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Giuliani L, Pezzella P, Giordano GM, Fazio L, Mucci A, Perrottelli A, Blasi G, Amore M, Rocca P, Rossi A, Bertolino A, Galderisi S, Maj M. Illness-related variables and abnormalities of resting-state brain activity in schizophrenia. Front Psychiatry 2024; 15:1458624. [PMID: 39165501 PMCID: PMC11333936 DOI: 10.3389/fpsyt.2024.1458624] [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: 07/02/2024] [Accepted: 07/17/2024] [Indexed: 08/22/2024] Open
Abstract
Background The development of neuroimaging biomarkers in patients with schizophrenia (SCZ) requires a refined clinical characterization. A limitation of the neuroimaging literature is the partial uptake of progress in characterizing disease-related features, particularly negative symptoms (NS) and cognitive impairment (CI). In the present study, we assessed NS and CI using up-to-date instruments and investigated the associations of abnormalities in brain resting-state (rs)-activity with disease-related features. Methods Sixty-two community-dwelling SCZ subjects participated in the study. Multiple regression analyses were performed with the rs-activity of nine regions of interest as dependent variables and disease-related features as explanatory variables. Results Attention/vigilance deficits were negatively associated with dorsal anterior cingulate rs-activity and, together with depression, were positively associated with right dorsolateral prefrontal cortex rs-activity. These deficits and impairment of Reasoning/problem-solving, together with conceptual disorganization, were associated with right inferior parietal lobule and temporal parietal junction rs-activity. Independent of other features, the NS Expressive Deficit domain was associated with the left ventral caudate, while the Motivational Deficit was associated with the dorsal caudate rs-activity. Conclusion Neurocognitive deficits and the two negative symptom domains are associated with different neural markers. Replications of these findings could foster the identification of clinically actionable biomarkers of poor functional outcomes.
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Affiliation(s)
- Luigi Giuliani
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Pasquale Pezzella
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | | | - Leonardo Fazio
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, Bari, Italy
- Department of Medicine and Surgery, Libera Università Mediterranea Giuseppe Degennaro, Casamassima, Italy
| | - Armida Mucci
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Andrea Perrottelli
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Giuseppe Blasi
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, Bari, Italy
| | - Mario Amore
- Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy
| | - Paola Rocca
- Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy
| | - Alessandro Rossi
- Department of Biotechnological and Applied Clinical Sciences, Section of Psychiatry, University of L’Aquila, L’Aquila, Italy
| | - Alessandro Bertolino
- Department of Basic Medical Science, Neuroscience and Sense Organs, University of Bari ‘Aldo Moro’, Bari, Italy
| | - Silvana Galderisi
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
| | - Mario Maj
- Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
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Feng S, Huang Y, Lu H, Li H, Zhou S, Lu H, Feng Y, Ning Y, Han W, Chang Q, Zhang Z, Liu C, Li J, Wu K, Wu F. Association between degree centrality and neurocognitive impairments in patients with Schizophrenia: A Longitudinal rs-fMRI Study. J Psychiatr Res 2024; 173:115-123. [PMID: 38520845 DOI: 10.1016/j.jpsychires.2024.03.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 02/27/2024] [Accepted: 03/04/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND Evidence indicates that patients with schizophrenia (SZ) experience significant changes in their functional connectivity during antipsychotic treatment. Despite previous reports of changes in brain network degree centrality (DC) in patients with schizophrenia, the relationship between brain DC changes and neurocognitive improvement in patients with SZ after antipsychotic treatment remains elusive. METHODS A total of 74 patients with acute episodes of chronic SZ and 53 age- and sex-matched healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS), Symbol Digit Modalities Test, digital span test (DST), and verbal fluency test were used to evaluate the clinical symptoms and cognitive performance of the patients with SZ. Patients with SZ were treated with antipsychotics for six weeks starting at baseline and underwent MRI and clinical interviews at baseline and after six weeks, respectively. We then divided the patients with SZ into responding (RS) and non-responding (NRS) groups based on the PANSS scores (reduction rate of PANSS ≥50%). DC was calculated and analyzed to determine its correlation with clinical symptoms and cognitive performance. RESULTS After antipsychotic treatment, the patients with SZ showed significant improvements in clinical symptoms, semantic fluency performance. Correlation analysis revealed that the degree of DC increase in the left anterior inferior parietal lobe (aIPL) after treatment was negatively correlated with changes in the excitement score (r = -0.256, p = 0.048, adjusted p = 0.080), but this correlation failed the multiple test correction. Patients with SZ showed a significant negative correlation between DC values in the left aIPL and DST scores after treatment, which was not observed at the baseline (r = -0.359, p = 0.005, adjusted p = 0.047). In addition, we did not find a significant difference in DC between the RS and NRS groups, neither at baseline nor after treatment. CONCLUSIONS The results suggested that DC changes in patients with SZ after antipsychotic treatment are correlated with neurocognitive performance. Our findings provide new insights into the neuropathological mechanisms underlying antipsychotic treatment of SZ.
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Affiliation(s)
- Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuanyuan Huang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hongxin Lu
- Department of Psychiatry, Longyan Third Hospital of Fujian Province, Longyan, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hanna Lu
- Department of Psychiatry, The Chinese University of Hong Kong, Hong Kong SAR, China
| | - Yangdong Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yuping Ning
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qing Chang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Kai Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; School of Biomedical Sciences and Engineering, South China University of Technology, Guangzhou International Campus, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China; National Engineering Research Center for Tissue Restoration and Reconstruction, South China University of Technology, Guangzhou, China; Key Laboratory of Biomedical Engineering of Guangdong Province, South China University of Technology, Guangzhou, China; Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China; Department of Nuclear Medicine and Radiology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan.
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China; Department of Biomedical Engineering, Guangzhou Medical University, Guangzhou, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China; Guangdong Engineering Technology Research Center for Diagnosis and Rehabilitation of Dementia, Guangzhou, China.
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3
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Chen M, Xia X, Kang Z, Li Z, Dai J, Wu J, Chen C, Qiu Y, Liu T, Liu Y, Zhang Z, Shen Q, Tao S, Deng Z, Lin Y, Wei Q. Distinguishing schizophrenia and bipolar disorder through a Multiclass Classification model based on multimodal neuroimaging data. J Psychiatr Res 2024; 172:119-128. [PMID: 38377667 DOI: 10.1016/j.jpsychires.2024.02.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/22/2024]
Abstract
This study aimed to identify neural biomarkers for schizophrenia (SZ) and bipolar disorder (BP) by analyzing multimodal neuroimaging. Utilizing data from structural magnetic resonance imaging (sMRI), diffusion tensor imaging (DTI), and resting-state functional magnetic resonance imaging (rs-fMRI), multiclass classification models were created for SZ, BP, and healthy controls (HC). A total of 113 participants (BP: 31, SZ: 39, and HC: 43) were recruited under strict enrollment control, from which 272, 200, and 1875 features were extracted from sMRI, DTI, and rs-fMRI data, respectively. A support vector machine (SVM) with recursive feature elimination (RFE) was employed to build the models using a one-against-one approach and leave-one-out cross-validation, achieving a classification accuracy of 70.8%. The most discriminative features were primarily from rs-fMRI, along with significant findings in sMRI and DTI. Key biomarkers identified included the increased thickness of the left cuneus cortex and decreased regional functional connectivity strength (rFCS) in the left supramarginal gyrus as shared indicators for BP and SZ. Additionally, decreased fractional anisotropy in the left superior fronto-occipital fasciculus was suggested as specific to BP, while decreased rFCS in the left inferior parietal area might serve as a specific biomarker for SZ. These findings underscore the potential of multimodal neuroimaging in distinguishing between BP and SZ and contribute to the understanding of their neural underpinnings.
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Affiliation(s)
- Ming Chen
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Guangdong Mental Health Institute, Guangdong ProvincialPeople's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Xiaowei Xia
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhuang Kang
- Department of Radiology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zhinan Li
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Jiamin Dai
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Junyan Wu
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Cai Chen
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Yong Qiu
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Department of Psychiatry, Mindfront Caring Medical, Guangzhou, China
| | - Tong Liu
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Department of Psychiatry, The First Affiliated Hospital of Xi'an Jiaotong University, Shaanxi, China
| | - Yanxi Liu
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ziyi Zhang
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Department of Medical Division, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - Qingni Shen
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Sichu Tao
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zixin Deng
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Ying Lin
- Department of Psychology, Sun Yat-sen University, Guangzhou, China.
| | - Qinling Wei
- Department of Psychiatry, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, China.
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Thomas PJ, Leow A, Klumpp H, Phan KL, Ajilore O. Default Mode Network Hypoalignment of Function to Structure Correlates With Depression and Rumination. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024; 9:101-111. [PMID: 37468065 DOI: 10.1016/j.bpsc.2023.06.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 06/06/2023] [Accepted: 06/30/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND Recent studies have begun to examine how signals in the brain correspond to the underlying white matter structure using tools from the field of graph signal processing to quantify brain function alignment to brain network topology. Here, we applied this framework for the first time toward a transdiagnostic cohort of individuals with internalizing psychopathologies, including mood and anxiety disorders, to uncover how such alignment within the default mode network (DMN) is related to depression and rumination symptoms. METHODS Both diffusion-weighted and resting-state functional magnetic resonance imaging were obtained from participants at baseline (n = 60 patients, n = 19 healthy control participants). Patients were randomized to 12 weeks of treatment with either a selective serotonin reuptake inhibitor or cognitive behavioral therapy, and symptom scales were readministered posttreatment (n = 46 patients at follow-up). Using graph signal processing methodology, we quantified the alignment of functional signals to their underlying white matter structural networks. RESULTS We found that signal alignment within the posterior DMN was decreased in patients with internalizing psychopathologies compared with healthy control participants and was inversely (negatively) correlated with baseline depression and rumination scales. Signal alignment within the posterior DMN was also correlated with the ratio of total within-DMN to extra-DMN functional connectivity for these regions. CONCLUSIONS These findings are consistent with previous literature regarding pathological promiscuity of posterior DMN connectivity and provide the first graph signal processing-based analyses in a transdiagnostic cohort of patients with internalizing psychopathologies.
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Affiliation(s)
- Paul J Thomas
- Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois
| | - Alex Leow
- Department of Biomedical Engineering, University of Illinois Chicago, Chicago, Illinois
| | - Heide Klumpp
- Department of Psychiatry & Behavioral Health, University of Illinois Chicago, Chicago, Illinois
| | - K Luan Phan
- Department of Psychiatry, The Ohio State University, Columbus, Ohio
| | - Olusola Ajilore
- Department of Psychiatry & Behavioral Health, University of Illinois Chicago, Chicago, Illinois.
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Stoyanov D, Paunova R, Dichev J, Kandilarova S, Khorev V, Kurkin S. Functional magnetic resonance imaging study of group independent components underpinning item responses to paranoid-depressive scale. World J Clin Cases 2023; 11:8458-8474. [PMID: 38188204 PMCID: PMC10768520 DOI: 10.12998/wjcc.v11.i36.8458] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Revised: 11/10/2023] [Accepted: 12/05/2023] [Indexed: 12/22/2023] Open
Abstract
BACKGROUND Our study expand upon a large body of evidence in the field of neuropsychiatric imaging with cognitive, affective and behavioral tasks, adapted for the functional magnetic resonance imaging (MRI) (fMRI) experimental environment. There is sufficient evidence that common networks underpin activations in task-based fMRI across different mental disorders. AIM To investigate whether there exist specific neural circuits which underpin differential item responses to depressive, paranoid and neutral items (DN) in patients respectively with schizophrenia (SCZ) and major depressive disorder (MDD). METHODS 60 patients were recruited with SCZ and MDD. All patients have been scanned on 3T magnetic resonance tomography platform with functional MRI paradigm, comprised of block design, including blocks with items from diagnostic paranoid (DP), depression specific (DS) and DN from general interest scale. We performed a two-sample t-test between the two groups-SCZ patients and depressive patients. Our purpose was to observe different brain networks which were activated during a specific condition of the task, respectively DS, DP, DN. RESULTS Several significant results are demonstrated in the comparison between SCZ and depressive groups while performing this task. We identified one component that is task-related and independent of condition (shared between all three conditions), composed by regions within the temporal (right superior and middle temporal gyri), frontal (left middle and inferior frontal gyri) and limbic/salience system (right anterior insula). Another component is related to both diagnostic specific conditions (DS and DP) e.g. It is shared between DEP and SCZ, and includes frontal motor/language and parietal areas. One specific component is modulated preferentially by to the DP condition, and is related mainly to prefrontal regions, whereas other two components are significantly modulated with the DS condition and include clusters within the default mode network such as posterior cingulate and precuneus, several occipital areas, including lingual and fusiform gyrus, as well as parahippocampal gyrus. Finally, component 12 appeared to be unique for the neutral condition. In addition, there have been determined circuits across components, which are either common, or distinct in the preferential processing of the sub-scales of the task. CONCLUSION This study has delivers further evidence in support of the model of trans-disciplinary cross-validation in psychiatry.
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Affiliation(s)
- Drozdstoy Stoyanov
- Department of Psychiatry, Medical University Plovdiv, Plovdiv 4000, Bulgaria
| | - Rositsa Paunova
- Research Institute, Medical University, Plovdiv 4002, Bulgaria
| | - Julian Dichev
- Faculty of Medicine, Medical University, Plovdiv 4002, Bulgaria
| | - Sevdalina Kandilarova
- Department of Psychiatry and Medical Psychology, Medical University, Plovdiv 4002, Bulgaria
| | - Vladimir Khorev
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia
| | - Semen Kurkin
- Baltic Center for Artificial Intelligence and Neurotechnology, Immanuel Kant Baltic Federal University, Kaliningrad 236041, Russia
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Kang Y, Zhang Y, Huang K, Wang Z. Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia. Brain Imaging Behav 2023; 17:584-594. [PMID: 37382826 DOI: 10.1007/s11682-023-00786-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/11/2023] [Indexed: 06/30/2023]
Abstract
Alterations in dynamic intrinsic brain activity and signaling of neurotransmitters, such as dopamine, have been independently detected in schizophrenia patients. Yet, it remains unclear whether the dopamine genetic risk variants have association with brain intrinsic activity. We aimed to investigate the schizophrenia-specific dynamic amplitude of low frequency fluctuation (dALFF) altered pattern, and its association with dopamine genetic risk score in first-episode drug-naïve schizophrenia (FES). Fifty-two FES and 51 healthy controls were included. A sliding-window method based on the dALFF was adopted to estimate the dynamic alterations in intrinsic brain activity. Subjects were genotyped, and a genetic risk score (GRS), which combined the additive effects of ten risk genotypes from five dopamine-related genes, was calculated. We used the voxel-wise correlation analysis to explore the association of dopamine-GRS with dALFF. FES showed significantly increased dALFF left medial prefrontal cortex and significantly decreased dALFF in the right posterior cingulate cortex compared with healthy controls. Greater dopamine GRS in FES was associated with higher dALFF in the left middle frontal gyrus and left inferior parietal gyrus. Our findings indicate that cumulative dopamine genetic risk is associated with a known imaging phenotype for schizophrenia.
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Affiliation(s)
- Yafei Kang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China
| | - Youming Zhang
- Department of Radiology, Xiangya Hospital, Central South University, Changsha, China
| | - Kexin Huang
- West China Biomedical Big Data Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Zhenhong Wang
- Shaanxi Provincial Key Research Center of Child Mental and Behavioral Health, School of Psychology, Shaanxi Normal University, Xi'an, China.
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Huang Y, Yi Y, Chen Q, Li H, Feng S, Zhou S, Zhang Z, Liu C, Li J, Lu Q, Zhang L, Han W, Wu F, Ning Y. Analysis of EEG features and study of automatic classification in first-episode and drug-naïve patients with major depressive disorder. BMC Psychiatry 2023; 23:832. [PMID: 37957613 PMCID: PMC10644563 DOI: 10.1186/s12888-023-05349-9] [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: 06/13/2023] [Accepted: 11/04/2023] [Indexed: 11/15/2023] Open
Abstract
BACKGROUND Major depressive disorder (MDD) has a high incidence and an unknown mechanism. There are no objective and sensitive indicators for clinical diagnosis. OBJECTIVE This study explored specific electrophysiological indicators and their role in the clinical diagnosis of MDD using machine learning. METHODS Forty first-episode and drug-naïve patients with MDD and forty healthy controls (HCs) were recruited. EEG data were collected from all subjects in the resting state with eyes closed for 10 min. The severity of MDD was assessed by the Hamilton Depression Rating Scale (HAMD-17). Machine learning analysis was used to identify the patients with MDD. RESULTS Compared to the HC group, the relative power of the low delta and theta bands was significantly higher in the right occipital region, and the relative power of the alpha band in the entire posterior occipital region was significantly lower in the MDD group. In the MDD group, the alpha band scalp functional connectivity was overall lower, while the scalp functional connectivity in the gamma band was significantly higher than that in the HC group. In the feature set of the relative power of the ROI in each band, the highest accuracy of 88.2% was achieved using the KNN classifier while using PCA feature selection. In the explanatory model using SHAP values, the top-ranking influence feature is the relative power of the alpha band in the left parietal region. CONCLUSIONS Our findings reveal that the abnormal EEG neural oscillations may reflect an imbalance of excitation, inhibition and hyperactivity in the cerebral cortex in first-episode and drug-naïve patients with MDD. The relative power of the alpha band in the left parietal region is expected to be an objective electrophysiological indicator of MDD.
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Affiliation(s)
- Yuanyuan Huang
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yun Yi
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
- Department of Psychiatry, The Brain Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China
| | - Qiang Chen
- Department of Psychiatry, The Brain Hospital of Guangxi Zhuang Autonomous Region, Guangxi, China
| | - Hehua Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Shixuan Feng
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sumiao Zhou
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Ziyun Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Chenyu Liu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Junhao Li
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Qiuling Lu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Lida Zhang
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Wei Han
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China
| | - Fengchun Wu
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China.
| | - Yuping Ning
- The First School of Clinical Medicine, Southern Medical University, Guangzhou, China.
- Department of Psychiatry, The Affiliated Brain Hospital of Guangzhou Medical University, Guangzhou, China.
- Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou, China.
- Key Laboratory of Neurogenetics and Channelopathies of Guangdong Province and the Ministry of Education of China, Guangzhou Medical University, Guangzhou, China.
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Cosmo C, Zandvakili A, Petrosino NJ, Toutain TGLDO, Miranda JGV, Philip NS. Examining the neural mechanisms of rTMS: a naturalistic pilot study of acute and serial effects in pharmacoresistant depression. Front Neural Circuits 2023; 17:1161826. [PMID: 37206978 PMCID: PMC10188923 DOI: 10.3389/fncir.2023.1161826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 04/10/2023] [Indexed: 05/21/2023] Open
Abstract
Introduction Previous studies have demonstrated the effectiveness of therapeutic repetitive transcranial magnetic stimulation (rTMS) to treat pharmacoresistant depression. Nevertheless, these trials have primarily focused on the therapeutic and neurophysiological effects of rTMS following a long-term treatment course. Identifying brain-based biomarkers of early rTMS therapeutic response remains an important unanswered question. In this pilot study, we examined the effects of rTMS on individuals with pharmacoresistant depression using a graph-based method, called Functional Cortical Networks (FCN), and serial electroencephalography (EEG). We hypothesized that changes in brain activity would occur early in treatment course. Methods A total of 15 patients with pharmacoresistant depression underwent five rTMS sessions (5Hz over the left dorsolateral prefrontal cortex, 120%MT, up to 4,000 pulses/session). Five participants received additional rTMS treatment, up to 40 sessions. Resting EEG activity was measured at baseline and following every five sessions, using 64-channel EEG, for 10 minutes with eyes closed. An FCN model was constructed using time-varying graphs and motif synchronization. The primary outcome was acute changes in weighted-node degree. Secondary outcomes included serial FFT-based power spectral analysis and changes in depressive symptoms measured by the 9-Item Patient Health Questionnaire (PHQ-9) and the 30-item Inventory of Depressive Symptoms-Self Report (IDS-SR). Results We found a significant acute effect over the left posterior area after five sessions, as evidenced by an increase in weighted-node degree of 37,824.59 (95% CI, 468.20 to 75,180.98) and a marginal enhancement in the left frontal region (t (14) = 2.0820, p = 0.056). One-way repeated measures ANOVA indicated a significant decrease in absolute beta power over the left prefrontal cortex (F (7, 28) = 2.37, p = 0.048) following ten rTMS sessions. Furthermore, a significant clinical improvement was observed following five rTMS sessions on both PHQ-9 (t (14) = 2.7093, p = 0.017) and IDS-SR (t (14) = 2.5278, p = 0.024) and progressed along the treatment course. Discussion Our findings suggest that FCN models and serial EEG may contribute to a deeper understanding of mechanisms underlying rTMS treatment. Additional research is required to investigate the acute and serial effects of rTMS in pharmacoresistant depression and assess whether early EEG changes could serve as predictors of therapeutic rTMS response.
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Affiliation(s)
- Camila Cosmo
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School, Brown University, Providence, RI, United States
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, United States
| | - Amin Zandvakili
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School, Brown University, Providence, RI, United States
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, United States
| | - Nicholas J. Petrosino
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School, Brown University, Providence, RI, United States
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, United States
| | | | | | - Noah S. Philip
- Department of Psychiatry and Human Behavior, The Warren Alpert Medical School, Brown University, Providence, RI, United States
- VA RR&D Center for Neurorestoration and Neurotechnology, VA Providence Healthcare System, Providence, RI, United States
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Acute TMS/fMRI response explains offline TMS network effects - An interleaved TMS-fMRI study. Neuroimage 2023; 267:119833. [PMID: 36572133 DOI: 10.1016/j.neuroimage.2022.119833] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2021] [Revised: 11/22/2022] [Accepted: 12/22/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Transcranial magnetic stimulation (TMS) is an FDA-approved therapeutic option for treatment resistant depression. However, exact mechanisms-of-action are not fully understood and individual responses are variable. Moreover, although previously suggested, the exact network effects underlying TMS' efficacy are poorly understood as of today. Although, it is supposed that DLPFC stimulation indirectly modulates the sgACC, recent evidence is sparse. METHODS Here, we used concurrent interleaved TMS/fMRI and state-of-the-science purpose-designed MRI head coils to delineate networks and downstream regions activated by DLPFC-TMS. RESULTS We show that regions of increased acute BOLD signal activation during TMS resemble a resting-state brain network previously shown to be modulated by offline TMS. There was a topographical overlap in wide spread cortical and sub-cortical areas within this specific RSN#17 derived from the 1000 functional connectomes project. CONCLUSION These data imply a causal relation between DLPFC-TMS and activation of the ACC and a broader network that has been implicated in MDD. In the broader context of our recent work, these data imply a direct relation between initial changes in BOLD activity mediated by connectivity to the DLPFC target site, and later consolidation of connectivity between these regions. These insights advance our understanding of the mechanistic targets of DLPFC-TMS and may provide novel opportunities to characterize and optimize TMS therapy in other neurological and psychiatric disorders.
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10
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Dong H, Li N, Fan L, Wei J, Xu J. Integrative interaction of emotional speech in audio-visual modality. Front Neurosci 2022; 16:797277. [PMID: 36440282 PMCID: PMC9695733 DOI: 10.3389/fnins.2022.797277] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2021] [Accepted: 09/21/2022] [Indexed: 11/13/2022] Open
Abstract
Emotional clues are always expressed in many ways in our daily life, and the emotional information we receive is often represented by multiple modalities. Successful social interactions require a combination of multisensory cues to accurately determine the emotion of others. The integration mechanism of multimodal emotional information has been widely investigated. Different brain activity measurement methods were used to determine the location of brain regions involved in the audio-visual integration of emotional information, mainly in the bilateral superior temporal regions. However, the methods adopted in these studies are relatively simple, and the materials of the study rarely contain speech information. The integration mechanism of emotional speech in the human brain still needs further examinations. In this paper, a functional magnetic resonance imaging (fMRI) study was conducted using event-related design to explore the audio-visual integration mechanism of emotional speech in the human brain by using dynamic facial expressions and emotional speech to express emotions of different valences. Representational similarity analysis (RSA) based on regions of interest (ROIs), whole brain searchlight analysis, modality conjunction analysis and supra-additive analysis were used to analyze and verify the role of relevant brain regions. Meanwhile, a weighted RSA method was used to evaluate the contributions of each candidate model in the best fitted model of ROIs. The results showed that only the left insula was detected by all methods, suggesting that the left insula played an important role in the audio-visual integration of emotional speech. Whole brain searchlight analysis, modality conjunction analysis and supra-additive analysis together revealed that the bilateral middle temporal gyrus (MTG), right inferior parietal lobule and bilateral precuneus might be involved in the audio-visual integration of emotional speech from other aspects.
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Affiliation(s)
- Haibin Dong
- Tianjin Key Lab of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China
| | - Na Li
- Tianjin Key Lab of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China
| | - Lingzhong Fan
- Brainnetome Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China
| | - Jianguo Wei
- Tianjin Key Lab of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China
| | - Junhai Xu
- Tianjin Key Lab of Cognitive Computing and Application, College of Intelligence and Computing, Tianjin University, Tianjin, China
- *Correspondence: Junhai Xu,
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11
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Thomas PJ, Leow A, Klumpp H, Phan KL, Ajilore O. Network Diffusion Embedding Reveals Transdiagnostic Subnetwork Disruption and Potential Treatment Targets in Internalizing Psychopathologies. Cereb Cortex 2022; 32:1823-1839. [PMID: 34521109 PMCID: PMC9070362 DOI: 10.1093/cercor/bhab314] [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: 05/18/2021] [Revised: 08/03/2021] [Accepted: 08/04/2021] [Indexed: 11/14/2022] Open
Abstract
Network diffusion models are a common and powerful way to study the propagation of information through a complex system and they offer straightforward approaches for studying multimodal brain network data. We developed an analytic framework to identify brain subnetworks with perturbed information diffusion capacity using the structural basis that best maps to resting state functional connectivity and applied it towards a heterogeneous dataset of internalizing psychopathologies (IPs), a set of psychiatric conditions in which similar brain network deficits are found across the swath of the disorders, but a unifying neuropathological substrate for transdiagnostic symptom expression is currently unknown. This research provides preliminary evidence of a transdiagnostic brain subnetwork deficit characterized by information diffusion impairment of the right area 8BM, a key brain region involved in organizing a broad spectrum of cognitive tasks, which may underlie previously reported dysfunction of multiple brain circuits in the IPs. We also demonstrate that models of neuromodulation involving targeting this brain region normalize IP diffusion dynamics towards those of healthy controls. These analyses provide a framework for multimodal methods that identify both brain subnetworks with disrupted information diffusion and potential targets of these subnetworks for therapeutic neuromodulatory intervention based on previously well-characterized methodology.
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Affiliation(s)
- Paul J Thomas
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60612, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Alex Leow
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60612, USA
- Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA
| | - Heide Klumpp
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60612, USA
| | - K Luan Phan
- Department of Psychiatry and Behavioral Health, The Ohio State University, Columbus, OH 43210, USA
| | - Olusola Ajilore
- Department of Psychiatry, University of Illinois at Chicago, Chicago, IL 60612, USA
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12
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Piani MC, Maggioni E, Delvecchio G, Brambilla P. Sustained attention alterations in major depressive disorder: A review of fMRI studies employing Go/No-Go and CPT tasks. J Affect Disord 2022; 303:98-113. [PMID: 35139418 DOI: 10.1016/j.jad.2022.02.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 12/23/2021] [Accepted: 02/04/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is a severe psychiatric condition characterized by selective cognitive dysfunctions. In this regard, functional Magnetic Resonance Imaging (fMRI) studies showed, both at resting state and during tasks, alterations in the brain functional networks involved in cognitive processes in MDD patients compared to controls. Among those, it seems that the attention network may have a role in the disease pathophysiology. Therefore, in this review we aim at summarizing the current fMRI evidence investigating sustained attention in MDD patients. METHODS We conducted a search on PubMed on case-control studies on MDD employing fMRI acquisitions during Go/No-Go and continuous performance tasks. A total of 12 studies have been included in the review. RESULTS Overall, the majority of fMRI studies reported quantitative alterations in the response to attentive tasks in selective brain regions, including the prefrontal cortex, the cingulate cortex, the temporal and parietal lobes, the insula and the precuneus, which are key nodes of the attention, the executive, and the default mode networks. LIMITATIONS The heterogeneity in the study designs, fMRI acquisition techniques and processing methods have limited the generalizability of the results. CONCLUSIONS The results from the included studies showed the presence of alterations in the activation patterns of regions involved in sustained attention in MDD, which are in line with current evidence and seemed to explain some of the key symptoms of depression. However, given the paucity and heterogeneity of studies available, it may be worthwhile to continue investigating the attentional domain in MDD with ad-hoc study designs to retrieve more robust evidence.
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Affiliation(s)
- Maria Chiara Piani
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano 20122, Italy
| | - Eleonora Maggioni
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano 20122, Italy
| | - Giuseppe Delvecchio
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano 20122, Italy.
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milano 20122, Italy; Department of Pathophysiology and Transplantation, University of Milan, Italy
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13
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Wang YM, Yang ZY. Aberrant pattern of cerebral blood flow in patients with major depressive disorder: A meta-analysis of arterial spin labelling studies. Psychiatry Res Neuroimaging 2022; 321:111458. [PMID: 35152052 DOI: 10.1016/j.pscychresns.2022.111458] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/30/2022] [Accepted: 02/07/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Accumulating evidence has suggested that patients with major depressive disorder (MDD) could exhibit resting-state cerebral blood flow (CBF) abnormalities. However, findings across studies are controversial. METHODS Our study aimed at identifying replicable CBF changes in MDD by conducting a case-control meta-analysis and meta-regression of arterial spin labelling studies using seed-based d mapping software. Fourteen studies encompassing 505 patients with MDD and 443 healthy controls were included. RESULTS We found increased CBF in the inferior parietal lobule, the striatum, and the bilateral thalamus in all patients with MDD relative to healthy controls. While decreased CBF was observed in the inferior frontal gyrus, the insula, the middle occipital gyrus and the bilateral superior temporal gyrus in patients with MDD. Moreover, increased CBF of the bilateral thalamus was associated with more severe depressive symptoms in patients with MDD. The subgroup meta-analysis showed that patients with acute phase had increased CBF in the bilateral thalamus, and decreased CBF in the left middle occipital gyrus and the left middle frontal gyrus. Chronic patients had decreased CBF in the left insula, the right calcarine sulcus, the right inferior frontal gyrus, and the left parahippocampal gyrus. Patients with medication-free had increased CBF in the right anterior cingulate cortex/medial prefrontal cortex, and decreased CBF in the left middle occipital gyrus, the left inferior frontal gyrus, and the left precentral gyrus. CONCLUSIONS These findings suggest an aberrant cerebral blood flow pattern of MDD involving the cortico-striatal-thalamic circuit, which may facilitate understanding of pathophysiology and suggest potential neural biomarkers for clinical assessment, monitoring and interventions of MDD. One important limitation is that eight recruited studies in our meta-analysis have recruited more males than females, which may have a selection bias of patients.
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Affiliation(s)
- Yong-Ming Wang
- School of Biology & Basic Medical Sciences, Medical College of Soochow University, Suzhou 215123, China
| | - Zhuo-Ya Yang
- Department of Basic Psychology, School of Psychology, Army Medical University, Chongqing 400038, China.
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14
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Li P, Zhou M, Yan W, Du J, Lu S, Xie S, Zhang R. Altered resting-state functional connectivity of the right precuneus and cognition between depressed and non-depressed schizophrenia. Psychiatry Res Neuroimaging 2021; 317:111387. [PMID: 34509807 DOI: 10.1016/j.pscychresns.2021.111387] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2021] [Revised: 08/31/2021] [Accepted: 08/31/2021] [Indexed: 01/27/2023]
Abstract
The study investigated the resting-state functional connectivity (FC) and cognitive changes in patients with depressed schizophrenia(DS) and non-depressed schizophrenia(NDS). Eighty patients with first-episode schizophrenia and 50 healthy controls (HC) were included to conduct resting-state fMRI. All participants completed MATRICS Consensus Cognitive Battery (MCCB). The right precuneus was selected as the seed in whole-brain FC analysis. Our results showed the cognitive function (All MCCB dimensions) of all schizophrenia patients were worse than HC, but no differences were found between DS and NDS. The DS had decreased FC than NDS between the right precuneus and left middle cingulate gyrus, left cerebellum, right cerebellum. The DS had increased FC than HC between the right precuneus and temporal lobe, occipital lobe, and decreased FC between the right precuneus and left cerebellum. However, the NDS had increased FC than HC between the right precuneus and left cerebellum, right cerebellum, temporal lobe, occipital lobe, left superior parietal lobule. Correlation analysis showed that FC between the right precuneus and occipital lobe was negatively correlated with visual learning in DS and with social cognition in NDS. Our results suggest DS and NDS patients have different patterns of FC, and their FC changes correlate with different domains of cognition.
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Affiliation(s)
- Pingping Li
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Min Zhou
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Wei Yan
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Jinglun Du
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Shuiping Lu
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
| | - Shiping Xie
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China.
| | - Rongrong Zhang
- Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University, Nanjing 210029, China
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15
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Cao W, Liao H, Cai S, Peng W, Liu Z, Zheng K, Liu J, Zhong M, Tan C, Yi J. Increased functional interaction within frontoparietal network during working memory task in major depressive disorder. Hum Brain Mapp 2021; 42:5217-5229. [PMID: 34328676 PMCID: PMC8519848 DOI: 10.1002/hbm.25611] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 07/17/2021] [Accepted: 07/20/2021] [Indexed: 12/28/2022] Open
Abstract
Abnormal fronto-parietal activation has been suggested as a neural underpinning of the working memory (WM) deficits in major depressive disorder (MDD). However, the potential interaction within the frontoparietal network during WM processing in MDD remains unclear. This study aimed to examine the role of abnormal functional interactions within frontoparietal network in the neuropathological mechanisms of WM deficits in MDD. A total of 40 MDD patients and 47 demographic matched healthy controls (HCs) were included. Functional magnetic resonance imaging and behavioral data were collected during numeric n-back tasks. The psychophysiological interaction and dynamic causal modelling methods were applied to investigate the connectivity within the frontoparietal network in MDD during n-back tasks. The psychophysiological interaction analysis revealed that MDD patients showed increased functional connectivity between the right inferior parietal lobule (IPL) and the right dorsolateral prefrontal cortex (dlPFC) compared with HCs during the 2-back task. The dynamic causal modelling analysis revealed that MDD patients had significantly increased forward modulation connectivity from the right IPL to the right dlPFC than HCs during the 2-back task. Partial correlation was used to calculate the relationship between connective parameters and psychological variables in the MDD group, which showed that the effective connectivity from right IPL to right dlPFC was correlated negatively with the sensitivity index d' of WM performances and positively with the depressive severity in MDD group. In conclusion, the abnormal functional and effective connectivity between frontal and parietal regions might contribute to explain the neuropathological mechanism of working memory deficits in major depressive disorder.
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Affiliation(s)
- Wanyi Cao
- Medical Psychological CenterThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
- Medical Psychological InstituteCentral South UniversityChangshaHunanChina
- National Clinical Research Center for Mental DisordersChangshaHunanChina
| | - Haiyan Liao
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
| | - Sainan Cai
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
| | - Wanrong Peng
- Medical Psychological CenterThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
- Medical Psychological InstituteCentral South UniversityChangshaHunanChina
- National Clinical Research Center for Mental DisordersChangshaHunanChina
| | - Zhaoxia Liu
- Medical Psychological CenterThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
- Medical Psychological InstituteCentral South UniversityChangshaHunanChina
- National Clinical Research Center for Mental DisordersChangshaHunanChina
| | - Kaili Zheng
- Medical Psychological CenterThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
- Medical Psychological InstituteCentral South UniversityChangshaHunanChina
- National Clinical Research Center for Mental DisordersChangshaHunanChina
| | - Jinyu Liu
- Center for Studies of Psychological ApplicationSchool of Psychology, South China Normal UniversityGuangzhouGuangdongChina
| | - Mingtian Zhong
- Center for Studies of Psychological ApplicationSchool of Psychology, South China Normal UniversityGuangzhouGuangdongChina
| | - Changlian Tan
- Department of RadiologyThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
| | - Jinyao Yi
- Medical Psychological CenterThe Second Xiangya Hospital, Central South UniversityChangshaHunanChina
- Medical Psychological InstituteCentral South UniversityChangshaHunanChina
- National Clinical Research Center for Mental DisordersChangshaHunanChina
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16
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Huang K, Kang Y, Wu Z, Wang Y, Cai S, Huang L. Asymmetrical alterations of grey matter among psychiatric disorders: A systematic analysis by voxel-based activation likelihood estimation. Prog Neuropsychopharmacol Biol Psychiatry 2021; 110:110322. [PMID: 33838150 DOI: 10.1016/j.pnpbp.2021.110322] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Revised: 04/02/2021] [Accepted: 04/04/2021] [Indexed: 10/21/2022]
Abstract
Schizophrenia (SZ), bipolar disorder (BD) and major depression disorder (MDD) have been regarded as highly diverged independent entities in current psychiatric diagnosis. However, ample new evidence suggests that they may have common biological traits. Neuroimaging studies showed that psychiatric disorders might associated with altered grey matter (GM) asymmetry compared to controls; however, the degree to which SZ, BD and MDD have common and/or distinct asymmetrical alterations in GM is still ambiguous. In this study, we analysed 169 voxel-based studies (including 3517 SZ patients, 1575 BD patients, 3280 MDD patients and 9733 controls) using activation likelihood estimation (ALE) meta-analysis to systematically review the existence of similar GM atrophy and asymmetrical alteration patterns among these psychiatric disorders, and the functional association between behaviour domains and topological alterations. We found that the right parahippocampal gyrus and left superior frontal gyrus showed commonly altered GM volume across all three illnesses, but did not identify common asymmetrical alteration. The asymmetrical alteration with leftward bias appeared in SZ and bipolar disorder at different locations, but more asymmetrical alteration with rightward bias appeared in MDD. Moreover, these changes have been confirmed to be associate with several symptoms and may have roles in functional networks. Our findings support the existence of common neurobiological damnification in these psychiatric disorders and provides valuable insights for the neural commonalties among different psychiatric disorders based on a large sample size.
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Affiliation(s)
- Kexin Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yafei Kang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Zhongcheng Wu
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Yubo Wang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Suping Cai
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China
| | - Liyu Huang
- School of Life Science and Technology, Xidian University, Xi'an, Shaanxi 710071, China.
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17
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Altered brain activity in the bilateral frontal cortices and neural correlation with cognitive impairment in schizophrenia. Brain Imaging Behav 2021; 16:415-423. [PMID: 34449034 DOI: 10.1007/s11682-021-00516-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/17/2021] [Indexed: 10/20/2022]
Abstract
Cognitive impairments are core aspects of schizophrenia and are highly related to poor outcomes. However, the effect of therapy on cognitive impairments remains unsatisfactory as its biological mechanisms are not fully understood. The purpose of this study was to investigate the disrupted intrinsic neural activity of the frontal areas and to further examine the functional connectivity of frontal areas related to cognitive impairments in schizophrenia. We collected brain imaging data using a 3T Siemens Prisma MRI system in 32 patients with schizophrenia and 34 age- and sex-matched healthy controls. The mean fractional amplitude of low-frequency fluctuation (mfALFF) in the frontal regions was calculated and analyzed to evaluate regional neural activity alterations in schizophrenia. Seed regions were generated from clusters showing significant changes in mfALFF in schizophrenia, and its resting-state functional connectivity (rs-FC) with other brain regions were estimated to detect possible aberrant rs-FC indicating cognitive impairments in schizophrenia. We found that mfALFF in the bilateral frontal cortices was increased in schizophrenia. mfALFF-based rs-FC revealed that decreased rs-FC between left middle frontal gyrus (MFG) and left medial superior frontal gyrus (MFSG) was associated with poor delayed memory (r = 0.566, Bonferroni-corrected p = 0.012). These findings demonstrate increased neural activity in the frontal cortices in schizophrenia. FC analysis revealed a diminished rs-FC pattern between the left MFG and left MSFG that was associated with cognitive impairments. These findings have provided deeper insight into the alterations in brain function related to specific domains of cognitive impairment and may provide evidence for precise interventions for cognitive deficits in schizophrenia.
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18
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Li R, Yang J, Li L, Shen F, Zou T, Wang H, Wang X, Li J, Deng C, Huang X, Wang C, He Z, Lu F, Zeng L, Chen H. Integrating Multilevel Functional Characteristics Reveals Aberrant Neural Patterns during Audiovisual Emotional Processing in Depression. Cereb Cortex 2021; 32:1-14. [PMID: 34642754 DOI: 10.1093/cercor/bhab185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Revised: 05/25/2021] [Accepted: 05/29/2021] [Indexed: 11/14/2022] Open
Abstract
Emotion dysregulation is one of the core features of major depressive disorder (MDD). However, most studies in depression have focused on unimodal emotion processing, whereas emotional perception in daily life is highly dependent on multimodal sensory inputs. Here, we proposed a novel multilevel discriminative framework to identify the altered neural patterns in processing audiovisual emotion in MDD. Seventy-four participants underwent an audiovisual emotional task functional magnetic resonance imaging scanning. Three levels of whole-brain functional features were extracted for each subject, including the task-evoked activation, task-modulated connectivity, combined activation and connectivity. Support vector machine classification and prediction models were built to identify MDD from controls and evaluate clinical relevance. We revealed that complex neural networks including the emotion regulation network (prefrontal areas and limbic-subcortical regions) and the multisensory integration network (lateral temporal cortex and motor areas) had the discriminative power. Moreover, by integrating comprehensive information of local and interactive processes, multilevel models could lead to a substantial increase in classification accuracy and depression severity prediction. Together, we highlight the high representational capacity of machine learning algorithms to characterize the complex network abnormalities associated with emotional regulation and multisensory integration in MDD. These findings provide novel evidence for the neural mechanisms underlying multimodal emotion dysregulation of depression.
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Affiliation(s)
- Rong Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Jiale Yang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China.,School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, PR China
| | - Liyuan Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Fei Shen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Ting Zou
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Hongyu Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Xuyang Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Jiyi Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Chijun Deng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Xinju Huang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Chong Wang
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Zongling He
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Fengmei Lu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China
| | - Ling Zeng
- School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, 611731, PR China
| | - Huafu Chen
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, University of Electronic Science and Technology of China, Chengdu, 610054, PR China.,Sichuan Provincial Center for Mental Health, The Center of Psychosomatic Medicine of Sichuan Provincial People's Hospital, University of Electronic Science and Technology of china, Chengdu 611731, PR China
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19
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Kim K, Duc NT, Choi M, Lee B. EEG microstate features for schizophrenia classification. PLoS One 2021; 16:e0251842. [PMID: 33989352 PMCID: PMC8121321 DOI: 10.1371/journal.pone.0251842] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 05/04/2021] [Indexed: 12/11/2022] Open
Abstract
Electroencephalography (EEG) microstate analysis is a method wherein spontaneous EEG activity is segmented at sub-second levels to analyze quasi-stable states. In particular, four archetype microstates and their features are known to reflect changes in brain state in neuropsychiatric diseases. However, previous studies have only reported differences in each microstate feature and have not determined whether microstate features are suitable for schizophrenia classification. Therefore, it is necessary to validate microstate features for schizophrenia classification. Nineteen microstate features, including duration, occurrence, and coverage as well as thirty-one conventional EEG features, including statistical, frequency, and temporal characteristics were obtained from resting-state EEG recordings of 14 patients diagnosed with schizophrenia and from 14 healthy (control) subjects. Machine-learning based multivariate analysis was used to evaluate classification performance. EEG recordings of patients and controls showed different microstate features. More importantly, when differentiating among patients and controls, EEG microstate features outperformed conventional EEG ones. The performance of the microstate features exceeded that of conventional EEG, even after optimization using recursive feature elimination. EEG microstate features applied with conventional EEG features also showed better classification performance than conventional EEG features alone. The current study is the first to validate the use of microstate features to discriminate schizophrenia, suggesting that EEG microstate features are useful for schizophrenia classification.
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Affiliation(s)
- Kyungwon Kim
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
- Department of Psychiatry and Biomedical Research Institute, Pusan National University Hospital, Busan, South Korea
| | - Nguyen Thanh Duc
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
- Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada
- McConnel Brain Imaging Center, Montreal Neurological Institute, McGill University, Montreal, Canada
- Ludmer Centre for Neuroinformatics and Mental Health, McGill University, Montreal, Canada
| | - Min Choi
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
| | - Boreom Lee
- Department of Biomedical Science and Engineering (BMSE), Institute Integrated Technology (IIT), Gwangju Institute of Science and Technology (GIST), Cheomdan-gwagiro, Gwangju, South Korea
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20
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Zhang J, Liu Y, Lan K, Huang X, He Y, Yang F, Li J, Hu Q, Xu J, Yu H. Gray Matter Atrophy in Amnestic Mild Cognitive Impairment: A Voxel-Based Meta-Analysis. Front Aging Neurosci 2021; 13:627919. [PMID: 33867968 PMCID: PMC8044397 DOI: 10.3389/fnagi.2021.627919] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Accepted: 03/02/2021] [Indexed: 12/13/2022] Open
Abstract
Background: Voxel-based morphometry (VBM) has been widely used to investigate structural alterations in amnesia mild cognitive impairment (aMCI). However, inconsistent results have hindered our understanding of the exact neuropathology related to aMCI. Objectives: Our aim was to systematically review the literature reporting VBM on aMCI to elucidate consistent gray matter alterations, their functional characterization, and corresponding co-activation patterns. Methods: The PubMed, Web of Science, and EMBASE databases were searched for VBM studies on aMCI published from inception up to June 2020. Peak coordinates were extracted from clusters that showed significant gray matter differences between aMCI patients and healthy controls (HC). Meta-analysis was performed using seed-based d mapping with the permutation of subject images (SDM-PSI), a newly improved meta-analytic method. Functional characterization and task-based co-activation patterns using the BrainMap database were performed on significant clusters to explore their functional roles. Finally, VBM was performed based on the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset to further support the findings. Results: A total of 31 studies with 681 aMCI patients and 837 HC were included in this systematic review. The aMCI group showed significant gray matter atrophy in the left amygdala and right hippocampus, which was consistent with results from the ADNI dataset. Functional characterization revealed that these regions were mainly associated with emotion, cognition, and perception. Further, meta-regression analysis demonstrated that gray matter atrophy in the left inferior frontal gyrus and the left angular gyrus was significantly associated with cognitive impairment in the aMCI group. Conclusions: The findings of gray matter atrophy in the left amygdala and right hippocampus are highly consistent and robust, and not only offer a better understanding of the underlying neuropathology but also provide accurate potential biomarkers for aMCI.
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Affiliation(s)
- Jinhuan Zhang
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.,Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yongfeng Liu
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Kai Lan
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Xingxian Huang
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Yuhai He
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China
| | - Fuxia Yang
- Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
| | - Jiaying Li
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Qingmao Hu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jinping Xu
- Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Haibo Yu
- The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.,Department of Acupuncture and Moxibustion, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, China
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21
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Zheng LJ, Lin L, Zhong J, Zhang Z, Ye YB, Zhang XY, Wang YF, Zhang H, Liu Y, Lu GM, Gong D, Zhang LJ. Gut dysbiosis-influence on amygdala-based functional activity in patients with end stage renal disease: a preliminary study. Brain Imaging Behav 2021; 14:2731-2744. [PMID: 32304020 DOI: 10.1007/s11682-019-00223-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Patients with end-stage renal disease (ESRD) are notably accompanied by cognitive disorder and anxiety or depressive symptom. We aimed to explore the linkages of the amygdala-based MR parameters, cognitive and mood performance, systematic inflammation and gut microbiota in ESRD. This prospective study enrolled 28 ESRD patients (13 males and 15 females, mean age of 43.9 ± 13.8 years) and 19 age- and sex-matched healthy control (HC) (12 males and 7 females, mean age of 44.1 ± 10.0 years). All subjects underwent cognitive assessment, inflammatory factor and stool microbiota analysis, and brain MRI analysis [amygdala-based functional connectivity and voxel-based morphometry (VBM)]. ERSD was separated by different microbiota strains. All factors were compared between ESRD and HC, as well as between ESRD subgroups. Pearson correlation analysis and causal mediation analysis were conducted to further investigate the relationship among the factors derived from the gut microbiota, brain and systemic inflammation. ESRD displayed gut dysbiosis and increased systemic inflammation when compared to HC (all P < 0.05). Meanwhile, ESRD showed smaller VBM in amygdala, decreased functional connectivity in left amygdala - right inferior parietal lobe [P < 0.05, Gaussian Random Field (GRF) corrected] and worse cognitive or mood performance. Moreover, ESRD-B (Prevutella mainly), when compared to ESRD-A (Bacteroides mainly), displayed increased interleukin-6, self-rating anxiety scale and functional connectivity in left amygdala - bilateral anterior cingulate cortex / medial superior frontal cortex (P < 0.05, GRF corrected). Furthermore, the correlation network of ESRD showed that both gut dysbiosis and amygdala-based alteration were correlated with cognitive performance and systemic inflammation. Causal mediation analysis validated that the disrupted distribution of Roseburia indirectly regulated the amygdala-based functional connectivity through tumor necrosis factor-alpha. The gut dysbiosis induced by ESRD was closely related to pro-inflammatory cytokines, amygdala-based phenotype, and mood performance. The lower abundance in Roseburia indirectly modulated amygdala-based functional connectivity pattern by tumor necrosis factor-alpha, which might provide a new way in diagnosis and treatment in patients of ESRD with depressive/anxious mood.
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Affiliation(s)
- Li Juan Zheng
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Li Lin
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Jianhui Zhong
- The Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, 38 Zheda Rd, Zhejiang, 310027, Hangzhou, China.,Department of Imaging Sciences, University of Rochester, Rochester, NY, 14642, USA
| | - Zhihong Zhang
- National Clinical Research Center of Kidney Disease, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu Province, China
| | - Yu Bing Ye
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Xin Yuan Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Yun Fei Wang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Han Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Ya Liu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Guang Ming Lu
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China
| | - Dehua Gong
- National Clinical Research Center of Kidney Disease, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu Province, China.
| | - Long Jiang Zhang
- Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, 305 Zhongshan East Road, Xuanwu District, Nanjing, 210002, Jiangsu, China.
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22
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Chen H, Qi G, Zhang Y, Huang Y, Zhang S, Yang D, He J, Mu L, Zhou L, Zeng M. Altered Dynamic Amplitude of Low-Frequency Fluctuations in Patients With Migraine Without Aura. Front Hum Neurosci 2021; 15:636472. [PMID: 33679354 PMCID: PMC7928334 DOI: 10.3389/fnhum.2021.636472] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 01/07/2021] [Indexed: 11/22/2022] Open
Abstract
Migraine is a chronic and idiopathic disorder leading to cognitive and affective problems. However, the neural basis of migraine without aura is still unclear. In this study, dynamic amplitude of low-frequency fluctuations (dALFF) analyses were performed in 21 patients with migraine without aura and 21 gender- and age-matched healthy controls to identify the voxel-level abnormal functional dynamics. Significantly decreased dALFF in the bilateral anterior insula, bilateral lateral orbitofrontal cortex, bilateral medial prefrontal cortex, bilateral anterior cingulate cortex, and left middle frontal cortex were found in patients with migraine without aura. The dALFF values in the anterior cingulate cortex were negatively correlated with pain intensity, i.e., visual analog scale. Finally, support vector machine was used to classify patients with migraine without aura from healthy controls and achieved an accuracy of 83.33%, sensitivity of 90.48%, and specificity of 76.19%. Our findings provide the evidence that migraine influences the brain functional activity dynamics and reveal the neural basis for migraine, which could facilitate understanding the neuropathology of migraine and future treatment.
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Affiliation(s)
- Hong Chen
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Guiqiang Qi
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Yingxia Zhang
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Ying Huang
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Shaojin Zhang
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Dongjun Yang
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Junwei He
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Lan Mu
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Lin Zhou
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
| | - Min Zeng
- Department of Radiology, The Third Affiliated Hospital of Chengdu Medical College, Pidu District People's Hospital, Chengdu, China
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23
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Shao R, Liu HL, Huang CM, Chen YL, Gao M, Lee SH, Lin C, Lee TMC. Loneliness and depression dissociated on parietal-centered networks in cognitive and resting states. Psychol Med 2020; 50:2691-2701. [PMID: 31615593 DOI: 10.1017/s0033291719002782] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Perceived loneliness, an increasingly prevalent social issue, is closely associated with major depressive disorder (MDD). However, the neural mechanisms previously implicated in key cognitive and affective processes in loneliness and MDD still remain unclear. Such understanding is critical for delineating the psychobiological basis of the relationship between loneliness and MDD. METHODS We isolated the unique and interactive cognitive and neural substrates of loneliness and MDD among 27 MDD patients (mean age = 51.85 years, 20 females), and 25 matched healthy controls (HCs; mean age = 48.72 years, 19 females). We assessed participants' behavioral performance and neural regional and network functions on a Stroop color-word task, and their resting-state neural connectivity. RESULTS Behaviorally, we found greater incongruence-related accuracy cost in MDD patients, but reduced incongruence effect on reaction time in lonelier individuals. When performing the Stroop task, loneliness positively predicted prefrontal-anterior cingulate-parietal connectivity across all participants, whereas MDD patients showed a decrease in connectivity compared to controls. Furthermore, loneliness negatively predicted parietal and cerebellar activities in MDD patients, but positively predicted the same activities in HCs. During resting state, MDD patients showed reduced parietal-anterior cingulate connectivity, which again positively correlated with loneliness in this group. CONCLUSIONS We speculate the distinct neurocognitive profile of loneliness might indicate increase in both bottom-up attention and top-down executive control functions. However, the upregulated cognitive control processes in lonely individuals may eventually become exhausted, which may in turn predispose to MDD onset.
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Affiliation(s)
- Robin Shao
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
- Laboratory of Neuropsychology, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Ho-Ling Liu
- Department of Imaging Physics, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Chih-Mao Huang
- College of Biological Science and Technology, National Chiao Tung University, Hsinchu, Taiwan
| | - Yao-Liang Chen
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Mengxia Gao
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
- Laboratory of Neuropsychology, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Shwu-Hua Lee
- Department of Psychiatry, Linkou Chang Gung Memorial Hospital, Taoyuan City, Taiwan
- College of Medicine, Chang Gung University, Taoyuan City, Taiwan
| | - Chemin Lin
- Department of Psychiatry, Chang Gung Memorial Hospital, Keelung City, Taiwan
| | - Tatia M C Lee
- State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong
- Laboratory of Neuropsychology, The University of Hong Kong, Pok Fu Lam, Hong Kong
- Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangzhou, China
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24
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Bellucci G, Camilleri JA, Eickhoff SB, Krueger F. Neural signatures of prosocial behaviors. Neurosci Biobehav Rev 2020; 118:186-195. [PMID: 32707344 PMCID: PMC7958651 DOI: 10.1016/j.neubiorev.2020.07.006] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2020] [Revised: 05/02/2020] [Accepted: 07/10/2020] [Indexed: 12/12/2022]
Abstract
Prosocial behaviors are hypothesized to require socio-cognitive and empathic abilities-engaging brain regions attributed to the mentalizing and empathy brain networks. Here, we tested this hypothesis with a coordinate-based meta-analysis of 600 neuroimaging studies on prosociality, mentalizing and empathy (∼12,000 individuals). We showed that brain areas recruited by prosocial behaviors only partially overlap with the mentalizing (dorsal posterior cingulate cortex) and empathy networks (middle cingulate cortex). Additionally, the dorsolateral and ventromedial prefrontal cortices were preferentially activated by prosocial behaviors. Analyses on the functional connectivity profile and functional roles of the neural patterns underlying prosociality revealed that in addition to socio-cognitive and empathic processes, prosocial behaviors further involve evaluation processes and action planning, likely to select the action sequence that best satisfies another person's needs. By characterizing the multidimensional construct of prosociality at the neural level, we provide insights that may support a better understanding of normal and abnormal social cognition (e.g., psychopathy).
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Affiliation(s)
- Gabriele Bellucci
- Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
| | - Julia A Camilleri
- Institute for Neuroscience and Medicine (INM-7), Research Center Jülich, Germany; Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute for Neuroscience and Medicine (INM-7), Research Center Jülich, Germany; Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Frank Krueger
- School of Systems Biology, George Mason University, Fairfax, VA, USA; Department of Psychology, George Mason University, Fairfax, VA, USA
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25
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Bellucci G, Camilleri JA, Iyengar V, Eickhoff SB, Krueger F. The emerging neuroscience of social punishment: Meta-analytic evidence. Neurosci Biobehav Rev 2020; 113:426-439. [PMID: 32302599 PMCID: PMC7291369 DOI: 10.1016/j.neubiorev.2020.04.011] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 04/08/2020] [Accepted: 04/09/2020] [Indexed: 02/07/2023]
Abstract
Social punishment (SOP)-third-party punishment (TPP) and second-party punishment (SPP)-sanctions norm-deviant behavior. The hierarchical punishment model (HPM) posits that TPP is an extension of SPP and both recruit common processes engaging large-scale domain-general brain networks. Here, we provided meta-analytic evidence to the HPM by combining the activation likelihood estimation approach with connectivity analyses and hierarchical clustering analyses. Although both forms of SOP engaged the dorsolateral prefrontal cortex and bilateral anterior insula (AI), a functional differentiation also emerged with TPP preferentially engaging social cognitive regions (temporoparietal junction) and SPP affective regions (AI). Further, although both TPP and SPP recruit domain-general networks (salience, default-mode, and central-executive networks), some specificity in network organization was observed. By revealing differences and commonalities of the neural networks consistently activated by different types of SOP, our findings contribute to a better understanding of the neuropsychological mechanisms of social punishment behavior--one of the most peculiar human behaviors.
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Affiliation(s)
- Gabriele Bellucci
- Department of Computational Neuroscience, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
| | - Julia A Camilleri
- Institute for Neuroscience and Medicine (INM-7), Research Center Jülich, Germany; Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Vijeth Iyengar
- Administration for Community Living/Administration on Aging, U.S. Department of Health and Human Services, Washington DC, USA
| | - Simon B Eickhoff
- Institute for Neuroscience and Medicine (INM-7), Research Center Jülich, Germany; Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Frank Krueger
- School of Systems Biology, George Mason University, Fairfax, VA, USA; Department of Psychology, George Mason University, Fairfax, VA, USA.
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26
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Abstract
BACKGROUND Brain regions are functionally diverse, and a given region may engage in a variety of tasks. This functional diversity of brain regions may be one factor that has prevented the finding of consistent biomarkers for brain disorders such as autism spectrum disorder (ASD). Thus, methods to characterise brain regions would help to determine how functional abnormalities contribute to affected behaviours. AIMS As the first illustration of the meta-analytic behavioural profiling procedure, we evaluated how the regions with disrupted connectivity in ASD contributed to various behaviours. METHOD Connectivity abnormalities were determined from a published degree centrality group comparison based on functional magnetic resonance imaging data from the Autism Brain Imaging Data Exchange. Using BrainMap's database of task-based neuroimaging studies, behavioural profiles were created for abnormally connected regions by relating these regions to tasks activating them. RESULTS Hyperconnectivity in ASD brains was significantly related to memory, attention, reasoning, social, execution and speech behaviours. Hypoconnectivity was related to vision, execution and speech behaviours. CONCLUSIONS The procedure outlines the first clinical neuroimaging application of a behavioural profiling method that estimates the functional diversity of brain regions, allowing for the relation of abnormal functional connectivity to diagnostic criteria. Behavioural profiling and the computational insights it provides can facilitate better understanding of the functional manifestations of various disorders, including ASD.
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Affiliation(s)
- William Snyder
- Student, Program in Neuroscience, Bucknell University; Research Assistant, Autism and Developmental Medicine Institute, Geisinger, USA
| | - Vanessa Troiani
- Assistant Professor, Autism and Developmental Medicine Institute, Geisinger; and Department of Basic Sciences, Geisinger Commonwealth School of Medicine, USA
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27
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Ishida T, Dierks T, Strik W, Morishima Y. Converging Resting State Networks Unravels Potential Remote Effects of Transcranial Magnetic Stimulation for Major Depression. Front Psychiatry 2020; 11:836. [PMID: 32973580 PMCID: PMC7468386 DOI: 10.3389/fpsyt.2020.00836] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Accepted: 07/31/2020] [Indexed: 12/20/2022] Open
Abstract
Despite being a commonly used protocol to treat major depressive disorder (MDD), the underlying mechanism of repetitive transcranial magnetic stimulation (rTMS) on dorsolateral prefrontal cortex (DLPFC) remains unclear. In the current study, we investigated the resting-state fMRI data of 100 healthy subjects by exploring three overlapping functional networks associated with the psychopathologically MDD-related areas (the nucleus accumbens, amygdala, and ventromedial prefrontal cortex). Our results showed that these networks converged at the bilateral DLPFC, which suggested that rTMS over DLPFC might improve MDD by remotely modulating the MDD-related areas synergistically. Additionally, they functionally converged at the DMPFC and bilateral insula which are known to be associated with MDD. These two areas could also be potential targets for rTMS treatment. Dynamic causal modelling (DCM) and Granger causality analysis (GCA) revealed that all pairwise connections among bilateral DLPFC, DMPFC, bilateral insula, and three psychopathologically MDD-related areas contained significant causality. The DCM results also suggested that most of the functional interactions between MDD-related areas and bilateral DLPFC, DMPFC, and bilateral insula can predominantly be explained by the effective connectivity from the psychopathologically MDD-related areas to the rTMS stimulation sites. Finally, we found the conventional functional connectivity to be a more representative measure to obtain connectivity parameters compared to GCA and DCM analysis. Our research helped inspecting the convergence of the functional networks related to a psychiatry disorder. The results identified potential targets for brain stimulation treatment and contributed to the optimization of patient-specific brain stimulation protocols.
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Affiliation(s)
- Takuya Ishida
- Center for Evolutionary Cognitive Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Meguro-ku, Japan.,Department of Neuropsychiatry, Graduate School of Wakayama Medical University, Kimiidera, Japan.,Division of Systems Neuroscience of Psychopathology, Translational Research Centre, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Thomas Dierks
- Division of Systems Neuroscience of Psychopathology, Translational Research Centre, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Werner Strik
- University Hospital of Psychiatry, University of Bern, Bern, Switzerland
| | - Yosuke Morishima
- Division of Systems Neuroscience of Psychopathology, Translational Research Centre, University Hospital of Psychiatry, University of Bern, Bern, Switzerland
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28
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Javaheripour N, Shahdipour N, Noori K, Zarei M, Camilleri JA, Laird AR, Fox PT, Eickhoff SB, Eickhoff CR, Rosenzweig I, Khazaie H, Tahmasian M. Functional brain alterations in acute sleep deprivation: An activation likelihood estimation meta-analysis. Sleep Med Rev 2019; 46:64-73. [PMID: 31063939 PMCID: PMC7279069 DOI: 10.1016/j.smrv.2019.03.008] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Revised: 03/18/2019] [Accepted: 03/21/2019] [Indexed: 12/26/2022]
Abstract
Sleep deprivation (SD) is a common problem in modern societies, which leads to cognitive dysfunctions including attention lapses, impaired working memory, hindering decision making, impaired emotional processing, and motor vehicle accidents. Numerous neuroimaging studies have investigated the neural correlates of SD, but these studies have reported inconsistent results. Thus, we aimed to identify convergent patterns of abnormal brain functions due to acute SD. Based on the preferred reporting for systematic reviews and meta-analyses statement, we searched the PubMed database and performed reference tracking and finally retrieved 31 eligible functional neuroimaging studies. Then, we applied activation estimation likelihood meta-analysis and found reduced activity mainly in the right intraparietal sulcus and superior parietal lobule. The functional decoding analysis using the BrainMap database indicated that this region is mostly related to visuospatial perception, memory and reasoning. The significant co-activation of this region using the BrainMap database were found in the left superior parietal lobule, intraparietal sulcus, bilateral occipital cortex, left fusiform gyrus and thalamus. This region also connected with the superior parietal lobule, intraparietal sulcus, insula, inferior frontal gyrus, precentral, occipital and cerebellum through resting-state functional connectivity in healthy subjects. Taken together, our findings highlight the role of superior parietal cortex in SD.
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Affiliation(s)
- Nooshin Javaheripour
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Niloofar Shahdipour
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Khadijeh Noori
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Mojtaba Zarei
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
| | - Julia A Camilleri
- Institute of Neuroscience and Medicine (INM-7), Research Center Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; South Texas Veterans Healthcare System University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine (INM-1; INM-7), Research Center Jülich, Jülich, Germany; Institute of Systems Neuroscience, Medical Faculty, Heinrich-Heine University, Düsseldorf, Germany
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine (INM-1; INM-7), Research Center Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Düsseldorf, Germany
| | - Ivana Rosenzweig
- Sleep Disorders Centre, Guy's and St Thomas' Hospital, GSTT NHS, London, UK; Sleep and Brain Plasticity Centre, Department of Neuroimaging, IOPPN, King's College London, London, UK
| | - Habibolah Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences, Kermanshah, Iran.
| | - Masoud Tahmasian
- Institute of Medical Science and Technology, Shahid Beheshti University, Tehran, Iran
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Wang L, Yu L, Wu F, Wu H, Wang J. Altered whole brain functional connectivity pattern homogeneity in medication-free major depressive disorder. J Affect Disord 2019; 253:18-25. [PMID: 31009844 DOI: 10.1016/j.jad.2019.04.040] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 03/11/2019] [Accepted: 04/07/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Many previous studies have revealed abnormal functional connectivity patterns between brain areas underlying the onset of major depressive disorder (MDD) using resting-state functional magnetic resonance imaging (rs-fMRI). However, how to exactly characterize the voxel-wise whole brain functional connectivity pattern changes in MDD remains unclear, which will provide more convincing evidence for localizing the exactly functional connectivity abnormality in MDD. METHODS In this study, we employed our newly developed whole brain functional connectivity homogeneity (FcHo) method to identify the voxel-wise changes of functional connectivity patterns in 27 medication-free MDD patients and 34 gender-, age-, and education level-matched healthy controls (HC). Furthermore, seed-based functional connectivity analysis was then used to identify the alteration of corresponding functional connectivity. RESULTS Significantly decreased FcHo values in right ventral anterior insula (INS) and medial prefrontal cortex (MPFC) were identified in MDD patients. The ensuing functional connectivity analyses identified decreased functional connectivity between MPFC and left angular gyrus (AG) in MDD patients. Moreover, both decreased FcHo values in INS, MPFC and functional connectivity between MPFC and left AG showed significant negative correlations with Hamilton depression rating scale (HDRS) scores. The FcHo values in INS were also negatively correlated with disease duration. Finally, meta-analysis based functional characterization found that these brain areas are mainly involved in emotion, theory of mind and reward processing. CONCLUSIONS Our findings revealed abnormal whole brain FcHo in INS and MPFC and functional interactions between MPFC and AG in MDD and suggested that dysfunctions of INS and MPFC play an important role in the neuropathology of MDD.
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Affiliation(s)
- Lijie Wang
- School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
| | - Lin Yu
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou 510370, China
| | - Fengchun Wu
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China
| | - Huawang Wu
- The Affiliated Brain Hospital of Guangzhou Medical University (Guangzhou Huiai Hospital), Guangzhou 510370, China; Guangdong Engineering Technology Research Center for Translational Medicine of Mental Disorders, Guangzhou 510370, China.
| | - Jiaojian Wang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, 610054, China.
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Schmitgen MM, Depping MS, Bach C, Wolf ND, Kubera KM, Vasic N, Hirjak D, Sambataro F, Wolf RC. Aberrant cortical neurodevelopment in major depressive disorder. J Affect Disord 2019; 243:340-347. [PMID: 30261449 DOI: 10.1016/j.jad.2018.09.021] [Citation(s) in RCA: 40] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2018] [Revised: 08/07/2018] [Accepted: 09/10/2018] [Indexed: 11/20/2022]
Abstract
BACKGROUND There is strong neuroimaging evidence that cortical alterations represent a core pathophysiological feature of major depressive disorder (MDD). Differential contributions of cortical features of neurodevelopmental origin, which may distinctly contribute to MDD vulnerability, disease-onset, or symptom expression, are unclear at present. METHODS We investigated distinct markers of cortical neurodevelopment, i.e. local cortical gyrification (LGI) and thickness (CT) in patients with MDD (n = 38) and healthy controls (HC, n = 22) using 3 T structural magnetic resonance imaging data and surface-based data analysis techniques. CT and LGI were computed using the Computational Anatomy Toolbox (CAT12). Analyses were performed for the entire cortical surface followed by a complementary regions-of-interest approach. RESULTS MDD patients showed significantly greater LGI in frontal, cingulate, parietal, temporal, and occipital regions compared to HC (FDR-corrected at p < 0.05 using threshold-free cluster enhancement). No significant differences of CT were found. In the MDD-group, correlations were found between duration of illness in years and number of depressive episodes and LGI of frontal, temporal, and parietal regions (p < 0.05). LIMITATIONS Main limitations are the relatively modest sample size and a cross-sectional study design. We did not control for early environmental factors potentially influencing neurodevelopment, such as childhood trauma. We report associations uncorrected for multiple comparisons. CONCLUSIONS The data suggest different local trajectories of cortical change in MDD. In addition, our data support the notion that aberrant cortical development may serve as a vulnerability marker of MDD, as well as a potential predictor of disease course.
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Affiliation(s)
- Mike M Schmitgen
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Vosstrasse 4, 69115 Heidelberg, Germany
| | - Malte S Depping
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Vosstrasse 4, 69115 Heidelberg, Germany
| | - Claudia Bach
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Vosstrasse 4, 69115 Heidelberg, Germany
| | - Nadine D Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Vosstrasse 4, 69115 Heidelberg, Germany
| | - Katharina M Kubera
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Vosstrasse 4, 69115 Heidelberg, Germany
| | - Nenad Vasic
- Department of Psychiatry and Psychotherapy, Clinical Center Christophsbad, Göppingen, Germany
| | - Dusan Hirjak
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University Mannheim, Germany
| | - Fabio Sambataro
- Department of Experimental and Clinical Medical Sciences (DISM), University of Udine, Italy
| | - Robert C Wolf
- Department of General Psychiatry, Center for Psychosocial Medicine, Heidelberg University, Vosstrasse 4, 69115 Heidelberg, Germany.
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31
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Zhang Z, Yan T, Wang Y, Zhang Q, Zhao W, Chen X, Zhai J, Chen M, Du B, Deng X, Ji F, Xiang Y, Wu H, Song J, Dong Q, Chen C, Li J. Polymorphism in schizophrenia risk gene MIR137 is associated with the posterior cingulate Cortex's activation and functional and structural connectivity in healthy controls. NEUROIMAGE-CLINICAL 2018; 19:160-166. [PMID: 30035013 PMCID: PMC6051762 DOI: 10.1016/j.nicl.2018.03.039] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Revised: 03/16/2018] [Accepted: 03/31/2018] [Indexed: 12/02/2022]
Abstract
MIR137 gene has been repeatedly reported as a schizophrenia risk gene in genome-wide association studies (GWAS). A polymorphism (rs1625579) at the MIR137 gene has been associated with both neural activation and behavioral performance during a working memory task. This study examined MIR137's associations with task-related (N-back working memory) fMRI, resting state fMRI, and diffusion tensor images (DTI) data in 177 healthy adults. We found less deactivation of the PCC in risk allele homozygotes (TT) as compared to the GT heterozygotes (cluster size = 630 voxels, cluster level PFWE < 0.001) during the N-back task, which replicated previous findings. Using the identified cluster within the PCC as the seed, we further found decreased functional connectivity between the PCC and the anterior cingulate cortex and its adjacent medial prefrontal cortex (ACC/MPFC) in risk allele homozygotes during both resting state (cluster size = 427 voxels, cluster level PFWE = 0.001) and the N-back task (cluster size = 73 voxels, cluster level PFWE = 0.05). Finally, an analysis of our DTI data showed decreased white matter integrity of the posterior cingulum in risk allele homozygotes (cluster size = 214 voxels, cluster level PFWE = 0.03). Taken together, rs1625579 seems to play an important role in both functional and structural connectivity between the PCC and the ACC/MPFC, which may serve as the brain mechanisms for the link between rs1625579 and schizophrenia. This study replicated the association between the risk allele of rs1625579 and altered activations at the PCC. This study found decreased functional connectivity between the PCC and the ACC/MPFC in the risk allele homozygotes. This study found decreased FA value in the posterior cingulum in the risk allele homozygotes.
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Affiliation(s)
- Zhifang Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Tongjun Yan
- The PLA 102nd Hospital and Mental Health Center of Military, Changzhou 213003, PR China
| | - Yanyan Wang
- The PLA 102nd Hospital and Mental Health Center of Military, Changzhou 213003, PR China
| | - Qiumei Zhang
- School of Mental Health, Jining Medical University, 45# Jianshe South Road, Jining 272013, Shandong Province, PR China; State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Wan Zhao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Xiongying Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Jinguo Zhai
- School of Mental Health, Jining Medical University, 45# Jianshe South Road, Jining 272013, Shandong Province, PR China
| | - Min Chen
- School of Mental Health, Jining Medical University, 45# Jianshe South Road, Jining 272013, Shandong Province, PR China
| | - Boqi Du
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Xiaoxiang Deng
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Feng Ji
- School of Mental Health, Jining Medical University, 45# Jianshe South Road, Jining 272013, Shandong Province, PR China
| | - Yutao Xiang
- Beijing Anding Hospital, Beijing 100088, PR China; Faculty of Health Sciences, University of Macau, Avenida da Universidade, Taipa, Macau
| | - Hongjie Wu
- Shengli Hospital of Shengli Petroleum Administration Bureau, Dongying 257022, Shandong Province, PR China
| | - Jie Song
- Shengli Hospital of Shengli Petroleum Administration Bureau, Dongying 257022, Shandong Province, PR China
| | - Qi Dong
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China
| | - Chuansheng Chen
- Department of Psychology and Social Behavior, University of California, Irvine, CA 92697, United States
| | - Jun Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, PR China; Center for Collaboration and Innovation in Brain and Learning Sciences, Beijing Normal University, PR China.
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Camilleri JA, Müller VI, Fox P, Laird AR, Hoffstaedter F, Kalenscher T, Eickhoff SB. Definition and characterization of an extended multiple-demand network. Neuroimage 2018; 165:138-147. [PMID: 29030105 PMCID: PMC5732056 DOI: 10.1016/j.neuroimage.2017.10.020] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 10/06/2017] [Accepted: 10/09/2017] [Indexed: 12/22/2022] Open
Abstract
Neuroimaging evidence suggests that executive functions (EF) depend on brain regions that are not closely tied to specific cognitive demands but rather to a wide range of behaviors. A multiple-demand (MD) system has been proposed, consisting of regions showing conjoint activation across multiple demands. Additionally, a number of studies defining networks specific to certain cognitive tasks suggest that the MD system may be composed of a number of sub-networks each subserving specific roles within the system. We here provide a robust definition of an extended MDN (eMDN) based on task-dependent and task-independent functional connectivity analyses seeded from regions previously shown to be convergently recruited across neuroimaging studies probing working memory, attention and inhibition, i.e., the proposed key components of EF. Additionally, we investigated potential sub-networks within the eMDN based on their connectional and functional similarities. We propose an eMDN network consisting of a core whose integrity should be crucial to performance of most operations that are considered higher cognitive or EF. This then recruits additional areas depending on specific demands.
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Affiliation(s)
- J A Camilleri
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1,7), 52425 Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany.
| | - V I Müller
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1,7), 52425 Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany
| | - P Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, Texas, United States
| | - A R Laird
- Department of Physics, Florida International University, Miami, United States
| | - F Hoffstaedter
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1,7), 52425 Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany
| | - T Kalenscher
- Institute of Comparative Psychology, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf Germany
| | - S B Eickhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1,7), 52425 Jülich, Germany; Institute of Systems Neuroscience, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University, Universitätstraße 1, 40225 Düsseldorf, Germany
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Kotkowski E, Price LR, Mickle Fox P, Vanasse TJ, Fox PT. The hippocampal network model: A transdiagnostic metaconnectomic approach. NEUROIMAGE-CLINICAL 2018; 18:115-129. [PMID: 29387529 PMCID: PMC5789756 DOI: 10.1016/j.nicl.2018.01.002] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/19/2017] [Revised: 01/05/2018] [Accepted: 01/06/2018] [Indexed: 12/14/2022]
Abstract
Purpose The hippocampus plays a central role in cognitive and affective processes and is commonly implicated in neurodegenerative diseases. Our study aimed to identify and describe a hippocampal network model (HNM) using trans-diagnostic MRI data from the BrainMap® database. We used meta-analysis to test the network degeneration hypothesis (NDH) (Seeley et al., 2009) by identifying structural and functional covariance in this hippocampal network. Methods To generate our network model, we used BrainMap's VBM database to perform a region-to-whole-brain (RtWB) meta-analysis of 269 VBM experiments from 165 published studies across a range of 38 psychiatric and neurological diseases reporting hippocampal gray matter density alterations. This step identified 11 significant gray matter foci, or nodes. We subsequently used meta-analytic connectivity modeling (MACM) to define edges of structural covariance between nodes from VBM data as well as functional covariance using the functional task-activation database, also from BrainMap. Finally, we applied a correlation analysis using Pearson's r to assess the similarities and differences between the structural and functional covariance models. Key findings Our hippocampal RtWB meta-analysis reported consistent and significant structural covariance in 11 key regions. The subsequent structural and functional MACMs showed a strong correlation between HNM nodes with a significant structural-functional covariance correlation of r = .377 (p = .000049). Significance This novel method of studying network covariance using VBM and functional meta-analytic techniques allows for the identification of generalizable patterns of functional and structural abnormalities pertaining to the hippocampus. In accordance with the NDH, this framework could have major implications in studying and predicting spatial disease patterns using network-based assays. We derived regions that structurally co-vary with the hippocampus in a network model using a transdiagnostic meta-analytic approach. We used meta-analytic connectivity mapping to assess inter-regional connectivity from BrainMap's structural and functional databases. We tested the network degeneration hypothesis by identifying network correlations between structural and functional networks.
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Affiliation(s)
- Eithan Kotkowski
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA.
| | - Larry R Price
- Department of Mathematics, Texas State University, San Marcos, TX, USA; College of Education, Texas State University, San Marcos, TX, USA
| | - P Mickle Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Thomas J Vanasse
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Psychiatry, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Radiology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Department of Neurology, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA; Institute for Neuroscience & Neurotechnology, Shenzhen University, Shenzen, China
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Towards understanding rTMS mechanism of action: Stimulation of the DLPFC causes network-specific increase in functional connectivity. Neuroimage 2017; 162:289-296. [DOI: 10.1016/j.neuroimage.2017.09.022] [Citation(s) in RCA: 106] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Revised: 09/08/2017] [Accepted: 09/09/2017] [Indexed: 02/04/2023] Open
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35
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Wensing T, Cieslik EC, Müller VI, Hoffstaedter F, Eickhoff SB, Nickl-Jockschat T. Neural correlates of formal thought disorder: An activation likelihood estimation meta-analysis. Hum Brain Mapp 2017; 38:4946-4965. [PMID: 28653797 DOI: 10.1002/hbm.23706] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 05/24/2017] [Accepted: 06/16/2017] [Indexed: 11/10/2022] Open
Abstract
Formal thought disorder (FTD) refers to a psychopathological dimension characterized by disorganized and incoherent speech. Whether symptoms of FTD arise from aberrant processing in language-related regions or more general cognitive networks, however, remains debated. Here, we addressed this question by a quantitative meta-analysis of published functional neuroimaging studies on FTD. The revised Activation Likelihood Estimation (ALE) algorithm was used to test for convergent aberrant activation changes in 18 studies (30 experiments) investigating FTD, of which 17 studies comprised schizophrenia patients and one study healthy subjects administered to S-ketamine. Additionally, we analyzed task-dependent and task-independent (resting-state) functional connectivity (FC) of brain regions showing convergence in activation changes. Subsequent functional characterization was performed for the initial clusters and the delineated connectivity networks by reference to the BrainMap database. Consistent activation changes were found in the left superior temporal gyrus (STG) and two regions within the left posterior middle temporal gyrus (p-MTG), ventrally (vp-MTG) and dorsally (dp-MTG). Functional characterization revealed a prominent functional association of ensuing clusters from our ALE meta-analysis with language and speech processing, as well as auditory perception in STG and with social cognition in dp-MTG. FC analysis identified task-dependent and task-independent networks for all three seed regions, which were mainly related to language and speech processing, but showed additional involvement in higher order cognitive functions. Our findings suggest that FTD is mainly characterized by abnormal activation in brain regions of the left hemisphere that are associated with language and speech processing, but also extend to higher order cognitive functions. Hum Brain Mapp 38:4946-4965, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Tobias Wensing
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Germany.,Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,JARA Translational Brain Medicine, Aachen, Germany
| | - Edna C Cieslik
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Veronika I Müller
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Felix Hoffstaedter
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Simon B Eickhoff
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, Germany.,Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany
| | - Thomas Nickl-Jockschat
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen, Germany.,JARA Translational Brain Medicine, Aachen, Germany
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Song XL, Kim GW, Moon CM, Jeong GW. Comparative functional neuroanatomy between implicit and explicit memory tasks under negative emotional condition in schizophrenia. Clin Imaging 2017; 44:27-32. [PMID: 28395192 DOI: 10.1016/j.clinimag.2017.03.021] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Revised: 02/01/2017] [Accepted: 03/29/2017] [Indexed: 11/15/2022]
Abstract
PURPOSE To evaluate the brain activation patterns in response to negative emotion during implicit and explicit memory in patients with schizophrenia. MATERIAL AND METHODS Fourteen patients with schizophrenia and 14 healthy controls were included in this study. The 3.0T fMRI was obtained while the subjects performed the implicit and explicit retrievals with unpleasant words. RESULTS The different predominant brain activation areas were observed during the implicit retrieval and explicit with unpleasant words. CONCLUSION The differential neural mechanisms between implicit and explicit memory tasks associated with negative emotional processing in schizophrenia.
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Affiliation(s)
- Xiao-Li Song
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Gwang-Won Kim
- Research Institute for Medical Imaging, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Chung-Man Moon
- Research Institute for Medical Imaging, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Gwang-Woo Jeong
- Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea; Research Institute for Medical Imaging, Chonnam National University Medical School, Gwangju, Republic of Korea.
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Tahmasian M, Eickhoff SB, Giehl K, Schwartz F, Herz DM, Drzezga A, van Eimeren T, Laird AR, Fox PT, Khazaie H, Zarei M, Eggers C, Eickhoff CR. Resting-state functional reorganization in Parkinson's disease: An activation likelihood estimation meta-analysis. Cortex 2017; 92:119-138. [PMID: 28467917 DOI: 10.1016/j.cortex.2017.03.016] [Citation(s) in RCA: 90] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2016] [Revised: 01/15/2017] [Accepted: 03/31/2017] [Indexed: 12/21/2022]
Abstract
Parkinson's disease (PD) is a common progressive neurodegenerative disorder. Studies using resting-state functional magnetic resonance imaging (fMRI) to investigate underlying pathophysiology of motor and non-motor symptoms in PD yielded largely inconsistent results. This quantitative neuroimaging meta-analysis aims to identify consistent abnormal intrinsic functional patterns in PD across studies. We used PubMed to retrieve suitable resting-state studies and stereotactic data were extracted from 28 individual between-group comparisons. Convergence across their findings was tested using the activation likelihood estimation (ALE) approach. We found convergent evidence for intrinsic functional disturbances in bilateral inferior parietal lobule (IPL) and the supramarginal gyrus in PD patients compared to healthy subjects. In follow-up task-based and task-independent functional connectivity (FC) analyses using two independent healthy subject data sets, we found that the regions showing convergent aberrations in PD formed an interconnected network mainly with the default mode network (DMN). Behavioral characterization of these regions using the BrainMap database suggested associated dysfunction of perception and executive processes. Taken together, our findings highlight the role of parietal cortex in the pathophysiology of PD.
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Affiliation(s)
- Masoud Tahmasian
- Department of Neurology, University Hospital Cologne, Germany; Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany; Institute of Medical Sciences and Technology, Shahid Beheshti University, Tehran, Iran; Sleep Disorders Research Center, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran.
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience & Medical Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1, INM-7), Research Center Jülich, Jülich, Germany
| | - Kathrin Giehl
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Frank Schwartz
- Department of Neurology, University Hospital Cologne, Germany
| | - Damian M Herz
- Medical Research Council Brain Network Dynamics Unit at the University of Oxford, Oxford, United Kingdom; Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Thilo van Eimeren
- Department of Neurology, University Hospital Cologne, Germany; Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA; South Texas Veterans Health Care System, San Antonio, TX, USA
| | - Habibolah Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran
| | - Mojtaba Zarei
- Institute of Medical Sciences and Technology, Shahid Beheshti University, Tehran, Iran; School of Cognitive Sciences, Institute for Research in Fundamental Sciences (IPM), Tehran, Iran
| | - Carsten Eggers
- Department of Neurology, University Hospital Cologne, Germany; Department of Neurology, Phillips University Marburg, Germany
| | - Claudia R Eickhoff
- Institute for Systems Neuroscience, Medical Faculty, Heinrich-Heine University Düsseldorf, Germany; Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany
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Fang L, Yao Z, An J, Chen X, Xie Y, Zhao H, Mao J, Liang W, Ma X. Topological Organization of Metabolic Brain Networks in Pre-Chemotherapy Cancer with Depression: A Resting-State PET Study. PLoS One 2016; 11:e0166049. [PMID: 27832148 PMCID: PMC5104370 DOI: 10.1371/journal.pone.0166049] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2016] [Accepted: 10/21/2016] [Indexed: 12/14/2022] Open
Abstract
This study aimed to investigate the metabolic brain network and its relationship with depression symptoms using 18F-fluorodeoxyglucose positron emission tomography data in 78 pre-chemotherapy cancer patients with depression and 80 matched healthy subjects. Functional and structural imbalance or disruption of brain networks frequently occur following chemotherapy in cancer patients. However, few studies have focused on the topological organization of the metabolic brain network in cancer with depression, especially those without chemotherapy. The nodal and global parameters of the metabolic brain network were computed for cancer patients and healthy subjects. Significant decreases in metabolism were found in the frontal and temporal gyri in cancer patients compared with healthy subjects. Negative correlations between depression and metabolism were found predominantly in the inferior frontal and cuneus regions, whereas positive correlations were observed in several regions, primarily including the insula, hippocampus, amygdala, and middle temporal gyri. Furthermore, a higher clustering efficiency, longer path length, and fewer hubs were found in cancer patients compared with healthy subjects. The topological organization of the whole-brain metabolic networks may be disrupted in cancer. Finally, the present findings may provide a new avenue for exploring the neurobiological mechanism, which plays a key role in lessening the depression effects in pre-chemotherapy cancer patients.
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Affiliation(s)
- Lei Fang
- Department of radiology, Qilu Hospital, First Affiliated Hospital of Shandong University, 107 Cultural West Road, Jinan, 250012, Shandong Province, P.R.China
- PET/CT Center, Affiliated Lanzhou General Hospital of Lanzhou Military Area Command, 333 South Binhe Road, Lanzhou, 730050, Gansu Province, P.R.China
| | - Zhijun Yao
- School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu Province, 730000, P.R.China
| | - Jianping An
- Nuclear Medicine Department, Affiliated Lanzhou General Hospital of Lanzhou Military Area Command, 333 South Binhe Road, Lanzhou, 730050, Gansu Province, P.R.China
| | - Xuejiao Chen
- School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu Province, 730000, P.R.China
| | - Yuanwei Xie
- School of Information Science and Engineering, Lanzhou University, Lanzhou, Gansu Province, 730000, P.R.China
| | - Hui Zhao
- Nuclear Medicine Department, Affiliated Lanzhou General Hospital of Lanzhou Military Area Command, 333 South Binhe Road, Lanzhou, 730050, Gansu Province, P.R.China
| | - Junfeng Mao
- PET/CT Center, Affiliated Lanzhou General Hospital of Lanzhou Military Area Command, 333 South Binhe Road, Lanzhou, 730050, Gansu Province, P.R.China
| | - Wangsheng Liang
- PET/CT Center, Affiliated Lanzhou General Hospital of Lanzhou Military Area Command, 333 South Binhe Road, Lanzhou, 730050, Gansu Province, P.R.China
| | - Xiangxing Ma
- Department of radiology, Qilu Hospital, First Affiliated Hospital of Shandong University, 107 Cultural West Road, Jinan, 250012, Shandong Province, P.R.China
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Chekouo T, Stingo FC, Guindani M, Do KA. A Bayesian predictive model for imaging genetics with application to schizophrenia. Ann Appl Stat 2016. [DOI: 10.1214/16-aoas948] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Resting-state test-retest reliability of a priori defined canonical networks over different preprocessing steps. Brain Struct Funct 2016; 222:1447-1468. [PMID: 27550015 DOI: 10.1007/s00429-016-1286-x] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2016] [Accepted: 08/09/2016] [Indexed: 01/12/2023]
Abstract
Resting-state functional connectivity analysis has become a widely used method for the investigation of human brain connectivity and pathology. The measurement of neuronal activity by functional MRI, however, is impeded by various nuisance signals that reduce the stability of functional connectivity. Several methods exist to address this predicament, but little consensus has yet been reached on the most appropriate approach. Given the crucial importance of reliability for the development of clinical applications, we here investigated the effect of various confound removal approaches on the test-retest reliability of functional-connectivity estimates in two previously defined functional brain networks. Our results showed that gray matter masking improved the reliability of connectivity estimates, whereas denoising based on principal components analysis reduced it. We additionally observed that refraining from using any correction for global signals provided the best test-retest reliability, but failed to reproduce anti-correlations between what have been previously described as antagonistic networks. This suggests that improved reliability can come at the expense of potentially poorer biological validity. Consistent with this, we observed that reliability was proportional to the retained variance, which presumably included structured noise, such as reliable nuisance signals (for instance, noise induced by cardiac processes). We conclude that compromises are necessary between maximizing test-retest reliability and removing variance that may be attributable to non-neuronal sources.
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Kogler L, Müller VI, Seidel EM, Boubela R, Kalcher K, Moser E, Habel U, Gur RC, Eickhoff SB, Derntl B. Sex differences in the functional connectivity of the amygdalae in association with cortisol. Neuroimage 2016; 134:410-423. [PMID: 27039701 PMCID: PMC6594554 DOI: 10.1016/j.neuroimage.2016.03.064] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2015] [Revised: 03/24/2016] [Accepted: 03/24/2016] [Indexed: 12/23/2022] Open
Abstract
Human amygdalae are involved in various behavioral functions such as affective and stress processing. For these behavioral functions, as well as for psychophysiological arousal including cortisol release, sex differences are reported. Here, we assessed cortisol levels and resting-state functional connectivity (rsFC) of left and right amygdalae in 81 healthy participants (42 women) to investigate potential modulation of amygdala rsFC by sex and cortisol concentration. Our analyses revealed that rsFC of the left amygdala significantly differed between women and men: Women showed stronger rsFC than men between the left amygdala and left middle temporal gyrus, inferior frontal gyrus, postcentral gyrus and hippocampus, regions involved in face processing, inner-speech, fear and pain processing. No stronger connections were detected for men and no sex difference emerged for right amygdala rsFC. Also, an interaction of sex and cortisol appeared: In women, cortisol was negatively associated with rsFC of the amygdalae with striatal regions, mid-orbital frontal gyrus, anterior cingulate gyrus, middle and superior frontal gyri, supplementary motor area and the parietal-occipital sulcus. Contrarily in men, positive associations of cortisol with rsFC of the left amygdala and these structures were observed. Functional decoding analyses revealed an association of the amygdalae and these regions with emotion, reward and memory processing, as well as action execution. Our results suggest that functional connectivity of the amygdalae as well as the regulatory effect of cortisol on brain networks differs between women and men. These sex-differences and the mediating and sex-dependent effect of cortisol on brain communication systems should be taken into account in affective and stress-related neuroimaging research. Thus, more studies including both sexes are required.
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Affiliation(s)
- Lydia Kogler
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Germany; Jülich-Aachen-Research Alliance, Translational Brain Medicine, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany.
| | - Veronika I Müller
- Institute of Neuroscience und Medicine, INM-1, Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Eva-Maria Seidel
- Department of Basic Psychological Research and Research Methods, Faculty of Psychology, University of Vienna, Vienna, Austria
| | - Roland Boubela
- MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Centre for Medical Physics and Biomedical Engineering, Medical University, Vienna, Austria
| | - Klaudius Kalcher
- MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Centre for Medical Physics and Biomedical Engineering, Medical University, Vienna, Austria
| | - Ewald Moser
- MR Centre of Excellence, Medical University of Vienna, Vienna, Austria; Centre for Medical Physics and Biomedical Engineering, Medical University, Vienna, Austria; Neuropsychiatry Division, Department of Psychiatry, Medical School, University of Pennsylvania, Philadelphia, USA
| | - Ute Habel
- Jülich-Aachen-Research Alliance, Translational Brain Medicine, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany; Institute of Neuroscience und Medicine, INM-6, Research Centre Jülich, Research Centre Jülich, Jülich, Germany; JARA BRAIN Institute 1: Structure Function Relationship
| | - Ruben C Gur
- Neuropsychiatry Division, Department of Psychiatry, Medical School, University of Pennsylvania, Philadelphia, USA
| | - Simon B Eickhoff
- Institute of Neuroscience und Medicine, INM-1, Research Centre Jülich, Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Birgit Derntl
- Department of Psychiatry and Psychotherapy, Medical School, University of Tübingen, Germany; Institute of Neuroscience und Medicine, INM-1, Research Centre Jülich, Jülich, Germany; Jülich-Aachen-Research Alliance, Translational Brain Medicine, Germany; Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany
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Deng D, Liao H, Duan G, Liu Y, He Q, Liu H, Tang L, Pang Y, Tao J. Modulation of the Default Mode Network in First-Episode, Drug-Naïve Major Depressive Disorder via Acupuncture at Baihui (GV20) Acupoint. Front Hum Neurosci 2016; 10:230. [PMID: 27242492 PMCID: PMC4869560 DOI: 10.3389/fnhum.2016.00230] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2015] [Accepted: 04/29/2016] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Previous neuroimaging studies have revealed that acupuncture modulates the default mode network (DMN) in healthy subjects and patients with certain disorder. However, few studies have been performed to investigate whether or not acupuncture might modulate the DMN in patients with major depressive disorder (MDD). Thereby, the aim of the present study was to assess alterations of the DMN induced by acupuncture stimulation in patients with first-episode, drug-naïve MDD. MATERIALS AND METHODS Twenty nine patients with first-episode, drug-naïve MDD and 29 healthy subjects were enrolled in this study. All the healthy subjects underwent 6-min resting-state functional magnetic resonance imaging (R-fMRI) scan. While patients underwent acupuncture stimulation for 20-min electro-acupuncture stimulation (EAS) at Baihui acupoint (GV20) and two 6-min R-fMRI scans before and after EAS. Based on the precuneus/posterior cingulate cortex (PC/PCC) as the seed region, functional connectivity (FC) method was adopted to examine abnormal DMN in patients by comparing with healthy subjects and to evaluate the influence of EAS on intrinsic connectivity within the DMN in patients with MDD. RESULTS Compared to healthy subjects, MDD patients had abnormal DMN. Moreover, results showed that EAS at GV20 induced increased FC between the PC/PCC and bilateral anterior cingulate cortex (ACC), and decreased FC between the PC/PCC and left middle prefrontal cortex, left angualr gyrus and bilateral hippocampus/parahippocampus (HIPP/paraHIPP) in patients with MDD, which were the main brain regions showing significant differences between the patients and healthy subjects. CONCLUSION Our findings provide imaging evidence to support that GV20-related acupuncture stimulation may modulate the DMN in patients with first-episode, drug-naïve MDD. This study may partly interpret the neural mechanisms of acupuncture at GV20 which is used to treat patients with MDD in clinical.
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Affiliation(s)
- Demao Deng
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Hai Liao
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Gaoxiong Duan
- Department of Radiology, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Yanfei Liu
- Life Science Research Center, School of Life Science and Technology, Xidian University Xi'an, China
| | - Qianchao He
- Department of Internal Neurology, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Huimei Liu
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Lijun Tang
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Yong Pang
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
| | - Jien Tao
- Department of Acupuncture, First Affiliated Hospital, Guangxi University of Chinese Medicine Nanning, China
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Tahmasian M, Rosenzweig I, Eickhoff SB, Sepehry AA, Laird AR, Fox PT, Morrell MJ, Khazaie H, Eickhoff CR. Structural and functional neural adaptations in obstructive sleep apnea: An activation likelihood estimation meta-analysis. Neurosci Biobehav Rev 2016; 65:142-56. [PMID: 27039344 PMCID: PMC5103027 DOI: 10.1016/j.neubiorev.2016.03.026] [Citation(s) in RCA: 87] [Impact Index Per Article: 10.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2015] [Revised: 03/27/2016] [Accepted: 03/29/2016] [Indexed: 12/14/2022]
Abstract
The right basolateral amygdala, the hippocampus and the right insular cortex are important nodes in obstructive sleep apnea (OSA). Functional characterization of these regions suggested associated dysfunction of emotional, sensory, and limbic processes in OSA. Connectivity analysis demonstrated that these regions are part of a joint network comprising the anterior insula, posterior-medial frontal cortex and thalamus.
Obstructive sleep apnea (OSA) is a common multisystem chronic disorder. Functional and structural neuroimaging has been widely applied in patients with OSA, but these studies have often yielded diverse results. The present quantitative meta-analysis aims to identify consistent patterns of abnormal activation and grey matter loss in OSA across studies. We used PubMed to retrieve task/resting-state functional magnetic resonance imaging and voxel-based morphometry studies. Stereotactic data were extracted from fifteen studies, and subsequently tested for convergence using activation likelihood estimation. We found convergent evidence for structural atrophy and functional disturbances in the right basolateral amygdala/hippocampus and the right central insula. Functional characterization of these regions using the BrainMap database suggested associated dysfunction of emotional, sensory, and limbic processes. Assessment of task-based co-activation patterns furthermore indicated that the two regions obtained from the meta-analysis are part of a joint network comprising the anterior insula, posterior-medial frontal cortex and thalamus. Taken together, our findings highlight the role of right amygdala, hippocampus and insula in the abnormal emotional and sensory processing in OSA.
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Affiliation(s)
- Masoud Tahmasian
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran; National Brain Mapping Center, Shahid Beheshti University (General & Medical campus), Tehran, Iran
| | - Ivana Rosenzweig
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, IOPPN, King's College and Imperial College, London, UK
| | - Simon B Eickhoff
- Institute of Clinical Neuroscience & Medical Psychology, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Amir A Sepehry
- Division of Neurology, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
| | - Angela R Laird
- Department of Physics, Florida International University, Miami, FL, USA
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center, San Antonio, TX, USA; South Texas Veterans Health Care System,San Antonio, TX 78229, USA
| | - Mary J Morrell
- Sleep and Brain Plasticity Centre, Department of Neuroimaging, IOPPN, King's College and Imperial College, London, UK; Academic Unit of Sleep and Breathing, National Heart and Lung Institute, Imperial College London, UK; NIHR Respiratory Disease Biomedical Research Unit at the Royal Brompton and Harefield NHS Foundation Trust and Imperial College London, UK
| | - Habibolah Khazaie
- Sleep Disorders Research Center, Kermanshah University of Medical Sciences (KUMS), Kermanshah, Iran.
| | - Claudia R Eickhoff
- Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany; Department of Psychiatry, Psychotherapy, and Psychosomatics, RWTH Aachen University, Aachen, Germany
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44
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Altered modular organization in schizophrenia patients and analysis using supervised association rule mining. Biocybern Biomed Eng 2016. [DOI: 10.1016/j.bbe.2016.02.002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
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45
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Gollan JK, Buchanan A, Connolly M, Hoxha D, Sankin L, Csernansky JG, Wang X. Differences in the neural correlates of affective responses in depressed and healthy women. Psychiatry Res 2015; 234:336-45. [PMID: 26490568 DOI: 10.1016/j.pscychresns.2015.10.006] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2014] [Revised: 09/22/2015] [Accepted: 10/01/2015] [Indexed: 12/11/2022]
Abstract
We aimed to characterize the extent to which there were differences in neural activation between female participants who were diagnosed with or without depression while viewing negative and neutral imagery. The study enrolled 105 medication-free, right-handed female participants between 17 and 63 years who met criteria for current Major Depressive Disorder (n=47) or no prior psychiatric diagnoses (n=58). All participants completed a clinical assessment and underwent a functional Magnetic Resonance Imaging (fMRI) scan while responding to an implicit affect task that required them to identify the location of ideographs embedded in one of four corners of each valenced image. When unpleasant (termed negative) stimuli were presented, depressed relative to healthy participants showed significantly decreased activation of the left amygdala and right Inferior Parietal Lobe (IPL). When activation was assessed during the negative versus neutral condition, depressed relative to healthy participants showed significantly increased activation in the Anterior Cingulate Cortex (ACC) and the left IPL. Notably, within-group analyses of healthy participants under the negative condition showed that depressive severity was positively correlated with activation in the left amygdala and left IPL. Our findings suggest that depression influences bottom-up and top-down processing of unpleasant information.
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Affiliation(s)
- Jackie K Gollan
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA.
| | - Angel Buchanan
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Megan Connolly
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Denada Hoxha
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Lindsey Sankin
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - John G Csernansky
- Department of Psychiatry and Behavioral Sciences, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Xue Wang
- Department of Radiology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611, USA
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46
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Cognition-related brain networks underpin the symptoms of unipolar depression: Evidence from a systematic review. Neurosci Biobehav Rev 2015; 61:53-65. [PMID: 26562681 DOI: 10.1016/j.neubiorev.2015.09.022] [Citation(s) in RCA: 65] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2015] [Revised: 09/16/2015] [Accepted: 09/21/2015] [Indexed: 01/23/2023]
Abstract
This systematic review sources the latest neuroimaging evidence for the role of cognition-related brain networks in depression, and relates their abnormal functioning to symptoms of the disorder. Using theoretically informed and rigorous inclusion criteria, we integrate findings from 59 functional neuroimaging studies of adults with unipolar depression using a narrative approach. Results demonstrate that two distinct neurocognitive networks, the autobiographic memory network (AMN) and the cognitive control network (CCN), are central to the symptomatology of depression. Specifically, hyperactivity of the introspective AMN is linked to pathological brooding, self-blame, rumination. Anticorrelated under-engagement of the CCN is associated with indecisiveness, negative automatic thoughts, poor concentration, distorted cognitive processing. Downstream effects of this imbalance include reduced regulation of networks linked to the vegetative and affective symptoms of depression. The configurations of these networks can change between individuals and over time, plausibly accounting for both the variable presentation of depressive disorders and their fluctuating course. Framing depression as a disorder of neurocognitive networks directly links neurobiology to psychiatric practice, aiding researchers and clinicians alike.
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Camilleri JA, Reid AT, Müller VI, Grefkes C, Amunts K, Eickhoff SB. Multi-Modal Imaging of Neural Correlates of Motor Speed Performance in the Trail Making Test. Front Neurol 2015; 6:219. [PMID: 26579066 PMCID: PMC4621429 DOI: 10.3389/fneur.2015.00219] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2015] [Accepted: 10/05/2015] [Indexed: 01/21/2023] Open
Abstract
The assessment of motor and executive functions following stroke or traumatic brain injury is a key aspect of impairment evaluation and used to guide further therapy. In clinical routine, such assessments are largely dominated by pen-and-paper tests. While these provide standardized, reliable, and ecologically valid measures of the individual level of functioning, rather little is yet known about their neurobiological underpinnings. Therefore, the aim of this study was to investigate brain regions and their associated networks that are related to upper extremity motor function, as quantified by the motor speed subtest of the trail making test (TMT-MS). Whole-brain voxel-based morphometry and whole-brain tract-based spatial statistics were used to investigate the association between TMT-MS performance with gray-matter volume (GMV) and white-matter integrity, respectively. While results demonstrated no relationship to local white-matter properties, we found a significant correlation between TMT-MS performance and GMV of the lower bank of the inferior frontal sulcus, a region associated with cognitive processing, as indicated by assessing its functional profile by the BrainMap database. Using this finding as a seed region, we further examined and compared networks as reflected by resting state connectivity, meta-analytic connectivity modeling, structural covariance, and probabilistic tractography. While differences between the different approaches were observed, all approaches converged on a network comprising regions that overlap with the multiple-demand network. Our data therefore indicate that performance may primarily depend on executive function, thus suggesting that motor speed in a more naturalistic setting should be more associated with executive rather than primary motor function. Moreover, results showed that while there were differences between the approaches, a convergence indicated that common networks can be revealed across highly divergent methods.
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Affiliation(s)
- Julia A Camilleri
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1) , Jülich , Germany ; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University , Düsseldorf , Germany
| | - Andrew T Reid
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1) , Jülich , Germany
| | - Veronika I Müller
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1) , Jülich , Germany ; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University , Düsseldorf , Germany
| | - Christian Grefkes
- Department of Neurology, University Hospital Cologne , Cologne , Germany
| | - Katrin Amunts
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1) , Jülich , Germany ; C. and O. Vogt Institute for Brain Research, Heinrich Heine University , Düsseldorf , Germany
| | - Simon B Eickhoff
- Research Centre Jülich, Institute of Neuroscience and Medicine (INM-1) , Jülich , Germany ; Institute of Clinical Neuroscience and Medical Psychology, Heinrich Heine University , Düsseldorf , Germany
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Kogler L, Müller VI, Chang A, Eickhoff SB, Fox PT, Gur RC, Derntl B. Psychosocial versus physiological stress - Meta-analyses on deactivations and activations of the neural correlates of stress reactions. Neuroimage 2015; 119:235-51. [PMID: 26123376 PMCID: PMC4564342 DOI: 10.1016/j.neuroimage.2015.06.059] [Citation(s) in RCA: 143] [Impact Index Per Article: 15.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2015] [Revised: 06/09/2015] [Accepted: 06/21/2015] [Indexed: 12/13/2022] Open
Abstract
Stress is present in everyday life in various forms and situations. Two stressors frequently investigated are physiological and psychosocial stress. Besides similar subjective and hormonal responses, it has been suggested that they also share common neural substrates. The current study used activation-likelihood-estimation meta-analysis to test this assumption by integrating results of previous neuroimaging studies on stress processing. Reported results are cluster-level FWE corrected. The inferior frontal gyrus (IFG) and the anterior insula (AI) were the only regions that demonstrated overlapping activation for both stressors. Analysis of physiological stress showed consistent activation of cognitive and affective components of pain processing such as the insula, striatum, or the middle cingulate cortex. Contrarily, analysis across psychosocial stress revealed consistent activation of the right superior temporal gyrus and deactivation of the striatum. Notably, parts of the striatum appeared to be functionally specified: the dorsal striatum was activated in physiological stress, whereas the ventral striatum was deactivated in psychosocial stress. Additional functional connectivity and decoding analyses further characterized this functional heterogeneity and revealed higher associations of the dorsal striatum with motor regions and of the ventral striatum with reward processing. Based on our meta-analytic approach, activation of the IFG and the AI seems to indicate a global neural stress reaction. While physiological stress activates a motoric fight-or-flight reaction, during psychosocial stress attention is shifted towards emotion regulation and goal-directed behavior, and reward processing is reduced. Our results show the significance of differentiating physiological and psychosocial stress in neural engagement. Furthermore, the assessment of deactivations in addition to activations in stress research is highly recommended.
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Affiliation(s)
- Lydia Kogler
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany; Jülich-Aachen-Research Alliance, Translational Brain Medicine, Germany.
| | - Veronika I Müller
- Institute of Neuroscience und Medicine, INM-1, Research Centre Jülich, 52425 Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Amy Chang
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany; Scripps College, Claremont, CA, USA
| | - Simon B Eickhoff
- Institute of Neuroscience und Medicine, INM-1, Research Centre Jülich, 52425 Jülich, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
| | - Peter T Fox
- Research Imaging Institute, University of Texas Health Science Center at San Antonio, 8403 Floyd Curl Dr, San Antonio, TX 78229, USA; South Texas Veterans Administration Medical Center, San Antonio, TX, USA
| | - Ruben C Gur
- Neuropsychiatry Division, Department of Psychiatry, Medical School, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Birgit Derntl
- Department of Psychiatry, Psychotherapy and Psychosomatics, Medical Faculty, RWTH Aachen University, Pauwelsstr. 30, 52074 Aachen, Germany; Jülich-Aachen-Research Alliance, Translational Brain Medicine, Germany; Institute of Neuroscience und Medicine, INM-1, Research Centre Jülich, 52425 Jülich, Germany
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Hardwick RM, Lesage E, Eickhoff CR, Clos M, Fox P, Eickhoff SB. Multimodal connectivity of motor learning-related dorsal premotor cortex. Neuroimage 2015; 123:114-28. [PMID: 26282855 DOI: 10.1016/j.neuroimage.2015.08.024] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2015] [Revised: 08/06/2015] [Accepted: 08/10/2015] [Indexed: 01/02/2023] Open
Abstract
The dorsal premotor cortex (dPMC) is a key region for motor learning and sensorimotor integration, yet we have limited understanding of its functional interactions with other regions. Previous work has started to examine functional connectivity in several brain areas using resting state functional connectivity (RSFC) and meta-analytical connectivity modelling (MACM). More recently, structural covariance (SC) has been proposed as a technique that may also allow delineation of functional connectivity. Here, we applied these three approaches to provide a comprehensive characterization of functional connectivity with a seed in the left dPMC that a previous meta-analysis of functional neuroimaging studies has identified as playing a key role in motor learning. Using data from two sources (the Rockland sample, containing resting state data and anatomical scans from 132 participants, and the BrainMap database, which contains peak activation foci from over 10,000 experiments), we conducted independent whole-brain functional connectivity mapping analyses of a dPMC seed. RSFC and MACM revealed similar connectivity maps spanning prefrontal, premotor, and parietal regions, while the SC map identified more widespread frontal regions. Analyses indicated a relatively consistent pattern of functional connectivity between RSFC and MACM that was distinct from that identified by SC. Notably, results indicate that the seed is functionally connected to areas involved in visuomotor control and executive functions, suggesting that the dPMC acts as an interface between motor control and cognition.
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Affiliation(s)
- Robert M Hardwick
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University, USA
| | - Elise Lesage
- Neuroimaging Research Branch, National Institutes of Drug Abuse, Baltimore, USA
| | - Claudia R Eickhoff
- Institute for Neuroscience and Medicine (INM-1), Research Center Jülich, Germany; Dept. of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University Hospital, Germany
| | - Mareike Clos
- Institute for Neuroscience and Medicine (INM-1), Research Center Jülich, Germany; Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany
| | | | - Simon B Eickhoff
- Institute for Neuroscience and Medicine (INM-1), Research Center Jülich, Germany; Institute for Clinical Neuroscience and Medical Psychology, Heinrich-Heine-Universität, Germany.
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Tseng HH, Bossong MG, Modinos G, Chen KM, McGuire P, Allen P. A systematic review of multisensory cognitive–affective integration in schizophrenia. Neurosci Biobehav Rev 2015; 55:444-52. [DOI: 10.1016/j.neubiorev.2015.04.019] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Revised: 03/25/2015] [Accepted: 04/26/2015] [Indexed: 11/16/2022]
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