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Evaluating Models of Dynamic Functional Connectivity Using Predictive Classification Accuracy

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Vis graf over relationer

Dynamic functional connectivity has become a prominent approach for tracking the changes of macroscale statistical dependencies between regions in the brain. Effective parametrization of these statistical dependencies, referred to as brain states, is however still an open problem. We investigate different emission models in the hidden Markov model framework, each representing certain assumptions about dynamic changes in the brain. We evaluate each model by how well they can discriminate between schizophrenic patients and healthy controls based on a group independent component analysis of resting-state functional magnetic resonance imaging data. We find that simple emission models without full covariance matrices can achieve similar classification results as the models with more parameters. This raises questions about the predictability of dynamic functional connectivity in comparison to simpler dynamic features when used as biomarkers. However, we must stress that there is a distinction between characterization and classification, which has to be investigated further.

OriginalsprogEngelsk
Titel2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
Antal sider5
Vol/bind2018-April
ForlagInstitute of Electrical and Electronics Engineers Inc.
Publikationsdato2018
Sider2566-2570
Artikelnummer8462310
ISBN (Trykt)9781538646588
DOI
StatusUdgivet - 2018
Begivenhed2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Varighed: 15 apr. 201820 apr. 2018

Konference

Konference2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
LandCanada
ByCalgary
Periode15/04/201820/04/2018
SponsorThe Institute of Electrical and Electronics Engineers Signal Processing Society

Begivenhed

2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018

15/04/201820/04/2018

Calgary, Canada

Begivenhed: Konference

ID: 56438284