1
|
Vassall SG, Wallace MT. Sensory and Multisensory Processing Changes and Their Contributions to Autism and Schizophrenia. Curr Top Behav Neurosci 2025. [PMID: 40346436 DOI: 10.1007/7854_2025_589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/11/2025]
Abstract
Natural environments are typically multisensory, comprising information from multiple sensory modalities. It is in the integration of these incoming sensory signals that we form our perceptual gestalt that allows us to navigate through the world with relative ease. However, differences in multisensory integration (MSI) ability are found in a number of clinical conditions. Throughout this chapter, we discuss how MSI differences contribute to phenotypic characterization of autism and schizophrenia. Although these clinical populations are often described as opposite each other on a number of spectra, we describe similarities in behavioral performance and neural functions between the two conditions. Understanding the shared features of autism and schizophrenia through the lens of MSI research allows us to better understand the neural and behavioral underpinnings of both disorders. We provide potential avenues for remediation of MSI function in these populations.
Collapse
Affiliation(s)
- Sarah G Vassall
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, TN, USA
| | - Mark T Wallace
- Department of Psychology, Vanderbilt University, Nashville, TN, USA.
- Department of Hearing and Speech, Vanderbilt University Medical Center, Nashville, TN, USA.
- Vanderbilt Vision Research Center, Nashville, TN, USA.
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA.
- Department of Pharmacology, Vanderbilt University, Nashville, TN, USA.
- Vanderbilt Kennedy Center, Vanderbilt University Medical Center, Nashville, TN, USA.
| |
Collapse
|
2
|
Dudina AN, Tomyshev AS, Ilina EV, Romanov DV, Lebedeva IS. Structural and functional alterations in different types of delusions across schizophrenia spectrum: A systematic review. Prog Neuropsychopharmacol Biol Psychiatry 2025; 136:111185. [PMID: 39486472 DOI: 10.1016/j.pnpbp.2024.111185] [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: 06/05/2024] [Revised: 10/22/2024] [Accepted: 10/27/2024] [Indexed: 11/04/2024]
Abstract
BACKGROUND Despite the high clinical role of delusions as a transnosological psychopathological phenomenon, the number of experimental studies on the different types of delusions across schizophrenia spectrum is still relatively small, and their results are somehow inconsistent. We aimed to understand the current state of knowledge regarding the structural and functional brain alterations in delusions to determine whether particular types of delusions are associated with specific brain changes and to identify common alterations underlying the formation and persistence of delusions regardless of their content. METHODS For this systematic review, we followed PRISMA guidelines to search in PubMed for English papers published between 1953 and September 30, 2023. The initial inclusion criteria for screening purposes were articles that investigated delusions or subclinical delusional beliefs in schizophrenia spectrum disorders, high clinical or genetic risk for schizophrenia using fMRI, sMRI or/and dwMRI methods. Exclusion criteria during the screening phase were articles that investigated lesion-induced or substance-induced delusions, delusions in Alzheimer's disease and other neurocognitive disorders, single case studies and non-human studies. The publication metadata were uploaded to the web-tool for working on systematic reviews, Rayyan. For each of the studies, a table was filled out with detailed information. RESULTS We found 1752 records, of which 95 full-text documents were reviewed and included in the current paper. Both nonspecific and particular types of delusions were associated with widespread structural and functional alterations. The most prominent areas affected across all types of delusions were the superior temporal cortex (predominantly left language processing areas), anterior cingulate/medial prefrontal cortex and insula. The most reproducible findings in paranoia may be alterations in the functioning of the amygdala and its interactions with other regions. Somatic delusions and delusional infestation were mostly characterized by alterations in the insula and thalamus. DISCUSSION The data are ambiguous; however, in general the predictive processing framework seems to be the most widely accepted approach to explaining different types of delusions. Aberrant prediction errors signaling during processing of social, self-generated and sensory information may lead to inaccuracies in assessing the intentions of others, self-relevancy of ambiguous stimuli, misattribution of self-generated actions and unusual sensations, which could provoke delusional ideation with persecutory, reference, control and somatic content correspondingly. However, currently available data are still insufficient to draw conclusions about the specific biological mechanisms of predictive coding account of delusions. Thus, further studies exploring more homogeneous groups and interaction of diagnoses by types of delusions are needed. There are also some limitations in this review. Studies that investigate delusions induced by lesions, substance abuse or neurodegeneration and studies using modalities other than fMRI, sMRI or dwMRI were not included in the review. Due to the relatively small number of publications, we systematized them based on a certain type of delusions, while the results could also be affected by the diagnosis of patients, the presence and type of therapy, illness duration etc.
Collapse
Affiliation(s)
- Anastasiia N Dudina
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation.
| | - Alexander S Tomyshev
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation
| | - Ekaterina V Ilina
- I.M. Sechenov First Moscow State Medical University, 8-2 Trubetskaya Str, Moscow 119991, Russian Federation
| | - Dmitriy V Romanov
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation; I.M. Sechenov First Moscow State Medical University, 8-2 Trubetskaya Str, Moscow 119991, Russian Federation
| | - Irina S Lebedeva
- Mental Health Research Center, 34 Kashirskoye Sh, Moscow 115522, Russian Federation
| |
Collapse
|
3
|
Martino M, Magioncalda P. A working model of neural activity and phenomenal experience in psychosis. Mol Psychiatry 2024; 29:3814-3825. [PMID: 38844531 DOI: 10.1038/s41380-024-02607-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 05/02/2024] [Accepted: 05/09/2024] [Indexed: 12/05/2024]
Abstract
According to classical phenomenology, phenomenal experience is composed of perceptions (related to environmental stimuli) and imagery/ideas (unrelated to environmental stimuli). Intensity/vividness is supposed to represent the key phenomenal difference between perceptions and ideas, higher in perceptions than ideas, and thus the core subjective criterion to distinguish reality from imagination. At a neural level, phenomenal experience is related to brain activity in the sensory areas, driven by receptor stimulation (underlying perception) or associative areas (underlying imagery/ideas). An alteration of the phenomenal experience that leads to a loss of contact with reality characterizes psychosis, which mainly consists of hallucinations (false perceptions) and delusions (fixed ideas). According to the current data on their neural correlates across subclinical conditions and different neuropsychiatric disorders (such as schizophrenia), hallucinations are mainly associated with: transient (modality-specific) activations of sensory cortices (primarily superior temporal gyrus, occipito-temporal cortex, postcentral gyrus, and insula) during the hallucinatory experience; increased intrinsic activity/connectivity of associative/default-mode network (DMN) areas (primarily temporoparietal junction, posterior cingulate cortex, and medial prefrontal cortex); and deficits in the sensory systems. Analogously, delusions are mainly associated with increased intrinsic activity/connectivity of associative/DMN areas (primarily medial prefrontal cortex). Integrating these data into our three-dimensional model of neural activity and phenomenal-behavioral patterns, we propose the following model of psychosis. A functional/structural deficit in the sensory systems complemented by a functional reconfiguration of intrinsic brain activity favoring hyperactivity of associative/DMN areas may drive neuronal activations in the sensory (auditory/visual/somatosensory) areas and insular (interoceptive) areas with spatiotemporal configurations maximally independent from environmental stimuli and predominantly related to associative processing. This manifests in perception deficit and imagery/ideas composed of exteroceptive-like and interoceptive/affective-like elements that show a phenomenal intensity indistinguishable from perceptions, impairing the reality monitoring, along with minimal changeability by environmental stimuli, ultimately resulting in dissociation of the phenomenal experience from the environment, i.e., psychosis.
Collapse
Affiliation(s)
- Matteo Martino
- Graduate Institute of Mind Brain and Consciousness, Taipei Medical University, Taipei, Taiwan.
| | - Paola Magioncalda
- International Master/Ph.D. Program in Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
- Department of Medical Research, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
- Department of Radiology, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan.
| |
Collapse
|
4
|
Liu X, Liu Z, Wang F, Cheng P, Yang J, Tan W, Cheng Y, Huang D, Xiang Z, Zhang J, Li J, Xie Y, Zhong M, Yang J. A connectome-based model of delusion in schizophrenia using functional connectivity under working memory task. J Psychiatr Res 2024; 177:75-81. [PMID: 38981411 DOI: 10.1016/j.jpsychires.2024.07.007] [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: 03/24/2024] [Revised: 06/30/2024] [Accepted: 07/03/2024] [Indexed: 07/11/2024]
Abstract
Delusion is an important feature of schizophrenia, which may stem from cognitive biases. Working memory (WM) is the core foundation of cognition, closely related to delusion. However, the knowledge of neural mechanisms underlying the relationship between WM and delusion in schizophrenia is poorly investigated. Two hundred and thirty patients with schizophrenia (dataset 1: n = 130; dataset 2: n = 100) were enrolled and scanned for an N-back WM task. We constructed the WM-related whole-brain functional connectome and conducted Connectome-based Predictive Modelling (CPM) to detect the delusion-related networks and built the correlation model in dataset 1. The correlation between identified networks and delusion severity was tested in a separate, heterogeneous sample of dataset 2 that mainly includes early-onset schizophrenia. The identified delusion-related network has a strong correlation with delusion severity measured by the NO.20 item of SAPS in dataset 1 (r = 0.433, p = 2.7 × 10-7, permutation-p = 0.035), and can be validated in the same dataset by using another delusion measurement, that is, the P1 item of PANSS (r = 0.362, p = 0.0005). It can be validated in another independent dataset 2 (NO.20 item of SAPS for r = 0.31, p = 0.0024, P1 item of PANSS for r = 0.27, p = 0.0074). The delusion-related network comprises the connections between the default mode network (DMN), cingulo-opercular network (CON), salience network (SN), subcortical, sensory-somatomotor network (SMN), and visual networks. We successfully established correlation models of individualized delusion based on the WM-related functional connectome and showed a strong correlation between delusion severity and connections within the DMN, CON, SMN, and subcortical network.
Collapse
Affiliation(s)
- Xiawei Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Zhening Liu
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Feiwen Wang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Peng Cheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jun Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Wenjian Tan
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Yixin Cheng
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Danqing Huang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Zhibiao Xiang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jiamei Zhang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jinyue Li
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Yuxin Xie
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Maoxing Zhong
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China
| | - Jie Yang
- Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China.
| |
Collapse
|
5
|
Gu YW, Fan JW, Zhao SW, Liu XF, Yin H, Cui LB. Large-scale mechanism hypothesis and research prospects of cognitive impairment in schizophrenia based on magnetic resonance imaging. Heliyon 2024; 10:e25915. [PMID: 38404811 PMCID: PMC10884805 DOI: 10.1016/j.heliyon.2024.e25915] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 01/09/2024] [Accepted: 02/05/2024] [Indexed: 02/27/2024] Open
Abstract
Cognitive impairments in schizophrenia are pivotal clinical issues that need to be solved urgently. However, the mechanism remains unknown. It has been suggested that cognitive impairments in schizophrenia are associated with connectome damage, and are especially relevant to the disrupted hub nodes in the frontal and parietal lobes. Activating the dorsolateral prefrontal cortex (DLPFC) via repetitive transcranial magnetic stimulation (rTMS) could result in improved cognition. Based on several previous magnetic resonance imaging (MRI) studies on schizophrenia, we found that the first-episode patients showed connectome damage, as well as abnormal activation and connectivity of the DLPFC and inferior parietal lobule (IPL). Accordingly, we proposed that DLPFC-IPL pathway destruction might mediate connectome damage of cognitive impairments in schizophrenia. In the meantime, with the help of multimodal MRI and noninvasive neuromodulation tool, we may not only validate the hypothesis, but also find IPL as the potential intervention target for cognitive impairments in schizophrenia.
Collapse
Affiliation(s)
- Yue-Wen Gu
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Radiology, The General Hospital of Western Theater Command, Chengdu, China
| | - Jing-Wen Fan
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Shu-Wan Zhao
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Xiao-Fan Liu
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
| | - Hong Yin
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Radiology, Xi'an People's Hospital (Xi'an Fourth Hospital), Xi'an, China
| | - Long-Biao Cui
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi’an, China
- Schizophrenia Imaging Lab, Xijing Hospital, Fourth Military Medical University, Xi’an, China
- Department of Radiology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| |
Collapse
|
6
|
Jameei H, Rakesh D, Zalesky A, Cairns MJ, Reay WR, Wray NR, Di Biase MA. Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review. Schizophr Bull 2024; 50:32-46. [PMID: 37354489 PMCID: PMC10754175 DOI: 10.1093/schbul/sbad087] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Abstract
BACKGROUND AND HYPOTHESIS Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology. STUDY DESIGN In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools. STUDY RESULTS In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9-80 years, Nrange = 64-76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community sample and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations. CONCLUSIONS Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.
Collapse
Affiliation(s)
- Hadis Jameei
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Divyangana Rakesh
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
| | - Andrew Zalesky
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Faculty of Engineering and Information Technology, The University of Melbourne, Parkville, VIC, Australia
| | - Murray J Cairns
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Newcastle, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - William R Reay
- School of Biomedical Sciences and Pharmacy, The University of Newcastle, Newcastle, NSW, Australia
- Precision Medicine Research Program, Hunter Medical Research Institute, Newcastle, NSW, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, Australia
| | - Maria A Di Biase
- Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Carlton South, VIC, Australia
- Department of Anatomy and Physiology, School of Biomedical Sciences, The University of Melbourne, VIC, Australia
- Department of Psychiatry, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
7
|
Liu XF, Zhao SW, Cui JJ, Gu YW, Fan JW, Fu YF, Zhang YH, Yin H, Chen K, Cui LB. Differential expression of diacylglycerol kinase ζ is involved in inferior parietal lobule-related dysfunction in schizophrenia with cognitive impairments. BMC Psychiatry 2023; 23:526. [PMID: 37479996 PMCID: PMC10362743 DOI: 10.1186/s12888-023-04955-x] [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: 04/21/2023] [Accepted: 06/13/2023] [Indexed: 07/23/2023] Open
Abstract
BACKGROUND Cognitive impairment is the main factor in the poor prognosis of schizophrenia, but its mechanism remains unclear. The inferior parietal lobule (IPL) is related to various clinical symptoms and cognitive impairment in schizophrenia. We aimed to explore the relationship between IPL-related functions and cognitive impairment in schizophrenia. METHODS 136 schizophrenia patients and 146 demographically matched healthy controls were enrolled for a cross-sectional study. High-spatial-resolution structural and resting-state functional images were acquired to demonstrate the alternations of brain structure and function. At the same time, the digit span and digit symbol coding tasks of the Chinese Wechsler Adult Intelligence Test Revised (WAIS-RC) were utilized in assessing the subjects' cognitive function. Patients were divided into cognitive impairment and normal cognitive groups according to their cognitive score and then compared whether there were differences between the three groups in fractional amplitude of low-frequency fluctuation (fALFF). In addition, we did a correlation analysis between cognitive function and the fALFF for the left IPL of patients and healthy controls. Based on the Allen Human Brain Atlas, we obtained genes expressed in the left IPL, which were then intersected with the transcriptome-wide association study results and differentially expressed genes in schizophrenia. RESULTS Grouping of patients by the backward digit span task and the digit symbol coding task showed differences in fALFF values between healthy controls and cognitive impairment patients (P < 0.05). We found a negative correlation between the backward digit span task score and fALFF of the left IPL in healthy controls (r = - 0.388, P = 0.003), which was not seen in patients (r = 0.203, P = 0.020). In addition, none of the other analyses were statistically significant (P > 0.017). In addition, we found that diacylglycerol kinase ζ (DGKζ) is differentially expressed in the left IPL and associated with schizophrenia. CONCLUSION Our study demonstrates that the left IPL plays a vital role in cognitive impairment in schizophrenia. DGKζ may act as an essential regulator in the left IPL of schizophrenia patients with cognitive impairment.
Collapse
Affiliation(s)
- Xiao-Fan Liu
- Department of Radiology, Xi'an People's Hospital, Xi'an, China
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Shu-Wan Zhao
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Jin-Jin Cui
- Department of Radiology, The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yue-Wen Gu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Jing-Wen Fan
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Yu-Fei Fu
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China
| | - Ya-Hong Zhang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Hong Yin
- Department of Radiology, Xi'an People's Hospital, Xi'an, China.
| | - Kun Chen
- Department of Human Anatomy and K. K. Leung Brain Research Centre, Fourth Military Medical University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
| | - Long-Biao Cui
- Schizophrenia Imaging Lab, Fourth Military Medical University, Xi'an, China.
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
- Shaanxi Provincial Key Laboratory of Clinic Genetics, Fourth Military Medical University, Xi'an, China.
- Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
| |
Collapse
|
8
|
Liu XQ, Ji XY, Weng X, Zhang YF. Artificial intelligence ecosystem for computational psychiatry: Ideas to practice. World J Meta-Anal 2023; 11:79-91. [DOI: 10.13105/wjma.v11.i4.79] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 03/18/2023] [Accepted: 04/04/2023] [Indexed: 04/14/2023] Open
|
9
|
Air pollution interacts with genetic risk to influence cortical networks implicated in depression. Proc Natl Acad Sci U S A 2021; 118:2109310118. [PMID: 34750260 DOI: 10.1073/pnas.2109310118] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/14/2021] [Indexed: 01/10/2023] Open
Abstract
Air pollution is a reversible cause of significant global mortality and morbidity. Epidemiological evidence suggests associations between air pollution exposure and impaired cognition and increased risk for major depressive disorders. However, the neural bases of these associations have been unclear. Here, in healthy human subjects exposed to relatively high air pollution and controlling for socioeconomic, genomic, and other confounders, we examine across multiple levels of brain network function the extent to which particulate matter (PM2.5) exposure influences putative genetic risk mechanisms associated with depression. Increased ambient PM2.5 exposure was associated with poorer reasoning and problem solving and higher-trait anxiety/depression. Working memory and stress-related information transfer (effective connectivity) across cortical and subcortical brain networks were influenced by PM2.5 exposure to differing extents depending on the polygenic risk for depression in gene-by-environment interactions. Effective connectivity patterns from individuals with higher polygenic risk for depression and higher exposures with PM2.5, but not from those with lower genetic risk or lower exposures, correlated spatially with the coexpression of depression-associated genes across corresponding brain regions in the Allen Brain Atlas. These converging data suggest that PM2.5 exposure affects brain network functions implicated in the genetic mechanisms of depression.
Collapse
|
10
|
Xi YB, Guo F, Liu WM, Fu YF, Li JM, Wang HN, Chen FL, Cui LB, Zhu YQ, Li C, Kang XW, Li BJ, Yin H. Triple network hypothesis-related disrupted connections in schizophrenia: A spectral dynamic causal modeling analysis with functional magnetic resonance imaging. Schizophr Res 2021; 233:89-96. [PMID: 34246865 DOI: 10.1016/j.schres.2021.06.024] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2020] [Revised: 04/15/2021] [Accepted: 06/21/2021] [Indexed: 10/20/2022]
Abstract
OBJECTIVE The symptom-related neurobiology characteristic of schizophrenia in the brain from a network perspective is still poorly understood, leading to a lack of potential biologically-based markers and difficulty identifying therapeutic targets. We aim to test the dysregulated cross-network interactions among the Salience Network (SN), Central Executive Network (CEN) and Default Mode Network (DMN) and how they contributed to different symptoms in schizophrenia patients. METHODS We examined network interactions among the SN, CEN and DMN in 76 patients with schizophrenia vs. 80 well-matched controls using dynamic causal modeling (DCM). We further analyzed the relation between network dynamics and Positive and Negative Syndrome Scale (PANSS). RESULTS We observed that the DMN, CEN and SN across healthy controls and schizophrenia patients showed several similarities within or between-network pattern in the resting state. Comparing schizophrenia to controls, SN-centered cross-network interactions were most significantly reduced. Crucially, the strength of connections from CEN subnetwork 1 to DMN subnetwork 1 was positively correlated with the Positive Score of PANSS. The connection from the DMN subnetwork 2 to CEN subnetwork 2 was negatively correlated with the Negative Score of PANSS. CONCLUSIONS Our study provides strong evidence for the dysregulation among SN, CEN and DMN in a triple-network perspective in schizophrenia. The connection between DMN and CEN could be clinically-relevant neurobiological signature of schizophrenia symptoms. Our study indicated that the description of brain triple network hypothesis could be a novel and possible bio-marker for schizophrenia.
Collapse
Affiliation(s)
- Yi-Bin Xi
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fan Guo
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Wen-Ming Liu
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Yu-Fei Fu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Jia-Ming Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Hua-Ning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Fu-Lin Chen
- College of Life Sciences, Northwest University, Taibai North Rd 229, Xi'an, Shaanxi, China
| | - Long-Biao Cui
- Department of Clinical Psychology, School of Medical Psychology, Fourth Military Medical University, Xi'an, Shaanxi, China; The Second Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Yuan-Qiang Zhu
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Chen Li
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Xiao-Wei Kang
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China
| | - Bao-Juan Li
- School of Biomedical Engineering, Fourth Military Medical University, Xi'an, Shaanxi, China.
| | - Hong Yin
- Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, Shaanxi, China.
| |
Collapse
|
11
|
Affiliation(s)
- Karl J Friston
- Wellcome Centre for Human Neuroimaging and Queen Square Institute of Neurology, University College London; and National Hospital for Neurology and Neurosurgery, London
| |
Collapse
|
12
|
Affiliation(s)
- Ned H Kalin
- Department of Psychiatry, University of Wisconsin School of Medicine and Public Health, Madison
| |
Collapse
|