The proposed research addresses the question of how perceptual organization interfaces with attentional selection in the visual system. While these questions are frequently considered separate, we believe that they are closely connected and may in fact share a common neural substrate. We propose that the neuronal mechanisms of figure-ground organization, that is, the neural representation of the borders of a visual object, relies on neuronal circuitry that is also used to represent whether these objects are attended or not. We will study single cell activity with multiple electrodes in extrastriate cortex. These data will be used to constrain large-scale detailed models of the underlying neuronal circuitry.
Three specific aims will be pursued.
The first Aim i s to model the mechanisms of attention-independent figure-ground organization in cortical area V2. In previous work, we have developed a model of figure-ground segregation that explains mechanisms underlying border ownership selectivity. The model can only explain changes in mean firing rates. The new model will be based on a model of single neurons that includes spiking and will thus be able to model amplitude and time course of the border ownership signals as well as pair wise spike train correlation between neurons.
The second Aim i s to study short-term memory for figure-ground structure. We will perform multiple simultaneous single-unit recordings in area V2 to characterize the recently observed hysteresis effects in border ownership coding. We will also record in higher extrastriate areas (V3 and V4) since the fast time course of border ownership selectivity makes it likely that it is imparted by connections through the white matter. These electrophysiological recordings will be complemented with the development of a model of persistence and hysteresis of border ownership signals. We will expand the spiking neural network model by introducing more complex single-neuron models that can explain the mechanisms underlying the hysteresis effects.
The third Aim i s to study how selective attention interacts with mechanisms of figure-ground organization and feature binding. We suggest that the selectivity to side of foreground figure observed in extrastriate cortex arises from a recurrent bias from grouping cells, and that the latter are also used to attentively select the figure. We will record from single cells and pairs of cells in extrastriate area V2 and study the influence of selective attention on border ownership selectivity. These recordings will be combined with a model of the interaction of top-down selective attention with figure ground organization. We will expand the spiking neural network model developed under Aim 1 to include selective attention. The model will explain rate effects and pair wise correlation functions under a variation of binding conditions and attentional states. The proposed research will contribute to our understanding of some of the most fundamental mechanisms of primate vision which is of importance for understanding both normal and impaired vision in humans. The insight gained from this project will contribute to the understanding of the neural basis of cognitive disorders such as dyslexia and hemi-neglect.
It appears to us that seeing is easy. In reality, it is a very complex process, as can be seen by the fact that no computer has a performance in artificial vision comparable to even simple animals. The goal of the proposed research is to understand how a visual scene is dissected into visual objects, and how these visual objects are attentively selected for more detailed processing. Deficiencies in attentional selection are present in many neurological diseases, e.g. hemineglect, and elucidating how selective attention works with image understanding will be important for understanding the mechanisms underlying these diseases.
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