Neural Basis of Multisensory Integration

多感觉统合的神经基础

• 批准号: 0446730
• 负责人: Alexandre Pouget
• 金额: $ 32.87万
• 依托单位: University of Rochester
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-08-01 至 2009-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0446730&HistoricalAwards=false
• 关键词: Neural; Basis; Multisensory; Integration

The nervous system can sense the world through a variety of sensory modalities providing complementary as well as redundant information about various aspects of the real world. Through a process known as multisensory integration, those sensory signals are merged and used to perform a variety of tasks such as locating objects in space or identifying the words uttered by a speaker. With funding from the National Science Foundation, Dr. Alexandre Pouget is conducting a strongly theory-driven research program combining modeling, human psychophysics and non-human primate neurophysiologal studies to investigate the neural basis of the process known as multisensory integration. Two factors make multisensory integration difficult: First, the sensory modalities are often in different formats (e.g., the sound and image of the same object are not directly comparable); and Second, the sensory modalities are not equally reliable (e.g., it is typically much easier to tell which word is uttered by a speaker based on sound than on lip movements). Using the framework of Bayesian inference, the research plan is to first develop a neural theory of multisensory integration that can solve both problems optimally. Then the plan is to perform recording in multisensory areas of awake monkeys to test the validity of the approach. While intuition would suggest that a neuron should respond to the same location in space regardless of the modality, a preliminary model suggests otherwise. In the computational network, the visual and tactile receptive fields of a given neuron do not occupy the exact same location. Experiments will involve recordings from cortical visuo-tactile neurons to test whether their receptive fields behave as predicted by simulations. The temporal aspect of the theory will also be tested through psychophysics experiments in humans. Subjects will be asked to perform sequences of eye movements in the presence of artificial motor error. The theory of optimal integration predicts that subjects will attempt to correct for their errors in proportion to the reliability of the visual feedback.This research will involve postdocs, undergraduate and graduate students, and the results will be presented at major multidisciplinary conferences. The results will also have implications well beyond multisensory integration. Indeed, multisensory integration is a subcase of the general problem of Bayesian inference, which is believed to be at the heart of numerous cognitive processes such as object recognition, visual perception, motor control and abstract reasoning.

神经系统可以通过各种感觉模式感知世界，提供关于现实世界各个方面的补充和冗余信息。通过一个被称为多感觉整合的过程，这些感觉信号被合并并用于执行各种任务，如定位空间中的物体或识别说话者说出的话。在国家科学基金会的资助下，亚历山大·普吉特博士正在进行一项强烈的理论驱动型研究计划，将建模、人类心理物理学和非人类灵长类动物的神经生理学研究结合在一起，以调查被称为多感觉整合的过程的神经基础。两个因素使得多感觉整合变得困难：第一，感觉形式通常是不同的(例如，同一物体的声音和图像不能直接比较)；第二，感觉形式不是同样可靠(例如，根据声音通常比根据嘴唇动作更容易辨别说话者说出的是哪个词)。利用贝叶斯推理的框架，研究计划是首先开发一种多感觉整合的神经理论，可以最优地解决这两个问题。然后，计划在清醒猴子的多感官区域进行记录，以测试该方法的有效性。虽然直觉表明，神经元应该对空间中相同的位置做出反应，而无论其形态如何，但初步模型表明并非如此。在计算网络中，给定神经元的视觉和触觉感受野并不占据完全相同的位置。实验将涉及大脑皮层视觉触觉神经元的录音，以测试它们的感受野是否如模拟所预测的那样表现。这一理论的时间性也将通过人体心理物理学实验进行检验。受试者将被要求在存在人工运动错误的情况下进行眼球运动序列。最优整合理论预测，受试者将尝试与视觉反馈的可靠性成正比地纠正错误。这项研究将涉及博士后、本科生和研究生，结果将在主要的多学科会议上公布。这一结果也将产生远远超出多感官整合的影响。事实上，多感觉整合是贝叶斯推理一般问题的一个子例，贝叶斯推理被认为是许多认知过程的核心，如物体识别、视觉感知、运动控制和抽象推理。