Causal Restructuring of Neural Rhythms Improves Adaptive Behavior

神经节律的因果重组可改善适应性行为

基本信息

批准号：
10056221
负责人：
Robert Reinhart
金额：
$ 41.25万
依托单位：
BOSTON UNIVERSITY (CHARLES RIVER CAMPUS)
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-12-27 至 2022-10-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10056221
关键词：
Adaptive Behaviors Anodes Architecture Area Attention deficit hyperactivity disorder Avoidance Learning Basic Science Behavior Behavior Control Behavioral Behavioral Mechanisms Beta Rhythm Boston Brain Brain Diseases Cathodes Clinical Cognition Cognitive Communication Computer Models Data Data Collection Development Double-Blind Method Electric Stimulation Electroencephalography Electrophysiology (science)Ensure Environment Failure Feedback Frequencies Gilles de la Tourette syndrome Goals Hour Human Impairment Individual Intervention Knowledge Laboratories Lateral Learning Maintenance Measurement Measures Medial Methodology Methods Modality Modeling Motor Motor Cortex Neurosciences Neurosciences Research Parkinson Disease Performance Periodicity Pharmaceutical Preparations Phase Physiological Prefrontal Cortex Procedures Punishment Reproducibility Research Research Personnel Rewards Sample Size Schizophrenia Sensory Signal Transduction Source System Techniques Technology Testing Theta Rhythm Universities adaptive learning addiction autism spectrum disorder base behavior measurement density executive function experimental study flexibility frontal lobe improved indexing information processing insight interest learned behavior neuroimaging neuromechanism neurophysiology neuropsychiatric disorder neuroregulation neurotransmission next generation noninvasive brain stimulation novel patient population power analysis programs reconstruction relating to nervous system response sensory cortex success support network tool

项目摘要

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.

项目摘要/摘要人类具有适应不断变化的环境并从中学习新信息的显着能力环境中的反馈。未能使用反馈适应或维持行为的情况与广泛有关各种脑部疾病，包括精神分裂症1，成瘾2，自闭症3，帕金森氏病4,5，图雷特综合征6和注意力缺陷多动障碍6。对神经机制有更好的了解潜在的反馈处理和学习有可能在一定范围内弥合神经科学研究物种以及理论和方法论框架，并有助于深入了解脑疾病。这项目研究了健康人类中正面反馈和负面反馈指导学习的机制生理启发的观点以大规模的大脑网络为中心，以及它们如何通过同步电生理节奏7,8。我们专注于假设索引额叶皮质的节奏计算和传达需要调整或维护当前信息的机制学习过程中跨广泛网络的处理。我们结合了高密度脑电图（EEG）高清经颅直接刺激（HD-TDCS）的同步节奏的测量 9,10确定是否可以修改额叶活动的组成部分并引起双向下一个审判行为和学习成功的变化。我们的初步数据令人鼓舞，并表明我们可以因果操纵低频节奏活动的时机，并改善或损害学习在行为上测量。研究计划的目标是使用新颖的神经科学工具和分析程序以更深入地了解灵活调整的认知机制行为和学习，并为发展有效的非药理学的发展做出新知识改善健康和患者人群认知的干预措施。