Mind Reading: Difference between revisions

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== Determine Targets ==
== Determine Targets ==
=== Classifying Blocks ===
=== Classifying Task vs Baseline Blocks ===
Use <code>findBlockBoundaries</code> to determine when blocks start and end. For each run, create a vector of zeros with a length equal to the endpoint of the last block:
If the goal is simply to distinguish task block from rest periods, use <code>findBlockBoundaries</code> as follows:
  b=bookends{1,1}; %creating targets for first run, so use first set of bookends
  b=bookends{1}; %creating targets for first run, so use first set of bookends
  s=zeros(1,b(end)); %1 zero for each volume -- default=baseline
  s=zeros(1,b(end)); %1 zero for each volume -- default=baseline
  for block=1:size(b,1)
  for block=1:size(b,1)
   s(b(block,1):b(block,2))=1; %block volumes get a '1'
   s(b(block,1):b(block,2))=1; %block volumes get a '1'
  end
  end
=== Classifying Task Blocks ===
If blocks are associated with different tasks to be classified, the schedule vector, '''''s''''' can be created similarly, but with some modification. Here's some examples.
TR=2.047; %the fMRI TR is 2.047 seconds in this example
t=cell2mat({expinfo.data.timestamp});
t=t/TR; %convert the timestamps into volume numbers
cond=double(cell2mat({expinfo.data.conditon})); %what condition is each trial?
%p.s., note the typo on "cond'''iton'''"
b=double(cell2mat({expinfo.data.block})); %what block is each trial?

Revision as of 15:47, 11 July 2016

Determine Targets

Classifying Task vs Baseline Blocks

If the goal is simply to distinguish task block from rest periods, use findBlockBoundaries as follows:

b=bookends{1}; %creating targets for first run, so use first set of bookends
s=zeros(1,b(end)); %1 zero for each volume -- default=baseline
for block=1:size(b,1)
 s(b(block,1):b(block,2))=1; %block volumes get a '1'
end

Classifying Task Blocks

If blocks are associated with different tasks to be classified, the schedule vector, s can be created similarly, but with some modification. Here's some examples.

TR=2.047; %the fMRI TR is 2.047 seconds in this example
t=cell2mat({expinfo.data.timestamp});
t=t/TR; %convert the timestamps into volume numbers
cond=double(cell2mat({expinfo.data.conditon})); %what condition is each trial? 
%p.s., note the typo on "conditon"
b=double(cell2mat({expinfo.data.block})); %what block is each trial?