Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.
Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.
Biol Psychiatry. 2022 Apr 15;91(8):699-708. doi: 10.1016/j.biopsych.2021.09.007. Epub 2021 Sep 20.
People with schizophrenia spectrum disorders (SSDs) often experience persistent social cognitive impairments, associated with poor functional outcome. There are currently no approved treatment options for these debilitating symptoms, highlighting the need for novel therapeutic strategies. Work to date has elucidated differential social processes and underlying neural circuitry affected in SSDs, which may be amenable to modulation using neurostimulation. Further, advances in functional connectivity mapping and electric field modeling may be used to identify individualized treatment targets to maximize the impact of brain stimulation on social cognitive networks. Here, we review literature supporting a roadmap for translating functional connectivity biomarker discovery to individualized treatment development for social cognitive impairments in SSDs. First, we outline the relevance of social cognitive impairments in SSDs. We review machine learning approaches for dimensional brain-behavior biomarker discovery, emphasizing the importance of individual differences. We synthesize research showing that brain stimulation techniques, such as repetitive transcranial magnetic stimulation, can be used to target relevant networks. Further, functional connectivity-based individualized targeting may enhance treatment response. We then outline recent approaches to account for neuroanatomical variability and optimize coil positioning to individually maximize target engagement. Overall, the synthesized literature provides support for the utility and feasibility of this translational approach to precision treatment. The proposed roadmap to translate biomarkers of social cognitive impairments to individualized treatment is currently under evaluation in precision-guided trials. Such a translational approach may also be applicable across conditions and generalizable for the development of individualized neurostimulation targeting other behavioral deficits.
精神分裂症谱系障碍（SSDs）患者常经历持续的社会认知障碍，与较差的功能结果相关。目前尚无针对这些使人衰弱的症状的批准治疗方法，这凸显了需要新的治疗策略。迄今为止的研究已经阐明了 SSD 中受影响的不同社会过程和潜在神经回路，这些过程和回路可能可以通过神经刺激来调节。此外，功能连接映射和电场建模的进展可用于确定个体化治疗靶点，以最大限度地提高脑刺激对社会认知网络的影响。在这里，我们回顾了支持将功能连接生物标志物发现转化为 SSD 中社会认知障碍个体化治疗的文献。首先，我们概述了 SSD 中社会认知障碍的相关性。我们回顾了用于维度脑-行为生物标志物发现的机器学习方法，强调了个体差异的重要性。我们综合了研究结果，表明重复经颅磁刺激等脑刺激技术可用于靶向相关网络。此外，基于功能连接的个体化靶向可能会增强治疗反应。然后，我们概述了最近考虑神经解剖学变异性并优化线圈定位以单独最大化目标参与的方法。总体而言，综合文献支持将社会认知障碍的生物标志物转化为个体化治疗的这种转化方法的实用性和可行性。将社会认知障碍的生物标志物转化为个体化治疗的路线图目前正在精准引导试验中进行评估。这种转化方法也可能适用于其他条件，并可推广用于开发针对其他行为缺陷的个体化神经刺激靶向。
