Population Neural Activity Mediating Sensory Perception Across Modalities
群体神经活动介导跨模态的感官知觉
基本信息
- 批准号:9789712
- 负责人:
- 金额:$ 100.48万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-09-30 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAlgorithmsAnimalsArchitectureAtlasesAuditoryBehaviorBehavioralBiological ModelsBrainBrain imagingCodeCollaborationsComplexComputer SimulationCourtshipCuesDataData AnalysesData SetDiseaseDrosophila genusEnvironmentEsthesiaFacial ExpressionFutureGeneticGoalsHumanImageImpairmentIndividualLeadLeftLinkLocomotionMapsMeasuresMediatingMethodsModalityModelingMonitorMotorNeuronsNeurosciencesParkinson DiseasePathway interactionsPerceptionPeripheralPopulationPopulation DynamicsPropertyResearch PersonnelResolutionSamplingSensorySensory ReceptorsShapesSignal TransductionSpeechStatistical ModelsStereotypingStimulusStreamSynapsesSystemTaste PerceptionTechnologyTestingVisionVisualWorkautism spectrum disorderbasebehavior measurementbehavioral responsecell typedesignexperienceexperimental studyflyimprovedin vivo two-photon imaginginsightintegration sitemultimodalitymultisensoryneural circuitneural modelrelating to nervous systemresponsesensory inputsensory integrationsensory stimulusstatisticstheoriestool
项目摘要
Project Summary:
Natural sensory inputs are typically complex, and often combine multiple modalities. Human speech, for
example, combines auditory signals with visual cues, such as facial expressions, that inform the interpretation
of the spoken words. As individual sensory pathways only provide a partial representation of the sensory
information available, selecting the context-appropriate behavioral response to a multimodal stimulus often
requires integrating information across modalities. How do neural circuits perform this fundamental
computation?
Our current understanding of sensory processing is predominantly built upon studies that have focused on
single sensory modalities, working into the brain beginning from sensory receptors. As a result, we have a
deep understanding of peripheral circuit computations in many different experimental contexts. However,
working inward, cell-type by cell-type, has left our understanding of the circuits and computational principles
that link sensation to action incomplete. Moreover, experimental strategies that focus exclusively on single
sensory modalities cannot, by design, lead to insights into how the unified percepts that guide behavior can be
assembled from information emerging in separate sensory processing streams. Here we leverage whole-brain
imaging and advanced computational approaches to establish the fruit fly Drosophila as a model system for
uncovering fundamental principles underpinning multisensory integration.
This proposal has three goals. First, we will optimize whole-brain imaging in this experimental system, and use
this technology to comprehensively characterize population dynamics underpinning the sensations of vision,
mechanosensation and taste. Second, we will systematically quantify circuit interactions between these
sensory modalities and across-animal variability, testing computational models of statistical inference, and
identifying the algorithmic bases of multimodal integration. Third, we will link population dynamics to the
response properties of single cell-types, providing a powerful path to characterizing circuit and synaptic
mechanisms. Taken together, by developing and applying improved methods for large-scale monitoring of
neural activity, combined with computational modeling and quantitative analysis, this project will greatly expand
our understanding of sensory processing mechanisms across the brain.
项目概要:
自然感觉输入通常是复杂的,并且通常联合收割机组合多种形式。人类的语言,因为
例如,将听觉信号与视觉线索(如面部表情)结合起来,为解释提供信息
的话语。由于单个感觉通路仅提供感觉的部分表征,
信息可用,选择上下文适当的行为反应,多模态刺激往往
需要整合各种模式的信息。神经回路如何执行这个基本的
计算?
我们目前对感觉加工的理解主要建立在以下研究的基础上:
单一的感觉方式,从感觉受体开始进入大脑。因此,我们有一个
在许多不同的实验环境中对外围电路计算有深刻的理解。然而,在这方面,
一个细胞一个细胞地向内工作,已经让我们对电路和计算原理的理解
将感觉和不完整的动作联系起来此外,实验策略,专门侧重于单一的
通过设计,感官形式不能导致对指导行为的统一感知如何被理解的洞察力。
由独立的感官处理流中出现的信息组合而成。在这里,我们利用全脑
成像和先进的计算方法来建立果蝇作为一个模型系统,
揭示多感官整合的基本原理。
这项建议有三个目标。首先,我们将在这个实验系统中优化全脑成像,并使用
这项技术可以全面描述支撑视觉感觉的人口动态,
机械感觉和味觉。其次,我们将系统地量化这些之间的电路相互作用,
感觉形态和跨动物变异性,测试统计推断的计算模型,以及
识别多模态整合的算法基础。第三,我们将把人口动态与
单细胞类型的响应特性,提供了一个强大的路径来表征电路和突触
机制等总之,通过开发和应用改进的方法,
神经活动,结合计算建模和定量分析,这个项目将大大扩大
我们对大脑感觉处理机制的理解。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Thomas Robert Clandinin其他文献
Thomas Robert Clandinin的其他文献
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{{ truncateString('Thomas Robert Clandinin', 18)}}的其他基金
How do neurons coordinate alternative energy sources to meet the demands of computation?
神经元如何协调替代能源以满足计算需求?
- 批准号:
10606195 - 财政年份:2022
- 资助金额:
$ 100.48万 - 项目类别:
Population Neural Activity Mediating Sensory Perception Across Modalities
群体神经活动介导跨模态的感官知觉
- 批准号:
10310712 - 财政年份:2021
- 资助金额:
$ 100.48万 - 项目类别:
Population Neural Activity Mediating Sensory Perception Across Modalities
群体神经活动介导跨模态的感官知觉
- 批准号:
10242189 - 财政年份:2018
- 资助金额:
$ 100.48万 - 项目类别:
A Brain Circuit Program for Understanding the Sensorimotor Basis of Behavior
用于理解行为的感觉运动基础的脑回路程序
- 批准号:
10202757 - 财政年份:2017
- 资助金额:
$ 100.48万 - 项目类别:
Revealing circuit control of neuronal excitation with next-generation voltage indicators
使用下一代电压指示器揭示神经元兴奋的电路控制
- 批准号:
9380741 - 财政年份:2017
- 资助金额:
$ 100.48万 - 项目类别:
A Brain Circuit Program for Understanding the Sensorimotor Basis of Behavior
用于理解行为的感觉运动基础的脑回路程序
- 批准号:
9444301 - 财政年份:2017
- 资助金额:
$ 100.48万 - 项目类别:
Project 3: Neural Basis of Motion Guidance Loops
项目 3:运动引导环的神经基础
- 批准号:
10202763 - 财政年份:2017
- 资助金额:
$ 100.48万 - 项目类别:
A new strategy for cell-type specific gene disruption in flies and mice
果蝇和小鼠细胞类型特异性基因破坏的新策略
- 批准号:
9297370 - 财政年份:2015
- 资助金额:
$ 100.48万 - 项目类别:
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