Sehara_et_al_2021_RealtimeDLC_DataRepository/README.md

Data for Sehara et al., 2021 eNeuro (the real-time DeepLabCut project)

The data repository for: Sehara K, Zimmer-Harwood P, Larkum ME, Sachdev RNS (2021) Real-time closed-loop feedback in behavioral time scales using DeepLabCut. ENEURO.0415-20.2021.

(The image is licensed under CC-BY 4.0, 2020 Keisuke Sehara)

The head-fixed mouse was allowed to whisk freely under infrared illumination. The behavior of the mouse was captured from the above, using the ImagingSource DMK37BUX287 camera.

The Pose-Trigger program was used to capture images and to generate output triggers.

Datasets

You can find more details about each dataset in the README file of the corresponding subfolder.

1. Raw videos: the raw videos acquired using Pose-Trigger. The files are converted to HDF5 files (instead of the original NumPy files).
2. Spike2 recordings: recordings of the frame and trigger signals during Pose-Trigger acquisition, using Spike2. The files are converted to HDF5 files (instead of the original .smrx files).
3. DeepLabCut projects: the DeepLabCut (v2.1) projects used in the study.
4. Post hoc pose estimation: the post-hoc pose-estimation data to be compared with the real-time data. The files are in the HDF5 format (in the structure different from the "original" PyTables format that DeepLabCut generates).
5. Performance profiling: the data and analytical procedures (and some figures) used to profile the speed and accuracy of Pose-Trigger.

License

Copyright (c) 2020 Keisuke Sehara, Paul Zimmer-Harwood, Matthew E. Larkum, and Robert N.S. Sachdev, Creative Commons Attribution 4.0 International (CC-BY 4.0).