Unraveling constraints on motor cortical activity exploration and shaping during structural skill learning using large-scale 2-photon imaging and holographic optogenetic stimulation

使用大规模 2 光子成像和全息光遗传学刺激，揭示结构技能学习过程中运动皮层活动探索和塑造的限制

• 批准号: 9788757
• 负责人: Vivek Athalye
• 金额: $ 6.62万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-16 至 2021-09-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9788757
• 关键词: Algorithms; Auditory; BRAIN initiative; Base of the Brain; Behavior; Behavioral; Brain; Calcium; Chronic; Communication; Data Analyses; Dimensions; Etiology; Factor Analysis; Feedback; Forelimb; Goals; Head; Image; Knowledge; Learning; Learning Skill; Link; Maps; Memory; Microscope; Motion; Motor; Motor Cortex; Movement; Mus; Muscle; Neurons; Outcome; Paralysed; Patients; Pattern; Performance; Play; Population; Role; Series; Shapes; Site; Source; Specific qualifier value; Structure; System; Testing; Training; Work; auditory feedback; base; brain machine interface; design; experience; high dimensionality; motor disorder; motor learning; multidimensional data; neural patterning; neuroprosthesis; novel; optogenetics; relating to nervous system; skills; two-photon

Project Summary When learning new skills, experience with previously-learned skills can facilitate faster learning by constraining behavioral exploration and shaping, a concept known as “structural learning”. The motor cortex plays an essential role in learning new skills, and its initially variable activity is shaped and consolidated over learning. However, how previous experience modulates exploration and shaping of cortical network activity to facilitate new skill learning is not well understood. When the brain learns to control a brain-machine interface (BMI), cortical network activity exploration and shaping is broad (high-dimensional) in BMI-naïve subjects and constrained (low-dimensional) in BMI-experienced subjects, suggesting the following hypothesis. Hypothesis: Previous experience facilitates faster learning of new, related skills by constraining how motor cortical network activity is explored and shaped, effectively reducing the number of neural parameters to learn. The hypothesis’ prediction is that during faster learning of related skills, neural dimensionality will be decreased and aligned with previously learned neural patterns. This project tests the prediction by leveraging novel closed-loop paradigms, chronic large-scale 2-photon calcium imaging, high-dimensional data analysis, and holographic optogenetic stimulation to study and manipulate the neural basis of structural skill learning. First, the correspondence between structural learning of muscle patterns and cortical network activity exploration and shaping will be studied using large-scale 2-photon calcium imaging. Second, to causally link neural variance to learning neural patterns, a high-performance, calcium imaging-based BMI will be developed, and the relationship between structural neuroprosthetic learning and neural exploration and shaping will be analyzed. Finally, the structure of cortical network activity will be artificially shaped using holographic optogenetic stimulation and tested on neuroprosthetic skill learning. The long-term objective of this proposal integrates several core goals of the BRAIN initiative. The proposal will produce a dynamic picture of the learning brain and demonstrate causality using BMIs and holographic optogenetic stimulation. This work’s outcome will contribute conceptual principles underlying skill learning and memory and guide the design of BMI systems to restore movement and assist learning. Aim 1: Investigate the relationship between structural motor learning and cortical network activity exploration and shaping using a novel motor task and large-scale 2-photon calcium imaging. Aim 2: Investigate the relationship between structural neuroprosthetic learning and cortical network activity exploration and shaping using a high-performance, calcium imaging-based BMI. Aim 3: Artificially shape structure of cortical network activity using closed-loop holographic optogenetic stimulation and test effect on neuroprosthetic learning.

项目总结