All participants in the phase2 extension of the studyforrest dataset underwent retinotopic mapping with standard flickering checkerboard stimulus (ring and wedges). More information on the procedure and the results can be found in:
Ayan Sengupta, Falko R. Kaule, J. Swaroop Guntupalli, Michael B. Hoffmann, Christian Häusler, Jörg Stadler, Michael Hanke. An extension of the studyforrest dataset for vision research. (submitted for publication)
For further information about the project visit: http://studyforrest.org
code/:
source code for retinotopic mapping analysis.
- The main script is process_retmap and a Python based GUI easyret_gui to call it from an easy to use front end. The process_retmap script calls the Python scripts RetMap_phaseshift for post processing phase shift (if required) and combine_volumes for combining the clw/ccw maps and ecc/con maps together.
src/:
links to repositories containing all inputs for the analysis
sub-??/:
analysis results per participant
surface_maps/:
contains eccentricity and polar angle maps of left and right hemispheres
of a particular participant's cortical surface in MGH format
post_processing/:
contains the post-processed/combined compressed NIfTI files in a
participant's bold3Tp2 image template space
(see src/templatetransforms), before it is aligned to the
T1 structural and represented on cortical surfaces.
qa/:
contains the pyretmap_subjQuali.ods file which details the quality of the
participant-wise retinotopic maps produced by the processing pipeline.
This repository is a DataLad dataset. It provides fine-grained data access down to the level of individual files, and allows for tracking future updates. In order to use this repository for data retrieval, DataLad is required. It is a free and open source command line tool, available for all major operating systems, and builds up on Git and git-annex to allow sharing, synchronizing, and version controlling collections of large files. You can find information on how to install DataLad at handbook.datalad.org/en/latest/intro/installation.html.
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datalad clone <url>
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datalad get -n <path/to/subdataset>
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datalad update --merge
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