Attentional Modulation of Neuronal Communication

神经元通讯的注意调节

基本信息

  • 批准号:
    7923612
  • 负责人:
  • 金额:
    $ 24.16万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-04-01 至 2011-12-31
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): Cognitive operations like selective attention are thought to involve coordinated activity of neuronal ensembles in multiple brain areas. It is abundantly clear that attention enhances visual responses within local ensembles of neurons throughout the visual system, the corollary idea that attention also facilitates the transmission of visual inputs between neuron ensembles in different cortical layers and in different cortical regions has not been thoroughly investigated. Similarly, while it is generally agreed that attentional modulation of low level visual processing is controlled by a higher order network, the specific circuits and physiological processes by which top-down control is imposed are not well understood. With these two problems in mind the overall goal of this project is to define the magnitude and physiological mechanisms of attention's influence on feedforward communication in low level visual processing. Using a combination of spike correlation, standard coherence and Granger causality analyses, we will analyze data from multielectrode recordings in V1 and V2 in monkeys performing a single, well-studied (intermodal) attention task. We have shown that because of the predictability of stimulus rhythms in this paradigm, attention can use low frequency oscillations as instruments to enhance neuronal responses to task relevant stimuli. This finding has wide ramifications because rhythm and predictability are prominent in many aspects of natural behavior. To follow it up, we will test the hypothesis that attention can use low frequency oscillatory phase synchrony to facilitate feedforward communication between neuronal ensembles in the visual pathways. Our specific aims are: 1) to characterize attention's influence on feedforward transmission between cortical layers, 2) to characterize attention's influence on transmission between V1 and V2, and 3) to define the brain mechanisms underlying attentional modulation of interlaminar and interareal interactions. Concurrent sampling of laminar current source density (CSD) and multiunit activity (MUA) profiles in V1 and V2 will index synaptic activity and firing patterns in neuronal ensembles at key locations in the supragranular, granular and infragranular layers. Laminar profiles of attention effects in V1 and V2, along with Granger causality analyses will help to differentiate between several of the alternative control circuits. Single trial analysis of both pre- stimulus and poststimulus oscillatory dynamics and of related variations in neuronal firing patterns in these locations will help to relate dynamics to underlying physiology. PUBLIC HEALTH RELEVANCE: Our methods allow use of the monkey as a model for understanding the neuronal mechanisms of ERP and EEG generation in humans. This study will also provide a data set that can be used to evaluate new functional connectivity analyses developed for use in humans, particularly those targeting the study of epilepsy.
描述(由申请人提供):像选择性注意这样的认知操作被认为涉及多个大脑区域的神经元群的协调活动。很明显,注意增强了整个视觉系统中局部神经元群的视觉反应,但关于注意也促进了视觉输入在不同皮层层和不同皮层区域的神经元群之间的传递的推论尚未得到充分的研究。同样,虽然人们普遍认为低水平视觉处理的注意调制是由高阶网络控制的,但自上而下控制的具体电路和生理过程却没有得到很好的理解。考虑到这两个问题,本项目的总体目标是确定低水平视觉加工中注意对前馈交流影响的大小和生理机制。使用脉冲相关性、标准相干性和格兰杰因果分析的组合,我们将分析猴子在执行单一的、经过充分研究的(多模式)注意力任务时V1和V2的多电极记录数据。我们已经证明,由于在这种范式中刺激节奏的可预测性,注意力可以使用低频振荡作为工具来增强神经元对任务相关刺激的反应。这一发现具有广泛的影响,因为节奏和可预测性在自然行为的许多方面都很突出。接下来,我们将验证注意可以使用低频振荡相位同步来促进视觉通路中神经元群之间的前馈通信的假设。我们的具体目标是:1)表征注意对皮层间前馈传递的影响,2)表征注意对V1和V2之间传递的影响,以及3)定义层间和区域间相互作用的注意调节的大脑机制。同时采样V1和V2的层流电流源密度(CSD)和多单位活动(MUA)谱,将反映核上、颗粒和核内层关键位置神经元群的突触活动和放电模式。V1和V2注意效应的层流曲线,以及格兰杰因果关系分析将有助于区分几种替代控制回路。单次试验分析刺激前和刺激后的振荡动力学以及这些位置神经元放电模式的相关变化将有助于将动力学与潜在生理学联系起来。

项目成果

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MINGZHOU DING其他文献

MINGZHOU DING的其他文献

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{{ truncateString('MINGZHOU DING', 18)}}的其他基金

Acquisition, extinction, and recall of attention biases to threat: Computational modeling and multimodal brain imaging
对威胁的注意偏差的获得、消除和回忆:计算模型和多模态脑成像
  • 批准号:
    10459607
  • 财政年份:
    2021
  • 资助金额:
    $ 24.16万
  • 项目类别:
Acquisition, extinction, and recall of attention biases to threat: Computational modeling and multimodal brain imaging
对威胁的注意偏差的获得、消除和回忆:计算模型和多模态脑成像
  • 批准号:
    10629385
  • 财政年份:
    2021
  • 资助金额:
    $ 24.16万
  • 项目类别:
Ding R01 Administrative Supplement
丁R01行政补遗
  • 批准号:
    10842657
  • 财政年份:
    2021
  • 资助金额:
    $ 24.16万
  • 项目类别:
Acquisition, extinction, and recall of attention biases to threat: Computational modeling and multimodal brain imaging
对威胁的注意偏差的获得、消除和回忆:计算模型和多模态脑成像
  • 批准号:
    10296986
  • 财政年份:
    2021
  • 资助金额:
    $ 24.16万
  • 项目类别:
Mechanisms of attentional control: Structure and dynamics from simultaneous EEG-fMRI and machine learning
注意力控制机制:同步脑电图-功能磁共振成像和机器学习的结构和动力学
  • 批准号:
    10368957
  • 财政年份:
    2018
  • 资助金额:
    $ 24.16万
  • 项目类别:
Mechanisms of attentional control: Structure and dynamics from simultaneous EEG-fMRI and machine learning
注意力控制机制:同步脑电图-功能磁共振成像和机器学习的结构和动力学
  • 批准号:
    10115818
  • 财政年份:
    2018
  • 资助金额:
    $ 24.16万
  • 项目类别:
Emotional Engagement Driven by Complex Visual Stimuli: Neural Dynamics Revealed by Multimodal Imaging
复杂视觉刺激驱动的情感参与:多模态成像揭示的神经动力学
  • 批准号:
    9883648
  • 财政年份:
    2017
  • 资助金额:
    $ 24.16万
  • 项目类别:
Spatiotemporal Network Dynamics in a Rat Model of Schizophrenia
精神分裂症大鼠模型中的时空网络动力学
  • 批准号:
    8720463
  • 财政年份:
    2014
  • 资助金额:
    $ 24.16万
  • 项目类别:
Measuring Cognitive Fatigability in Older Adults
测量老年人的认知疲劳度
  • 批准号:
    8926342
  • 财政年份:
    2014
  • 资助金额:
    $ 24.16万
  • 项目类别:
Spatiotemporal Network Dynamics in a Rat Model of Schizophrenia
精神分裂症大鼠模型中的时空网络动力学
  • 批准号:
    8826825
  • 财政年份:
    2014
  • 资助金额:
    $ 24.16万
  • 项目类别:

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