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: 10592377
• 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 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10592377
• 关键词: Abbreviations; Animals; Anxiety; Area; BRAIN initiative; Basal Ganglia; Behavior; Behavioral Paradigm; Brain; Calcium; Cells; Color; 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; 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; neural; nicotine reward; optogenetics; recruit; response; superior colliculus Corpora quadrigemina; supervised learning; theories; 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.

项目概要/摘要 为了生存，动物必须通过某种方式学习感觉线索和运动动作之间的适当关联。 我们期望这种学习将加强之间的突触联系。 代表感觉线索的神经元和启动运动动作的神经元可能会增强。 这些神经群体之间的直接突触连接或通过这些神经群体之间的中间系统 神经元，即“可塑性大脑回路”或“通路”，已在许多不同的大脑中观察到突触可塑性。 然而，我们一直在努力确定哪些领域。 特别是，可塑性脑回路是感觉线索与运动动作关联的基础，这种关联是通过以下方式学习的： 这在一定程度上是由于许多大脑区域经历了可塑性变化。 在学习过程中，因为学习经历会招募各种不同的认知过程，包括 感觉检测、运动控制、反馈、工作记忆和强化学习——认知过程 在我的博士后期间，我开发了一种方法来处理不同的大脑区域和分布式网络。 在小鼠试错学习的案例中，将这些认知功能分配给不同的大脑回路。 方法涉及创新的行为范式和光遗传学工具，这些工具在空间和时间上 小鼠学会了将视觉皮层（提示）的光遗传学激活与前肢的伸展联系起来。 抓住食物颗粒（运动动作）作为我的博士后工作的结果，我现在知道大脑中有哪些神经元。 编码这个提示以及启动这个运动动作所需的信息，因此我现在有能力识别。 在此我建议，该提示与该动作之间的可塑性大脑回路是习得关联的基础。 研究线索编码神经元和启动运动所需的神经元之间的大脑回路 当小鼠学习提示-动作关联时，我将研究来自提示的神经活动流。 将视觉皮层中的神经元编码到上丘中的神经元，这些神经元是启动 在目标 1 中，我将识别视觉皮层在学习过程中的提示活动的变化。 确定上丘的活动在学习过程中如何变化。在目标 3 中，我将确定是否 该通路的输出足以触发学习后的运动动作，因此这项工作直接说明了这一点。 大脑计划的一个关键目标是“展示大脑活动和行为之间的因果关系”。 在 Aims 2 技术专家 Sabatini 博士的指导下，对 Aim 1 进行了体内双光子成像。 和 3 将在独立阶段使用体内电生理学进行，这是我使用的一种技术 这些实验将有助于确定从视觉皮层到高级皮层的途径。 存储学习的联想记忆的丘，寻找学习的感觉线索运动的神经基础。 行动关联对于治疗特定的有害关联至关重要，例如发生在创伤后应激障碍（PTSD）、强迫症（OCD）、 自闭症和焦虑症，通常不会扰乱感觉或运动行为。