DOI: 10.5281/zenodo.6774389
title: Data access for figures of Chen, Ginoux, Wyart, Mora & Walczak

description: README: <br> Pandas DataFrame to load: <br> import pickle<br> pickle_filename = 'YOUR_DATA_PATH/df_name.pkl' # change accordingly<br> with open(pickle_filename, 'rb') as pickle_in:<br> df_name = pickle.load(pickle_in) <br> Motorneuron data:<br> Fish 3 Trial 1 and Fish 5 Trial 2 for Figure 3.<br> Fish 5 Trial 2 for figure 4. Columns:<br> - Fish: fish index<br> - Trial: trial index<br> - fluo: fluorescence traces [n_cells x n_timesteps]<br> - fluo_type: 'dff' or 'f_smooth', respectively before and after smoothing procedure<br> - n_cells: number of cells in the plane (only those kept for analysis, "bad" cells removed)<br> - mid: middle cell, to split left vs right neurons (left until index mid-1, right from index mid and on)<br> - cell_centers: x and y position of the cell center [n_cells x 2]<br> - multivariate: boolean to indicate bivariate (False) or multivariate (True) GC<br> - GC: Granger causality matrix results [n_cells x n_cells]<br> - GC_sig: Granger causality matrix results, significant with original threshold (where Fstat &gt; threshold_F) [n_cells x n_cells]<br> - GC_sig_new_thresh: Granger causality matrix results, significant with new threshold (where Fstat &gt; new_threshold_F) [n_cells x n_cells]<br> - Fstat: F-statistics matrix [n_cells x n_cells]<br> - threshold_F: original threshold for the F-statistics significance<br> - new_threshold_F: new threshold for the F-statistics after the whole pipeline is applied <br> Hindbrain data<br> Fish 6 Trial 07 Columns:<br> - fluo: fluorescence traces [n_cells x n_timesteps]<br> - cell_centers: x and y position of the cell center [n_cells x 2]<br> - background: plane background for plotting [249 x 512]<br> - n_cells: number of cells in the plane<br> - tail_angle: array of angle of the tail [75000,] - 75000 timesteps: higher frequency than calcium imaging recording<br> - tail_angle_regressor: tail angle convolved to calcium decay function [75000,] <br> - is_swim: boolean array whether each cell in correlated to swim activity (True if pearson correlation between cell's fluorescence trace and tail_angle_regressor &gt; 0.6) [n_cells,]<br> - swim_neurons: indices of swim-correlated neurons [n_swim_cells,]<br> - medial_neurons: indices of swim-correlated neurons [n_medial_cells,]<br> - SNR: signal-to-noise ratio for each cell [n_cells,] - BV_GC_medial: original bivariate (BV) Granger causality results matrix [n_medial_cells,n_medial_cells]<br> - BV_Fstat_medial: original BV F-statistics matrix [n_medial_cells,n_medial_cells]<br> - BV_threshold_F_ori: original threshold for the BV F-statistics significance<br> - BV_threshold_F_new_mat_medial: new threshold customized for each pair of neurons (BV) [n_medial_cells,n_medial_cells]<br> - BV_Fstat_normalized_medial: new BV F-statistics matrix normalized by customized threshold [n_medial_cells,n_medial_cells]<br> - BV_GC_normalized_medial: new BV GC results matrix normalized by customized threshold [n_medial_cells,n_medial_cells] - MV_GC_medial: original multivariate (MV) Granger causality results matrix [n_medial_cells,n_medial_cells]<br> - MV_Fstat_medial: original MV F-statistics matrix [n_medial_cells,n_medial_cells]<br> - MV_threshold_F_ori_medial: original threshold for the MV F-statistics significance<br> - MV_threshold_F_new_mat_medial: new MV F-statistics matrix normalized by customized threshold [n_medial_cells,n_medial_cells]<br> - MV_Fstat_normalized_medial: new MV F-statistics matrix normalized by customized threshold [n_medial_cells,n_medial_cells]<br> - MV_GC_normalized_medial: new MV GC results matrix normalized by customized threshold [n_medial_cells,n_medial_cells]
description: {"references": ["Chen, Ginoux, Mora, Walczak, Wyart. Granger causality analysis for calcium transients in neuronal networks: challenges and improvements. https://doi.org/10.1101/2022.06.27.497721"]}