Result: Connectivity-informed fMRI Activation Detection

Title:
Connectivity-informed fMRI Activation Detection
Authors:
Ng, Bernard, Rafeef, Abugharbieh, Varoquaux, Gaël, Poline, Jean Baptiste, Thirion, Bertrand
Contributors:
Biomedical Signal and Image Computing Laboratory (BiSICL), University of British Columbia [Canada] (UBC), Laboratoire de Neuroimagerie Assistée par Ordinateur (LNAO), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Modelling brain structure, function and variability based on high-field MRI data (PARIETAL), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Institut des Sciences du Vivant Frédéric JOLIOT (JOLIOT), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Institut des Sciences du Vivant Frédéric JOLIOT (JOLIOT), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre Inria de Saclay, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Neuroimagerie cognitive - Psychologie cognitive expérimentale (UNICOG-U992), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Gabor Fichtinger and Anne Martel and Terry Peters, Imagen
Source:
Medical Image Computing and Computed Aided Intervention. :285-292
Publisher Information:
CCSD; Springer-Verlag, 2011.
Publication Year:
2011
Collection:
collection:CEA
collection:INRIA
collection:INRIA-SACLAY
collection:INRIA_TEST
collection:TESTALAIN1
collection:INRIA2
collection:JOLIOT
collection:CEA-DRF
collection:NEUROSPIN
collection:INRIA-CANADA
Subject Terms:
ACM: J.: Computer Applications, J.3: LIFE AND MEDICAL SCIENCES, ACM: G.: Mathematics of Computing, G.3: PROBABILITY AND STATISTICS, G.3.5: Multivariate statistics, [INFO.INFO-IM]Computer Science [cs], Medical Imaging
Subject Geographic:
Toronto, Canada
Original Identifier:
HAL:
Document Type:
Conference conferenceObject<br />Conference papers
Language:
English
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1007/978-3-642-23629-7_35
DOI:
10.1007/978-3-642-23629-7_35
Access URL:
https://inria.hal.science/inria-00627523
https://inria.hal.science/inria-00627523v1/document
https://inria.hal.science/inria-00627523v1/file/camera_ready.pdf
Rights:
info:eu-repo/semantics/OpenAccess
Accession Number:
edshal.inria.00627523v1
Database:
HAL

Further Information

A growing interest has emerged in studying the correlation structure of spontaneous and task-induced brain activity to elucidate the functional architecture of the brain. In particular, functional networks estimated from resting state (RS) data were shown to exhibit high resemblance to those evoked by stimuli. Motivated by these findings, we propose a novel generative model that integrates RS-connectivity and stimulus-evoked responses under a unified analytical framework. Our model permits exact closed-form solutions for both the posterior activation effect estimates and the model evidence. To learn RS networks, graphical LASSO and the oracle approximating shrinkage technique are deployed. On a cohort of 65 subjects, we demonstrate increased sensitivity in fMRI activation detection using our connectivity-informed model over the standard univariate approach. Our results thus provide further evidence for the presence of an intrinsic relationship between brain activity during rest and task, the exploitation of which enables higher detection power in task-driven studies.