The Responses of V4 Cortical Neurons to Multiple Visual Stimuli

University Of Alabama At Birmingham, Birmingham AL

Investigators

Abstract

The sense of vision seems effortless, and intuitively visual perception seems like it should be simple. However, research has shown that visual scene analysis requires, in addition to the retinas and numerous brainstem nuclei, the use of about one-third of the cerebral cortex. This is because visual perception (as opposed to the mere image recording seen in a digital camera) means taking the pattern of light and dark from a 2D image and from it inferring the structure and properties of objects in the real 3D world. Vision is not a low-level process, but a higher cognitive process whose study has drawn the attention of a large fraction of the neuroscientists. The rhesus monkey is the best available model of the human visual system. This project will involve recording from single V4 cortical neurons from behaving rhesus monkeys to multiple simultaneous visual stimuli. Visual cortical area V4 is a major cortical center for form perception. Unlike so-called "higher" cortical areas such as the inferotemporal (IT) cortex, neurons in V4 can be easily stimulated with simple geometric shapes. Unlike so-called "lower" areas such as V1 and V2, neurons in V4 have receptive fields large enough to encompass more than one discrete visual stimulus at a time. These properties mean that V4 is an ideal location to study how neurons in the visual system combine information from different parts of an image. Neurons early in the visual system examine only a small part of an image (i.e., they have small receptive fields), but neurons in later areas of processing have much larger receptive fields. Neurons with large receptive fields cannot be simply summing their inputs, or the result would be objects that appear as just a large blur. Neurons must be processing their inputs in a manner other than averaging or summing. But what are the rules of this processing? Experimental and theoretical studies suggest that one set of rules is for a neuron to select only the inputs that by themselves would elicit the maximum response. A competing theory is that neurons should compute the weighted average of their inputs. This study aims to resolve this controversy, an aim that is of significant importance to the field of visual neuroscience, and potentially, of importance to computer vision. While the focus of this project is on vision, in principal the results could apply to all of the cerebral cortex. Nature is conservative, and rarely creates a mechanism that is only used on just one location. Also, cerebral cortex is notable for it's relative homogeneity, i.e, the neural circuits in part of the cerebral cortex follow generally the same organization as the circuits on another place in cortex. Finally, the cerebral cortex is notable for the richness of reciprocal connections between different regions. Indeed, it is this richness of interconnections that makes the cerebral cortex so susceptible to seizures. A core part of how the cerebral cortex functions must be how a given region combines or selects from the richness of inputs available to it. As such, this study aims to explore not just the visual system but fundamental aspects of cortical function. The broader impact of the research is to promote interdisciplinary teaching and training of both undergraduate and graduate students. There will be a focus on encouraging participation from members of underrepresented groups from several minority serving institutions in Alabama.