#hdeeg

[treyseegblog]

Getting Started with EEG

I found the below articles and books very helpful in learning about EEG as a grad student. I often cite them in papers and recommend them to anyone interested learning more about electrophysiology. Many of them are open-access or freely available online with a Google Scholar search. Hopefully people find this useful! Let me know if there are others you think I should add.

The Basics:

Electrophysiology as a theoretical and methodological hub for the neural sciences

·     https://tinyurl.com/y9dqxbqc

An introduction to the event-related potential technique.

·     https://tinyurl.com/ycw2wd5y

The Oxford handbook of event-related potential components.

·     https://tinyurl.com/ych9ff3q

Publication guidelines and recommendations for studies using electroencephalography and magnetoencephalography.

·     https://tinyurl.com/ydah2tbf

The use of brain electrophysiology techniques to study language: A basic guide for the beginning consumer of electrophysiology information.

·     https://tinyurl.com/yak6j5kh

EEG Data Acquisition, Data Quality and Experimental Design:

Recording and analyzing high-density event-related potentials with infants using the Geodesic Sensor Net

·     https://tinyurl.com/y9xshtrj

Scalp electrode impedance, infection risk, and EEG data quality

·     https://tinyurl.com/ybnzhjoh

EEG source localization: sensor density and head surface coverage

·     https://tinyurl.com/yct2wqp3

Common Components, Oscillations and Effects

The mismatch negativity (MMN) in basic research of central auditory processing: a review.

·     https://tinyurl.com/y8nhmnnd

Neuropsychology and neuropharmacology of P3a and P3b  

·     https://tinyurl.com/ybm77yd4

A cortical network for semantics:(de) constructing the N400.

·     https://tinyurl.com/y89b29fb

[mripapers]

Development of cortical motor circuits between childhood and adulthood: A navigated TMS-HdEEG study.

HBM: http://dlvr.it/NRlzws

[treyseegblog]

Visualizing HD-EEG Data with the Mohawk Toolbox / App

One of the best visualizations of HD-EEG data is now available to everyone, thanks to the MOHAWK Matlab toolbox/app created and released by Srivas Chennu: https://www.cs.kent.ac.uk/people/staff/sc785/mohawk.html.

The MOHAWK toolbox utilizes free and powerful tools (ICA and machine learning) available in EEGLAB and Fieldtrip – and makes the process of cleaning HD-EEG data more standardized, faster, and easier to use than trying to run files through the individual toolboxes on your own. Most importantly, in the end it provides you with really amazing visualizations of spectral power and connectivity across the scalp, as a measure of consciousness and other brain states.

The toolbox requires you to have MATLAB, EEGLAB, and Fieldtrip installed, and it runs HD-EEG files from Philips Neuro (EGI) in MFF or RAW format. Installation of the MATLAB app is simple, and it’s available for free: https://github.com/srivaschennu/MOHAWK/wiki

The GitHub wiki site above also provides links to the papers published thus far that have used the analysis that Mohawk makes available in a seamless pipeline.

The basic steps that MOHAWK walks the user through are as follows (see images below):

·      Load HD-EEG data (128 or 256 channels) in MFF or RAW format

·      Downsample file to 250 Hz, filter 0.5-45 Hz, remove line noise

·      Segment data into 10 second epochs, and remove baseline

·      Popup: review, adjust as needed, and accept bad channel and epoch detection

Run ICA and review component waveforms and topomaps

Popup: review ICA corrected data in channel and epoch views

MOHAWK will then generate rotating visualizations of the delta, theta and alpha bands that can be saved as images or movies.