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Complex decisions and the brain: an experimental and theoretical approach

Complex decisions and the brain: an experimental and theoretical approach
复杂决策和大脑:实验和理论方法
批准号:
8142504
负责人:
ANNE KATHRYN CHURCHLAND
金额:
$24.9万
依托单位国家:
美国
项目类别:
财政年份:
2010
资助国家:
美国
项目状态:
已结题
起止时间:
2010-09-01 至 2013-08-31
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中文摘要
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英文摘要
The goal of this proposal Is to extend our understanding of decision-making beyond the simple paradigms that have been studied thus far. During the mentored phase, I used an experimental and theoretical approach to examine how subjects Integrate sensory evidence for simple decisions. The research proposed here will explore how subjects Integrate evidence for more complex decisions- in particular, decisions where the sensory evidence comes not only from the visual system (single cue decisions), but from the auditory system as well (cue Integration decisions). While it has been known for some time that vision can be influenced by other modalities, the neural mechanisms underlying this phenomenon remain largely unknown. To investigate the neural mechanisms underlying cue integration, I will use a rate discrimination decision task. I will examine how the speed and accuracy of subjects' decisions changes depending on whether rate information is presented to the visual system, the auditory system, or both. Because the information about rate in the task is noisy and unreliable, subjects can potentially make better decisions if they integrate information from the two modalities. I will record electrophysiological responses from parietal cortex as the animals are engaged in the task. Further, I will use theoretical models to ask: can the behavioral differences on the single-cue vs cue integration tasks be explained by the different electrophysiological responses on the two tasks? My training thus fa r makes me ideally suited for this endeavor: I have extensive experience conducting physiology experiments in awake, behaving animals. Further, because of the mentored phase, I have gained expertise in theoretical modeling and have developed analysis tools that will be critical for interpreting the physiological data.
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