August 2014
Volume 14, Issue 10
Free
Vision Sciences Society Annual Meeting Abstract  |   August 2014
Evidence for Feature Integration in the Fusiform Face Area
Author Affiliations
  • Maxim Bushmakin
    Department of Psychological and Brain Sciences, Indiana University
  • Thomas James
    Department of Psychological and Brain Sciences, Indiana University
Journal of Vision August 2014, Vol.14, 1296. doi:https://doi.org/10.1167/14.10.1296
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      Maxim Bushmakin, Thomas James; Evidence for Feature Integration in the Fusiform Face Area. Journal of Vision 2014;14(10):1296. https://doi.org/10.1167/14.10.1296.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

There is a considerable amount of evidence that different kinds of objects are processed differently by the visual system and brain, but there is a need for more mechanistic explanations for those effects. Specifically, there is a long-standing debate whether the so-called Fusiform Face Area (FFA) is responsible for only face perception or is also involved in other non-face specific cognitive processes (Kanwisher et. al, 1997; Gauthier et. al, 2000). Here, we demonstrate that the FFA is preferentially recruited with non-face objects, but only when participants need to process and integrate multiple, spatially-separated features at the same time. Specifically, I will report on an fMRI study examining face and object perception where participants relied on single features: diagnostic "top" or "bottom" features; or relied on multiple features: conjunction of both "top" and "bottom" features. The main finding was that BOLD signal change was greater in the FFA for conditions with feature conjunctions than with single diagnostic features. We conclude that activation in the FFA is driven in part by the need to integrate object features and suggest that the need to integrate facial features may explain its consistent recruitment with face stimuli. This work has a potential to bring together disparate accounts of face and object perception under a more cohesive and unified framework.

Meeting abstract presented at VSS 2014

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