brainbox.task.passive

Functions dealing with passive task

Functions

get_on_off_times_and_positions

Prepares passive receptive field mapping into format for analysis

get_rf_map_over_depth

Compute receptive field map for each stimulus onset binned across depth

get_stim_aligned_activity

param stim_events:

get_svd_map

Perform SVD on the spatiotemporal rf_map and return the first spatial components

get_on_off_times_and_positions(rf_map)[source]

Prepares passive receptive field mapping into format for analysis

Parameters:

rf_map (output from brainbox.io.one.load_passive_rfmap)

Returns:

  • rf_map_times (time of each receptive field map frame np.array(len(stim_frames))

  • rf_map_pos (unique position of each pixel on screen np.array(len(x_pos), len(y_pos)))

  • rf_stim_frames (for each pixel on screen stores array of stimulus frames where stim onset)

  • occurred. For both white squares ‘on’ and black squares ‘off’

get_rf_map_over_depth(rf_map_times, rf_map_pos, rf_stim_frames, spike_times, spike_depths, t_bin=0.01, d_bin=80, pre_stim=0.05, post_stim=1.5, y_lim=[0, 3840], x_lim=None)[source]

Compute receptive field map for each stimulus onset binned across depth

Parameters:
  • rf_map_times

  • rf_map_pos

  • rf_stim_frames

  • spike_times (array of spike times)

  • spike_depths (array of spike depths along probe)

  • t_bin (bin size along time dimension)

  • d_bin (bin size along depth dimension)

  • pre_stim (time period before rf map stim onset to epoch around)

  • post_stim (time period after rf map onset to epoch around)

  • y_lim (values to limit to in depth direction)

  • x_lim (values to limit in time direction)

Returns:

  • rfmap (receptive field map for ‘on’ ‘off’ stimuli.)

  • Each rfmap has shape (depths, x_pos, y_pos, epoch_window)

  • depths (depths between which receptive field map has been computed)

get_svd_map(rf_map)[source]

Perform SVD on the spatiotemporal rf_map and return the first spatial components

Parameters:

rf_map

Returns:

  • rf_svd (First spatial component of rf map for ‘on’ ‘off’ stimuli.)

  • Each dict has shape (depths, x_pos, y_pos)

get_stim_aligned_activity(stim_events, spike_times, spike_depths, z_score_flag=True, d_bin=20, t_bin=0.01, pre_stim=0.4, post_stim=1, base_stim=1, y_lim=[0, 3840], x_lim=None)[source]
Parameters:
  • stim_events (dict of different stim events. Each key contains time of stimulus onset)

  • spike_times (array of spike times)

  • spike_depths (array of spike depths along probe)

  • z_score_flag (whether to return values as z_score of firing rate)

  • T_BIN (bin size along time dimension)

  • D_BIN (bin size along depth dimension)

  • pre_stim (time period before rf map stim onset to epoch around)

  • post_stim (time period after rf map onset to epoch around)

  • base_stim (time period before rf map stim to use as baseline for z_score correction)

  • y_lim (values to limit to in depth direction)

  • x_lim (values to limit in time direction)

Returns:

  • stim_activity (stimulus aligned activity for each stimulus type, returned as z_score of firing)

  • rate