Fitting a logistic function using a script to data individually and then analysing it together

Hi there,

For background, this analysis related to an experiment in which 12 participants done a auditory temporal bisection task in which they were represented auditory stimuli lasting from 300-700ms and had to judge if this stimuli was closer in duration to the long stimuli (lasting 700ms) or to the short one (lasting 300ms). I have the data from each participant in 12 separate mat files. I am meant to first fit a logistic function to ach datafile separately with this script:

function [bp,wf,plongs]=tb_script(filename)

%% RUN THE FUNCTION

% tb_script(filename) (e.g. 'ts_12.mat')

%% add path for toolbox (you need to change this!)

addpath /Users/anacc/Desktop/MATLAB/palamedes1_10_9/Palamedes

%% INPUTS

file=load('ts_1.mat');

data=file.data;

%% DATA PREPARATION

% identify the stimulus levels

stimlevels=unique(data(:,1));

% compute p(long) for each interval and number of trials

plong=zeros(1,size(stimlevels,1));

for i = 1:size(stimlevels,1)

temp=data(data(:,1)==stimlevels(i),:);

plong(1,i)=size(temp(temp(:,2)==2,:),1) / size(temp,1);

trials(1,i)=size(temp,1);

end

% compute the number of "long" responses at each interval

numpos=plong.*trials;

% compute the number of trials at each interval

outofnum=[ones(1,size(stimlevels,2)).*trials];

%% PSYCHOMETRIC FUNCTION FIT

% psychometric function type

PF=@PAL_Logistic;

% number of bootstraps

boot=1000;

% which parameters are free (1=free, 0=fixed)

paramsfree=[1 1 0 0];

% search grid for different parameters

searchgrid.alpha = [.300:005:.700];

searchgrid.beta = .01:.02:2;

searchgrid.gamma = 0;

searchgrid.lambda =0.1;

% fit psychometric function & compute values

paramsvalues = PAL_PFML_Fit(stimlevels',numpos,outofnum,searchgrid,paramsfree,PF);

% bisection point

fit75 = PAL_Logistic(paramsvalues, .75, 'Inverse');

fit25 = PAL_Logistic(paramsvalues, .25, 'Inverse');

bp = PAL_Logistic(paramsvalues, .5, 'Inverse');

wf=((fit75-fit25)/2)/bp;

% compute pdev

[dev pdev devsim converged] = PAL_PFML_GoodnessOfFit(stimlevels',numpos,outofnum,paramsvalues,paramsfree,boot,PF,'searchGrid',searchgrid);%'lapseLimits',[0 .3]);

%% PLOT

% p(long)

proplongdata=numpos./outofnum;

% psychometric function

stimlevelsfine=[min(stimlevels):(max(stimlevels)-min(stimlevels))./1000:max(stimlevels)];

fit=PF(paramsvalues,stimlevelsfine);

% plot plong

plot(stimlevels,proplongdata,'k.','markersize',20);

set(gca,'fontsize',12,'TickDir','out');

axis([.250 .750 0 1]);

xlabel('Stimulus duration (ms)')

ylabel('p(long)')

pbaspect([1 1 1])

box off

hold on

% plot logistic function

plot(stimlevelsfine,fit,'b-','linewidth',0.5);

hold off

%% PRINT

% present information in command window

% print values

bp=bp

wf=wf

pdev=pdev

plongs=proplongdata

----

I have gathered that I need to alter this bit:

%% INPUTS

file=load('ts_1.mat');

data=file.data;

according to the name of the datafile I want to analyse. So far, I have been doing 'ts_1.mat', then 'ts_2.mat' until number 12 (12 participants). However, this is the bit where I am stuck at. So, I am meant to run the script for each datafile separately and then save all the information which comes up in the command window. After that, I am meant to compare the 2 groups of participants (6 of them fit one group as they have Tourette’s syndrome and the other 6 fit the other group which does not have the condition) on the two dependent variables (that those with the condition will have an underestimation bias; and that they will also be prone to poorer temporal decision). I also know that the participants with Tourettes are 2, 3, 5, 7, 11, 12. Now, how am I meant to save the command window info in a way in which I can then analyse there two groups against one another on the 2 variables? Am I meant to save it independently, group it according to the group they belong to (create 2 data 'sets'), create just one data set? I thought that maybe I am meant to concatonate the data together, but now I am not sure anymore. And how exactly can I save it?

As you can see from this picture, this is the info that comes up in the command window for the datafile ts_1.mat after I ran the script.

Answer 1

[ANKIT MAURYA]

Hi Ana,

I am working on temporal bisection task for my experiment. Now, i have to write analysis code in Matlab. Luckily I found your this post. Many of the things are clear to me by understanding your logic. I want to understand few of the things.

I will be proceeding for analysis in the same way -- first individual and then will concatenate all the data files. I also have two conditions, but my designing in within group and not beween group.

Can you kindly explain me the portion of the code written below ---------------

plong=zeros(1,size(stimlevels,1));

for i = 1:size(stimlevels,1)

temp=data(data(:,1)==stimlevels(i),:);

plong(1,i)=size(temp(temp(:,2)==2,:),1) / size(temp,1);

trials(1,i)=size(temp,1);

% What is stimlevels? Is it the comparison durations between 300 -700 ms?

%%% What is 1 after stimlevels in second line?

Please explain me this portion of code line by line. I am not able to get this. Also , can you share the mat file of function you wrote for temporal bisection task with me. My mail id is -- [e-mail] . I would highly appreaciate your effort for this. Thanks in advance.