localized visual areas (FFA, OFA, PPA, EBA, LOC, early visual)

https://studyforrest.org/

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README.rst

studyforrest.org Dataset
************************

|license| |access| |doi|

Localization of higher-level visual ROIs
========================================

For all participants in the phase2 extension of the studyforrest dataset, the
following visual areas were localized:

- fusiform face area (FFA)
- occipital face area (OFA)
- parahippocampal place area (PPA)
- extrastriate body area (EBA)
- lateral occipital complex (LOC)
- early visual cortex (VIS)

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

Content
-------

``code/``:
all source code to perform the analysis of the block-design
localizer fMRI data

``src/``:
links to repositories containing all inputs for the analysis

``sub-??/``:
analysis results per participant

``onsets/``:
per-stimulus condition timing in FSL's EV3 format (converted from the BIDS
event specifications)

``2ndlvl.gfeat/``:
Full output folder of the 2nd level fixed-effects analysis aggregating
1st-level GLM parameters across all four experiment runs. This contains
thresholded and unthresholded Z-stat maps which were the basis for the
subsequent titration of ROI masks per participant.

``rois/``:
One mask volume per isolated voxel cluster in the results. Each filename
starts with the ROI label (e.g. lFFA for left fusiform face area). There
can be more than one file/cluster per ROI per subject, if more than one
isolated voxel cluster was present in the results.

How to obtain the data files
----------------------------

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 up to the level of single files. 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
`_.

Get the dataset
^^^^^^^^^^^^^^^

A DataLad dataset can be ``cloned`` by running::

datalad clone

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

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

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 ``, 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 `_. 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