Spontaneous behavior is a succession of self-directed tasks

Data and code from the paper "Spontaneous behavior is a succession of self-directed tasks." Behavioral data Files named *-behavior.parquet contain dataframes with processed behavioral data (MoSeq syllabes, shMoSeq states, pose information and other metadata). Supplemental Table 2 from the paper specifies which figure panels each dataset contributed to. Files can be loaded into python using the command pandas.read_parquet. Note that shMoSeq states were filtered and renumbered post-hoc to remove state with extremely low frequency; timepoints assigned to these low-frequency states are treated as missing data. All centroid locations, distances, heights, and 3D keypoint coordinates are in mm. 2D keypoint coordinates and object bounding boxes are in pixel units. "Egocentric angle to wall" is defined as the angle between the mouse's heading and a vector pointing toward the nearest wall location. "Wall direction" is the cosine of this angle. Neural data Files named *-neural.parquet contain neural activity for each recording. Each array has shape (n_timepoints, n_neurons). The data have been resampled so that the n'th row of the neural activity array corresponds to the n'th row of the behavior dataframe (after filtering the dataframe by session). For calcium recordings, activity levels correspond to Z-scored dF/F. For ephys data, activity levels correspond to spike counts within 1/120-second intervals (since behavior was recorded at 120 frames/second). In some datasets, neural data is missing from the first and last few seconds of each recording. Arrays have been padded with constant values to cover these missing timepoints. Model parameters File named *-model_params.h5 contain parameters for the final shMoSeq models derived from each dataset. The parameters can loaded to a dictionary using state_moseq.load_hdf5. In a subset of models, states were renumbered before downstream analysis. The file state_indexes.csv specifies the renumbering for each dataset. For example, the following row in state_indexes.csv would mean that state 3 in lesion-model_params.h5 corresponds to state 1 in lesion-behavior.parquet. dataset original index renumbered index lesion 3 1 Code top-bottom-moseq-shMoSeq-paper.zip contains code from the top-bottom-moseq github repo, which was used for preprocessing depth videos as part of the MoSeq pipeline. multicam-calibration-0.0.0.zip contains code from the multicam-calibration github repo, which was used for 3D keypoint tracking. state-moseq-0.0.0.zip contains code from the state-moseq github repo, which was used for estimating behavioral states.