Natural scenes often contain multiple entities. The ability to segregate visual scenes into distinct objects and surfaces, referred to as segmentation, is a fundamental function of vision. Segmentation is crucial for interpreting visual images and for generating the perception of our environment. However, the neural mechanisms underlying image segmentation are not well understood. Our long-term goal is to understand the neural basis underlying perceptual organization and ultimately how perception arises from activity in neuronal network. Among sub-modalities of vision, visual motion provides a potent cue for segmentation. The proposed research uses visual motion to investigate how multiple stimuli are represented by neurons in the visual cortex such that the segmentation and perception of multiple stimuli can be achieved. To isolate the effects of visual motion cues from those of spatial cues on image segmentation, we will use random-dot patterns that move in the same region of visual space in different directions. Previous studies have shown that the responses of cortical neurons elicited by multiple, perceptually separable, stimuli tend to follow the average of the responses elicited by the constituent stimuli presented alone. Such a scheme, however, poses a challenge in segmenting two stimuli that differ only slightly, because averaging essentially takes away the information regarding the identities of individual stimulus components. The central problem to be addressed by the proposed research is how the segmentation of slightly different, but perceptually distinguishable, stimuli is achieved by the visual system. We will combine the methods of neurophysiology, behavior and computation to achieve our goals. The proposal has two specific aims.
In Aim #1, we will determine how multiple moving stimuli are represented by populations of neurons in the visual cortex and the temporal dynamics of such neural representation, while the visual system solves the problem of segmenting overlapping stimuli moving in different directions.
In Aim #2, we will elucidate how visual depth and speed cues, and selective attention modulate the neural representation of multiple stimuli moving in different directions. The proposed research will provide insight into fundamental neural operations of cortical network in processing sensory information and will expand our knowledge of the neural mechanisms underlying perceptual organization. Insights gained from studying normal visual functions promise to improve our understanding of the cause, treatment and prevention of disorders of vision and eye movements.
Normal brain functions arise from the activity of populations of neurons within intricately connected cortical networks. When normal patterns of activity across neuronal populations go awry, many neurological disorders, such as epilepsy and schizophrenia, occur. The proposed research will advance our understanding of representing sensory information in neuronal populations in the cerebral cortex. The results will help to inform the causes for neurological disorders that involve populations of neurons in cortical networks. In particular, the proposed research will deepen our understanding of physiological mechanisms underlying how visual scenes are segmented into multiple objects and surfaces. The insights gained from the proposed research using a primate model may contribute to a better understanding of neurological disorders such as dyslexia and visual agnosia that involve malfunction of visual segmentation.
|Xiao, Jianbo; Niu, Yu-Qiong; Wiesner, Steven et al. (2014) Normalization of neuronal responses in cortical area MT across signal strengths and motion directions. J Neurophysiol 112:1291-306|