Advanced EEG analysis workshop Cog-SDS/CogNeS/AnEEG
Warsztat (WAR) Semestr letni 2020/2021

Knowledge

The student:

- Knows and understands the principles of EEG signal generation, and best-practice for pre-processing data.

- Knows and can evaluate the applicability of different EEG analysis methods (time, frequency, and time-frequency domain processing).

- Knows and understands current state-of-the-art methods for analysing narrow-band time-frequency data (steady-state visually evoked potentials).

- Knows relevant critical principles to evaluate the use of time-frequency analyses, in the context of peer-review.

Skills

The student:

- is able to use EEGLAB to fulfil crucial data analysis objectives, and automate the processing pipeline using custom MATLAB scripts.

- is able to pre-process, plot, and analyse EEG data using different EEGlab functions, in the MATLAB environment.

- is able to administer separate time-frequency analysis methods (single taper, multi-taper, Morlet-wavelet filter, SNR conversion).

- is able to collaborate with peers, and contribute to constructive scientific peer review.

Social competences

The student:

- is able to collaborate with peers on a scientific project related to brain signal processing

- is able to create novel solutions to problems encountered during data analysis

- is updated on the latest research in specialized areas of cognitive science

- Analysis of sample EEG data (single and group work)

- Short responses: students will provide inferences in response to provided, processed data.

- Scientific revision: students will review scientific preprints as if they were actual reviewers for a scientific journal.

Within class participation

- During the workshop students will work collaboratively to develop an EEG analysis pipeline. The scripts used for this analysis will be submitted after class

Independent EEG analysis

- Using the skills developed above, students will inspect processed data and provide a short response to demonstrate their ability to infer meaning from processed time-frequency data.

Scientific review

- Using the knowledge gained, students will provide a short scientific peer-review of an unpublished manuscript, focused on the EEG analysis methods.

- EEG signal pre-processing, the Matlab environment, EEGLab GUI.

- Time, frequency and time-frequency analysis methods.

- Variants of time-frequency analysis.

- Bistable perception (Binocular Rivalry, Perceptual filling-in).

- Frequency-tagging (SSVEPs).

- Consciousness and attention

Lectures, readings, discussions, demonstrations, problem solving (Matlab), group work (Matlab), peer-review