123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137 |
- studyforrest.org Dataset
- ************************
- |license| |access| |doi|
- Retinotopic Mapping
- ===================
- 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
- <http://biorxiv.org/content/early/2016/03/31/046573>`_. (submitted for
- publication)
- For further information about the project visit: http://studyforrest.org
- Content
- -------
- ``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*.
- How to obtain the data files
- ----------------------------
- This repository is a `DataLad <https://www.datalad.org/>`__ dataset. It provides
- fine-grained data access down to the level of individual files, and allows for
- tracking future updates up to the level of single files. In order to use
- this repository for data retrieval, `DataLad <https://www.datalad.org>`_ 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
- <https://git-annex.branchable.com>`__ 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
- <http://handbook.datalad.org/en/latest/intro/installation.html>`_.
- Get the dataset
- ^^^^^^^^^^^^^^^
- A DataLad dataset can be ``cloned`` by running::
- datalad clone <url>
- Once a dataset is cloned, it is a light-weight directory on your local machine.
- At this point, it contains only small metadata and information on the
- identity of the files in the dataset, but not actual *content* of the
- (sometimes large) data files.
- Retrieve dataset content
- ^^^^^^^^^^^^^^^^^^^^^^^^
- After cloning a dataset, you can retrieve file contents by running::
- datalad get <path/to/directory/or/file>
- This command will trigger a download of the files, directories, or
- subdatasets you have specified.
- DataLad datasets can contain other datasets, so called *subdatasets*. If you
- clone the top-level dataset, subdatasets do not yet contain metadata and
- information on the identity of files, but appear to be empty directories. In
- order to retrieve file availability metadata in subdatasets, run::
- datalad get -n <path/to/subdataset>
- Afterwards, you can browse the retrieved metadata to find out about
- subdataset contents, and retrieve individual files with ``datalad get``. If you
- use ``datalad get <path/to/subdataset>``, all contents of the subdataset will
- be downloaded at once.
- Stay up-to-date
- ^^^^^^^^^^^^^^^
- DataLad datasets can be updated. The command ``datalad update`` will *fetch*
- updates and store them on a different branch (by default
- ``remotes/origin/master``). Running::
- datalad update --merge
- will *pull* available updates and integrate them in one go.
- More information
- ^^^^^^^^^^^^^^^^
- More information on DataLad and how to use it can be found in the DataLad Handbook at
- `handbook.datalad.org <http://handbook.datalad.org/en/latest/index.html>`_. The
- chapter "DataLad datasets" can help you to familiarize yourself with the
- concept of a dataset.
- .. _Git: http://www.git-scm.com
- .. _git-annex: http://git-annex.branchable.com/
- .. |license|
- image:: https://img.shields.io/badge/license-PDDL-blue.svg
- :target: http://opendatacommons.org/licenses/pddl/summary
- :alt: PDDL-licensed
- .. |access|
- image:: https://img.shields.io/badge/data_access-unrestricted-green.svg
- :alt: No registration or authentication required
- .. |doi|
- image:: https://img.shields.io/badge/doi-missing-lightgrey.svg
- :target: http://dx.doi.org/
- :alt: DOI
|