City Research Online

Abstract

Disparity tuning measured in the primary visual cortex (V1) is described well by the disparity energy model, but not all aspects of disparity tuning are fully explained by the model. Such deviations from the disparity energy model provide us with insight into how network interactions may play a role in disparity processing and help to solve the stereo correspondence problem. Here, we propose a neuronal circuit model with recurrent connections that provides a simple account of the observed deviations. The model is based on recurrent connections inferred from neurophysiological observations on spike timing correlations, and is in good accord with existing data on disparitytuning dynamics.Wefurther performedtwo additional experimentstotest predictions ofthe model. First, we increased the size of stimuli to drive more neurons and provide a stronger recurrent input. Our model predicted sharper disparity tuning for larger stimuli. Second, we displayed anticorrelated stereograms, where dots of opposite luminance polarity are matched between the left- and right-eye images and result in inverted disparity tuning in the disparity energy model. In this case, our model predicted reduced sharpening and strength of inverted disparity tuning. For both experiments, the dynamics of disparity tuning observed from the neurophysiological recordings in macaque V1 matched model simulation predictions. Overall, the results of this study support the notion that, whilethe disparity energy model provides a primary account of disparitytuning in V1 neurons, neural disparity processing in V1 neurons is refined by recurrent interactions among elements in the neural circuit.

Publication Type:	Article
Additional Information:	Copyright Society of Neuroscience 2013
Subjects:	R Medicine > RE Ophthalmology
Departments:	School of Health & Psychological Sciences > Optometry & Visual Sciences
SWORD Depositor:	Symplectic Administrator

Export

Downloads