Halassa Michael M, Frank Michael J, Garety Philippa, Ongur Dost, Airan Raag D, Sanacora Gerard, Dzirasa Kafui, Suresh Sahil, Fitzpatrick Susan M, Rothman Douglas L
Department of Neuroscience, Tufts University School of Medicine, Boston, MA, USA; Department of Psychiatry, Tufts University School of Medicine, Boston, MA, USA.
Department of Cognitive and Psychological Sciences, Carney Institute for Brain Sciences, Brown University, Providence, RI, USA.
Cell Rep Med. 2025 May 20;6(5):102094. doi: 10.1016/j.xcrm.2025.102094. Epub 2025 Apr 28.
Modern psychiatry faces challenges in translating neurobiological insights into treatments for severe illnesses. The mid-20th century witnessed the rise of molecular mechanisms as pathophysiological and treatment models, with recent holistic proposals keeping this focus unaltered. In this perspective, we explore how psychiatry can utilize systems neuroscience to develop a vertically integrated understanding of brain function to inform treatment. Using schizophrenia as a case study, we discuss scale-related challenges faced by researchers studying molecules, circuits, networks, and cognition and clinicians operating within existing frameworks. We emphasize computation as a bridging language, with algorithmic models like hierarchical predictive processing offering explanatory potential for targeted interventions. Developing such models will not only facilitate new interventions but also optimize combining existing treatments by predicting their multi-level effects. We conclude with the prognosis that the future is bright, but that continued investment in research closely driven by clinical realities will be critical.
现代精神病学在将神经生物学见解转化为重症治疗方法方面面临挑战。20世纪中叶见证了分子机制作为病理生理学和治疗模型的兴起,最近的整体提议仍保持这一重点不变。从这个角度出发,我们探讨精神病学如何利用系统神经科学来形成对大脑功能的纵向综合理解,从而为治疗提供依据。以精神分裂症为例,我们讨论研究分子、回路、网络和认知的研究人员以及在现有框架内工作的临床医生所面临的与规模相关的挑战。我们强调计算作为一种桥梁语言,像分层预测处理这样的算法模型为有针对性的干预提供了解释潜力。开发这样的模型不仅将促进新的干预措施,还将通过预测现有治疗的多层次效果来优化它们的联合使用。我们得出的结论是,未来前景光明,但持续投入紧密受临床实际驱动的研究至关重要。
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