Computational protocol: Decoding the view expectation during learned maze navigation from human fronto-parietal network

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Protocol publication

[…] A 3.0-Tesla Siemens MAGNETOM Trio A Tim scanner was used to acquire interleaved T2*-weighted echo-planar images (EPI) (TR = 2 s, TE = 30 ms, flip angle = 80°, matrix 64 × 64, field of view 192 × 192, voxel 3 × 3 × 4 mm, number of slices 30). A high-resolution T1 image of the whole head was also acquired (TR = 2250 ms, TE = 3.06 ms, flip angle = 90°, field of view 256 × 256, voxel 1 × 1 × 1 mm).The first six scans of each run were discarded so as not to be affected by initial field inhomogeneity. The acquired fMRI data underwent 3D motion correction using SPM8 (http://www.fil.ion.ucl.ac.uk/spm). The data were coregistered to the whole-head high-resolution anatomical image, and then spatially smoothed with a Gaussian kernel filter (FWHM, 8 mm). In a post-hoc analysis, we confirmed that a smaller (3 mm) setting of the spatial smoothing did not change any of our conclusions. [...] During spatial navigation of rats, firing patterns of hippocampal system was reported to represent spatial status. Neurons in medial prefrontal cortex (mPFC) and posterior parietal regions showed choice- and proceeding- specific firing patterns. Early visual areas in the occipital cortex (OC) retain specific information about contents of visual working memory when no physical visual cue is present. Moreover, spatial working memory is thought to be represented in dPFC. Based on these previous studies related to the view expectation, we examined six bilateral regions of interest (ROIs) in the decoding analysis: the mPFC, dPFC, precuneus, superior parietal cortex (sPC), hippocampal-parahippocampal cortex (HC-paraHC) and OC (). We integrated the HC and paraHC into a single region, making the size of the combined region (HC-paraHC) comparable to those of the other ROIs. Using ITK-SNAP (www.itksnap.org), the six anatomical ROIs were identified on the high-resolution T1 image of each participant in reference to the Automated Anatomical Labeling, whose mean voxel numbers and their variances over the eight participants are summarized in . The fMRI signals from these ROIs then underwent quadratic polynomial trend removal and noise reduction by means of singular value decomposition (K = 3), and were then normalized within each session. […]

Pipeline specifications

Software tools SPM, ITK-SNAP, AAL
Applications Magnetic resonance imaging, Functional magnetic resonance imaging
Organisms Homo sapiens