The ventral visual pathway in the brain plays central role in visual object recognition. The classical model of the ventral visual pathway, which poses it as a hierarchical, distributed and feed-forward network, does not match the actual structure of the pathway, which is highly interconnected with reciprocal and non-hierarchical projections. Here we address three major consequences of this non-classical structure with regard to neural dynamics and interactions: (i) the model does not consider any extended information processing dynamics; (ii) the model does not allow for adaptive and recurrent interactions between areas; (iii) the model only characterizes evoked-response with no state-dependence from the neural context. To begin to address these gaps in the classical model, we focus on the categorical-selective regions in the ventral pathway and study the neural dynamics and interactions using intracranial electroencephalography (iEEG), which overcomes the limitations of spatiotemporal resolution in current non-invasive human neuroimaging techniques.
Avniel Singh Ghuman (Co-Chair/Pitt Neurosurgery)
Max G. G'Sell (Co-Chair)
Robert E. Kass
Christopher I. Baker (NIMH)