Seminar in Computer Science:
EEG Brain Scanning
סמינר במדעי המחשב:
קריאה
וניתוח גלי
מוח
0368-3237-01, Autumn 2013-14
Monday
14-16 Schreiber 7
Prof.
Nathan Intrator
Contact
info Nathan Intrator nin@post.tau.ac.il 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.
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
|
|
Date |
Name |
Lecture |
|
1 |
28/10 |
Yael Miron |
EEG
alpha and theta oscillations reflect cognitive and memory performance: a
review and analysis |
|
2 |
28/10 |
Meital Kremer |
Amplitude-integrated EEG (aEEG) predicts
outcome after cardiac arrest and induced hypothermia." |
|
3 |
11/11 |
Roi Klein |
"Using novel MEMS EEG sensors in
detecting drowsiness application."
Extended |
|
4 |
11/11 |
Chen Shuval |
Heritability of “small‐world” networks
in the brain: A graph theoretical analysis of resting‐state EEG
functional connectivity." |
|
5 |
18/11 |
Oren Geri |
EEGLAB: an open source toolbox for analysis of
single-trial EEG dynamics including independent component analysis." |
|
6 |
18/11 |
Eidan |
Consciousness
as Integrated Information: a Provisional Manifesto |
|
7 |
25/11 |
Ira Vitenzon |
How many people are able to control a
P300-based brain–computer interface (BCI)?." |
|
8 |
25/11 |
Evgeny Kravchuk |
Analysis of the EEG bispectrum, auditory
evoked potentials and the EEG power spectrum during repeated transitions from
consciousness to |
|
9 |
9/12 |
Aya Lev |
|
|
10 |
9/12 |
Shira Hayman |
FieldTrip: open source software for advanced
analysis of MEG, EEG, and invasive electrophysiological data |
|
11 |
16/12 |
Matan Peleg |
Human sleep and sleep EEG." Measurement
Science Review 4.2 (2004): 59-74. |
|
12 |
16/12 |
Yitzhak Hafner |
Brain computer interfaces, a review."
Sensors 12.2 (2012): 1211-1279. |
|
13 |
23/12 |
Tomer Loterman |
|
|
14 |
23/12 |
Maor Gaon |
"Classification of patterns of EEG
synchronization for seizure prediction." Clinical neurophysiology 120.11
(2009): 1927-1940. |
|
15 |
30/12 |
Ofek Doitch |
|
|
16 |
30/12 |
Natai Itzhaki |
Decision Support Algorithm for Diagnosis of
ADHD Using Electroencephalograms” |
|
17 |
6/1 |
Gal Arnon |
|
|
18 |
6/1 |
|
|
Partial list of papers
1.
S. Makig. Review of EEG.
Presentation.
2.
W. Klimesch. EEG alpha and theta oscillations
reflect cognitive and memory performance: a review and analysis. Brain
Research Reviews 1999.
10.
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.
11.
Šušmáková, Kristina. "Human sleep and sleep EEG." Measurement Science Review
4.2 (2004): 59-74.
12.
Nicolas-Alonso, Luis
Fernando, and Jaime Gomez-Gil. "Brain
computer interfaces, a review." Sensors 12.2 (2012): 1211-1279.
13.
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.
14.
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.
15.
Pardey, James, Stephen
Roberts, and Lionel Tarassenko. "A review of parametric modeling techniques for EEG
analysis." Medical engineering & physics 18.1 (1996): 2-11.
16. Astolfi, Laura, et al. "Comparison of
different cortical connectivity estimators for high‐resolution EEG
recordings." Human brain mapping 28.2 (2007): 143-157.
17.
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.
18.
G. Tononi. “Consciousness as Integrated Information: a
Provisional Manifesto” Biol. Bull. 215: 216–242. (December 2008)
19.
Mirowski, Piotr, et al. "Classification
of patterns of EEG synchronization for seizure prediction."
Clinical neurophysiology 120.11 (2009): 1927-1940.
20.
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).
21.
B. Abibullaev and
and J. An. “Decision Support Algorithm for Diagnosis of ADHD
Using Electroencephalograms” 2011
23. 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
