Jobe T H, Harrow M, Martin E M, Whitfield H J, Sands J R
Dept. of Psychiatry, University of Illinois College of Medicine, Chicago 60612-7327.
Schizophr Bull. 1994;20(3):413-6; discussion 417-21. doi: 10.1093/schbul/20.3.413.
Modern techniques have been applied to brain modeling, based on recent approaches in the artificial intelligence field that use brain-like "connectionistic" computational architectures. The model proposed by Cohen and Servan-Schreiber uses a gain parameter which they identify with dopamine function. They apply their model to neuroleptically treated schizophrenia patients who show improved task performance which they link to increased dopamine function and increased gain in the prefrontal cortex. However, evidence indicates that antipsychotic medications block dopamine (especially D2) receptors, decreasing mesolimbic and mesocortical dopamine function. If therapeutic dosages of neuroleptics diminish dopamine function, this would decrease gain in context modules needed for adequate task performance. Schizophrenia patients would perform more poorly by further reducing gain in their already compromised context modules. The current investigators suggest three possible ways to resolve this difficulty, to explain why normals perform more poorly when taking neuroleptics, although acute schizophrenia patients' performance may be enhanced in several areas. Evidence would suggest that multiple processes occur simultaneously in neuroleptically treated patients with some processes counterbalancing others.
基于人工智能领域中使用类似大脑的“连接主义”计算架构的最新方法，现代技术已被应用于大脑建模。科恩和塞尔万 - 施赖伯提出的模型使用了一个增益参数，他们将其与多巴胺功能联系起来。他们将模型应用于接受抗精神病药物治疗的精神分裂症患者，这些患者的任务表现有所改善，他们将此与多巴胺功能增加以及前额叶皮质增益增加联系起来。然而，有证据表明抗精神病药物会阻断多巴胺（尤其是D2）受体，降低中脑边缘和中脑皮质的多巴胺功能。如果抗精神病药物的治疗剂量会降低多巴胺功能，那么这将减少充分完成任务所需的情境模块中的增益。精神分裂症患者通过进一步降低其已经受损的情境模块中的增益，表现会更差。目前的研究人员提出了三种可能解决这一难题的方法，以解释为什么正常人服用抗精神病药物时表现更差，尽管急性精神分裂症患者在某些方面的表现可能会得到改善。有证据表明，在接受抗精神病药物治疗的患者中，多种过程同时发生，一些过程会抵消其他过程的影响。
