[Eeglablist] automated detection of slow wave sleep periods in intracranial EEG

[James Desjardins]

While re-reading my earlier post I noticed a typo.

There needs to be a single quote on each side of "exact" in the calls  
to strmatch. The correct command for creating the pnts vector from the  
new events is:

%create a points vector from the new events in the data.
pnts=[EEG.event(strmatch('slowW_start',{EEG.event.type},'exact')).latency;EEG.event(strmatch('slowW_stop',{EEG.event.type},'exact')).latency]';


Sorry about that.

James Desjardins
Technician, MA Student
Department of Psychology, Behavioural Neuroscience
Cognitive and Affective Neuroscience Lab
Brock University
500 Glenridge Ave.
St. Catharines, ON, Canada
L2S 3A1
905-688-5550 x4676


Quoting James Desjardins <jdesjardins at brocku.ca>:

> Hi Athena and Erin,
>
> You can manually place events in the continuous data using "Edit >
> Visually edit events and identify bad channels". This will bring up
> the eegplot scroll window. If you hold CTRL and left click on the data
> a window will pop up allowing you insert a new event and you can call
> it whatever you want (type the new name into the "Event type" edit
> box). If you place new events in your data that mark the boundaries
> for periods of interest (eg. "slowW_start" & "slowW_stop") and then
> click on the "Update EEG structure" button in the bottom right corner
> of the data scrolling figure you will be able to select the periods of
> time between those events by doing the following in the Matlab command
> line (assuming the event labels "slowW_start" & "slowW_stop" were used):
>
> %create a points vector from the new events in the data.
> pnts=[EEG.event(strmatch('slowW_start',{EEG.event.type},'exact)).latency;EEG.event(strmatch('slowW_stop',{EEG.event.type},'exact)).latency]';
>
> %select the data using the points vector.
> EEG=pop_select(EEG,'points',pnts);
>
> %redraw eeglab
> eeglab redraw
>
>
>
> I hope that this is helpful.
>
>
> James Desjardins
> Technician, MA Student
> Department of Psychology, Behavioural Neuroscience
> Cognitive and Affective Neuroscience Lab
> Brock University
> 500 Glenridge Ave.
> St. Catharines, ON, Canada
> L2S 3A1
> 905-688-5550 x4676
>
>
> Quoting Erin Wamsley <EWamsley at bidmc.harvard.edu>:
>
>> Athena-
>>
>> Unfortunately, the only strongly reliable way to pull out periods of slow
>> wave sleep is to score this data by hand, marking every epoch that you want
>> to include.  Although there are some automated sleep scoring algorithms out
>> there, reliability is generally not great, and I am not aware of any
>> automated scoring method which has been applied to intracranial data. In
>> EEGLab, the simplest thing to do would be to manually highlight and delete
>> all non slow-wave periods using the artifact rejection tool (Tools > Reject
>> continuous data).  Alternatively, you could use an outside program to
>> classify each 30sec epoch according to sleep stage, and then use the ³select
>> data² function to select a list of time periods that were classified as slow
>> wave sleep ‹ but I am not aware of any existing script for doing this type
>> of sleep scoring in MatLab/EEGLab ‹ does anyone else know of something?
>>
>> Best,
>> Erin Wamsley
>>
>>
>> Erin J. Wamsley, Ph.D.
>> Instructor, Harvard Medical School
>> 330 Brookline Avenue E/FD 862
>> Boston MA 02215
>> 617.667.8486
>>
>>
>>
>> On 2/23/11 8:33 AM, "Athena Lemesiou" <a.lemesiou at ucl.ac.uk> wrote:
>>
>>> Hi All,
>>>
>>> I have recently started my PhD and I am very new to EEGLab and Matlab in
>>> general so please forgive my ignorance.
>>>
>>> I have a lot of intracranial EEG data from which I only want to   
>>> look at slow
>>> wave sleep periods. Is this something that can be done through
>>> EEGlab? If not,
>>> is anyone aware of any scripts written in Matlab for this purpose?
>>>
>>> Any help/feedback is very much appreciated.
>>>
>>> Best wishes,
>>> Athena
>>>
>>
>>
>> Erin J. Wamsley, Ph.D.
>> Instructor, Harvard Medical School
>> 330 Brookline Avenue E/FD 862
>> Boston MA 02215
>> 617.667.8486
>>
>>
>>
>>
>
>
>
>
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