000224839 001__ 224839
000224839 005__ 20180913064130.0
000224839 0247_ $$2doi$$a10.1109/ISBI.2016.7493507
000224839 020__ $$a978-1-4799-2349-6
000224839 020__ $$a978-1-4799-2350-2
000224839 02470 $$2ISI$$a000386377400309
000224839 037__ $$aCONF
000224839 245__ $$aTraces Of Human Functional Activity: Moment-To-Moment Fluctuations In Fmri Data
000224839 269__ $$a2016
000224839 260__ $$aNew York$$bIEEE$$c2016
000224839 300__ $$a4
000224839 336__ $$aConference Papers
000224839 490__ $$aIEEE International Symposium on Biomedical Imaging
000224839 520__ $$aDynamic functional connectivity (dFC) measured by functional magnetic resonance imaging (fMRI) shows evidence of large-scale networks with highly dynamic (re) configurations. We propose a novel approach to extract traces of human brain function by the construction of a trajectory in a meaningful low-dimensional space. This allows studying dFC in more detail and identify possible meaningful brain states from the moment-to-moment fluctuations of the brain signals during resting state or naturalistic conditions such as passive movie watching. Specifically, we explored dynamic organization of sub-networks derived from the time-dependent graph Laplacian in combination with Riemannian manifold distance to measure dissimilarity over time of dFC and to subsequently build the trajectory of brain activity. As a proof-of-principle, we show results for an fMRI dataset containing both rest and movie epochs in 15 healthy participants. The movie condition varied (i.e., fearful, joyful, and neutral movie excerpts) and clearly influenced the subsequent resting-state period in terms of FC brain state.
000224839 6531_ $$afunctional MRI
000224839 6531_ $$aRiemannian distance
000224839 6531_ $$anetwork modeling
000224839 6531_ $$abrain activity
000224839 700__ $$aDodero, Luca$$uIst Italiano Tecnol, PAVIS, Pattern Anal & Comp Vis, Genoa, Italy
000224839 700__ $$aSona, Diego$$uIst Italiano Tecnol, PAVIS, Pattern Anal & Comp Vis, Genoa, Italy
000224839 700__ $$0242939$$aMeskaldji, Djalel E.$$g120480$$uEcole Polytech Fed Lausanne, Inst Bioengn, CH-1015 Lausanne, Switzerland
000224839 700__ $$aMurino, Vittorio$$uIst Italiano Tecnol, PAVIS, Pattern Anal & Comp Vis, Genoa, Italy
000224839 700__ $$0240173$$aVan De Ville, Dimitri$$g152027$$uEcole Polytech Fed Lausanne, Inst Bioengn, CH-1015 Lausanne, Switzerland
000224839 7112_ $$aIEEE 13th International Symposium on Biomedical Imaging (ISBI)$$cPrague, Czech Republic$$d13-16 April 2016
000224839 773__ $$q1307-1310$$tIEEE 13th International Symposium on Biomedical Imaging (ISBI)
000224839 8564_ $$s969956$$uhttps://infoscience.epfl.ch/record/224839/files/dodero1601.pdf$$yPublisher's version$$zPublisher's version
000224839 909C0 $$0252169$$pMIPLAB$$xU12143
000224839 909CO $$ooai:infoscience.tind.io:224839$$pconf$$pSTI
000224839 917Z8 $$x152027
000224839 917Z8 $$x148230
000224839 937__ $$aEPFL-CONF-224839
000224839 973__ $$aEPFL$$rREVIEWED$$sPUBLISHED
000224839 980__ $$aCONF