[Eeglablist] how to apply ICA methods on pre-clinical electrode configurations

[Brian Harvey]

Thanks Dr Makeig for your response,

What if one only wanted to see the spectra of each component?  ICA doesn't require info about channel locations and in this application, I am not concerned about topographies (thus topoplot.m is moot)...

I am naive in regards how to manually use the w and s variables from the output of ICA to manually generate the PSDs of each component.

More specifically, the experiment is aimed at evaluating thalamic activity in response to whisker deflection (10Hz)... I am hoping to find a component that can isolate the driven neural activity... I can do this in the channel space using FFT but was thinking to apply ICA and ignore channels....

Cheers,
Brian






________________________________
From: Scott Makeig <smakeig at gmail.com>
Sent: Sunday, January 17, 2021 6:27 PM
To: Brian Harvey <brian.harvey at biogen.com>
Cc: eeglablist at sccn.ucsd.edu <eeglablist at sccn.ucsd.edu>
Subject: Re: [Eeglablist] how to apply ICA methods on pre-clinical electrode configurations

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Brian -

The commandline function topoplot.m has a mode in which you can plot interpolated electrode positions specified in a rectangular grid (with arbitrary 'missing nodes', allowing any grid shape). This can be used to plot the IC 'maps'.

As for your main question, read the EEGLAB wiki on building an EEG dataset.

Scott


On Sat, Jan 16, 2021 at 11:30 PM Brian Harvey <brian.harvey at biogen.com<mailto:brian.harvey at biogen.com>> wrote:
Hi all,

A bit of a hack attempt here... I have LFP data using a 16 channel linear probe in VPL/VPM thalamus (in mouse)... I can successfully run ICA using CUDAICA

[w,s] = cudaica(LFP,'extended', 1, 'maxsteps', 2048);


If I am only interested in the spectral properties of the components (not scalp topographies etc) how can I manually plot them for rejection or selection? EEGlab functions require channel locations to proceed further and I am uncertain how to hack.

Thanks for any insight/assistance

Brian






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Scott Makeig, Research Scientist and Director, Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego, La Jolla CA 92093-0559, http://sccn.ucsd.edu/~scott<https://urldefense.proofpoint.com/v2/url?u=http-3A__sccn.ucsd.edu_-257Escott&d=DwMFaQ&c=n7UHtw8cUfEZZQ61ciL2BA&r=TRx_2zPEKjt2eUqOrrQ2qy2yNPA3tLhBWOLba81oTK8&m=r-h6S6KfqT9rZVFIbDIP4Qt9PJOt7DgkUF_y33pqIFU&s=bdcVmA8PJfQcuHArK8GRazNFPSmeLjEAzUay6q83IzI&e=>