Neural Connectivity Resource Core

神经连接资源核心

• 批准号: 10231002
• 负责人: Hillel Adesnik
• 金额: $ 16.96万
• 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: 2018-09-15 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10231002
• 关键词: Address; Anatomy; Animals; Autopsy; Brain; Brain imaging; Brain region; Calcium; Cells; Cellular Structures; Data; Development; Electrophysiology (science); Genetic Transcription; Goals; Image; In Vitro; Individual; Interneurons; Knowledge; Maps; Measures; Microscopy; Modeling; Mus; Neuraxis; Neurons; Pattern; Population; Prevalence; Pyramidal Cells; RNA; Recurrence; Research Project Grants; Resolution; Resources; Rodent; Role; Sampling; Slice; Somatostatin; Stimulus; Synapses; Technology; Testing; Thalamic structure; Theoretical model; Time; Tissues; V1 neuron; Viral; Vision; Visual; Visual Cortex; Work; base; cell type; connectome; experimental study; in vivo; in vivo imaging; mouse model; neural circuit; optogenetics; orientation selectivity; patch clamp; predictive modeling; preference; presynaptic; prevent; relating to nervous system; response; retinotopic; sensory input; spatial relationship; theories; tool; visual processing; visual stimulus

ABSTRACT An accurate and predictive model of the function and dynamics of any neural circuit requires a complete picture of the synaptic connections between all of its composite cell types. Despite extensive work, we still lack such a diagram in V1, or for any other neural circuit in the mammalian central nervous system. The goal of the Neural Connectivity Resource Core is to combine in vivo multiphoton optogenetic circuit mapping with functional calcium imaging and post-hoc seqFISH RNA profiling to obtain the functional connectome of all transcriptionally distinguishable V1 cell types – that is a complete connectivity diagram between all of V1’s component cell types, specifically including data on the strength and short-term plasticity of the unitary monosynaptic connections between each cell type. It will thus provide critical support to the theoretical modeling projects that require these data to build accurate models of V1 dynamics. Furthermore, by working in vivo, this resource core will map synaptic connectivity onto neurons that will also be functionally characterized with respect to their responses to visual stimuli. This will permit direct correlation between visual responses, synaptic connectivity and dynamics, and transcriptional identity at the cellular level. This knowledge is critical for constraining our development of the most accurate and predictive theoretical models of visual cortical dynamics and computation.

摘要