9th SINAPSE Neuro-oncology Imaging Meeting [rescheduled] Mar 11, 2021 09:30 AM - 03:30 PM — West Park Conferencing & Events, 319 Perth Road, Dundee DD2 1NN
Total Body PET 2020 conference [rescheduled] Jun 05, 2021 - Jun 07, 2021 — McEwan Hall, University of Edinburgh
Medical Imaging Convention [rescheduled] Sep 15, 2021 - Sep 16, 2021 — National Exhibition Centre, Birmingham, England

eLearning

SINAPSE experts from around Scotland have developed ten online modules designed to explain medical imaging. They are freely available and are intended for non-specialists.


Edinburgh Imaging Academy at the University of Edinburgh offers the following online programmes through a virtual learning environment:

Neuroimaging for Research MSc/Dip/Cert

Imaging MSc/Dip/Cert

PET-MR Principles & Applications Cert

Applied Medical Image Analysis Cert

Online Short Courses

How to use fMRI functional localizers to improve EEG/MEG source estimation. LID - S0165-0270(14)00266-0 [pii] LID - 10.1016/j.jneumeth.2014.07.015 [doi]

Author(s): B. R. Cottereau, J. M. Ales, A. M. Norcia

Abstract:
EEG and MEG have excellent temporal resolution, but the estimation of the neural sources that generate the signals recorded by the sensors is a difficult, ill-posed problem. The high spatial resolution of functional MRI makes it an ideal tool to improve the localization of the EEG/MEG sources using data fusion. However, the combination of the two techniques remains challenging, as the neural generators of the EEG/MEG and BOLD signals might in some cases be very different. Here we describe a data fusion approach that was developed by our team over the last decade in which fMRI is used to provide source constraints that are based on functional areas defined individually for each subject. This mini-review describes the different steps that are necessary to perform source estimation using this approach. It also provides a list of pitfalls that should be avoided when doing fMRI-informed EEG/MEG source imaging. Finally, it describes the advantages of using a ROI-based approach for group-level analysis and for the study of sensory systems.

Full version: Available here

Click the link to go to an external website with the full version of the paper


ISBN:
Publication Year: 2014
Periodical:
Periodical Number: 1872-678X (Electronic)
Volume:
Pages:
Author Address: Universite de Toulouse, Centre de Recherche Cerveau et Cognition, UPS, France; CNRS UMR 5549, CerCo, Toulouse, France. Electronic address: cottereau@cerco.ups-tlse.fr. FAU - Ales, Justin M School of Psychology and Neuroscience, University of St Andrews, St Mary's Quad, South Street, St Andrews KY16 9JP, UK. FAU - Norcia, Anthony M Department of Psychology, Stanford University, Stanford, CA, United States.