Uncovering the neural circuit and synaptic mechanisms underlying interval timing

揭示间隔计时背后的神经回路和突触机制

• 批准号: 10241747
• 负责人: JAMES Gerard HEYS
• 金额: $ 124.65万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10241747
• 关键词: Address; Alzheimer' s Disease; Anterior; Axon; Behavior; Behavioral; Behavioral Paradigm; Brain; Brain region; Code; Cognition; Complex; Dendrites; Event; Functional Imaging; Future; Hour; Image; Imaging Techniques; Individual; Laboratories; Learning; Medial; Memory; Memory impairment; Methods; Modeling; Monitor; Mus; Nervous System Physiology; Neurons; Operative Surgical Procedures; Optics; Outcome; Population; Positioning Attribute; Process; Publishing; Resolution; Schizophrenia; Signal Transduction; Synapses; System; Testing; Time; Work; awake; base; cingulate cortex; circadian; cognitive neuroscience; entorhinal cortex; experience; millisecond; neural circuit; neuromechanism; novel; optical imaging; relating to nervous system; time interval; virtual reality

Project Summary/Abstract Many functions of the nervous system, such as learning and memory, inferring cause and effect, and predicting future outcomes, depend upon the brain’s ability to perceive and form memories of the temporal duration of events. Despite progress in establishing the neural basis of timing on the scale of milliseconds and circadian timing over hours, many fundamental questions remain about time encoding on the intermediate scale of interval timing (i.e. seconds to minutes). To investigate how interval time is represented in the brain, I developed a novel behavioral approach (Heys and Dombeck, 2018) and a novel surgical and optical approach to enable large- scale, cellular-resolution functional imaging in MEC in the behaving mouse (Heys et al., 2014). By combining these imaging and behavioral methods, I discovered a previously unknown population of neurons in MEC that encode interval time, whereby individual time-encoding neurons become regularly activated at a specific moment during an interval timing task (Heys and Dombeck, 2018). I then established that MEC is critical for interval timing during learning (Heys et al., In Press). This previous work has positioned my laboratory to address fundamental questions regarding the neural circuit and synaptic mechanisms underlying interval timing. We will test a novel conceptual framework, whereby time is encoded through a multi-stage process. In the first stage of this model, a neural clock generates a context-independent representation of elapsed time. In the second stage, a downstream circuit reads out the clock and associates time with other features of experience, such as spatial context. Building upon my published, this proposal will test the hypothesis that the anterior cingulate cortex (ACC) serves as an upstream neural clock, providing context-independent temporal information to medial entorhinal cortex (MEC), which in turn integrates elapsed time with spatial context. To test this model, I will apply my cutting- edge imaging techniques to record and manipulate neural activity from synapses and dendrites, up to thousands of individual neurons simultaneously in awake behaving mice (Heys et al. 2014) during virtual-reality behavioral paradigms that allow precise control of timing behavior (Heys and Dombeck, 2018). Using this approach, we will first evaluate the ability of ACC axons terminating in MEC to serve as a neural clock signal in MEC. Second, we will determine whether MEC encodes a context-dependent representation of time by integrating synaptic input from ACC with spatial coding input from other upstream brain regions. Third, we will identify the synaptic and dendritic mechanisms underlying cellular integration of context-dependent representations of time in MEC. This proposal will have a far-reaching influence on cellular, systems and cognitive neuroscience. As interval timing is a fundamental component of essentially all major brain functions, understanding the neural mechanisms of interval timing, from synaptic to population level neural coding, will provide a basis for understanding how the brain performs all complex functions that depend upon encoding of time on the scale of seconds to minutes.

项目总结/文摘