Journal article icon

Journal article

Using generative models to make probabilistic statements about hippocampal engagement in MEG.

Abstract:

Magnetoencephalography (MEG) enables non-invasive real time characterization of brain activity. However, convincing demonstrations of signal contributions from deeper sources such as the hippocampus remain controversial and are made difficult by its depth, structural complexity and proximity to neocortex. Here, we demonstrate a method for quantifying hippocampal engagement probabilistically using simulated hippocampal activity and realistic anatomical and electromagnetic source modelling. ...

Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

Actions


Access Document


Files:
Publisher copy:
10.1016/j.neuroimage.2017.01.029

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Psychiatry
Role:
Author
Expand authors...
Wellcome Trust More from this funder
National Institute for Health Research More from this funder
Publisher:
Elsevier Publisher's website
Journal:
Neuroimage Journal website
Volume:
149
Pages:
468-482
Publication date:
2017-01-01
Acceptance date:
2017-01-13
DOI:
ISSN:
1095-9572
Source identifiers:
675083
Language:
English
Keywords:
Pubs id:
pubs:675083
UUID:
uuid:40ffb796-ea82-4248-9919-c8f75cd840c0
Local pid:
pubs:675083
Deposit date:
2017-03-07

Terms of use


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP