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Huang BK, Zhou JH, Deng Y, Li CH, Ning BL, Ye ZY, Huang XC, Zhao MM, Dong D, Liu M, Zhang DL, Fu WB. Perceived stress and brain connectivity in subthreshold depression: Insights from eyes-closed and eyes-open states. Brain Res 2024; 1838:148947. [PMID: 38657887 DOI: 10.1016/j.brainres.2024.148947] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Revised: 04/09/2024] [Accepted: 04/16/2024] [Indexed: 04/26/2024]
Abstract
Perceived stress is an acknowledged risk factor for subthreshold depression (StD), and fluctuations in perceived stress are thought to disrupt the harmony of brain networks essential for emotional and cognitive functioning. This study aimed to elucidate the relationship between eye-open (EO) and eye-closed (EC) states, perceived stress, and StD. We recruited 27 individuals with StD and 33 healthy controls, collecting resting state fMRI data under both EC and EO conditions. We combined intrinsic connectivity and seed-based functional connectivity analyses to construct the functional network and explore differences between EC and EO conditions. Graph theory analysis revealed weakened connectivity strength in the right superior frontal gyrus (SFG) and right median cingulate and paracingulate gyrus (MCC) among participants with StD, suggesting an important role for these regions in the stress-related emotions dysregulation. Notably, altered SFG connectivity was observed to significantly relate to perceived stress levels in StD, and the SFG connection emerges as a neural mediator potentially influencing the relationship between perceived stress and StD. These findings highlight the role of SFG and MCC in perceived stress and suggest that understanding EC and EO states in relation to these regions is important in the neurobiological framework of StD. This may offer valuable perspectives for early prevention and intervention strategies in mental health disorders.
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Affiliation(s)
- Bin-Kun Huang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - Jun-He Zhou
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; Department of Acupuncture and Moxibustion, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Ying Deng
- The Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Chang-Hong Li
- College of Teacher Education, Guangdong University of Education, Guangzhou 510303, China
| | - Bai-Le Ning
- Department of Acupuncture and Moxibustion, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Zi-Yu Ye
- Acupuncture and Rehabilitation Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Xi-Chang Huang
- The Second Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Mi-Mi Zhao
- Acupuncture and Rehabilitation Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Dian Dong
- Acupuncture and Rehabilitation Clinical Medical College, Guangzhou University of Chinese Medicine, Guangzhou 510000, China
| | - Ming Liu
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China
| | - De-Long Zhang
- Key Laboratory of Brain, Cognition and Education Sciences (South China Normal University), Ministry of Education, Guangzhou 510631, China; School of Psychology, Center for Studies of Psychological Application, and Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China.
| | - Wen-Bin Fu
- Department of Acupuncture and Moxibustion, The Second Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou 510000, China.
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2
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Kristanto D, Burkhardt M, Thiel C, Debener S, Gießing C, Hildebrandt A. The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis. Neurosci Biobehav Rev 2024; 165:105846. [PMID: 39117132 DOI: 10.1016/j.neubiorev.2024.105846] [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: 01/22/2024] [Revised: 04/04/2024] [Accepted: 08/04/2024] [Indexed: 08/10/2024]
Abstract
The large number of different analytical choices used by researchers is partly responsible for the challenge of replication in neuroimaging studies. For an exhaustive robustness analysis, knowledge of the full space of analytical options is essential. We conducted a systematic literature review to identify the analytical decisions in functional neuroimaging data preprocessing and analysis in the emerging field of cognitive network neuroscience. We found 61 different steps, with 17 of them having debatable parameter choices. Scrubbing, global signal regression, and spatial smoothing are among the controversial steps. There is no standardized order in which different steps are applied, and the parameter settings within several steps vary widely across studies. By aggregating the pipelines across studies, we propose three taxonomic levels to categorize analytical choices: 1) inclusion or exclusion of specific steps, 2) parameter tuning within steps, and 3) distinct sequencing of steps. We have developed a decision support application with high educational value called METEOR to facilitate access to the data in order to design well-informed robustness (multiverse) analysis.
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Affiliation(s)
- Daniel Kristanto
- Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany.
| | - Micha Burkhardt
- Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany
| | - Christiane Thiel
- Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Germany; Cluster of Excellence "Hearing4All", Carl von Ossietzky Universität Oldenburg, Germany
| | - Stefan Debener
- Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Germany; Cluster of Excellence "Hearing4All", Carl von Ossietzky Universität Oldenburg, Germany
| | - Carsten Gießing
- Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Germany.
| | - Andrea Hildebrandt
- Department of Psychology, Carl von Ossietzky Universität Oldenburg, Oldenburg 26129, Germany; Research Center Neurosensory Science, Carl von Ossietzky Universität Oldenburg, Germany; Cluster of Excellence "Hearing4All", Carl von Ossietzky Universität Oldenburg, Germany.
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3
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Krukow P, Rodríguez-González V, Kopiś-Posiej N, Gómez C, Poza J. Tracking EEG network dynamics through transitions between eyes-closed, eyes-open, and task states. Sci Rep 2024; 14:17442. [PMID: 39075178 PMCID: PMC11286934 DOI: 10.1038/s41598-024-68532-2] [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: 04/30/2024] [Accepted: 07/24/2024] [Indexed: 07/31/2024] Open
Abstract
Our study aimed to verify the possibilities of effectively applying chronnectomics methods to reconstruct the dynamic processes of network transition between three types of brain states, namely, eyes-closed rest, eyes-open rest, and a task state. The study involved dense EEG recordings and reconstruction of the source-level time-courses of the signals. Functional connectivity was measured using the phase lag index, and dynamic analyses concerned coupling strength and variability in alpha and beta frequencies. The results showed significant and dynamically specific transitions regarding processes of eyes opening and closing and during the eyes-closed-to-task transition in the alpha band. These observations considered a global dimension, default mode network, and central executive network. The decrease of connectivity strength and variability that accompanied eye-opening was a faster process than the synchronization increase during eye-opening, suggesting that these two transitions exhibit different reorganization times. While referring the obtained results to network studies, it was indicated that the scope of potential similarities and differences between rest and task-related networks depends on whether the resting state was recorded in eyes closed or open condition.
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Affiliation(s)
- Paweł Krukow
- Department of Clinical Neuropsychiatry, Medical University of Lublin, Ul. Głuska 1, 20-439, Lublin, Poland.
| | - Victor Rodríguez-González
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Natalia Kopiś-Posiej
- Department of Clinical Neuropsychiatry, Medical University of Lublin, Ul. Głuska 1, 20-439, Lublin, Poland
| | - Carlos Gómez
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús Poza
- Biomedical Engineering Group, University of Valladolid, Valladolid, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Instituto de Salud Carlos III, Madrid, Spain
- IMUVA, Instituto de Investigación en Matemáticas, University of Valladolid, Valladolid, Spain
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Bätz LR, Ye S, Lan X, Ziaei M. Increased functional integration of emotional control network in late adulthood. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.10.588823. [PMID: 38659752 PMCID: PMC11040603 DOI: 10.1101/2024.04.10.588823] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Across the adult lifespan, there are changes in how emotions are perceived and regulated. As individuals age, there is an observed improvement in emotion regulation and overall quicker recovery from negative emotions. While previous studies have shown differences in emotion processing in late adulthood, the corresponding differences in large-scale brain networks remain largely underexplored. By utilizing large-scale datasets such as the Human Connectome Project (HCP-Aging, N = 621 ) and Cambridge Centre for Ageing and Neuroscience (Cam-CAN, N = 333 ), we were able to investigate how emotion regulation networks' functional topography differs across the entire adult lifespan. Based on previous meta-analytic work that identified four large-scale functional brain networks involved in emotion generation and regulation, we found an increase in the functional integration of the emotional control network among older adults. Additionally, confirming through the nonlinear model, individuals around the age of 70 showed a steadier decline in integration of a network mediating emotion generation and regulation via interoception. Furthermore, the analyses revealed a negative association between age and perceived stress and loneliness that could be attributed to differences in large-scale emotion regulation networks. Our study highlights the importance of identifying topological changes in the functional emotion network architecture across the lifespan, as it allows for a better understanding of emotional aging and psychological well-being in late adulthood.
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Affiliation(s)
- Leona Rahel Bätz
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Shuer Ye
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Xiaqing Lan
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
| | - Maryam Ziaei
- Kavli Institute for Systems Neuroscience, Norwegian University of Science and Technology, Trondheim, Norway
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- K.G. Jebsen Centre for Alzheimer’s disease, Norwegian University of Science and Technology, Trondheim, Norway
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5
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Xie M, Huang Y, Cai W, Zhang B, Huang H, Li Q, Qin P, Han J. Neurobiological Underpinnings of Hyperarousal in Depression: A Comprehensive Review. Brain Sci 2024; 14:50. [PMID: 38248265 PMCID: PMC10813043 DOI: 10.3390/brainsci14010050] [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: 12/11/2023] [Revised: 12/26/2023] [Accepted: 12/30/2023] [Indexed: 01/23/2024] Open
Abstract
Patients with major depressive disorder (MDD) exhibit an abnormal physiological arousal pattern known as hyperarousal, which may contribute to their depressive symptoms. However, the neurobiological mechanisms linking this abnormal arousal to depressive symptoms are not yet fully understood. In this review, we summarize the physiological and neural features of arousal, and review the literature indicating abnormal arousal in depressed patients. Evidence suggests that a hyperarousal state in depression is characterized by abnormalities in sleep behavior, physiological (e.g., heart rate, skin conductance, pupil diameter) and electroencephalography (EEG) features, and altered activity in subcortical (e.g., hypothalamus and locus coeruleus) and cortical regions. While recent studies highlight the importance of subcortical-cortical interactions in arousal, few have explored the relationship between subcortical-cortical interactions and hyperarousal in depressed patients. This gap limits our understanding of the neural mechanism through which hyperarousal affects depressive symptoms, which involves various cognitive processes and the cerebral cortex. Based on the current literature, we propose that the hyperconnectivity in the thalamocortical circuit may contribute to both the hyperarousal pattern and depressive symptoms. Future research should investigate the relationship between thalamocortical connections and abnormal arousal in depression, and explore its implications for non-invasive treatments for depression.
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Affiliation(s)
- Musi Xie
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (M.X.); (Y.H.)
| | - Ying Huang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (M.X.); (Y.H.)
| | - Wendan Cai
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (W.C.); (B.Z.); (H.H.)
| | - Bingqi Zhang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (W.C.); (B.Z.); (H.H.)
| | - Haonan Huang
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (W.C.); (B.Z.); (H.H.)
| | - Qingwei Li
- Department of Psychiatry, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China;
| | - Pengmin Qin
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, School of Psychology, Center for Studies of Psychological Application, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (M.X.); (Y.H.)
- Pazhou Laboratory, Guangzhou 510330, China
| | - Junrong Han
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education, Institute for Brain Research and Rehabilitation, Guangdong Key Laboratory of Mental Health and Cognitive Science, South China Normal University, Guangzhou 510631, China; (W.C.); (B.Z.); (H.H.)
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6
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Ryan M, Glonek G, Tuke J, Humphries M. Capturing functional connectomics using Riemannian partial least squares. Sci Rep 2023; 13:17386. [PMID: 37833370 PMCID: PMC10576060 DOI: 10.1038/s41598-023-44687-2] [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: 07/11/2023] [Accepted: 10/10/2023] [Indexed: 10/15/2023] Open
Abstract
For neurological disorders and diseases, functional and anatomical connectomes of the human brain can be used to better inform targeted interventions and treatment strategies. Functional magnetic resonance imaging (fMRI) is a non-invasive neuroimaging technique that captures spatio-temporal brain function through change in blood-oxygen-level-dependent (BOLD) signals over time. FMRI can be used to study the functional connectome through the functional connectivity matrix; that is, Pearson's correlation matrix between time series from the regions of interest of an fMRI image. One approach to analysing functional connectivity is using partial least squares (PLS), a multivariate regression technique designed for high-dimensional predictor data. However, analysing functional connectivity with PLS ignores a key property of the functional connectivity matrix; namely, these matrices are positive definite. To account for this, we introduce a generalisation of PLS to Riemannian manifolds, called R-PLS, and apply it to symmetric positive definite matrices with the affine invariant geometry. We apply R-PLS to two functional imaging datasets: COBRE, which investigates functional differences between schizophrenic patients and healthy controls, and; ABIDE, which compares people with autism spectrum disorder and neurotypical controls. Using the variable importance in the projection statistic on the results of R-PLS, we identify key functional connections in each dataset that are well represented in the literature. Given the generality of R-PLS, this method has the potential to investigate new functional connectomes in the brain, and with future application to structural data can open up further avenues of research in multi-modal imaging analysis.
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Affiliation(s)
- Matthew Ryan
- School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, 5005, Australia.
| | - Gary Glonek
- School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, 5005, Australia
| | - Jono Tuke
- School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, 5005, Australia
| | - Melissa Humphries
- School of Computer and Mathematical Sciences, The University of Adelaide, Adelaide, 5005, Australia
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7
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Groot JM, Miletic S, Isherwood SJS, Tse DHY, Habli S, Håberg AK, Forstmann BU, Bazin PL, Mittner M. Echoes from Intrinsic Connectivity Networks in the Subcortex. J Neurosci 2023; 43:6609-6618. [PMID: 37562962 PMCID: PMC10538587 DOI: 10.1523/jneurosci.1020-23.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/11/2023] [Accepted: 07/28/2023] [Indexed: 08/12/2023] Open
Abstract
Decades of research have greatly improved our understanding of intrinsic human brain organization in terms of functional networks and the transmodal hubs within the cortex at which they converge. However, substrates of multinetwork integration in the human subcortex are relatively uncharted. Here, we leveraged recent advances in subcortical atlasing and ultra-high field (7 T) imaging optimized for the subcortex to investigate the functional architecture of 14 individual structures in healthy adult males and females with a fully data-driven approach. We revealed that spontaneous neural activity in subcortical regions can be decomposed into multiple independent subsignals that correlate with, or "echo," the activity in functional networks across the cortex. Distinct subregions of the thalamus, striatum, claustrum, and hippocampus showed a varied pattern of echoes from attention, control, visual, somatomotor, and default mode networks, demonstrating evidence for a heterogeneous organization supportive of functional integration. Multiple network activity furthermore converged within the globus pallidus externa, substantia nigra, and ventral tegmental area but was specific to one subregion, while the amygdala and pedunculopontine nucleus preferentially affiliated with a single network, showing a more homogeneous topography. Subregional connectivity of the globus pallidus interna, subthalamic nucleus, red nucleus, periaqueductal gray, and locus coeruleus did not resemble patterns of cortical network activity. Together, these finding describe potential mechanisms through which the subcortex participates in integrated and segregated information processing and shapes the spontaneous cognitive dynamics during rest.SIGNIFICANCE STATEMENT Despite the impact of subcortical dysfunction on brain health and cognition, large-scale functional mapping of subcortical structures severely lags behind that of the cortex. Recent developments in subcortical atlasing and imaging at ultra-high field provide new avenues for studying the intricate functional architecture of the human subcortex. With a fully data-driven analysis, we reveal subregional connectivity profiles of a large set of noncortical structures, including those rarely studied in fMRI research. The results have implications for understanding how the functional organization of the subcortex facilitates integrative processing through cross-network information convergence, paving the way for future work aimed at improving our knowledge of subcortical contributions to intrinsic brain dynamics and spontaneous cognition.
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Affiliation(s)
- Josephine M Groot
- Department of Psychology, UiT-Arctic University of Norway, Tromsø, 9037, Norway
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Steven Miletic
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Scott J S Isherwood
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Desmond H Y Tse
- Department of Neuropsychology and Psychopharmacology, Maastricht University, Maastricht, 6200 MD, The Netherlands
| | - Sarah Habli
- Department of Psychology, Norwegian University of Science and Technology, Trondheim, 8900, Norway
| | - Asta K Håberg
- Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, Trondheim, 8900, Norway
- Department of Radiology and Nuclear Medicine, St. Olavs Hospital, Trondheim, 7006, Norway
| | - Birte U Forstmann
- Integrative Model-based Cognitive Neuroscience research unit, University of Amsterdam, Amsterdam, 1001 NK, The Netherlands
| | - Pierre-Louis Bazin
- Department of Psychology, UiT-Arctic University of Norway, Tromsø, 9037, Norway
- Departments of Neurophysics and Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, 04303, Germany
| | - Matthias Mittner
- Department of Psychology, UiT-Arctic University of Norway, Tromsø, 9037, Norway
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Wang X, Xia J, Wang W, Lu J, Liu Q, Fan J, Soondrum T, Yu Q, Tan C, Zhu X. Disrupted functional connectivity of the cerebellum with default mode and frontoparietal networks in young adults with major depressive disorder. Psychiatry Res 2023; 324:115192. [PMID: 37054552 DOI: 10.1016/j.psychres.2023.115192] [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: 01/04/2023] [Revised: 03/15/2023] [Accepted: 04/04/2023] [Indexed: 04/15/2023]
Abstract
Cerebellar dysconnectivity has repeatedly been documented in major depressive disorder (MDD). The cerebellum is composed of multiple functionally distinct subunits, and whether those subunits show similar or distinct dysconnectivity patterns with the cerebrum in MDD, is still unclear and needs to be further clarified. In this study, 91 MDD patients (23 male and 68 female) and 59 demographically matched healthy controls (22 male and 37 female) were enrolled to explore the cerebellar-cerebral dysconnectivity pattern in MDD by using the cutting-edge cerebellar partition atlas. Results showed that MDD patients exhibit decreased cerebellar connectivity with cerebral regions of default mode (DMN), frontoparietal networks (FPN), and visual areas. The dysconnectivity pattern was statistically similar across cerebellar subunits, with no significant diagnosis-by-subunit interactions. Correlation analyzes showed that cerebellar-dorsal lateral prefrontal cortex (DLPFC) connectivity is significantly correlated with anhedonia in MDD patients. Such dysconnectivity pattern was not affected by sex, which, however, should be further replicated in larger samples. These findings suggest a generalized disrupted cerebellar-cerebral connectivity pattern in MDD across all cerebellar subunits, which partially accounts for depressive symptoms in MDD, thus highlighting the pivotal role of the disrupted connectivity of cerebellum with DMN and FPN in the neuropathology of depression.
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Affiliation(s)
- Xiang Wang
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Jie Xia
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Weiyan Wang
- National Clinical Research Center for Mental Disorders, Changsha, Hunan, China; Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Jingjie Lu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Qian Liu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Jie Fan
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Tamini Soondrum
- Association Alzheimer of Mauritius, Old Moka Road, Belle Rose, Quatre Bornes, Mauritius
| | - Quanhao Yu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China
| | - Changlian Tan
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Xiongzhao Zhu
- Medical Psychological Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China; Medical Psychological Institute of Central South University, Changsha, Hunan, China; National Clinical Research Center for Mental Disorders, Changsha, Hunan, China.
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