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Kim MS, Kim K, Nam J, Lee SJ, Lee SW. Impact of Childhood Maltreatment on Cognitive Function and Its Relationship With Emotion Regulation in Young Adults. Soa Chongsonyon Chongsin Uihak 2024; 35:155-162. [PMID: 38966202 PMCID: PMC11220472 DOI: 10.5765/jkacap.240001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/13/2024] [Accepted: 03/19/2024] [Indexed: 07/06/2024] Open
Abstract
Objectives Childhood maltreatment can negatively impact cognitive development, including executive function, working memory, and processing speed. This study investigated the impact of childhood maltreatment on cognitive function in young adults using various measurements, including computerized tests, and their relationship with emotional dysregulation. Methods We recruited 149 healthy individuals with and without maltreatment experiences and used the Wechsler Adult Intelligence Scale IV (WAIS-IV) and a computerized battery to analyze cognitive function. Results Both the WAIS-IV and computerized tests revealed that individuals with a history of childhood maltreatment had decreased cognitive function, especially in terms of working memory and processing speed. These individuals tended to employ maladaptive emotion regulation strategies. Among cognitive functions, working memory is negatively related to maladaptive emotion regulation strategies such as catastrophizing. Conclusion This study highlights the effects of childhood maltreatment on cognitive function in young adulthood. Moreover, the study suggests clinical implications of cognitive interventions for improving emotion regulation and cognitive function in individuals with a history of childhood maltreatment.
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Affiliation(s)
- Min Seok Kim
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
| | - Kyungmin Kim
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea
| | - Jihyun Nam
- Bio-Medical Research Institute, Kyungpook National University Hospital, Daegu, Korea
| | - Seung Jae Lee
- Department of Psychiatry, Kyungpook National University Hospital, Daegu, Korea
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
| | - Sang Won Lee
- Department of Psychiatry, Kyungpook National University Chilgok Hospital, Daegu, Korea
- Department of Psychiatry, School of Medicine, Kyungpook National University, Daegu, Korea
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Zhou HY, Zhou L, Zheng TX, Ma LP, Fan MX, Liu L, Zhao XD, Yan C. Unraveling the link between childhood maltreatment and depression: Insights from the role of ventral striatum and middle cingulate cortex in hedonic experience and emotion regulation. Dev Psychopathol 2024:1-11. [PMID: 38179683 DOI: 10.1017/s0954579423001591] [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: 01/06/2024]
Abstract
Childhood maltreatment is an established risk factor for psychopathology. However, it remains unclear how childhood traumatic events relate to mental health problems and how the brain is involved. This study examined the serial mediation effect of brain morphological alterations and emotion-/reward-related functions on linking the relationship from maltreatment to depression. We recruited 156 healthy adolescents and young adults and an additional sample of 31 adolescents with major depressive disorder for assessment of childhood maltreatment, depressive symptoms, cognitive reappraisal and anticipatory/consummatory pleasure. Structural MRI data were acquired to identify maltreatment-related cortical and subcortical morphological differences. The mediation models suggested that emotional maltreatment of abuse and neglect, was respectively associated with increased gray matter volume in the ventral striatum and greater thickness in the middle cingulate cortex. These structural alterations were further related to reduced anticipatory pleasure and disrupted cognitive reappraisal, which contributed to more severe depressive symptoms among healthy individuals. The above mediating effects were not replicated in our clinical group partly due to the small sample size. Preventative interventions can target emotional and reward systems to foster resilience and reduce the likelihood of future psychiatric disorders among individuals with a history of maltreatment.
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Affiliation(s)
- Han-Yu Zhou
- Shanghai Key Laboratory of Mental Health and Psychological Crisis Intervention, Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
- Shanghai Changning Mental Health Centre, Shanghai, China
| | - Lan Zhou
- Department of Biomedical Sciences of Cells and Systems, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | | | - Li-Ping Ma
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Ming-Xia Fan
- Department of Physics, Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Materials Science, East China Normal University, Shanghai, China
| | - Liang Liu
- Clinical Research Center for Mental Disorders, Chinese-German Institute of Mental Health, Shanghai Pu-dong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China
| | - Xu-Dong Zhao
- Clinical Research Center for Mental Disorders, Chinese-German Institute of Mental Health, Shanghai Pu-dong New Area Mental Health Center, School of Medicine, Tongji University, Shanghai, China
| | - Chao Yan
- Shanghai Changning Mental Health Centre, Shanghai, China
- Key Laboratory of Brain Functional Genomics (MOE&STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
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Rolls ET, Deco G, Zhang Y, Feng J. Hierarchical organization of the human ventral visual streams revealed with magnetoencephalography. Cereb Cortex 2023; 33:10686-10701. [PMID: 37689834 DOI: 10.1093/cercor/bhad318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 08/17/2023] [Accepted: 08/17/2023] [Indexed: 09/11/2023] Open
Abstract
The hierarchical organization between 25 ventral stream visual cortical regions and 180 cortical regions was measured with magnetoencephalography using the Human Connectome Project Multimodal Parcellation atlas in 83 Human Connectome Project participants performing a visual memory task. The aim was to reveal the hierarchical organization using a whole-brain model based on generative effective connectivity with this fast neuroimaging method. V1-V4 formed a first group of interconnected regions. Especially V4 had connectivity to a ventrolateral visual stream: V8, the fusiform face cortex, and posterior inferior temporal cortex PIT. These regions in turn had effectivity connectivity to inferior temporal cortex visual regions TE2p and TE1p. TE2p and TE1p then have connectivity to anterior temporal lobe regions TE1a, TE1m, TE2a, and TGv, which are multimodal. In a ventromedial visual stream, V1-V4 connect to ventromedial regions VMV1-3 and VVC. VMV1-3 and VVC connect to the medial parahippocampal gyrus PHA1-3, which, with the VMV regions, include the parahippocampal scene area. The medial parahippocampal PHA1-3 regions have connectivity to the hippocampal system regions the perirhinal cortex, entorhinal cortex, and hippocampus. These effective connectivities of two ventral visual cortical streams measured with magnetoencephalography provide support to the hierarchical organization of brain systems measured with fMRI, and new evidence on directionality.
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Affiliation(s)
- Edmund T Rolls
- Oxford Centre for Computational Neuroscience, Oxford, United Kingdom
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Gustavo Deco
- Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain
- Brain and Cognition, Pompeu Fabra University, Barcelona 08018, Spain
- Institució Catalana de la Recerca i Estudis Avançats (ICREA), Universitat Pompeu Fabra, Passeig Lluís Companys 23, Barcelona 08010, Spain
| | - Yi Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, United Kingdom
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai 200403, China
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Jiang R, Noble S, Sui J, Yoo K, Rosenblatt M, Horien C, Qi S, Liang Q, Sun H, Calhoun VD, Scheinost D. Associations of physical frailty with health outcomes and brain structure in 483 033 middle-aged and older adults: a population-based study from the UK Biobank. Lancet Digit Health 2023; 5:e350-e359. [PMID: 37061351 PMCID: PMC10257912 DOI: 10.1016/s2589-7500(23)00043-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 02/12/2023] [Accepted: 02/16/2023] [Indexed: 04/17/2023]
Abstract
BACKGROUND Physical frailty is a state of increased vulnerability to stressors and is associated with serious health issues. However, how frailty affects and is affected by numerous other factors, including mental health and brain structure, remains underexplored. We aimed to investigate the mutual effects of frailty and health using large, multidimensional data. METHODS For this population-based study, we used data from the UK Biobank to examine the pattern and direction of association between physical frailty and 325 health-related measures across multiple domains, using linear mixed-effect models and adjusting for numerous confounders. Participants were included if complete data were available for all five indicators of frailty, all covariates, and at least one health measure. We further examined the association between frailty and brain structure and the role of this association in mediating the relationship between frailty and health outcomes. FINDINGS 483 033 participants aged 38-73 years were included in the study at baseline (between Dec 19, 2006, and Oct 1, 2010); at a median follow-up of 9 years (IQR 8-10), behavioural data were available for 46 501 participants and neuroimaging data for 40 210 participants. The severity of physical frailty was significantly associated with decreased cognitive performance (Cohen's d=0·025-0·162), increased early-life risks (d=0·026-0·111), unhealthy lifestyle (d=0·013-0·394), poor physical fitness (d=0·007-0·668), increased symptoms of poor mental health (d=0·032-0·607), severe environmental pollution (d=0·013-0·064), and adverse biochemical markers (d=0·025-0·198). Some associations were bidirectional, with the strongest effects on mental health measures. The severity of frailty correlated with increased total white matter hyperintensity and lower grey matter volume, particularly in subcortical regions (d=0·027-0·082), which significantly mediated the association between frailty and health-related outcomes, although the mediated effects were small. INTERPRETATION Physical frailty is associated with diverse unfavourable health-related outcomes, which can be mediated by differences in brain structure. Our findings offer a framework for guiding preventative strategies targeting both frailty and psychiatric disorders. FUNDING National Institute of Mental Health, National Science Foundation.
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Affiliation(s)
- Rongtao Jiang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA.
| | - Stephanie Noble
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Jing Sui
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
| | - Kwangsun Yoo
- Department of Psychology, Yale University, New Haven, CT, USA
| | - Matthew Rosenblatt
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Corey Horien
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Shile Qi
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Qinghao Liang
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Huili Sun
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Vince D Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA; Child Study Center, Yale School of Medicine, New Haven, CT, USA; Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA; Department of Statistics and Data Science, Yale University, New Haven, CT, USA
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