or networks in mechanistic models of depression. In this chapter, we review the proposed mechanisms of action and evidence for clinical efficacy of vagal nerve stimulation, deep brain stimulation, and epidural cortical stimulation in patients with depression. The evidence for efficacy remains limited for all three modalities, but the long-term follow-up studies of treated patients have highlighted the importance of interactions between neural regions in determining therapeutic response, and suggest that personalized approaches to stimulation are likely to be required.
Collapse
Affiliation(s)
- Peter Theiss
- Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA
| | - Francesco G Pucci
- Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA
| | - Konstantin V Slavin
- Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA.
- Neurology Section, Jesse Brown Veterans Administration Medical Center, Chicago, IL, USA.
| |
Collapse
|
34
|
Lee SW, Kim S, Lee S, Seo HS, Cha H, Chang Y, Lee SJ. Neural mechanisms of acceptance-commitment therapy for obsessive-compulsive disorder: a resting-state and task-based fMRI study. Psychol Med 2024; 54:374-384. [PMID: 37427558 DOI: 10.1017/s0033291723001769] [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] [Indexed: 07/11/2023]
Abstract
BACKGROUND There is growing evidence for the use of acceptance-commitment therapy (ACT) for the treatment of obsessive-compulsive disorder (OCD). However, few fully implemented ACT have been conducted on the neural mechanisms underlying its effect on OCD. Thus, this study aimed to elucidate the neural correlates of ACT in patients with OCD using task-based and resting-state functional magnetic resonance imaging (fMRI). METHODS Patients with OCD were randomly assigned to the ACT (n = 21) or the wait-list control group (n = 21). An 8-week group-format ACT program was provided to the ACT group. All participants underwent an fMRI scan and psychological measurements before and after 8 weeks. RESULTS Patients with OCD showed significantly increased activation in the bilateral insula and superior temporal gyri (STG), induced by the thought-action fusion task after ACT intervention. Further psycho-physiological interaction analyses with these regions as seeds revealed that the left insular-left inferior frontal gyrus (IFG) connectivity was strengthened in the ACT group after treatment. Increased resting-state functional connectivity was also found in the posterior cingulate cortex (PCC), precuneus, and lingual gyrus after ACT intervention Most of these regions showed significant correlations with ACT process measures while only the right insula was correlated with the obsessive-compulsive symptom measure. CONCLUSIONS These findings suggest that the therapeutic effect of ACT on OCD may involve the salience and interoception processes (i.e. insula), multisensory integration (i.e. STG), language (i.e. IFG), and self-referential processes (i.e. PCC and precuneus). These areas or their interactions could be important for understanding how ACT works psychologically.
Collapse
Affiliation(s)
- Sang Won Lee
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Seungho Kim
- Department of Medical & Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Sangyeol Lee
- Department of Medical & Biological Engineering, Kyungpook National University, Daegu, Korea
| | - Ho Seok Seo
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
| | - Hyunsil Cha
- Institute of Biomedical Engineering Research, Kyungpook National University, Daegu, Korea
| | - Yongmin Chang
- Department of Molecular Medicine, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Radiology, Kyungpook National University Hospital, Daegu, Korea
| | - Seung Jae Lee
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
| |
Collapse
|
35
|
Lee TW, Tramontano G, Hinrichs C. Concordant dynamic changes of global network properties in the frontoparietal and limbic compartments: An EEG study. Biosystems 2024; 235:105101. [PMID: 38101726 DOI: 10.1016/j.biosystems.2023.105101] [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: 05/05/2023] [Revised: 12/07/2023] [Accepted: 12/07/2023] [Indexed: 12/17/2023]
Abstract
INTRODUCTION Despite its complexity, deciphering nodal interaction is imperative to understanding a neural network. Network interaction is an even more complicated topic that must be addressed. This study aimed to examine the relationship between the brain waves of two canonical brain structures, i.e., the frontoparietal and limbic compartments, during a resting state. METHODS Electroencephalography (EEG) of 51 subjects in eye-closed condition was analyzed, and the eLORETA method was applied to convert the signals from the scalp to the brain. By way of community detection, representative neural nodes and the associated mean activities were retrieved. Total and lagged coherences were computed to indicate functional connectivity between those neural nodes. Two global network properties were elucidated based on the connectivity measures, i.e., global efficiency and mean functional connectivity strength. The temporal correlation of the global network indices between the two studied networks was explored. RESULTS It was found that there was a significant trend of positive correlation across the four metrics (lagged vs. total coherence x global efficiency vs. average connectivity). In other words, when the neural interaction in the FP network was stronger, so did that in the limbic network, and vice versa. Notably, the above interaction was not spectrally specific and only existed at a finer temporal scale (under hundreds of milliseconds level). CONCLUSION The concordant change in network properties indicates an intricate balance between FP and LM compartments. Possible mechanisms and implications for the findings are discussed.
Collapse
Affiliation(s)
- Tien-Wen Lee
- The NeuroCognitive Institute (NCI) Clinical Research Foundation, NJ, 07856, USA. http://neuroci.com
| | - Gerald Tramontano
- The NeuroCognitive Institute (NCI) Clinical Research Foundation, NJ, 07856, USA.
| | - Clay Hinrichs
- Hackettstown Medical Center, Atlantic Health System, NJ, 07840, USA.
| |
Collapse
|
36
|
Zheng A, Chen X, Xiang G, Li Q, Du X, Liu X, Xiao M, Chen H. Association Between Negative Affect and Perceived Mortality Threat During the COVID-19 Pandemic: The Role of Brain Activity and Connectivity. Neuroscience 2023; 535:63-74. [PMID: 37913860 DOI: 10.1016/j.neuroscience.2023.10.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Revised: 10/21/2023] [Accepted: 10/24/2023] [Indexed: 11/03/2023]
Abstract
The prevalence of the novel coronavirus (COVID-19) has been considered a major threat to physical and mental health around the world, causing great pressure and mortality threat to most people. The current study aimed to investigate the neurological markers underlying the relationship between perceived mortality threat (PMT) and negative affect (NA). We examined whether the regional amplitude of low-frequency fluctuations (ALFF) and resting-state functional connectivity (RSFC) before the COVID-19 outbreak (October 2019 to December 2019, wave 1) were predictive for NA and PMT during the mid-term of the COVID-19 pandemic (February 22 to 28, 2020, wave 2) among 603 young adults (age range 17-22, 70.8% females). Results indicated that PMT was associated with spontaneous activity in several regions (e.g., inferior temporal gyrus, medial occipital gyrus, medial frontal gyrus, angular gyrus, and cerebellum) and their RSFC with the distributed regions of the default mode network and cognitive control network. Furthermore, longitudinal mediation models showed that ALFF in the cerebellum, medial occipital gyrus, medial frontal gyrus, and angular gyrus (wave 1) predicted PMT (wave 2) through NA (wave 2). These findings revealed functional neural markers of PMT and suggest candidate mechanisms for explaining the complex relationship between NA and mental/neural processing related to PMT in the circumstance of a major crisis.
Collapse
Affiliation(s)
- Anqi Zheng
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing 400715, China.
| | - Ximei Chen
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing 400715, China.
| | - Guangcan Xiang
- Tian Jiabing College of Education, China Three Gorges University, Yichang 443002, China.
| | - Qingqing Li
- School of Psychology, Central China Normal University, China.
| | - Xiaoli Du
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing 400715, China.
| | - Xinyuan Liu
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing 400715, China.
| | - Mingyue Xiao
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing 400715, China.
| | - Hong Chen
- Faculty of Psychology, Southwest University, Chongqing 400715, China; Key Laboratory of Cognition and Personality (Southwest University), Ministry of Education, Chongqing 400715, China; Research Center of Psychology and Social Development, Chongqing 400715, China.
| |
Collapse
|
37
|
Gerin MI, Viding E, Herringa RJ, Russell JD, McCrory EJ. A systematic review of childhood maltreatment and resting state functional connectivity. Dev Cogn Neurosci 2023; 64:101322. [PMID: 37952287 PMCID: PMC10665826 DOI: 10.1016/j.dcn.2023.101322] [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: 07/10/2023] [Revised: 10/13/2023] [Accepted: 11/08/2023] [Indexed: 11/14/2023] Open
Abstract
Resting-state functional connectivity (rsFC) has the potential to shed light on how childhood abuse and neglect relates to negative psychiatric outcomes. However, a comprehensive review of the impact of childhood maltreatment on the brain's resting state functional organization has not yet been undertaken. We systematically searched rsFC studies in children and youth exposed to maltreatment. Nineteen studies (total n = 3079) met our inclusion criteria. Two consistent findings were observed. Childhood maltreatment was linked to reduced connectivity between the anterior insula and dorsal anterior cingulate cortex, and with widespread heightened amygdala connectivity with key structures in the salience, default mode, and prefrontal regulatory networks. Other brain regions showing altered connectivity included the ventral anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus. These patterns of altered functional connectivity associated with maltreatment exposure were independent of symptoms, yet comparable to those seen in individuals with overt clinical disorder. Summative findings indicate that rsFC alterations associated with maltreatment experience are related to poor cognitive and social functioning and are prognostic of future symptoms. In conclusion, maltreatment is associated with altered rsFC in emotional reactivity, regulation, learning, and salience detection brain circuits. This indicates patterns of recalibration of putative mechanisms implicated in maladaptive developmental outcomes.
Collapse
Affiliation(s)
- Mattia I Gerin
- Division of Psychology and Language Sciences, University College London, London, UK; Anna Freud National Centre for Children and Families, London, UK.
| | - Essi Viding
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Ryan J Herringa
- Department of Psychiatry, University of Wisconsin School of Medicine & Public Health, Madison, WI, UK
| | - Justin D Russell
- Department of Psychiatry, University of Wisconsin School of Medicine & Public Health, Madison, WI, UK
| | - Eamon J McCrory
- Division of Psychology and Language Sciences, University College London, London, UK; Anna Freud National Centre for Children and Families, London, UK
| |
Collapse
|
38
|
Ma X, Zhou W, Zheng H, Ye S, Yang B, Wang L, Wang M, Dong GH. Connectome-based prediction of the severity of autism spectrum disorder. PSYCHORADIOLOGY 2023; 3:kkad027. [PMID: 38666105 PMCID: PMC10917386 DOI: 10.1093/psyrad/kkad027] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 11/14/2023] [Accepted: 11/23/2023] [Indexed: 04/28/2024]
Abstract
Background Autism spectrum disorder (ASD) is characterized by social and behavioural deficits. Current diagnosis relies on behavioural criteria, but machine learning, particularly connectome-based predictive modelling (CPM), offers the potential to uncover neural biomarkers for ASD. Objective This study aims to predict the severity of ASD traits using CPM and explores differences among ASD subtypes, seeking to enhance diagnosis and understanding of ASD. Methods Resting-state functional magnetic resonance imaging data from 151 ASD patients were used in the model. CPM with leave-one-out cross-validation was conducted to identify intrinsic neural networks that predict Autism Diagnostic Observation Schedule (ADOS) scores. After the model was constructed, it was applied to independent samples to test its replicability (172 ASD patients) and specificity (36 healthy control participants). Furthermore, we examined the predictive model across different aspects of ASD and in subtypes of ASD to understand the potential mechanisms underlying the results. Results The CPM successfully identified negative networks that significantly predicted ADOS total scores [r (df = 150) = 0.19, P = 0.008 in all patients; r (df = 104) = 0.20, P = 0.040 in classic autism] and communication scores [r (df = 150) = 0.22, P = 0.010 in all patients; r (df = 104) = 0.21, P = 0.020 in classic autism]. These results were reproducible across independent databases. The networks were characterized by enhanced inter- and intranetwork connectivity associated with the occipital network (OCC), and the sensorimotor network (SMN) also played important roles. Conclusions A CPM based on whole-brain resting-state functional connectivity can predicted the severity of ASD. Large-scale networks, including the OCC and SMN, played important roles in the predictive model. These findings may provide new directions for the diagnosis and intervention of ASD, and maybe could be the targets in novel interventions.
Collapse
Affiliation(s)
- Xuefeng Ma
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province 650500, China
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Weiran Zhou
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Hui Zheng
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiaotong University School of Medicine, Shanghai 200030, China
| | - Shuer Ye
- Kavli Institute for Systems Neuroscience, Centre for Neural Computation, Norwegian University of Science and Technology, Trondheim 7491, Norway
| | - Bo Yang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Institutes of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Lingxiao Wang
- Center for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
- Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou Normal University, Hangzhou, Zhejiang Province 311121, China
| | - Min Wang
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province 650500, China
| | - Guang-Heng Dong
- Department of Psychology, Yunnan Normal University, Kunming, Yunnan Province 650500, China
| |
Collapse
|
39
|
Feng Q, Wang L, Tang X, Hu H, Ge X, Liao Z, Ding Z. Static and dynamic functional connectivity combined with the triple network model in amnestic mild cognitive impairment and Alzheimer's disease. Front Neurol 2023; 14:1284227. [PMID: 38107647 PMCID: PMC10723161 DOI: 10.3389/fneur.2023.1284227] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Accepted: 10/31/2023] [Indexed: 12/19/2023] Open
Abstract
Background Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI) are characterized by abnormal functional connectivity (FC) of default-mode network (DMN), salience network (SN), and central executive network (CEN). Static FC (sFC) and dynamic FC (dFC) combined with triple network model can better study the dynamic and static changes of brain networks, and improve its potential diagnostic value in the diagnosis of AD spectrum disorders. Methods Differences in sFC values and dFC variability patterns among the three brain networks of the three groups (53 AD patients, 40 aMCI patients, and 40 NCs) were computed by ANOVA using Gaussian Random Field theory (GRF) correction. The correlation between FC values (sFC values and dFC variability) in the three networks and cognitive scores (MMSE and MoCA) in AD and aMCI groups was analyzed separately. Results Within the DMN network, there were significant differences of sFC values in right/left medial superior frontal gyrus and dFC variability in left opercular part inferior frontal gyrus and right dorsolateral superior frontal gyrus among the three groups. Within the CEN network, there were significant differences of sFC values in left superior parietal gyrus. Within the SN network, there were significant differences of dFC variability in right Cerebelum_7b and left opercular part inferior frontal gyrus. In addition, there was a significant negative correlation between FC values (sFC values of CEN and dFC variability of SN) and MMSE and MoCA scores. Conclusion It suggests that sFC, dFC combined with triple network model can be considered as potential biomarkers for AD and aMCI.
Collapse
Affiliation(s)
- Qi Feng
- Department of Radiology, Hangzhou First People's Hospital, Hangzhou, China
| | - Luoyu Wang
- Department of Radiology, Hangzhou First People's Hospital, Hangzhou, China
| | - Xue Tang
- School of Medical Imaging, Hangzhou Medical College, Hangzhou, China
| | - Hanjun Hu
- Fourth Clinical School, Zhejiang Chinese Medical University, Hangzhou, China
| | - Xiuhong Ge
- Department of Radiology, Hangzhou First People's Hospital, Hangzhou, China
| | - Zhengluan Liao
- Department of Psychiatry, Zhejiang Provincial People's Hospital/People's Hospital of Hangzhou Medical College, Hangzhou, China
| | - Zhongxiang Ding
- Department of Radiology, Hangzhou First People's Hospital, Hangzhou, China
| |
Collapse
|
40
|
Si Y, He R, Jiang L, Yao D, Zhang H, Xu P, Ma X, Yu L, Li F. Differentiating Between Alzheimer's Disease and Frontotemporal Dementia Based on the Resting-State Multilayer EEG Network. IEEE Trans Neural Syst Rehabil Eng 2023; 31:4521-4527. [PMID: 37922187 DOI: 10.1109/tnsre.2023.3329174] [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: 11/05/2023]
Abstract
Frontotemporal dementia (FTD) is frequently misdiagnosed as Alzheimer's disease (AD) due to similar clinical symptoms. In this study, we constructed frequency-based multilayer resting-state electroencephalogram (EEG) networks and extracted representative network features to improve the differentiation between AD and FTD. When compared with healthy controls (HC), AD showed primarily stronger delta-alpha cross-couplings and weaker theta-sigma cross-couplings. Notably, when comparing the AD and FTD groups, we found that the AD exhibited stronger delta-alpha and delta-beta connectivity than the FTD. Thereafter, by extracting the representative network features and then applying these features in the classification between AD and FTD, an accuracy of 81.1% was achieved. Finally, a multivariable linear regressive model was built, based on the differential topologies, and then adopted to predict the scores of the Mini-Mental State Examination (MMSE) scale. Accordingly, the predicted and actual measured scores were indeed significantly correlated with each other ( r = 0.274, p = 0.036). These findings consistently suggest that frequency-based multilayer resting-state networks can be utilized for classifying AD and FTD and have potential applications for clinical diagnosis.
Collapse
|
41
|
Franzova E, Shen Q, Doyle K, Chen JM, Egbebike J, Vrosgou A, Carmona JC, Grobois L, Heinonen GA, Velazquez A, Gonzales IJ, Egawa S, Agarwal S, Roh D, Park S, Connolly ES, Claassen J. Injury patterns associated with cognitive motor dissociation. Brain 2023; 146:4645-4658. [PMID: 37574216 PMCID: PMC10629765 DOI: 10.1093/brain/awad197] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 04/14/2023] [Accepted: 05/28/2023] [Indexed: 08/15/2023] Open
Abstract
In unconscious appearing patients with acute brain injury, wilful brain activation to motor commands without behavioural signs of command following, known as cognitive motor dissociation (CMD), is associated with functional recovery. CMD can be detected by applying machine learning to EEG recorded during motor command presentation in behaviourally unresponsive patients. Identifying patients with CMD carries clinical implications for patient interactions, communication with families, and guidance of therapeutic decisions but underlying mechanisms of CMD remain unknown. By analysing structural lesion patterns and network level dysfunction we tested the hypothesis that, in cases with preserved arousal and command comprehension, a failure to integrate comprehended motor commands with motor outputs underlies CMD. Manual segmentation of T2-fluid attenuated inversion recovery and diffusion weighted imaging sequences quantifying structural injury was performed in consecutive unresponsive patients with acute brain injury (n = 107) who underwent EEG-based CMD assessments and MRI. Lesion pattern analysis was applied to identify lesion patterns common among patients with (n = 21) and without CMD (n = 86). Thalamocortical and cortico-cortical network connectivity were assessed applying ABCD classification of power spectral density plots and weighted pairwise phase consistency (WPPC) to resting EEG, respectively. Two distinct structural lesion patterns were identified on MRI for CMD and three for non-CMD patients. In non-CMD patients, injury to brainstem arousal pathways including the midbrain were seen, while no CMD patients had midbrain lesions. A group of non-CMD patients was identified with injury to the left thalamus, implicating possible language comprehension difficulties. Shared lesion patterns of globus pallidus and putamen were seen for a group of CMD patients, which have been implicated as part of the anterior forebrain mesocircuit in patients with reversible disorders of consciousness. Thalamocortical network dysfunction was less common in CMD patients [ABCD-index 2.3 (interquartile range, IQR 2.1-3.0) versus 1.4 (IQR 1.0-2.0), P < 0.0001; presence of D 36% versus 3%, P = 0.0006], but WPPC was not different. Bilateral cortical lesions were seen in patients with and without CMD. Thalamocortical disruption did not differ for those with CMD, but long-range WPPC was decreased in 1-4 Hz [odds ratio (OR) 0.8; 95% confidence interval (CI) 0.7-0.9] and increased in 14-30 Hz frequency ranges (OR 1.2; 95% CI 1.0-1.5). These structural and functional data implicate a failure of motor command integration at the anterior forebrain mesocircuit level with preserved thalamocortical network function for CMD patients with subcortical lesions. Amongst patients with bilateral cortical lesions preserved cortico-cortical network function is associated with CMD detection. These data may allow screening for CMD based on widely available structural MRI and resting EEG.
Collapse
Affiliation(s)
- Eva Franzova
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Qi Shen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Kevin Doyle
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Justine M Chen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jennifer Egbebike
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Athina Vrosgou
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jerina C Carmona
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Lauren Grobois
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Gregory A Heinonen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Angela Velazquez
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | | | - Satoshi Egawa
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Sachin Agarwal
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - David Roh
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Soojin Park
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - E Sander Connolly
- Department of Neurological Surgery, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| | - Jan Claassen
- Department of Neurology, Columbia University Medical Center, NewYork-Presbyterian Hospital, New York, NY, USA
| |
Collapse
|
42
|
Ma M, Li Y, Shao Y, Weng X. Effect of total sleep deprivation on effective EEG connectivity for young male in resting-state networks in different eye states. Front Neurosci 2023; 17:1204457. [PMID: 37928738 PMCID: PMC10620317 DOI: 10.3389/fnins.2023.1204457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Background Many studies have investigated the effect of total sleep deprivation (TSD) on resting-state functional networks, especially the default mode network (DMN) and sensorimotor network (SMN), using functional connectivity. While it is known that the activities of these networks differ based on eye state, it remains unclear how TSD affects them in different eye states. Therefore, we aimed to examine the effect of TSD on DMN and SMN in different eye states using effective functional connectivity via isolated effective coherence (iCoh) in exact low-resolution brain electromagnetic tomography (eLORETA). Methods Resting-state electroencephalogram (EEG) signals were collected from 24 male college students, and each participant completed a psychomotor vigilance task (PVT) while behavioral data were acquired. Each participant underwent 36-h TSD, and the data were acquired in two sleep-deprivation times (rested wakefulness, RW: 0 h; and TSD: 36 h) and two eye states (eyes closed, EC; and eyes open, EO). Changes in neural oscillations and effective connectivity were compared based on paired t-test. Results The behavioral results showed that PVT reaction time was significantly longer in TSD compared with that of RW. The EEG results showed that in the EO state, the activity of high-frequency bands in the DMN and SMN were enhanced compared to those of the EC state. Furthermore, when compared with the DMN and SMN of RW, in TSD, the activity of DMN was decreased, and SMN was increased. Moreover, the changed effective connectivity in the DMN and SMN after TSD was positively correlated with an increased PVT reaction time. In addition, the effective connectivity in the different network (EO-EC) of the SMN was reduced in the β band after TSD compared with that of RW. Conclusion These findings indicate that TSD impairs alertness and sensory information input in the SMN to a greater extent in an EO than in an EC state.
Collapse
Affiliation(s)
- Mengke Ma
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yutong Li
- School of Psychology, Beijing Sport University, Beijing, China
| | - Yongcong Shao
- School of Psychology, Beijing Sport University, Beijing, China
- Key Laboratory for Biomechanics and Mechanobiology of the Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, China
| | - Xiechuan Weng
- Department of Neuroscience, Beijing Institute of Basic Medical Sciences, Beijing, China
| |
Collapse
|
43
|
Kurtin DL, Araña‐Oiarbide G, Lorenz R, Violante IR, Hampshire A. Planning ahead: Predictable switching recruits task-active and resting-state networks. Hum Brain Mapp 2023; 44:5030-5046. [PMID: 37471699 PMCID: PMC10502652 DOI: 10.1002/hbm.26430] [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: 01/29/2023] [Revised: 06/08/2023] [Accepted: 07/05/2023] [Indexed: 07/22/2023] Open
Abstract
Switching is a difficult cognitive process characterised by costs in task performance; specifically, slowed responses and reduced accuracy. It is associated with the recruitment of a large coalition of task-positive regions including those referred to as the multiple demand cortex (MDC). The neural correlates of switching not only include the MDC, but occasionally the default mode network (DMN), a characteristically task-negative network. To unpick the role of the DMN during switching we collected fMRI data from 24 participants playing a switching paradigm that perturbed predictability (i.e., cognitive load) across three switch dimensions-sequential, perceptual, and spatial predictability. We computed the activity maps unique to switch vs. stay trials and all switch dimensions, then evaluated functional connectivity under these switch conditions by computing the pairwise mutual information functional connectivity (miFC) between regional timeseries. Switch trials exhibited an expected cost in reaction time while sequential predictability produced a significant benefit to task accuracy. Our results showed that switch trials recruited a broader activity map than stay trials, including regions of the DMN, the MDC, and task-positive networks such as visual, somatomotor, dorsal, salience/ventral attention networks. More sequentially predictable trials recruited increased activity in the somatomotor and salience/ventral attention networks. Notably, changes in sequential and perceptual predictability, but not spatial predictability, had significant effects on miFC. Increases in perceptual predictability related to decreased miFC between control, visual, somatomotor, and DMN regions, whereas increases in sequential predictability increased miFC between regions in the same networks, as well as regions within ventral attention/ salience, dorsal attention, limbic, and temporal parietal networks. These results provide novel clues as to how DMN may contribute to executive task performance. Specifically, the improved task performance, unique activity, and increased miFC associated with increased sequential predictability suggest that the DMN may coordinate more strongly with the MDC to generate a temporal schema of upcoming task events, which may attenuate switching costs.
Collapse
Affiliation(s)
- Danielle L. Kurtin
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK
- Department of Brain Sciences, Faculty of MedicineImperial College LondonLondonUK
| | | | - Romy Lorenz
- MRC Cognition and Brain Sciences UnitUniversity of CambridgeCambridgeUK
- The Poldrack LabStanford UniversityStanfordCaliforniaUSA
- Department of NeurophysicsMax‐Planck Institute for Human Cognitive and Brain SciencesLeipzigGermany
| | - Ines R. Violante
- NeuroModulation Lab, Department of Psychology, Faculty of Health and Medical SciencesUniversity of SurreyGuildfordUK
| | - Adam Hampshire
- Department of Brain Sciences, Faculty of MedicineImperial College LondonLondonUK
| |
Collapse
|
44
|
Rodríguez-González V, Núñez P, Gómez C, Shigihara Y, Hoshi H, Tola-Arribas MÁ, Cano M, Guerrero Á, García-Azorín D, Hornero R, Poza J. Connectivity-based Meta-Bands: A new approach for automatic frequency band identification in connectivity analyses. Neuroimage 2023; 280:120332. [PMID: 37619796 DOI: 10.1016/j.neuroimage.2023.120332] [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: 04/02/2023] [Revised: 07/05/2023] [Accepted: 08/14/2023] [Indexed: 08/26/2023] Open
Abstract
The majority of electroencephalographic (EEG) and magnetoencephalographic (MEG) studies filter and analyse neural signals in specific frequency ranges, known as "canonical" frequency bands. However, this segmentation, is not exempt from limitations, mainly due to the lack of adaptation to the neural idiosyncrasies of each individual. In this study, we introduce a new data-driven method to automatically identify frequency ranges based on the topological similarity of the frequency-dependent functional neural network. The resting-state neural activity of 195 cognitively healthy subjects from three different databases (MEG: 123 subjects; EEG1: 27 subjects; EEG2: 45 subjects) was analysed. In a first step, MEG and EEG signals were filtered with a narrow-band filter bank (1 Hz bandwidth) from 1 to 70 Hz with a 0.5 Hz step. Next, the connectivity in each of these filtered signals was estimated using the orthogonalized version of the amplitude envelope correlation to obtain the frequency-dependent functional neural network. Finally, a community detection algorithm was used to identify communities in the frequency domain showing a similar network topology. We have called this approach the "Connectivity-based Meta-Bands" (CMB) algorithm. Additionally, two types of synthetic signals were used to configure the hyper-parameters of the CMB algorithm. We observed that the classical approaches to band segmentation are partially aligned with the underlying network topologies at group level for the MEG signals, but they are missing individual idiosyncrasies that may be biasing previous studies, as revealed by our methodology. On the other hand, the sensitivity of EEG signals to reflect this underlying frequency-dependent network structure is limited, revealing a simpler frequency parcellation, not aligned with that defined by the "canonical" frequency bands. To the best of our knowledge, this is the first study that proposes an unsupervised band segmentation method based on the topological similarity of functional neural network across frequencies. This methodology fully accounts for subject-specific patterns, providing more robust and personalized analyses, and paving the way for new studies focused on exploring the frequency-dependent structure of brain connectivity.
Collapse
Affiliation(s)
- Víctor Rodríguez-González
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain.
| | - Pablo Núñez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; Coma Science Group, GIGA-Consciousness, University of Liège, Liège, Belgium
| | - Carlos Gómez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain
| | | | | | - Miguel Ángel Tola-Arribas
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; Servicio de Neurología. Hospital Universitario Río Hortega, Valladolid, Spain
| | - Mónica Cano
- Servicio de Neurología. Hospital Universitario Río Hortega, Valladolid, Spain
| | - Ángel Guerrero
- Hospital Clínico Universitario, Valladolid, Spain; Department of Medicine, University of Valladolid, Spain
| | | | - Roberto Hornero
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain; Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina, Instituto de Salud Carlos III (CIBER-BBN), Spain; IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Spain
| |
Collapse
|
45
|
Bandyopadhyay A, Ghosh S, Biswas D, Chakravarthy VS, S Bapi R. A phenomenological model of whole brain dynamics using a network of neural oscillators with power-coupling. Sci Rep 2023; 13:16935. [PMID: 37805660 PMCID: PMC10560247 DOI: 10.1038/s41598-023-43547-3] [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: 07/02/2023] [Accepted: 09/25/2023] [Indexed: 10/09/2023] Open
Abstract
We present a general, trainable oscillatory neural network as a large-scale model of brain dynamics. The model has a cascade of two stages - an oscillatory stage and a complex-valued feedforward stage - for modelling the relationship between structural connectivity and functional connectivity from neuroimaging data under resting brain conditions. Earlier works of large-scale brain dynamics that used Hopf oscillators used linear coupling of oscillators. A distinctive feature of the proposed model employs a novel form of coupling known as power coupling. Oscillatory networks based on power coupling can accurately model arbitrary multi-dimensional signals. Training the lateral connections in the oscillator layer is done by a modified form of Hebbian learning, whereas a variation of the complex backpropagation algorithm does training in the second stage. The proposed model can not only model the empirical functional connectivity with remarkable accuracy (correlation coefficient between simulated and empirical functional connectivity- 0.99) but also identify default mode network regions. In addition, we also inspected how structural loss in the brain can cause significant aberration in simulated functional connectivity and functional connectivity dynamics; and how it can be restored with optimized model parameters by an in silico perturbational study.
Collapse
Affiliation(s)
| | - Sayan Ghosh
- Indian Institue of Technology Madras, Biotechnology, Chennai, 600036, India
| | - Dipayan Biswas
- Indian Institue of Technology Madras, Biotechnology, Chennai, 600036, India
| | | | - Raju S Bapi
- IIIT Hyderabad, Biotechnology, Hyderabad, 500008, India
| |
Collapse
|
46
|
Fateh AA, Huang W, Hassan M, Zhuang Y, Lin J, Luo Y, Yang B, Zeng H. Default mode network connectivity and social dysfunction in children with Attention Deficit/Hyperactivity Disorder. Int J Clin Health Psychol 2023; 23:100393. [PMID: 37829190 PMCID: PMC10564936 DOI: 10.1016/j.ijchp.2023.100393] [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: 03/28/2023] [Accepted: 06/23/2023] [Indexed: 10/14/2023] Open
Abstract
Objective Attention Deficit/Hyperactivity Disorder (ADHD) negatively affects social functioning; however, its neurological underpinnings remain unclear. Altered Default Mode Network (DMN) connectivity may contribute to social dysfunction in ADHD. We investigated whether DMN's dynamic functional connectivity (dFC) alterations were associated with social dysfunction in individuals with ADHD. Methods Resting-state fMRI was used to examine DMN subsystems (dorsal medial prefrontal cortex (dMPFC), medial temporal lobe (MTL)) and the midline core in 40 male ADHD patients (7-10 years) and 45 healthy controls (HCs). Connectivity correlations with symptoms and demographic data were assessed. Group-based analyses compared rsFC between groups with two-sample t-tests and post-hoc analyses. Results Social dysfunction in ADHD patients was related to reduced DMN connectivity, specifically in the MTL subsystem and the midline core. ADHD patients showed decreased dFC between parahippocampal cortex (PHC) and left superior frontal gyrus, and between ventral medial prefrontal cortex (vMPFC) and right middle frontal gyrus compared to HCs (MTL subsystem). Additionally, decreased dFC between posterior cingulate cortex (PCC), anterior medial prefrontal cortex (aMPFC), and right angular gyrus (midline core) was observed in ADHD patients relative to HCs. No abnormal connectivity was found within the dMPFC. Conclusion Preliminary findings suggest that DMN connectional abnormalities may contribute to social dysfunction in ADHD, providing insights into the disorder's neurobiology and pathophysiology.
Collapse
Affiliation(s)
- Ahmed Ameen Fateh
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Wenxian Huang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Muhammad Hassan
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Yijiang Zhuang
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Jieqiong Lin
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Yi Luo
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Binrang Yang
- Children's Healthcare and Mental Health Center, Shenzhen Children's Hospital, Shenzhen 518038, China
| | - Hongwu Zeng
- Department of Radiology, Shenzhen Children's Hospital, Shenzhen 518038, China
| |
Collapse
|
47
|
da Silveira RV, Li LM, Castellano G. Texture-based brain networks for characterization of healthy subjects from MRI. Sci Rep 2023; 13:16421. [PMID: 37775531 PMCID: PMC10541866 DOI: 10.1038/s41598-023-43544-6] [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: 04/12/2023] [Accepted: 09/25/2023] [Indexed: 10/01/2023] Open
Abstract
Brain networks have been widely used to study the relationships between brain regions based on their dynamics using, e.g. fMRI or EEG, and to characterize their real physical connections using DTI. However, few studies have investigated brain networks derived from structural properties; and those have been based on cortical thickness or gray matter volume. The main objective of this work was to investigate the feasibility of obtaining useful information from brain networks derived from structural MRI, using texture features. We also wanted to verify if texture brain networks had any relation with established functional networks. T1-MR images were segmented using AAL and texture parameters from the gray-level co-occurrence matrix were computed for each region, for 760 subjects. Individual texture networks were used to evaluate the structural connections between regions of well-established functional networks; assess possible gender differences; investigate the dependence of texture network measures with age; and single out brain regions with different texture-network characteristics. Although around 70% of texture connections between regions belonging to the default mode, attention, and visual network were greater than the mean connection value, this effect was small (only between 7 and 15% of these connections were larger than one standard deviation), implying that texture-based morphology does not seem to subside function. This differs from cortical thickness-based morphology, which has been shown to relate to functional networks. Seventy-five out of 86 evaluated regions showed significant (ANCOVA, p < 0.05) differences between genders. Forty-four out of 86 regions showed significant (ANCOVA, p < 0.05) dependence with age; however, the R2 indicates that this is not a linear relation. Thalamus and putamen showed a very unique texture-wise structure compared to other analyzed regions. Texture networks were able to provide useful information regarding gender and age-related differences, as well as for singling out specific brain regions. We did not find a morphological texture-based subsidy for the evaluated functional brain networks. In the future, this approach will be extended to neurological patients to investigate the possibility of extracting biomarkers to help monitor disease evolution or treatment effectiveness.
Collapse
Affiliation(s)
- Rafael Vinícius da Silveira
- Department of Cosmic Rays and Chronology, Gleb Wataghin Physics Institute, University of Campinas - UNICAMP, R. Sérgio Buarque de Holanda, 777, Cidade Universitária Zeferino Vaz, Campinas, SP, 13083-859, Brazil.
- Brazilian Institute of Neuroscience and Neurotechnology - BRAINN, Campinas, SP, 13083-887, Brazil.
| | - Li Min Li
- Department of Neurology, School of Medical Sciences, University of Campinas - UNICAMP, R. Tessália Vieira de Camargo, 126, Cidade Universitária Zeferino Vaz, Campinas, SP, 13083-887, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology - BRAINN, Campinas, SP, 13083-887, Brazil
| | - Gabriela Castellano
- Department of Cosmic Rays and Chronology, Gleb Wataghin Physics Institute, University of Campinas - UNICAMP, R. Sérgio Buarque de Holanda, 777, Cidade Universitária Zeferino Vaz, Campinas, SP, 13083-859, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology - BRAINN, Campinas, SP, 13083-887, Brazil
| |
Collapse
|
48
|
Nunes JD, Vourvopoulos A, Blanco-Mora DA, Jorge C, Fernandes JC, Bermudez i Badia S, Figueiredo P. Brain activation by a VR-based motor imagery and observation task: An fMRI study. PLoS One 2023; 18:e0291528. [PMID: 37756271 PMCID: PMC10529559 DOI: 10.1371/journal.pone.0291528] [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: 01/02/2023] [Accepted: 08/07/2023] [Indexed: 09/29/2023] Open
Abstract
Training motor imagery (MI) and motor observation (MO) tasks is being intensively exploited to promote brain plasticity in the context of post-stroke rehabilitation strategies. This may benefit from the use of closed-loop neurofeedback, embedded in brain-computer interfaces (BCI's) to provide an alternative non-muscular channel, which may be further augmented through embodied feedback delivered through virtual reality (VR). Here, we used functional magnetic resonance imaging (fMRI) in a group of healthy adults to map brain activation elicited by an ecologically-valid task based on a VR-BCI paradigm called NeuRow, whereby participants perform MI of rowing with the left or right arm (i.e., MI), while observing the corresponding movement of the virtual arm of an avatar (i.e., MO), on the same side, in a first-person perspective. We found that this MI-MO task elicited stronger brain activation when compared with a conventional MI-only task based on the Graz BCI paradigm, as well as to an overt motor execution task. It recruited large portions of the parietal and occipital cortices in addition to the somatomotor and premotor cortices, including the mirror neuron system (MNS), associated with action observation, as well as visual areas related with visual attention and motion processing. Overall, our findings suggest that the virtual representation of the arms in an ecologically-valid MI-MO task engage the brain beyond conventional MI tasks, which we propose could be explored for more effective neurorehabilitation protocols.
Collapse
Affiliation(s)
- João D. Nunes
- INESC TEC - Institute for Systems and Computer Engineering, Technology and Science, and Faculty of Engineering, University of Porto, Porto, Portugal
| | - Athanasios Vourvopoulos
- Institute for Systems and Robotics - Lisboa, and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Diego Andrés Blanco-Mora
- Faculdade de Ciências Exatas e da Engenharia, N-LINCS Madeira — ARDITI, Universidade da Madeira, Funchal, Portugal
| | - Carolina Jorge
- Faculdade de Ciências Exatas e da Engenharia, N-LINCS Madeira — ARDITI, Universidade da Madeira, Funchal, Portugal
| | - Jean-Claude Fernandes
- Central Hospital of Funchal, Physical Medicine and Rehabilitation Service, Funchal, Portugal
| | - Sergi Bermudez i Badia
- Faculdade de Ciências Exatas e da Engenharia, N-LINCS Madeira — ARDITI, Universidade da Madeira, Funchal, Portugal
| | - Patrícia Figueiredo
- Institute for Systems and Robotics - Lisboa, and Department of Bioengineering, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| |
Collapse
|
49
|
Chu SA, Tadayonnejad R, Corlier J, Wilson AC, Citrenbaum C, Leuchter AF. Rumination symptoms in treatment-resistant major depressive disorder, and outcomes of repetitive Transcranial Magnetic Stimulation (rTMS) treatment. Transl Psychiatry 2023; 13:293. [PMID: 37684229 PMCID: PMC10491586 DOI: 10.1038/s41398-023-02566-4] [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: 12/12/2022] [Revised: 07/18/2023] [Accepted: 07/20/2023] [Indexed: 09/10/2023] Open
Abstract
Rumination is a maladaptive style of regulating thoughts and emotions. It is a common symptom of Major Depressive Disorder (MDD), and more severe rumination is associated with poorer medication and psychotherapy treatment outcomes, particularly among women. It is unclear to what extent rumination may influence the outcomes of, or be responsive to, repetitive Transcranial Magnetic Stimulation (rTMS) treatment of MDD. We retrospectively examined data collected during rTMS treatment of 155 patients (age 42.52 ± 14.22, 79 female) with moderately severe treatment-resistant MDD. The severity of rumination and depression was assessed before and during a course of 30 sessions of measurement-based rTMS treatment using the Ruminative Responses Scale (RSS) and the Patient Health Questionnaire (PHQ-9), respectively. Relationships among baseline levels of rumination, depression, and treatment outcome were assessed using a series of repeated measures linear mixed effects models. Both depression and rumination symptoms significantly improved after treatment, but improvement in depression was not a significant mediator of rumination improvement. Higher baseline rumination (but not depression severity) was associated with poorer depression outcomes independently of depression severity. Female gender was a significant predictor of worse outcomes for all RRS subscales. Both depressive and ruminative symptoms in MDD improved following rTMS treatment. These improvements were correlated, but improvement in rumination was not fully explained by reduction in depressive symptoms. These findings suggest that while improvement in rumination and depression severity during rTMS treatment are correlated, they are partly independent processes. Future studies should examine whether rumination symptoms should be specifically targeted with different rTMS treatment parameters.
Collapse
Affiliation(s)
- Stephanie A Chu
- Neuroscience Interdepartmental Program, UCLA, Los Angeles, USA.
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA.
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
| | - Reza Tadayonnejad
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
- Division of the Humanities and Social Sciences, California Institute of Technology, Pasadena, CA, USA
| | - Juliana Corlier
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Andrew C Wilson
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Cole Citrenbaum
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| | - Andrew F Leuchter
- TMS Clinical and Research Service, Neuromodulation Division, Semel Institute for Neuroscience and Human Behavior at UCLA, Los Angeles, CA, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA
| |
Collapse
|
50
|
Chaudhari A, Wang X, Wu A, Liu H. Repeated Transcranial Photobiomodulation with Light-Emitting Diodes Improves Psychomotor Vigilance and EEG Networks of the Human Brain. Bioengineering (Basel) 2023; 10:1043. [PMID: 37760145 PMCID: PMC10525861 DOI: 10.3390/bioengineering10091043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 08/16/2023] [Accepted: 08/29/2023] [Indexed: 09/29/2023] Open
Abstract
Transcranial photobiomodulation (tPBM) has been suggested as a non-invasive neuromodulation tool. The repetitive administration of light-emitting diode (LED)-based tPBM for several weeks significantly improves human cognition. To understand the electrophysiological effects of LED-tPBM on the human brain, we investigated alterations by repeated tPBM in vigilance performance and brain networks using electroencephalography (EEG) in healthy participants. Active and sham LED-based tPBM were administered to the right forehead of young participants twice a week for four weeks. The participants performed a psychomotor vigilance task (PVT) during each tPBM/sham experiment. A 64-electrode EEG system recorded electrophysiological signals from each participant during the first and last visits in a 4-week study. Topographical maps of the EEG power enhanced by tPBM were statistically compared for the repeated tPBM effect. A new data processing framework combining the group's singular value decomposition (gSVD) with eLORETA was implemented to identify EEG brain networks. The reaction time of the PVT in the tPBM-treated group was significantly improved over four weeks compared to that in the sham group. We observed acute increases in EEG delta and alpha powers during a 10 min LED-tPBM while the participants performed the PVT task. We also found that the theta, beta, and gamma EEG powers significantly increased overall after four weeks of LED-tPBM. Combining gSVD with eLORETA enabled us to identify EEG brain networks and the corresponding network power changes by repeated 4-week tPBM. This study clearly demonstrated that a 4-week prefrontal LED-tPBM can neuromodulate several key EEG networks, implying a possible causal effect between modulated brain networks and improved psychomotor vigilance outcomes.
Collapse
Affiliation(s)
| | | | | | - Hanli Liu
- Department of Bioengineering, University of Texas at Arlington, 500 UTA Blvd, Arlington, TX 76019, USA; (A.C.); (X.W.); (A.W.)
| |
Collapse
|