Functional Architectural of Area V4

University Of Texas Hlth Sci Ctr Houston, Houston TX

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Abstract

Area V4 is a key component of primate visual cortex that is involved in many aspects of 'intermediate'processing including higher-order shape processing, color constancy, and attention. V4 performs more complex computations than lower areas V1 or V2, but it does not complete object analysis that occurs in the temporal lobe. Despite considerable knowledge about the properties of individual V4 neurons, little is known about how simple and more complex visual features are represented by populations of neurons in V4. Recent experiments indicate that V4 orientation-preferred regions consist of small iso-orientation clusters that systematically shift to form orientation maps. Similarly, V4 color-preferring regions consist of small iso-hue clusters that shift systematically to form pinwheel-, line-, or angle-shaped hue maps. Most importantly, these orientation- and color-preferring maps partially overlap each other, resulting in both color or orientation single-feature modules and color-orientation feature-conjunction modules. In the proposed experiments, intrinsic cortical imaging will determine quantitatively, how preferred color and orientation preference and selectivity are represented in V4 and whether these features are organized into single-feature and feature-conjunction modules. Electrophysiological recording will determine the neuronal bases of these feature maps. Since V4 modules are expected to be small (~0.5-1 mm across), closely spaced microelectrode arrays will optimize the detection of systematic differences in neuronal color and orientation tuning across the cortex. V4 receives dense, largely segregated inputs from V2 thin and interstripes that are thought to convey color and shape information, respectively. However, it remains largely unknown how these inputs contribute to the neuronal properties and functional architecture of V4. In these experiments, distinguishable neuroanatomical tracers will be injected into two or more functionally characterized V4 modules to determine their specific patterns of connections with V2. The long-term goal of this research is to determine how different visual features are represented at different hierarchical levels of visual cortex and to determine how these architectures contributes to object recognition and memory.