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Li X, Wei W, Qian L, Li X, Li M, Kakkos I, Wang Q, Yu H, Guo W, Ma X, Matsopoulos GK, Zhao L, Deng W, Sun Y, Li T. Individualized prediction of multi-domain intelligence quotient in bipolar disorder patients using resting-state functional connectivity. Brain Res Bull 2025; 222:111238. [PMID: 39909352 DOI: 10.1016/j.brainresbull.2025.111238] [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: 11/19/2024] [Revised: 12/31/2024] [Accepted: 01/31/2025] [Indexed: 02/07/2025]
Abstract
BACKGROUND Although accumulating studies have explored the neural underpinnings of intelligence quotient (IQ) in patients with bipolar disorder (BD), these studies utilized a classification/comparison scheme that emphasized differences between BD and healthy controls at a group level. The present study aimed to infer BD patients' IQ scores at the individual level using a prediction model. METHODS We applied a cross-validated Connectome-based Predictive Modeling (CPM) framework using resting-state fMRI functional connectivity (FCs) to predict BD patients' IQ scores, including verbal IQ (VIQ), performance IQ (PIQ), and full-scale IQ (FSIQ). For each IQ domain, we selected the FCs that contributed to the predictions and described their distribution across eight widely-recognized functional networks. Moreover, we further explored the overlapping patterns of the contributed FCs for different IQ domains. RESULTS The CPM achieved statistically significant prediction performance for three IQ domains in BD patients. Regarding the contributed FCs, we observed a widespread distribution of internetwork FCs across somatomotor, visual, dorsal attention, and ventral attention networks, demonstrating their correspondence with aberrant FCs correlated to cognition deficits in BD patients. A convergent pattern in terms of contributed FCs for different IQ domains was observed, as evidenced by the shared-FCs with a leftward hemispheric dominance. CONCLUSIONS The present study preliminarily explored the feasibility of inferring individual IQ scores in BD patients using the FCs-based CPM framework. It is a step toward the development of applicable techniques for quantitative and objective cognitive assessment in BD patients and contributes novel insights into understanding the complex neural mechanisms underlying different IQ domains.
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Affiliation(s)
- Xiaoyu Li
- Key Laboratory for Biomedical Engineering of the Ministry of Education of China, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Wei Wei
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Linze Qian
- Key Laboratory for Biomedical Engineering of the Ministry of Education of China, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China
| | - Xiaojing Li
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Mingli Li
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Ioannis Kakkos
- School of Electrical and Computer Engineering, National Technical University of Athens, Athens 15790, Greece
| | - Qiang Wang
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Hua Yu
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Wanjun Guo
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Xiaohong Ma
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, China
| | - George K Matsopoulos
- School of Electrical and Computer Engineering, National Technical University of Athens, Athens 15790, Greece
| | - Liansheng Zhao
- Mental Health Center and Psychiatric Laboratory, West China Hospital of Sichuan University, Chengdu 610041, China
| | - Wei Deng
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China
| | - Yu Sun
- Key Laboratory for Biomedical Engineering of the Ministry of Education of China, Department of Biomedical Engineering, Zhejiang University, Hangzhou 310027, China.
| | - Tao Li
- Department of Psychiatry, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310013, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China.
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Rossetti MG, Girelli F, Perlini C, Brambilla P, Bellani M. Neuropsychological instruments for bipolar disorders: A systematic review on psychometric properties. J Affect Disord 2023; 338:358-364. [PMID: 37331381 DOI: 10.1016/j.jad.2023.06.026] [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: 09/19/2022] [Revised: 05/26/2023] [Accepted: 06/15/2023] [Indexed: 06/20/2023]
Abstract
BACKGROUND Cognitive deficits are a core feature of bipolar disorder (BD) that persist during the euthymic phase and affect global functioning. However, nowadays, there is no consensus on the optimal tool to capture cognitive deficits in BD. Therefore, this review aims to examine the psychometric properties of tools commonly used to assess cognitive functioning in BD. METHODS Literature search was conducted on PubMed and Web of Science databases on August 1, 2022 and on April 20, 2023, yielding 1758 de-duplicated records. Thirteen studies fulfilled the inclusion criteria and were included in the review. RESULTS All tools examined showed acceptable-to-good psychometric properties suggesting that both brief cognitive screeners and comprehensive batteries may be appropriate for detecting or monitoring cognitive changes in BD. LIMITATIONS Methodological differences between the included studies precluded a direct comparison of the results. Further research is needed to investigate the psychometric properties of cognitive tools that assess also affective and social cognition. CONCLUSIONS The tools examined appear sensitive enough to distinguish between BD patients with versus without cognitive deficits, however, an optimal tool has not yet been identified. The applicability and clinical utility of the tools may depend on multiple factors such as available resources. That said, web-based instruments are expected to become the first-choice instrument for cognitive screening as they can be applied on a large scale and at an affordable cost. As for second-level assessment instruments, the BACA shows robust psychometric properties and tests both affective and non-affective cognition.
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Affiliation(s)
- Maria Gloria Rossetti
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Milan, Italy; Section of Psychiatry, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Francesca Girelli
- UOC Psichiatria, Azienda Ospedaliera Universitaria Integrata (AOUI), Verona, Italy
| | - Cinzia Perlini
- Section of Clinical Psychology, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy.
| | - Paolo Brambilla
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca'Granda Ospedale Maggiore Policlinico, Milan, Italy; Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Marcella Bellani
- Section of Psychiatry, Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
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