Illustrations of work on replay in humans using fMRI

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README.md

Replay Illustrations

made-with-datalad

About

This repository contains illustrations that I regularly use in talks about my work on investigating fast sequential memory reactivation (replay) in humans using fMRI.

DataLad datasets and how to use them

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.

Get the dataset

This DataLad dataset can be cloned by running

datalad clone https://github.com/lnnrtwttkhn/replay-illustrations

Once the 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.

For example, you can retrieve all illustrations in .pdf-format by running

datalad get illustrations/*/*.pdf

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. The chapter "DataLad datasets" can help you to familiarize yourself with the concept of a dataset.

Requirements

Affinity Designer

To edit the .afdesign files you need Affinity Designer. I currently use version 1.5.5. Affinity Designer is not free but cheaper than Adobe Illustrator.

DataLad

DataLad Docker

After updating the Dockerfile, I use the following command to build and push the newest image to dockerhub (following docker login):

export DATALAD_VERSION=0.17.6
docker build -t lennartwittkuhn/datalad:$DATALAD_VERSION --platform linux/arm64 --build-arg DOCKER_TAG=$DATALAD_VERSION .docker/datalad
docker push lennartwittkuhn/datalad:$DATALAD_VERSION
docker run --rm  --entrypoint /bin/sh --platform linux/arm64 --memory="100M" lennartwittkuhn/datalad:$DATALAD_VERSION -c "datalad install --get-data https://github.com/lnnrtwttkhn/replay-illustrations"

Credit

Several illustrations contain images from BioRender.com which were created under a plan for the Max Planck Society which allows publication in journals and for other academic purposes (for details, see BioRender's overview of Licensing and Usage). The illustrations are used for academic purposes only.

Illustrations in replay-linear-track were inspired by Figure 1 in Carr et al., 2011, Nature Neuroscience. Please refer to the original paper for reference:

Carr, M., Jadhav, S. & Frank, L. Hippocampal replay in the awake state: a potential substrate for memory consolidation and retrieval. Nature Neuroscience 14, 147–153 (2011). https://doi.org/10.1038/nn.2732

License

All illustrations are licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). Details can be found in the LICENSE file.

Contact

If you have questions or any suggestions for improvement, please contact Lennart Wittkuhn or create a new issue on the issue board. Thank you! :pray: