Seminar in Computer Science:

EEG Brain Scanning

סמינר במדעי המחשב:

 קריאה וניתוח גלי מוח

0368-3237-01, Autumn 2014-15

Monday 14-16  Shenkar 222

Prof. Nathan Intrator


Course Mailing List         Yedion


Contact info                   Nathan Intrator                 03 640 7598


The seminar is intended to students who wish to get some background in EEG brain scanning. It will cover basic to advanced methods of EEG scanning and analysis methods.

It will cover multi-electrode analysis methods and maybe some more recent single electrode techniques.

It will cover some applications from Medical to Neuro-marketing.

The background of the students is expected to be diverse.

Students are expected to have a basic background in probability (first year courses) and numerical analysis or optimization (CS course or equivalent).

Basic knowledge in electricity/physics/signal processing/machine learning can be useful but not essential.


This year the seminar topics will be (all should be using EEG):

1.       Advanced anesthesia monitoring

2.       Neurofeedback: projects like Lumosity, videogames

3.       EEG for meditation and relaxation

4.       Games for neurofeedback: Adam Gazzaley

5.       Attention/cognitive load monitoring (including difference between memory recall to deduction)

6.       Migraine monitoring, detection, prediction

7.       Coma monitoring

8.       ADD/ADHD monitoring and discrimination

9.       fatigue monitoring


Please check the Wikipedia page on EEG to get some idea what it is.

For those interested in actual hands on, please check the EEGLAB and FieldTrip software for Matlab.

An example of a paper on Independent Components Analysis for Artifact Removal


Students will be required to create a PowerPoint presentation that will be loaded on this site 2 days before the talk and to present in class.

Each presentation will be on a single or few papers and should take about 45 minutes.


Grading will be based on the quality and depth of the presentation, and on the quality of the presentation material. The papers below are the basis on which the presentation will be based, but for the presentation, several previous papers (books) will need to be used.


Instructions for the presentation

1.       Make sure that you can give the assigned lecture at your allocated date.

2.       Email the PowerPoint presentation for first set of comments by Thursday the week before your lecture.

3.       Email the second version of the presentation by Sunday before your lecture.

4.       If any changes are required following comments you received before or after the lecture, send the final version not later than a day after your lecture.

5.       Font should not be smaller than 28pt, use a round font like Tahoma.

6.       Be prepared with 30-40 slides for a 40min presentation.

7.       The slides complement your lecture; they do not replace your talk. Use rich multi-media presentation.

8.       The paper assigned to you should be complemented with supporting background material.  Please try to add recent applications to the method or topic that you present.


List of presentations









Idan Misgav

Neural Feedback: Adam Gazzaley


Matan Poleg

Migraines with patients with Aura EEG monitoring and NF (Tommaso)


Rony Yahel

Meditation:  (Davidson. But not mindfulness) 




Yarden Sibony



Rotem Glass







Partial list of papers

1.       Mindfulness

2.       S. Makig. Review of EEG. Presentation.

3.       W. Klimesch. EEG alpha and theta oscillations reflect cognitive and memory performance: a review and analysis. Brain Research Reviews 1999.

4.      Gajraj, R. J., et al. " Analysis of the EEG bispectrum, auditory evoked potentials and the EEG power spectrum during repeated transitions from consciousness to unconsciousness." British journal of anesthesia 80.1 (1998): 46-52.

5.       Blankertz, Benjamin, et al. "Boosting bit rates and error detection for the classification of fast-paced motor commands based on single-trial EEG analysis." Neural Systems and Rehabilitation Engineering, IEEE Transactions on 11.2 (2003): 127-131.

6.       Guger, Christoph, et al. "How many people are able to control a P300-based brain–computer interface (BCI)." Neuroscience letters 462.1 (2009): 94-98.

7.      Coan, James A., and John JB Allen. "Frontal EEG asymmetry as a moderator and mediator of emotion." Biological psychology 67.1 (2004): 7-50.

8.      Rundgren, Malin, Ingmar Rosén, and Hans Friberg. "Amplitude-integrated EEG (aEEG) predicts outcome after cardiac arrest and induced hypothermia." Intensive care medicine 32.6 (2006): 836-842.

9.       Delorme, Arnaud, and Scott Makeig. "EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis." Journal of neuroscience methods 134.1 (2004): 9-21.

10.   Delorme, Arnaud, et al. "EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing." Computational intelligence and neuroscience (2011): 10.

11.   Bai, Ou, et al. "Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG." Clinical Neurophysiology 118.12 (2007): 2637-2655.

12.   Šušmáková, Kristina. "Human sleep and sleep EEG." Measurement Science Review 4.2 (2004): 59-74.

13.   Nicolas-Alonso, Luis Fernando, and Jaime Gomez-Gil. "Brain computer interfaces, a review." Sensors 12.2 (2012): 1211-1279.

14.   Chiou, Jin-Chern, et al. "Using novel MEMS EEG sensors in detecting drowsiness application." Biomedical Circuits and Systems Conference, 2006. BioCAS 2006. IEEE. IEEE, 2006.  

15.   Lin, Chin-Teng, et al. "Development of wireless brain computer interface with embedded multitask scheduling and its application on real-time driver's drowsiness detection and warning." Biomedical Engineering, IEEE Transactions on 55.5 (2008): 1582-1591.

16.   Pardey, James, Stephen Roberts, and Lionel Tarassenko. "A review of parametric modeling techniques for EEG analysis." Medical engineering & physics 18.1 (1996): 2-11.

17.   Astolfi, Laura, et al. "Comparison of different cortical connectivity estimators for high‐resolution EEG recordings." Human brain mapping 28.2 (2007): 143-157.

18.   Smit, Dirk JA, et al. "Heritability of “small‐world” networks in the brain: A graph theoretical analysis of resting‐state EEG functional connectivity." Human brain mapping 29.12 (2008): 1368-1378.

19.   G. Tononi. “Consciousness as Integrated Information: a Provisional Manifesto” Biol. Bull. 215: 216–242. (December 2008)

20.   Mirowski, Piotr, et al. "Classification of patterns of EEG synchronization for seizure prediction." Clinical neurophysiology 120.11 (2009): 1927-1940.

21.   Khushaba, Rami N., et al. "Consumer neuroscience: Assessing the brain response to marketing stimuli using electroencephalogram (EEG) and eye tracking." Expert Systems with Applications (2013).

22.   B. Abibullaev and and J. An. “Decision Support Algorithm for Diagnosis of ADHD Using Electroencephalograms” 2011

23.  Myles, P. S., et al. "Bispectral index monitoring to prevent awareness during anesthesia: the B-Aware randomized controlled trial." The lancet 363.9423 (2004): 1757-1763.

24.  Oostenveld, Robert, et al. "FieldTrip

: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data

Computational intelligence and neuroscience 2011 (2011): 1.


Example of the required level of explanation