Functional T2* MR images were acquired using a GE 3-Tesla Sigma Excite HDX MRI scanner. Gradient-recalled echo pulse sequences were used to measure blood oxygenation level-dependent (BOLD) signal as a function of time (TR = 3000 ms, TE = 29 ms, FOV = 192 cm, 128 × 128 matrix, 39 contiguous slices, 1.5 × 1.5 × 1.5 mm3, interleaved slice order with no gap). A 16-channel phased-array half-head coil positioned at the occipital pole of the subject was used to measure MR signal focused on the visual cortex. A high-resolution T1-weighted 3D anatomical data set was used for co-registration of functional and structural data. This was acquired using an 8-channel phased-array full-head coil (TR = 7.8 ms, TE = 3 ms, TI = 450 ms, FOV = 290 × 290 x 276, 256 × 256 × 176 matrix, flip angle = 20°, 1.13 × 1.13 × 1.0 mm3).
The data obtained from these functional scans were analyzed using BrainVoyager QX software (Version 3.0, Brain Innovation). Preprocessing of this data included spatial smoothing (3 mm Gaussian kernel, full width at half maximum), 3D motion correction, slice scan timing correction, and high-pass (GLM-Fourier) temporal filtering (0.01 Hz). Multiple linear regression was then applied to the data allowing contrasts to be made between moving–static conditions within each subject across multiple runs. Hemodynamic responses were corrected appropriately for neurovascular lag (Boynton et al. 1996 (link)).
The data obtained from these functional scans were analyzed using BrainVoyager QX software (Version 3.0, Brain Innovation). Preprocessing of this data included spatial smoothing (3 mm Gaussian kernel, full width at half maximum), 3D motion correction, slice scan timing correction, and high-pass (GLM-Fourier) temporal filtering (0.01 Hz). Multiple linear regression was then applied to the data allowing contrasts to be made between moving–static conditions within each subject across multiple runs. Hemodynamic responses were corrected appropriately for neurovascular lag (Boynton et al. 1996 (link)).
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