Distributed Neural Activity Patterns Underlying Practice-Based Learning

基于实践的学习的分布式神经活动模式

• 批准号: 10447345
• 负责人: Kimberly Reinhold
• 金额: $ 11.74万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-04-01 至 2024-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10447345
• 关键词: Animals; Anxiety; Area; Association Learning; BRAIN initiative; Basal Ganglia; Behavior; Behavioral Paradigm; Brain; Calcium; Cells; Color; Cues; Data; Detection; Electrophysiology (science); Environment; Feedback; Food; Forelimb; Goals; Image; Label; Learning; Link; Measures; Memory; Methods; Microscope; Modeling; Motor; Mus; Neurons; Outcome; Output; Pathway interactions; Pattern; Persons; Phase; Population; Post-Traumatic Stress Disorders; Postdoctoral Fellow; Process; Psychological reinforcement; Reporter; Retina; Sensory; Shapes; Short-Term Memory; Smell Perception; Smoking; Synapses; Synaptic plasticity; System; Techniques; Testing; Update; Visual; Visual Cortex; Visual Pathways; Work; addiction; autism spectrum disorder; base; cigarette smoke; cognitive function; cognitive process; experience; experimental study; fluorophore; in vivo; in vivo two-photon imaging; innovation; insight; learned behavior; loss of function; motor behavior; motor control; nicotine reward; optogenetics; recruit; relating to nervous system; response; superior colliculus Corpora quadrigemina; supervised learning; tool; two-photon

PROJECT SUMMARY / ABSTRACT To survive, animals must learn appropriate associations between sensory cues and motor actions through a process of trial and error. We expect that this learning will strengthen the synaptic connections between neurons representing the sensory cue and neurons initiating the motor action. The strengthened synapses may be direct synaptic connections between these neuronal populations or via systems intermediate between these neurons, i.e., a “plastic brain circuit” or “pathway.” Synaptic plasticity has been observed in many different brain areas, and the mechanisms are moderately well understood. However, we have struggled to identify which plastic brain circuit underlies, specifically, the sensory cue-to-motor action association that is learned through the process of trial and error. This is due, in part, to the fact that many brain areas undergo plastic changes during learning, as the experience of learning recruits a variety of different cognitive processes, including sensory detection, motor control, feedback, working memory and reinforcement learning -- cognitive processes that all engage different brain areas and distributed networks. During my postdoc, I developed an approach to assign these cognitive functions to different brain circuits for a case of trial and error learning in mice. The approach involved an innovative behavior paradigm and optogenetic tools that are spatially and temporally precise. Mice learned to associate the optogenetic activation of visual cortex (cue) with a forelimb reach to grab a food pellet (motor action). As a result of my postdoc work, I now know which neurons in the brain encode this cue and which are required to initiate this motor action. Therefore I am now equipped to identify the plastic brain circuit underlying the learned association between this cue and this action. Here I propose to study the brain circuit between the cue-encoding neurons and the neurons necessary to initiate the motor action, in vivo while mice learn the cue-action association. I will study the flow of neural activity from the cue- encoding neurons in the visual cortex to the neurons in the superior colliculus that are necessary to initiate the motor action. In Aim 1, I will identify changes in the cued activity in visual cortex over learning. In Aim 2, I will determine how activity in the superior colliculus changes over learning. In Aim 3, I will determine whether the output of this pathway is sufficient to trigger the motor action after learning. Hence this work speaks directly to a key goal of the Brain Initiative, to “demonstrate causal links between brain activity and behavior.” I will learn in vivo two-photon imaging for Aim 1 under the guidance of Dr. Sabatini, an expert at this technique. Aims 2 and 3 will be conducted in the independent phase using in vivo electrophysiology, a technique with which I have extensive experience. These experiments will help to identify a pathway from visual cortex to superior colliculus that stores a learned, associative memory. Finding the neural basis of learned, sensory cue-motor action associations will be essential to treat specific harmful associations, such as occur in PTSD, OCD, autism and anxiety, without generally disrupting sensory or motor behavior.

项目摘要 /摘要 为了生存，动物必须通过一个人学习感觉线索和运动动作之间的适当关联 反复试验的过程。我们希望这种学习将加强 代表感觉提示和神经元的神经元启动运动动作。加强的突触可能 是这些神经元种群之间的直接突触连接，或通过系统中间的系统 神经元，即“塑料脑电路”或“途径”。在许多不同的大脑中已经观察到突触可塑性 区域和机制众所周知。但是，我们一直在努力确定哪个 塑料脑电路的基础，特别是通过感官提示到运动动作关联 反复试验的过程。这部分是由于许多大脑区域发生塑料变化的事实 在学习过程中，随着学习的经验招募了各种不同的认知过程，包括 感官检测，运动控制，反馈，工作记忆和增强学习 - 认知过程 所有这些都吸引了不同的大脑区域和分布式网络。在博士后期间，我开发了一种方法 将这些认知功能分配给不同的大脑回路，以进行小鼠的反复试验。 方法涉及一种创新的行为范式和光遗传学工具，这些工具在空间和临时 精确的。小鼠学会将视觉皮层（CUE）的光遗传激活与前肢接触到 抓住食物颗粒（运动动作）。由于我的博士后工作，我现在知道大脑中哪些神经元 编码此提示，并且需要启动此电动机动作。因此，我现在有能力识别 该提示与该动作之间学到的关联的塑料脑电路。我在这里建议 研究提示编码神经元与启动电动机所需的神经元之间的脑电路 动作，在体内学习提示性协会时。我将研究提示的神经活动流动 在上丘中的神经元中编码视觉皮层中的神经元是启动必要的 运动动作。在AIM 1中，我将确定视觉皮层中通过学习的提示活动的变化。在AIM 2中，我会 确定上丘的活动如何随着学习而变化。在AIM 3中，我将确定是否 该途径的输出足以在学习后触发电动机动作。因此，这项工作直接说明 大脑计划的关键目标是“展示大脑活动与行为之间的因果关系”。我会学习的 在该技术专家Sabatini博士的指导下，在AIM 1的体内两光子成像。目标2 3将在独立阶段使用体内电生理学进行，这是I的技术 有丰富的经验。这些实验将有助于确定从视觉皮层到上级的途径 存储有学识渊博的关联记忆的胶囊。找到学习的，感觉提示运动的神经基础 行动协会对于处理特定有害关联至关重要，例如在PTSD，OCD中发生 自闭症和动画，通常不会破坏感觉或运动行为。