New approaches to understand neuronal microcircuit dynamics for working memory

理解工作记忆神经元微电路动力学的新方法

• 批准号: 8955230
• 负责人: Christopher D Harvey
• 金额: $ 53.39万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-11 至 2020-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8955230
• 关键词: Area; Attention deficit hyperactivity disorder; Autistic Disorder; Behavior; Behavioral; Biological; Biological Neural Networks; Bipolar Disorder; Brain region; Chronic; Computer Simulation; Cues; Data; Data Set; Disease; Future; Health; Image; Individual; Information Storage; Learning; Measurement; Measures; Mediating; Memory; Mental disorders; Methods; Modeling; Mus; Neurons; Parietal Lobe; Pattern; Performance; Phase; Population; Property; Recurrence; Rotation; Sampling; Schizophrenia; Short-Term Memory; Stable Populations; Testing; Theoretical model; Thinking; Time; Visual; Work; base; cognitive function; cognitive process; flexibility; insight; neural circuit; neuromechanism; novel; novel strategies; public health relevance; research study; theories; tool; two-photon; virtual; virtual reality

 DESCRIPTION (provided by applicant): Working memory, the temporary storage of information for future manipulation to guide actions, is an essential component of nearly all cognitive processes. Deficits in working memory contribute to a variety of mental health disorders, including schizophrenia, autism, bipolar disorder, and attention-deficit hyperactivity disorder. Working memory is thought to be an emergent property of neurons acting in groups to form microcircuits. However, due in large part to technical limitations, working memory has been studied nearly exclusively at the scales of entire brain regions or individual neurons, both of which fail to reveal interactions in neuronal populations. A major challenge in understanding the neural mechanisms for working memory is to develop tools to measure, analyze, and model working memory at the scale of the neuronal microcircuit. In this application, we present approaches to solve this challenge using two-photon imaging of activity in neuronal populations in mice performing working memory tasks in virtual reality. We will combine our large imaging data sets with theoretical modeling approaches to develop new computational models of how working memory is generated in microcircuits. First, we will examine how working memory representations are encoded in neuronal populations by examining the stability of representations over long timescales, using chronic two- photon imaging of the same neurons over weeks during working memory behaviors. Second, we will perform imaging experiments during novel working memory tasks to test competing, long-standing theoretical models of working memory, including models based on attractor dynamics and sequence dynamics. Third, we will develop a new theoretical modeling framework in conjunction with rapid experiment-model iterations to generate and test new microcircuit-scale hypotheses for the neural mechanisms underlying working memory. Together the proposed work is expected to establish new approaches to measure, analyze, and model microcircuit function during working memory in the mouse, leading toward mechanistic studies of how working memory and its underlying microcircuits are disrupted in mental illness.

 描述（由申请人提供）：工作记忆是对未来操作的临时存储，这是几乎盟友认知过程的必要条件。霍夫（Howver）在很大程度上是由于技术局限性的，几乎已经在整个大脑区域或单个神经元的尺度上研究了工作记忆，这两者都无法揭示神经元种群中的相互作用。 ，分析和模型在神经元微塞的尺度上工作。新的复合体是在微电路中生成的，我们将使用长期的慢性两光子成像在神经元中编码的录音在记忆任务中执行成像实验，以基于吸引力动力学和序列动态来测试竞争的长期工作模型，我们将开发模型迭代，以生成和测试新的微电路尺度。并在小鼠F中的工作记忆中对微电路进行建模，从而在精神疾病中如何破坏工作记忆及其潜在的微电路。