studyforrest.org: Multi-resolution 3T fMRI on visual orientation representation [BIDS]
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An Extension of studyforrest.org Dataset **************************************** Multi-resolution 3T fMRI data on the representation of visual orientation ========================================================================= This dataset consists of empirical 3T fMRI data recorded at three spatial resolutions (1.4 mm, 2 mm, and 3 mm isotropic voxel size) for orientation decoding in visual cortex — in order to test hypotheses on the strength and spatial scale of orientation discriminating signals. This is an extension of the studyforrest project. All seven participants previously volunteered for the audio-only and the audio-visual Forrest Gump study. Five of the seven participants also participated in a matching study using identical protocols, but 7T data acquisition (with the same the three spatial resolutions used here, plus a 0.8 mm acquisition). The dataset is compliant with the BIDS data description standard (http://bids.neuroimaging.io). A detailed description can be found in: Sengupta, A., Speck, O., Yakupov, R., Kanowski, M., Tempelmann, C., Pollmann, S. & Hanke, M. (2018) The effect of acquisition resolution on orientation decoding from V1: comparison of 3T and 7T. bioRxiv. https://doi.org/10.1101/305417 For more information about the project visit: http://studyforrest.org 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. 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. Find out what has been done ^^^^^^^^^^^^^^^^^^^^^^^^^^^ DataLad datasets contain their history in the ``git log``. By running ``git log`` (or a tool that displays Git history) in the dataset or on specific files, you can find out what has been done to the dataset or to individual files by whom, and when. 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.