CRCNS US-France-Israel-Research Proposal: Processing of Complex Sounds: Cortical Network Mechanisms and Computations

CRCNS 美国-法国-以色列研究提案：复杂声音的处理：皮质网络机制和计算

• 批准号: 1724421
• 负责人: Tatyana Sharpee
• 金额: $ 95万
• 依托单位: The Salk Institute for Biological Studies
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1724421&HistoricalAwards=false
• 关键词: CRCNS; US; France; Israel; Research

What are the relationships between the complex and constantly changing soundscapes that surround us and the electrical activity that represents them in the brain? This project brings together three groups, one experimental and two computational, to address this question at two different levels. First, mechanistic models will be developed, based on known properties of neural networks, to describe how different types of neurons cooperate to represent sounds. Second, the function of these neurons will be characterized by describing the features of sounds that they represent. These two goals will be achieved by combining experimental studies of neural responses to sounds with computational analyses to test candidate mechanisms for how sounds are represented in large cortical circuits. In addition to deeper understanding of auditory perception, this research will provide insights into general principles of cooperation between neurons within a single neural network. As such, the research has implications for understanding representation of signals in other sensory modalities as well as the general principles of neural coding in the brain. The research has a number of potential practical applications, including the design of advanced hearing aids and artificial speech recognition systems. Further, given that the altered balance between excitatory and inhibitory neurons has been implicated in a number of attention deficits and psychiatric disorders, including autism and schizophrenia, the project has potential medical relevance. The outreach component of the project will involve demonstration involving music and speech perception for K-12 students and exhibitions.Technically, the experimental group will produce recordings of neural responses from the auditory thalamus and cortex in response to pure tones and complex sounds known as tone clouds. The tone clouds have sharp transitions like natural sounds, but with well-controlled spectral and temporal power distributions. Computational components of this project will aim to reproduce neural recordings through analytical modeling and simulations of large scale neural circuits composed of multiple cell types. The experimental and computational results will be matched not only in statistical terms, such as average dynamics of neural responses across the population, but also in terms of specific features of sounds that are encoded by different types of neurons in the network.This award is cofunded by the Office of International Science and Engineering. Companion projects are being funded by the French National Research Agency (ANR) and the US-Israel Binational Science Foundation (BSF).

我们周围复杂且不断变化的音景与大脑中代表它们的电活动之间有什么关系？这个项目汇集了三个小组，一个实验和两个计算，以解决这个问题在两个不同的水平。首先，将根据神经网络的已知特性开发机械模型，以描述不同类型的神经元如何合作来表示声音。其次，这些神经元的功能将通过描述它们所代表的声音的特征来表征。这两个目标将通过结合实验研究的神经反应的声音与计算分析，以测试候选机制的声音是如何表示在大型皮层电路。除了对听觉感知有更深入的了解外，这项研究还将深入了解单个神经网络中神经元之间合作的一般原则。因此，这项研究对理解其他感觉方式中的信号表示以及大脑中神经编码的一般原理具有影响。这项研究有许多潜在的实际应用，包括设计先进的助听器和人工语音识别系统。此外，鉴于兴奋性和抑制性神经元之间的平衡改变与许多注意力缺陷和精神疾病（包括自闭症和精神分裂症）有关，该项目具有潜在的医学意义。该项目的外展部分将包括为K-12学生演示音乐和语音感知以及展览。从技术上讲，实验组将记录听觉丘脑和皮层对纯音和称为音调云的复杂声音的神经反应。音云具有像自然声音一样的急剧过渡，但具有良好控制的频谱和时间功率分布。该项目的计算部分旨在通过分析建模和模拟由多种细胞类型组成的大规模神经回路来重现神经记录。实验和计算结果不仅在统计学方面相匹配，例如整个人群神经反应的平均动态，而且在网络中不同类型神经元编码的声音的特定特征方面也相匹配。该奖项由国际科学与工程办公室共同资助。伴随项目由法国国家研究机构（ANR）和美国-以色列两国科学基金会（BSF）资助。

项目成果

Linking neural responses to behavior with information-preserving population vectors

将神经反应与行为与信息保存群体向量联系起来

• DOI: 10.1016/j.cobeha.2019.03.004
• 发表时间: 2019
• 期刊: Current Opinion in Behavioral Sciences
• 影响因子: 5
• 作者: Sharpee, Tatyana O.;Berkowitz, John A.
• 通讯作者: Berkowitz, John A.

How inhibitory neurons increase information transmission under threshold modulation.

抑制性神经元如何在阈值调制下增加信息传递。

• DOI: 10.1016/j.celrep.2021.109158
• 发表时间: 2021-05-25
• 期刊: Cell reports
• 影响因子: 8.8
• 作者: Hsu WM;Kastner DB;Baccus SA;Sharpee TO
• 通讯作者: Sharpee TO

An argument for hyperbolic geometry in neural circuits

• DOI: 10.1016/j.conb.2019.07.008
• 发表时间: 2019-10-01
• 期刊: CURRENT OPINION IN NEUROBIOLOGY
• 影响因子: 5.7
• 作者: Sharpee, Tatyana O.