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Mina Kim, Mathieu Ducros, Kamil Ugurbil, Dae-Shik Kim; Topography of high-order human object areas measured with DTI and fMRI. Journal of Vision 2005;5(8):905. doi: 10.1167/5.8.905.
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© ARVO (1962-2015); The Authors (2016-present)
Positional invariance is a characteristic of object category selectivity. Given the fact that the central visual fields become progressively overrepresented in higher visual areas, one might assume that a confluence of information from central fields is necessary to generate positional invariance. Alternatively, it seems also reasonable to suppose that a convergence of peripheral inputs is necessary to support positional invariance. In the present study, we used diffusion tensor imaging (DTI) fiber tracking to separately follow the connectivity of central and peripheral fields in the human visual system. The functional areas (FFA, LOC, and PPA) including primary/higher order organization of the both hemispheres of the human visual cortices were obtained using standard stimuli. DTI in conjunction with functional MRI was performed using a 3 Tesla whole body scanner (Intera, Philips). Functional imaging scans were used to localize retinotopic and non-retinotopic visual areas in healthy human volunteers. BOLD contrast was obtained using gradient-echo echo-planar imaging (EPI) sequence (30 axial slices of 2-mm thickness). For DTI, diffusion-weighted images (DWI) with 15 gradient encoding directions were acquired from the same subjects by spin-echo EPI. fMRI data was analyzed with BrainVoyager (Brain Innovation, Netherlands), and custom-written Matlab (Mathworks) software was used for diagonalization, fiber tracing, and visualization. The areas identified using functional imaging were used as seeding ROIs for DTI based axonal fiber reconstructions. The results of our study suggest that central and peripheral visual field areas in the primary visual cortices preferentially connect with the areas FFA, LO (central-biased) and PPA (peripheral-biased), respectively. This differential pattern of eccentricity-dependent connectivity pattern may form the basis for the distinct positional/object specific processing properties in these higher visual areas.
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