DOI: 10.5061/dryad.g614mb0
title: Data from: Retinotopic-like maps of spatial sound in primary 'visual' cortex of blind human echolocators

description: The functional specialisations of cortical sensory areas were
 traditionally viewed as being tied to specific modalities. A radically
 different emerging view is that the brain is organized by task rather than
 sensory modality, but it has not yet been shown that this applies to
 primary sensory cortices. Here we report such evidence by showing that
 primary ‘visual’ cortex can be adapted to map spatial locations of sound
 in blind humans who regularly perceive space through sound echoes.
 Specifically, we objectively quantify the similarity between measured
 stimulus maps for sound eccentricity and predicted stimulus maps for
 visual eccentricity in primary ‘visual’ cortex (using a probabilistic
 atlas based on cortical anatomy) to find that stimulus maps for sound in
 expert echolocators are directly comparable to those for vision in sighted
 people. Furthermore, the degree of this similarity is positively related
 with echolocation ability. We also rule out explanations based on top-down
 modulation of brain activity – e.g. through imagery. This result is clear
 evidence that task-specific organization can extend even to primary
 sensory cortices, and in this way is pivotal in our reinterpretation of
 the functional organisation of the human brain.
description: Data
 summarySummary excel
 spreadsheet that contains the data that was entered into the multiple
 linear regression reported in the manuscriptretinotopic mapping summary
 data.xlsMatlab functions for
 data analysisCustom/modified Matlab
 functions that were used in the cross-correlation analysis pipeline. These
 functions are designed to be used in conjunction with the mrTools analysis
 suite (Gardner Lab, Stanford University, USA). These functions are: a.
 corAnal – designed to replace the function of the same name in the mrTools
 suite. This function includes a call to the following function: b.
 computeCoranal –designed to replace the function of the same name in the
 mrTools suite. This function includes a call to the following function: c.
 myXcorr – this is an entirely custom built function that carries out
 phase-encoded mapping on sparse sampling mri data in a way that is
 compatible with the mrTools analysis pipeline.Matlab
 functions.zipSubject mapping
 dataNeural mapping data and
 fitted probabilistic retinotopic maps for each individual subject. Each
 data folder corresponds to a single subject (e.g. EE1, SC2) – details on
 these subjects can be found in the manuscript and supplemental materials.
 Within each of these folders are the following data files: • aseg.hdr and
 aseg.img o header and image files • ret_areas.hdr and ret_areas.img o The
 probabilistic atlas for cortical visual areas fitted to this subject’s
 cortical anatomy. o The .img file can be loaded into matlab using the
 function mlrImageReadNifti (Gardner Lab, Stanford University, USA) o The
 file includes a 3-dimensional data matrix, in which each cell corresponds
 to a single voxel. Each of these cells includes a single value to denote
 which visual area (if any) that voxel is mostly likely to be part of.
 Please see https://hub.docker.com/r/nben/occipital_atlas/ for further
 details. • ret_eccen.hdr and ret_eccen.img o The probabilistic atlas for
 retinotopic eccentricity fitted to this subject’s cortical anatomy. o The
 .img file can be loaded into matlab using the function mlrImageReadNifti
 (mrTools analysis suite, Justin Gardner) o The file includes a
 3-dimensional data matrix, in which each cell corresponds to a single
 voxel. Each of these cells includes a single value to denote which point
 in visual space (eccentricity) that voxel is mostly likely to represent.
 Values range from 0 (central) to +90 (most eccentric) in each hemisphere.
 Please see https://hub.docker.com/r/nben/occipital_atlas/ for further
 details. • corAnal.mat o Results of the cross-correlation analysis
 (described in the manuscript). This is a standard matlab .mat file, which
 was created using the mrTools analysis suite (Gardner Lab, Stanford
 University, USA). For proper exploration of these data we recommend
 installing the mrTools analysis package for Matlab. o Within the corAnal
 data variable, field “overlays” is a 1 x 3 structure array. These 3
 subfields correspond to the following data from the cross-correlation
 analysis  Coherence values  Amplitude values (unused in our analysis) 
 Phase values o Within each of these subfields there are further subfields
 corresponding to the data for each of the stimulus conditions that the
 subject took part in (in the order echo, source, vision) o Each of these
 data variables is a 3-dimensional data matrix, where each cell corresponds
 to a single voxel. The positions of these voxels correspond to those in
 the ret_areas, ret_eccen and aseg data files.