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The role of area V4 in the perception and recognition of visual objects

V4区在视觉物体感知和识别中的作用

基本信息

批准号：
9248377
负责人：
Anitha Pasupathy
金额：
$ 47.94万
依托单位：
UNIVERSITY OF WASHINGTON
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-04-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9248377
关键词：
Agnosia Animal Behavior Animals Area Back Behavior Behavior Control Behavioral Brain Brain Diseases Color Complex Computer Simulation Computer Vision Systems Custom Data Discrimination Eye Feedback Functional disorder Goals Grouping Human Image Impairment Lesion Macaca Mediating Methods Modeling Monkeys Neurons Pathway interactions Perception Performance Peripheral Physiological Play Population Prefrontal Cortex Primates Process Property Psychology Psychophysics Role Schizophrenia Shapes Signal Transduction Stimulus Stream Surface Surface Properties Techniques Testing Texture Time V4 neuron Vision Visual Visual Agnosias Visual Cortex Visual system structure area V4 awake base design executive function experimental study fovea centralis imaging Segmentation impaired capacity neurophysiology neurotransmission object recognition public health relevance relating to nervous system response stereoscopic study population visual processing

项目摘要

DESCRIPTION (provided by applicant): The human visual system parses the information that reaches our eyes into a meaningful arrangement of regions and objects. This process, called image segmentation, is one of the most challenging computations accomplished by the primate brain. To discover its neural basis we will study neuronal processes in two brain areas in the macaque monkey-V4, a fundamental stage of form processing along the occipito-temporal pathway, and the prefrontal cortex (PFC), important for executive control. Dysfunctions of both areas impair shape discrimination behavior in displays that require the identification of segmented objects, strongly suggesting that they are important for image segmentation. Our experimental techniques will include single and multielectrode recordings, behavioral manipulations, perturbation methods and computer models. In Aim 1 we will identify the neural signals that reflect segmentation in visual cortex. Using a variety of parametric stimuli with occlusion, clutter and shadows-stimulus features known to challenge segmentation in natural vision-we will evaluate whether segmentation is achieved by grouping regions with similar surface properties, such as surface color, texture and depth, or by grouping contour segments that are likely to form the boundary of an object or some interplay between these two strategies. We will test the hypothesis that contour grouping mechanisms are most effective under low clutter and close to the fovea. In Aim 2, we will investigate how feedback from PFC modulates shape responses in V4 and facilitates segmentation: we will test the longstanding hypothesis that object recognition in higher cortical stages precedes and facilitates segmentation in the midlevels of visual form processing. We will simultaneously study populations of V4 and PFC neurons while animals engage in shape discrimination behavior. We will use single-trial decoding methods and correlation analyses to relate the content and timing of neuronal responses in the two areas. To causally test the role of feedback from PFC, we will reversibly inactivate PFC by cooling and study V4 neurons. Our results will provide the first detailed, analytical models of V4 neuronal response dynamics in the presence of occlusion and clutter and advance our understanding of how complex visual scenes are processed in area V4. They will also reveal how V4 and PFC together mediate performance on a complex shape discrimination task, how executive function and midlevel vision may be coordinated during behavior and how feedback is used in cortical computation. Object recognition is impaired in visual agnosia, a dysfunction of the occipito-temporal pathway, and in dysfunctions of the PFC (e.g. schizophrenia). Results from these experiments will constitute a major advance in our understanding of the brain computations that underlie segmentation and object recognition and will bring us closer to devising strategies to alleviate and treat brain disorders in which these capacities are impaired.