Data Analysis - GoldbergLab/RodentJoystick GitHub Wiki

After the full post processing pipeline is executed, any number of analysis scripts from the list below can be called.

#Data Analysis Scripts Below is a list of analysis functions and a brief overview. For detailed information and the full specification see the individual function's documentation.

###PPUtilities Common utilities used by multiple scripts.

  • rdir: returns a list of files or directories (supports arbitrary file matching - ex: rdir([pwd, '*']);
  • load_jstructs: returns a cell array of jstruct structures from a list of directories of processed data.
  • load_stats: returns a struct array of stats structures from a list of directories of processed data.
  • extract_contingency_info: returns the contingency values for a specific directory day, assuming that directory is in the format root\<date>_<contingency>\<date>
  • sort_traj_into_bins: sorts trajectories from a stats.traj_struct field into bins, and can be used to filter trajectories by defining a 2 element bin.
  • draw_heat_map: draws a heat map, supporting options for logarithmic mapping and color percentiles.
  • hist2d: computes a 2d histogram from 2 dimensional data.
  • multiday_pcolor_template: a template for plotting progress in two dimensional data over time.

###SensorDistributions This group of scripts displays/generates data for various sensor onset/offset distributions.

Dependencies: requires jstruct, stats struct to be saved in directory

  • gaps: plots the distribution of the duration a sensor was on
  • np_js_distribution: plots the nosepoke joystick onset distribution
  • np_post_distribution: plots the nosepoke post touch onset distribution
  • multipcolor_np_js: generates a pcolor plot of a single mouse's progress in the nosepoke joystick onset distribution for all days with data.
  • multipcolor_np_post: generates a pcolor plot of a single mouse's progress in the nosepoke post onset distribution for all days the mouse.

###ActivityDistributions This group of plots performs various heat maps of velocity/acceleration/position profiles.

Dependencies: requires stats, velaccel, and velaccelraw structs to be saved in directory (generated by xy_getstats and compute_vel_accel_distr):

  • multiday_video: generates a video showing the progression of the activity heat map for multiple days
  • activity_summary_heat_maps: performs all of the analysis listed below on a single figure
  • activity_heat_map: heat map of joystick position during valid trajectories
  • velocity_heat_map: heat map of trajectory velocities using median
  • velocityvar_heat_map: heat map of trajectory velocity variation using difference between 75th and 25th percentiles for each cell.
  • accel_heat_map: heat map of trajectory acceleration at each point in (x,y) space using median measure
  • accelvar_heat_map: heat map of trajectory acceleration variation at each point in (x,y) space using difference between 75th and 25th percentiles
  • accelnorm_heat_map: heat map of the normal component of acceleration at each point in (x,y) space
  • accelang_heat_map: heat map of the angular component of acceleration at each point in (x, y) space
  • get_vel_accel_distr: loads information required for the above distributions/plots assuming that they have been saved to appropriate directories (data only). also combines data when appropriate rather than compute from scratch.
  • compute_vel_accel_distr: computes all information required for the above distributions/plots (data only) - can be very slow. does it separately for each day.

###Trajectory Analysis Dependencies: requires stats structs to be saved in directories:

  • getmaxcontlength: returns the length of time that a specific trajectory stayed within some threshold, finding the maximum continuous length, if multiple segments satisfy this condition.

  • js_touch_dist: computes the recommended center hold threshold based on current data, and plots a distribution of the maximum hold times for all trajectories.

  • multi_js_touch_dist: runs js_touch_dist for multiple directories/days

  • multipcolor_jstouch_dist: generates a pcolor plot showing the progress in the js_touch_dist distribution over multiple days

  • perform_sector_analysis: computes a probability distribution describing the probability a trajectory covers the angle described as well as computing a target sector based on some reward rate

  • multi_sector_analysis: runs perform_sector_analysis for multiple days.

  • trajectory_analysis: bins trajectories by hold time and then computes percentiles of trajectory distance at each time point

  • multi_trajectory_analysis: calls trajectory_analysis of magnitude of several days on one set of plots

  • multipcolor_trajectory_analysis: generates a pcolor plot showing the progress in the median trajectory displacement over multiple days.

###Time Distributions Dependencies: requires jstruct, stats structs to be saved in directories (future edits may change this to improve efficiency, requiring a separate struct containing raw data instead)

  • hold_time_distr: plots distribution of hold times of all trajectories using js onset to js offset as measure of hold times

  • rewarded_time_distr: plots distribution of rewarded hold times

  • rewardrate_distr: plots distribution of reward rate by hold time interval

  • joystick_to_reward_distr: plots distribution of joystick touch onset time to reward time

  • get_rewardandht_distr: generates/computes the data used by the 4 plots above.

  • all_holdtimes_distr.m: plots all four kinds of hold time distributions above onto a single figure.

  • multipcolor_allht: generates a pcolor plot using hold_time_distr to show the progress in learning hold times.

  • generate_time_distr: generates a histogram showing the activity of the mouse using nosepoke and reward timestamps.

  • multi_time_distr: runs generate_time_distr for multiple days

#Post Processing GUI The post processing GUI (pp_gui) is a tool to visualize multiple plots and perform data analysis. It allows selection of multiple different days and allows selection of any combination of plots. The process for making a new function and adding support for it to the GUI is described on the page Guidelines for New Analysis Scripts

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