Abstract
The fusiform gyrus contains category-selective patches that are critical for visual recognition with damage to these patches leading to category-selective impairments in object recognition, such as acquired alexia and prosopagnosia. However, many gaps remain in our understanding of the dynamic role the fusiform plays in contributing to multiple stages of category-specific information processing. To assess the information processing dynamics of the fusiform, here we report results from 7 subjects with intracranial electrodes placed directly on word selective (2 subjects) or face selective (5 subjects) fusiform gyrus (the "visual word form area [VWFA]" and "fusiform face area [FFA]" respectively). Specifically, we use multivariate machine learning methods in conjunction with multiple face and word processing paradigms to uncover common neurodynamic information processing principles of category-selective fusiform gyrus. The results show strong decoding accuracy (d' = 1.5-3.5 across subjects) for faces and words in the FFA and VWFA respectively, first becoming statistically significant between 50-100 ms and peaking between 150-200 ms. Next we examined the dynamics of within category decoding. For words significant decoding was seen in both subjects between approximately 150-300 ms wherein visually similar words could not be decoded from one another, but dissimilar words could be decoded (organized by orthographic similarity). There was a later phase between approximately 250-500 ms where even orthographically similar words could be significantly decoded from one another (individual-level representation). For faces significant expression-invariant decoding was seen in each subject in the same 250-500 ms time frame. The neural response for faces was organized by facial feature similarity, emphasizing the role of the eyes and mouth in face individuation. Taken together, these results suggest a multi-stage information processing dynamic wherein the representation in category-selective fusiform gyrus evolves from a coarse category-level representation to an invariant and highly detailed individual representation over the course of 500 ms.
Meeting abstract presented at VSS 2016