Progress in the application of computational psychiatry research strategies in schizophrenia research
10.3760/cma.j.cn113661-20231012-00132
- VernacularTitle:计算精神病学研究策略在精神分裂症研究中的应用进展
- Author:
Lige GE
1
;
Chuanyue WANG
Author Information
1. 首都医科大学精神卫生学院，北京100069
- Publication Type:Journal Article
- Keywords:
Schizophrenia;
Computational psychiatry;
Neurophysiology;
Deep learning
- From:
Chinese Journal of Psychiatry
2023;56(6):465-470
- CountryChina
- Language:Chinese
-
Abstract:
Schizophrenia is a type of mental illness characterized by delusions and hallucinations. Computational psychiatry, as a novel clinical approach, integrates principles and theories from multiple disciplines such as computational anatomy and cognitive neuroscience into research and practice of clinical psychiatry. By using hypothesis-driven or data-driven computational models, it explains the mechanisms of mental illnesses and improves or develops new treatment options. With the improvement of hardware levels such as artificial intelligence specific integrated circuit, neuroimaging and neuroelectrophysiology techniques, and the enhancement of model interpretability, a large number of models are applied to schizophrenia-related research. This review summarizes the hypotheses and data foundations of computational psychiatry related to schizophrenia and discusses the application of computational psychiatry research strategies in the study of schizophrenia.
