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GLAMPI_PrepareBaseConfig.m
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28 lines (24 loc) · 1.99 KB
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%% Generative Linear-Angular Model of Path Integration (GLAMPI) Base Configurator
% Andrea Castegnaro, UCL, 2022 uceeaca@ucl.ac.uk
% This script loads the Howett et al., 2019 behavioural and MRI data. The
% dataset contains also the healthy young participants collected elsewhere.
% It also set global properties that are used for the preprocecssing
% stage and for fitting the model. Information for the config parameters
% can be found within the script.
%% Cleaning variables
clearvars; clear all; close all; clc;
rng('default');
%% Loading data
disp('%%%%%%%%%%%%%%% Data loading ... %%%%%%%%%%%%%%%');
load('Data/HowettBrain2019_Dataset.mat');
%% setting the configuration
config.Speed.alpha = 0.9; % Paramanter for running speed calculation
config.Speed.timeOffsetAfterFlagReach = 0.5; % Time to track after cone reached in seconds
config.Speed.smoothWindow = 20; % tracking rate should be 10Hz so 4 secs window is 40 datapoints
config.Speed.velocityCutoff = 0.2; % velocity cutoff to select only the walking part of the reconstructed velocity
config.Speed.timeOffsetForDetectedTemporalWindow = 0.2; % time in seconds that will push earlier/ the detected rising edge
config.TrackedInboundAngularDeltaT = 1; % delta time step to integrate the angular information from the tracking data
config.includeStand = false; % set to true if the model should also include for duration of time spent on each segment the time calculate from tracking data while standing at each cone
config.useOoBtrials = true; % Are we using out of bound trials in the model?
config.useTrialFilter = true; % when true the model will be fitted for each of the task conditions separately. If false it will discard the
disp('%%%%%%%%%%%%%%% Data loading complete... %%%%%%%%%%%%%%%');