Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London, WC1N 3AR, UK.
Mol Psychiatry. 2023 Jan;28(1):256-268. doi: 10.1038/s41380-022-01743-z. Epub 2022 Sep 2.
This review considers computational psychiatry from a particular viewpoint: namely, a commitment to explaining psychopathology in terms of pathophysiology. It rests on the notion of a generative model as underwriting (i) sentient processing in the brain, and (ii) the scientific process in psychiatry. The story starts with a view of the brain-from cognitive and computational neuroscience-as an organ of inference and prediction. This offers a formal description of neuronal message passing, distributed processing and belief propagation in neuronal networks; and how certain kinds of dysconnection lead to aberrant belief updating and false inference. The dysconnections in question can be read as a pernicious synaptopathy that fits comfortably with formal notions of how we-or our brains-encode uncertainty or its complement, precision. It then considers how the ensuing process theories are tested empirically, with an emphasis on the computational modelling of neuronal circuits and synaptic gain control that mediates attentional set, active inference, learning and planning. The opportunities afforded by this sort of modelling are considered in light of in silico experiments; namely, computational neuropsychology, computational phenotyping and the promises of a computational nosology for psychiatry. The resulting survey of computational approaches is not scholarly or exhaustive. Rather, its aim is to review a theoretical narrative that is emerging across subdisciplines within psychiatry and empirical scales of investigation. These range from epilepsy research to neurodegenerative disorders; from post-traumatic stress disorder to the management of chronic pain, from schizophrenia to functional medical symptoms.
即，致力于根据病理生理学来解释精神病理学。它基于生成模型的概念，作为（i）大脑中的感知处理和（ii）精神病学中的科学过程的基础。这个故事从认知和计算神经科学的角度出发，将大脑视为一种推理和预测的器官。这为神经元信息传递、分布式处理和神经元网络中的信念传播提供了一个形式描述；以及某些类型的连接中断如何导致异常的信念更新和错误推理。所讨论的连接中断可以被视为一种有害的突触病，它与我们或我们的大脑如何编码不确定性或其补数精度的形式概念非常吻合。然后，它考虑了如何通过实验来检验由此产生的过程理论，重点是对介导注意设置、主动推理、学习和规划的神经元回路和突触增益控制进行计算建模。这种建模所提供的机会是根据计算机实验来考虑的；即，计算神经心理学、计算表型和精神病学计算分类学的前景。这种计算方法的综述不是学术性的或详尽无遗的。相反，它的目的是回顾一个正在精神病学的子学科和实证研究范围内出现的理论叙述。这些范围从癫痫研究到神经退行性疾病；从创伤后应激障碍到慢性疼痛的管理，从精神分裂症到功能性医疗症状。
