From microscale structure to population coding of normal and learned behavior

从微观结构到正常和习得行为的群体编码

• 批准号: 10225540
• 负责人: Wiliam McIntyre DeBello
• 金额: $ 51.76万
• 依托单位: ALBERT EINSTEIN COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-25 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10225540
• 关键词: Achievement; Adaptive Behaviors; Address; Afferent Neurons; Anatomy; Architecture; Auditory; Automobile Driving; Axon; Barn Owls; Behavior; Behavioral; Binaural; Binding; Biological Models; Brain; Cells; Characteristics; Code; Computer Models; Contralateral; Cues; Data; Distributional Activity; Electron Microscopy; Electrophysiology (science); Experimental Designs; Goals; Head; Learning; Link; Location; Maps; Measures; Methods; Microanatomy; Microelectrodes; Microscopy; Midbrain structure; Modeling; Movement; Neurons; Noise; Optics; Pathologic; Pathway interactions; Pattern; Peripheral; Physiological; Population; Property; Research; Resolution; Shapes; Sound Localization; Stimulus; Strigiformes; Structure; System; Testing; Time; Tissues; Translating; Vertebrates; Visual; Work; approach behavior; base; behavior measurement; behavior test; cell type; cellular targeting; comparative; driving behavior; experimental study; gaze; information processing; learned behavior; light microscopy; multi-electrode arrays; multidisciplinary; network architecture; network models; neural patterning; neurotransmission; prismatic spectacles; receptive field; relating to nervous system; response; sound; theories

Abstract This study aims to understand how the ensemble activity and network architecture of a neuronal population guides natural and learned behavior. The model system is the midbrain localization pathway of the owl. Ensemble recordings, microcircuit analysis, behavioral measurements and computational modeling will be used to analyze the neural representation of auditory space and the head-orienting movement driven by it. The compact volume of tissue commanding this behavior makes a complete understanding of information processing tractable with high-throughput electrophysiological and microanatomical methods. How information about sound location is readout to guide orienting behaviors has not been demonstrated in any species. This project has the potential to fill this gap. Aim 1 will investigate the relationship between orienting behavior and activity in the neuronal population representing auditory space, in which frontal space is overrepresented. The hypothesis is based on recent work showing that sound localization can be explained by statistical inference, computed by integrating activity across the entire population. Microelectrode arrays (MEAs) will be used to map the activity of the population upon presentation of sounds. Population decoders will be constructed to determine how the population activity is readout to drive behavior. In Aim 2, the network architecture supporting the activity pattern will be studied with light and electron microscopy. Network models will combine the data to explain how connectivity and cellular computations result in the population activity and correlated firing that drives behavior. When auditory-visual cues are modified, the midbrain representation of auditory space adapts over time, and consequently drives a learned behavior. Aim 3 will directly examine this link. MEA recordings, microcircuit analysis and behavioral measurements will be made in owls adapted to prismatic spectacles. Population decoders will be used to test the hypothesis that population activity in the learned condition maintains a non-uniform population code with an overrepresentation of frontal space. Network models will be used to examine how local re-wiring may explain changes in the distribution of activity across the population. This would be the first time that neural activity and network architecture underlying sound localization are approached from the complete-population down to single-cell level, before and after learning. This integrative approach holds potential for understanding principles of population coding, plasticity and learning that operate across species and brain circuits.

摘要 本研究旨在了解神经元群体的整体活动和网络结构 引导自然和习得的行为。模型系统为猫头鹰中脑定位通路。 实验记录、微电路分析、行为测量和计算建模将在 用于分析听觉空间的神经表征及其驱动的头部定向运动。 指挥这种行为的紧凑组织体积可以完整地理解信息 用高通量电生理学和显微解剖学方法处理易处理的。如何 关于声音位置的信息被读出以引导定向行为还没有在任何 物种该项目有可能填补这一空白。 目的1将研究神经元群体中定向行为和活动之间的关系 代表听觉空间，其中额叶空间被过度代表。该假设是基于最近的 工作表明，声音定位可以解释统计推断，计算通过整合 整个人口的活动。微电极阵列（MEA）将被用于映射的活动， 人口的声音呈现。将建造人口解码器，以确定 种群活动被读出以驱动行为。 在目标2中，支持活动模式的网络架构将与光和电子一起研究 显微镜网络模型将结合联合收割机的数据来解释如何连接和细胞计算 导致种群活动和驱动行为的相关放电。 当听觉-视觉线索被修改时，听觉空间的中脑表征会随着时间的推移而适应， 从而驱动习得的行为。目标3将直接研究这一联系。MEA记录， 将在适应棱镜眼镜的猫头鹰中进行微电路分析和行为测量。 人口解码器将被用来测试假设，人口活动在学习条件 保持着一个不统一的人口代码与正面空间的过度代表性。网络模型将 可以用来研究如何当地重新布线可以解释在整个活动分布的变化， 人口 这将是第一次，神经活动和网络架构的基础声音定位是 接近从完整的人口下降到单细胞水平，之前和之后的学习。这 综合方法具有理解群体编码、可塑性和学习原理的潜力 跨物种和大脑回路运作。

项目成果

Natural ITD statistics predict human auditory spatial perception.

• DOI: 10.7554/elife.51927
• 发表时间: 2020-10-12
• 期刊: eLife
• 影响因子: 7.7
• 作者: Pavão R;Sussman ES;Fischer BJ;Peña JL
• 通讯作者: Peña JL

Development of frequency tuning shaped by spatial cue reliability in the barn owl's auditory midbrain.

• DOI: 10.7554/elife.84760
• 发表时间: 2023-05-11
• 期刊: eLife
• 影响因子: 7.7
• 作者: Shadron K;Peña JL
• 通讯作者: Peña JL

Diverse processing underlying frequency integration in midbrain neurons of barn owls.

• DOI: 10.1371/journal.pcbi.1009569
• 发表时间: 2021-11
• 期刊: PLoS computational biology
• 影响因子: 4.3
• 作者: Gorman JC;Tufte OL;Miller AVR;DeBello WM;Peña JL;Fischer BJ
• 通讯作者: Fischer BJ

Toric Spines at a Site of Learning

学习场所的环面脊柱

• DOI: 10.1523/eneuro.0197-19.2019
• 发表时间: 2020
• 期刊: eneuro
• 影响因子: 3.4
• 作者: Sanculi, Daniel;Pannoni, Katherine E.;Bushong, Eric A.;Crump, Michael;Sung, Michelle;Popat, Vyoma;Zaher, Camilia;Hicks, Emma;Song, Ashley;Mofakham, Nikan
• 通讯作者: Mofakham, Nikan