课题基金 / 基金详情

Neurocognitive basis of attention and eye movement guidance in the real world scenes

Neurocognitive basis of attention and eye movement guidance in the real world scenes
现实世界场景中注意力和眼动引导的神经认知基础
批准号:
10004653
负责人:
AVNIEL S GHUMAN
金额:
$19.56万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2022-07-31

项目摘要

项目成果

AVNIEL S GHUMAN的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
Summary/Abstract Real world scenes contain a wealth of information that guide where we look and help us search for things in our visual environment more efficiently. For example, if you were looking for a person in a city, you would look mostly on the sidewalk, whereas if you were looking for a car, you would concentrate your attention on the street. Despite the fact that behavioral experiments have increasingly quantified the role of object and scene knowledge in the guidance of attention and eye movements, models of these processes, particularly neural models, neglect the role of visual knowledge. The goal of this project is to determine whether regions of the brain shown to be important for object and scene recognition are involved in visual guidance in natural scenes. Prior results, including our preliminary data, show that the neural activity from object processing regions can be used to predict what object a person is going to look at next. However, critical questions that remain are: is this predictive activity influenced by scene and object knowledge and is it causally related to visual guidance? Answering these two questions are the specific goals of this proposal. Individuals undergoing neurosurgical evaluation for epilepsy provide the rare opportunity of recording directly from the human brain (intracranial electroencephalography, iEEG), which provides a superior spatial and temporal resolution measure of brain activity compared to other technique. These direct recordings also allow for electrical brain stimulation (EBS), which can provide causal evidence tying the activity in particular regions to cognitive function. Finally, these data will be supplemented by magnetoencephalography (MEG) data to examine whole brain effects in healthy individuals. iEEG and MEG data arising from regions involved in object and scene recognition will be analyzed by multivariate machine learning techniques to continually classify what subjects are viewing on a moment-to- moment basis. Furthermore, we will try to predict what object subjects will view next during free viewing and visual search in natural scenes based on their neural data. We will assess how these neural signals are modified by the presence or absence of information about typical locations of objects or people in the scene that have been shown to guide behavior. Finally, using EBS we will determine if there is a causal link between the activity in regions involved in coding for object and scene knowledge and visual guidance in natural scene vision. If successful, these studies would necessitate a substantial reshaping of models of visual attention in the human brain. The results could form the foundation of a program of research into the neural basis of attention and eye movement guidance in the real world. Attention, perception, and eye movement abnormalities are seen in a host of neurological and psychiatric disorders. Thus, these studies, and the models that arise from them, have the translational potential to advance our understanding of the neurological basis of these disorders and suggest potential neurally inspired rehabilitation strategies.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Active Social Vision: How the Brain Processes Visual Information During Natural Social Perception
Neural basis of local and circuit-level spontaneous and task-evoked hemodynamic brain activity
Neural basis of local and circuit-level spontaneous and task-evoked hemodynamic brain activity
Inside the social perception network: dynamics, connectivity, and stimulation
海外基金