Causal Restructuring of Neural Rhythms Improves Adaptive Behavior

项目摘要/摘要 人类具有很强的适应环境变化和学习新信息的能力 环境中的反馈。未能使用反馈来调整或维持行为会导致广泛的 各种脑部疾病，包括精神分裂症1，成瘾2，自闭症3，帕金森氏病4，5，抽动症 综合症6和注意缺陷多动障碍6.更好地理解神经机制 潜在的反馈处理和学习有可能跨越一系列神经科学研究 物种以及理论和方法框架，并帮助深入了解大脑疾病。这 该项目研究了健康人群中正反馈和负反馈引导学习的机制。 受生理启发的观点集中在大规模大脑网络及其如何通过 同步电生理节律7，8。我们将重点放在假设前额叶皮质的节律上 计算和传达调整或维护当前信息的需要的机制 在学习过程中通过广泛的网络进行处理。我们结合了高密度脑电(EEG) 高清晰度经颅直流电刺激同步节律的测量 9，10以确定是否有可能改变额叶活动的组成部分并导致双向 下一次尝试行为的改变和学习成功。我们的初步数据非常令人鼓舞，表明 我们可以随意地操纵低频节律活动的时间，从而改善或损害学习 在行为上进行测量。研究计划的目标是使用新的神经科学工具和分析 程序，以获得更深层次的认知机制背后的灵活调整 行为和学习，并为开发有效的、非药理学的 改善健康人群和患者人群认知的干预措施。

PROJECT SUMMARY/ABSTRACT Humans have a remarkable capacity to adapt to changing circumstances and learn new information from feedback in the environment. Failures to use feedback to adapt or maintain behavior are implicated in a wide variety of brain disorders, including schizophrenia 1, addiction 2, autism 3, Parkinson's disease 4,5, Tourette syndrome 6, and attention deficit hyperactive disorder 6. A better understanding of the neural mechanisms underlying feedback processing and learning has the potential to bridge neuroscience research across a range of species and theoretical and methodological frameworks, and to help gain insight into brain disorders. This project examines the mechanisms of positive and negative feedback-guided learning in healthy humans from a physiologically inspired perspective centered on large-scale brain networks and how they interact through synchronized electrophysiological rhythms 7,8. We focus on rhythms hypothesized to index frontal cortical mechanisms that compute and communicate the need for adjustment or maintenance of current information processing across broad networks during learning. We combine high-density electroencephalographic (EEG) measurements of synchronized rhythms with high definition transcranial direct-current stimulation (HD-tDCS) 9,10 to determine whether it is possible to modify components of frontal activity and cause bi-directional changes in next-trial behavior and learning success. Our preliminary data are highly encouraging and indicate that we can causally manipulate the timing of low-frequency rhythmic activity, and improve or impair learning measured behaviorally. The goals of the research program are to use novel neuroscience tools and analysis procedures to gain a deeper understanding of the cognitive mechanisms underlying the flexible adjustment of behavior and learning, and contribute new knowledge to the development of effective, non-pharmacological interventions for improving cognition in healthy and patient populations.