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Adam Steel, Edward Silson, Chris Baker; Functional connectivity of ventral temporal cortex reveals category-specificity in medial parietal areas. Journal of Vision 2018;18(10):1084. https://doi.org/10.1167/18.10.1084.
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Medial parietal cortex contains a scene-selective region (medial place area, MPA) that shows strong functional connectivity to anterior parahippocampal place area (PPA). It has been posited that MPA is an interface between perceptual and memory processes (Silson et al., 2016). However, it is unclear whether selectivity for other categories is also present within this region. Here, we investigate the functional topology of medial parietal cortex based on its resting-state functional connectivity with ventral temporal cortex (vTC) and compare this organization to stimulus-evoked activation. Resting state fMRI was collected in 42 subjects and aligned to a standard surface mesh. Posterior, medial, and anterior regions of vTC were anatomically defined by dividing the fusiform gyrus and collateral sulcus along their posterior-anterior axis, corresponding to divisions of FFA and PPA, respectively. Using multiple regression, the unique functional connectivity of each region was calculated for each subject. Medial parietal cortex was parcellated based on its connectivity to the vTC regions. This analysis revealed two adjacent regions anterior to the parietal occipital sulcus that show strong differential connectivity to anterior PPA and FFA. Preferential connectivity to anterior PPA overlapped with MPA, and preferential FFA connectivity was immediately anterior. The category selectivity of the medial parietal parcels was calculated using an independent dataset acquired in a separate group of subjects. The PPA-preferring region had a larger response to scenes than other categories, while the FFA-preferring region had a larger response to faces than other categories. Therefore, these results suggest that category specificity may be preserved in regions of medial parietal cortex.
Meeting abstract presented at VSS 2018
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