Saccade Cookbook - Revision history

Lof at 12:48, 22 January 2024

2024-01-22T12:48:43Z

← Older revision		Revision as of 12:48, 22 January 2024
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	<p>Easily calibrate, detect, and analyze [~~[http~~://en.wikipedia.org/wiki/Saccade\|saccades]] with PandA. For a more detailed description, visit the other [[http://www.neural-code.com/index.php/panda/action/saccade\|broken link]] sections, starting with the [[http://www.neural-code.com/index.php/panda/action/87-saccade/70\|broken link]].</p>		<p>Easily calibrate, detect, and analyze [https://en.wikipedia.org/wiki/Saccade saccades] with PandA. For a more detailed description, visit the other [http://www.neural-code.com/index.php/panda/action/saccade broken link] sections, starting with the [http://www.neural-code.com/index.php/panda/action/87-saccade/70 broken link].</p>

	== Calibration ==		== Calibration ==

Lof at 12:47, 22 January 2024

2024-01-22T12:47:41Z

← Older revision		Revision as of 12:47, 22 January 2024
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	<p ~~class="clearnone"~~>A tutorial, for students and coworkers: a recipe to calibrate, detect, and analyze saccades</p>		<p>A tutorial, for students and coworkers: a recipe to calibrate, detect, and analyze saccades</p>
	~~<hr id="system-readmore" /~~>

	<p ~~class="clearnone"~~>Easily calibrate, detect, and analyze [[http://en.wikipedia.org/wiki/Saccade\|saccades]] with [[<p class="clearnone"> <a href="https://gitlab.science.ru.nl/marcw/biofysica" target="_blank">PANDA</a> tutorial, for students and coworkers: a recipe to calibrate, detect, and analyze saccades</p>\|PandA]]. For a more detailed description, visit the other [[http://www.neural-code.com/index.php/panda/action/saccade\|~~saccade~~]] sections, starting with the [[http://www.neural-code.com/index.php/panda/action/87-saccade/70\|~~introduction~~]].</p>
			<p>Easily calibrate, detect, and analyze [[http://en.wikipedia.org/wiki/Saccade\|saccades]] with PandA. For a more detailed description, visit the other [[http://www.neural-code.com/index.php/panda/action/saccade\|broken link]] sections, starting with the [[http://www.neural-code.com/index.php/panda/action/87-saccade/70\|broken link]].</p>

	== Calibration ==		== Calibration ==

Lof at 12:42, 22 January 2024

2024-01-22T12:42:43Z

← Older revision		Revision as of 12:42, 22 January 2024
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			<p class="clearnone">A tutorial, for students and coworkers: a recipe to calibrate, detect, and analyze saccades</p>
			<hr id="system-readmore" />

			<p class="clearnone">Easily calibrate, detect, and analyze [[http://en.wikipedia.org/wiki/Saccade\|saccades]] with [[<p class="clearnone"> <a href="https://gitlab.science.ru.nl/marcw/biofysica" target="_blank">PANDA</a> tutorial, for students and coworkers: a recipe to calibrate, detect, and analyze saccades</p>\|PandA]]. For a more detailed description, visit the other [[http://www.neural-code.com/index.php/panda/action/saccade\|saccade]] sections, starting with the [[http://www.neural-code.com/index.php/panda/action/87-saccade/70\|introduction]].</p>

			== Calibration ==
			<p>First you have to calibrate (see also saccade [[http://www.neural-code.com/index.php/tutorials/action/saccade/55-saccade-calibration\|calibration]])
			by training an artificial neural network to learn the relationship between measured voltages and head orientation:
			<pre xml:lang="matlab">pa_calibrate</pre>
			<p>(choose the calibration dat-file in the pop-up menu, usually ending in 0000).
			Then you can calibrate (and low-pass filter) the data-files, by using the button in the pa_calibrate interface
			(this will calibrate ALL dat-files with the .net-file you got from the pa_calibrate-procedure). </p>

			== Detection ==
			<p>Then you have to detect (see also saccade [[http://www.neural-code.com/index.php/tutorials/action/saccade/56-saccade-detection\|detection]])
			with:
			<pre xml:lang="matlab">pa_sacdet</pre>
			<p>(choose an experimental hv-file, usually ending with numbers 0001 and up). </p>

			== Parameters ==
			<p>Obtain all movement parameters, such as end-point location, reaction time, peak velocity. </p>
			<pre xml:lang="matlab">pa_sac2mat</pre>
			(these will be saved in a mat-file)</p>
	== Analysis ==		== Analysis ==
	Finally, you can start some high-level analysis (see also saccade [[http://www.neural-code.com/index.php/tutorials/action/saccade/54-saccade-analysis\|analysis]])		Finally, you can start some high-level analysis (see also saccade [[http://www.neural-code.com/index.php/tutorials/action/saccade/54-saccade-analysis\|analysis]])

Lof: Created page with "== Analysis == Finally, you can start some high-level analysis (see also saccade analysis..."

2024-01-22T12:41:55Z

Created page with "== Analysis == Finally, you can start some high-level analysis (see also saccade analysis..."

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== Analysis ==
Finally, you can start some high-level analysis (see also saccade [[http://www.neural-code.com/index.php/tutorials/action/saccade/54-saccade-analysis|analysis]])

After all these obligatory steps, you can actually start analyzing the data. This usually involves custom-made analysis functions, suited for your experiment. First, you have to load the data:

<pre xml:lang="matlab">
load MW-RG-2011-03-02-0001
</pre>

You will now have a Sac- and a Stim-matrix. The Sac-matrix contains all the movement parameters, the Stim-matrix all the stimulus parameters. You can combine them into a single matrix, containing in each column a relevant parameter, and each row containing a single saccade.

<pre xml:lang="matlab">
SupSac = pa_supersac(Sac,Stim,XX,YY);
</pre>

Note that the XX and YY should be numbers describing the type of stimulus, and the number of that type of stimulus in the trial, e.g.

<pre xml:lang="matlab">
SupSac = pa_supersac(Sac,Stim,1,2);
</pre>

for the second (YY=2) stimulus of type 1 (XX=1, usually an LED) in a trial, or

<pre xml:lang="matlab">
SupSac = pa_supersac(Sac,Stim,2,1);
</pre>

for the first (YY=1) stimulus of type 2 (XX=2, usually a sound) in the trial (you have to check what number is assigned to which stimulus type, by typing:

<pre xml:lang="matlab">
help pa_readcsv
</pre>

in the trial information of the LOG-matrix, line 5).

To plot target location versus response location:

<pre xml:lang="matlab">
plot(SupSac(:,23),SupSac(:,8),'k.');
</pre>

or

<pre xml:lang="matlab">
pa_plotloc(SupSac);
</pre>