Time Course of Shape and Category Selectivity Revealed by EEG Rapid Adaptation

Clara A. Scholl, Xiong Jiang, Jacob G. Martin, and Maximilian Riesenhuber (2013)

Journal of Cognitive Neuroscience

A hallmark of human cognition is the ability to rapidly assign meaning to sensory stimuli. It has been suggested that this fast visual object categorization ability is accomplished by a feedforward processing hierarchy consisting of shape-selective neurons in occipito-temporal cortex that feed into task circuits in frontal cortex computing conceptual category membership. We performed an EEG rapid adaptation study to test this hypothesis. Participants were trained to categorize novel stimuli generated with a morphing system that precisely controlled both stimulus shape and category membership. We subsequently performed EEG recordings while participants performed a category matching task on pairs of successively presented stimuli. We used space-time cluster analysis to identify channels and latencies exhibiting selective neural responses. Neural signals before 200 msec on posterior channels demonstrated a release from adaptation for shape changes, irrespective of category membership, compatible with a shape- but not explicitly category-selective neural representation. A subsequent cluster with anterior topography appeared after 200 msec and exhibited release from adaptation consistent with explicit categorization. These signals were subsequently modulated by perceptual uncertainty starting around 300 msec. The degree of category selectivity of the anterior signals was strongly predictive of behavioral performance. We also observed a posterior category-selective signal after 300 msec exhibiting significant functional connectivity with the initial anterior category-selective signal. In summary, our study supports the proposition that perceptual categorization is accomplished by the brain within a quarter second through a largely feedforward process culminating in frontal areas, followed by later category-selective signals in posterior regions.

For more background information, refer to Jiang et al. (2007).