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Emulated-Inc/ca1-position-decoding

ca1-position-decoding Data for the terminal-bench-science task ca1-position-decoding: decode a mouse's position in an open field from raw two-photon calcium imaging of hippocampal CA1. This card is the only place the provenance is written down; the task deliberately gives the agent no acquisition metadata beyond the frame rate, the pixel scales and the plane alternation stated in its instruction. Source Zong, W., Obenhaus, H. A., Skytoen, E. R., et al. (2022).… See the full description on the dataset page: https://huggingface.co/datasets/Emulated-Inc/ca1-position-decoding.

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Dataset Card

ca1-position-decoding

Data for the terminal-bench-science task ca1-position-decoding: decode a mouse's position in an open field from raw two-photon calcium imaging of hippocampal CA1. This card is the only place the provenance is written down; the task deliberately gives the agent no acquisition metadata beyond the frame rate, the pixel scales and the plane alternation stated in its instruction.

Source

Zong, W., Obenhaus, H. A., Skytoen, E. R., et al. (2022). Large-scale two-photon calcium imaging in freely moving mice. Cell 185(6), 1240-1256. Deposited in the NIRD Research Data Archive, DOI 10.11582/2022.00008, licence CC BY 4.0. One session of one mouse imaged in CA1 with the MINI2P miniature two-photon microscope while foraging in a square open field: mouse 97289, session 2021-03-22, the deposit's ca1-97289 tarball, ScanImage TIFFs 97289-20210322_00001.tif to _00003.tif (8700 pages each) and their DeepLabCut tracking files.

What was done

The three TIFFs were read in order (26,100 pages, int16, 256 x 256, the focus alternating between two planes 50 micrometres apart on every page at 14.49 frames per second) and split in time only, at page 13,050, into input/ (the agent's training segment) and verification/ (the held-out segment the verifier grades on). Pages are written as acquired, interleaved and unregistered, to a plain BigTIFF without the ScanImage headers. tracking.csv in each folder is the DeepLabCut output for the same pages, one row per page, the file's three header rows kept, the index column restarted at 0. Nothing else was changed. The task's authoring/provenance/build_data.py is the exact script.

filepages / rowssha256
input/frames.tif1305043a65fc72f910fbe8d2e1bc498b6b464f7fa241afd26497460c46c92c0082662
input/tracking.csv130508ca8f8753fc9687398e69cface8a8687813247b6f547304bbe0f34b9240bac27
verification/frames.tif13050687bf07ec619e3234d2450bdac21d420245fa9b429ccd747e358dd1cbec2b12a
verification/tracking.csv13050da9a5e8c5cf0a74d4b02c682b558b640ef0e91ba1f38b846c6a5372b3c12a122

The camera scale, 0.08 cm per pixel, is TrackingResolution in the deposit's ExperimentInformation.mat; the imaging scale is 0.96 micrometres per pixel.