[BIC-announce] New course now available in Biomed Engineering and IPN for Winter 2013 : BMDE610 - Functional neuroimaging fusion - Registration is open

[Christophe Grova]

Dear all,

I am happy to announce you that my new graduate course BMDE610, entitled Functional neuroimaging fusion will be offered for the second time in Winter 2013 in Biomedical Engineering Dpt and IPN.

Here is the link to BME course list: http://www.mcgill.ca/bme/students/courses

where you can download the syllabus of the course:
http://www.mcgill.ca/bme/sites/mcgill.ca.bme/files/course_outline_bmde610.pdf

The course is now listed as an IPN course as well: http://www.mcgill.ca/ipn/courses#B610

Most of the lectures will be done by myself  + few invited lecturers.

Registration is now open on Minerva !


Course description:
BMDE610: Biomedical engineering: Multimodal data fusion of electrophysiology and functional neuroimaging data, including: detailed description of source localization methods for Electro- and MagnetoEncephaloGraphy data, analysis of brain hemodynamic activity through simultaneous recordings with electrophysiology, analysis and reconstruction of Near Infra-RedSpectroscopydata, modelling of the neurovascular coupling, validation methodology.

Key words : EEG/ MEG , source localization, fMRI, NIRS, statistical analysis, GLM, deconvolution, neurovacular coupling, multimodal fusion

Objectives of the course:
The main objectives of this new course BMED 610 is to address specific issues related to data fusion of functional neuroimaging data. The lecture will first adress in details the issue of performing source localization from Electro-EncephaloGraphy EEG and Magneto-EncephaloGraphy MEG data, reviewing in details most of the available methods.
The second part of the course will adress statistical analysis of techniques using hemodynamic processes to study brain activity, so mainly functional Magnetic Resonance Imagine (fMRI) data but also Near Infra Red Spectroscopy (NIRS) data, as well as combined recordings involvings simultaneous EEG/MEG, EEG/fMRI or EEG/NIRS acquisition and data analysis.


The objectives of the course are to introduce methods necessary to address the difficult problem of functional neuroimaging data fusion. The first part of the course will be dedicated to a detailed presentation of methods for which source localization has to be inferred from data acquired on the scalp: (1) in electrophysiology when using EEG or MEG, and (2) for hemodynamic activity when using Near Infra Red Spectroscopy (NIRS) data. The second part of the course will concern the link between bioelectrical activity and hemodynamic processes, the so-called neurovascular coupling. Applications for which simultaneous recordings of more than one modality are required will be presented, as well as related technical and methodological difficulties. The course will end with a state of the art of the models proposed to characterize the neurovascular coupling.

Objectives of the course
After completing this course, the students will be able to perform source localization from EEG and MEG data, which is far from trivial for most available softwares. They will also acquire sufficient knowledge to start analyzing hemodynamic data (fMRI, NIRS)  to study  neurovascular coupling.

Evaluation of the course:
4 Assignments: 40%
lParticipation (attendance): 10%
Final Project: report (30%) oral (20%): Detailed analysis of an article or a particular application of neuroimaging data fusion, with specific emphasis on validation methodology. The objective of the project is to present, in details, the added value of using data fusion in a specific application context. A clear understanding of the proposed methodology is expected.



Preliminary syllabus
Week 1: Basis of electrophysiology (EEG, MEG) and hemodynamic signals (fMRI, NIRS)
Week 2: Forward model in EEG/MEG and in NIRS modelling
Week 3: Validation methodology in neuroimaging
Week 4: Source localization: equivalent current dipole and dipole scanning approaches
Week 5: Source localization: distributed models and Bayesian approaches
Week 6: Source localization: hierarchical Bayesian models, entropic framework
Week 7: Source localization: time-frequency based source localization
Week 8: Simultaneous EEG/fMRI: acquisition, analysis, and interpretation
Week 9: Multimodal fusion and neurovascular coupling modelling
Week 10: NIRS : data acquisition, data analysis and inverse problem
Weeks 11-12: oral presentations of the final projects



Feel free to contact me if you need more information

Hope to see many of you in the course

Christophe Grova

***************************
Christophe Grova, PhD
Assistant Professor
Biomedical Engineering Dpt
Neurology and Neurosurgery Dpt

Montreal Neurological Institute
Centre de Recherches en Mathématiques

Biomedical Engineering Department - Room 304 McGill University
3775 University Street, Montreal, Quebec, Canada, H3A 2B4
email : christophe.grova at mcgill.ca
tel : (514) 398 2516
fax : (514) 398 7461

web:
http://apps.mni.mcgill.ca/research/gotman/members/christophe.html
http://www.bmed.mcgill.ca/
***************************

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://www.bic.mni.mcgill.ca/pipermail/bic-announce/attachments/20121123/e2bf8c52/attachment.htm>