Causal Restructuring of Neural Rhythms Improves Adaptive Behavior

项目总结/摘要 人类具有适应不断变化的环境和从环境中学习新信息的非凡能力。 环境中的反馈。未能使用反馈来适应或维持行为涉及广泛的 各种大脑疾病，包括精神分裂症1，成瘾2，自闭症3，帕金森病4，5，妥瑞症 注意缺陷多动障碍6例。更好地理解神经机制 潜在的反馈处理和学习有可能在一系列神经科学研究中起到桥梁作用。 物种和理论和方法框架，并帮助深入了解大脑疾病。这 该项目研究了健康人的积极和消极反馈引导学习的机制， 生理启发的观点集中在大规模的大脑网络，以及它们如何通过 同步的电生理节律7，8.我们专注于假设的节奏，以指数额叶皮层 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。我们将联合收割机高密度脑电图（EEG） 用高清晰度经颅直流电刺激（HD-tDCS）测量同步节律 9，10以确定是否有可能修改额叶活动的组成部分，并导致双向 下一次试验行为和学习成功的变化。我们的初步数据非常令人鼓舞， 我们可以随意控制低频节律活动的时间， 从行为上衡量。研究计划的目标是使用新的神经科学工具和分析 程序，以获得更深入的了解认知机制的灵活调整， 行为和学习，并为开发有效的非药理学 改善健康人群和患者群体认知的干预措施。

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.