Prediction of long-term memory scores in MCI based on resting-state fMRI.
Resting-state functional MRI (rs-fMRI) opens a window on large-scale organization of brain function. However, establishing relationships between resting-state brain activity and cognitive or clinical scores is still a difficult task, in particular in terms of prediction as would be meaningful for clinical applications such as early diagnosis of Alzheimer's disease. In this work, we employed partial least square regression under cross-validation scheme to predict episodic memory performance from functional connectivity (FC) patterns in a set of fifty-five MCI subjects for whom rs-fMRI acquisition and neuropsychological evaluation was carried out. We show that a newly introduced FC measure capturing the moments of anti-correlation between brain areas, discordance, contains key information to predict long-term memory scores in MCI patients, and performs better than standard measures of correlation to do so. Our results highlighted that stronger discordance within default mode network (DMN) areas, as well as across DMN, attentional and limbic networks, favor episodic memory performance in MCI.
Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland; Institute of Mathematics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Djalel-Eddine
DE
Meskaldji
Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
Maria Giulia
MG
Preti
Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
Thomas Aw
TA
Bolton
Divisions of Diagnostic and Interventional Neuroradiology, Geneva University Hospitals, Geneva, Switzerland.
Marie-Louise
ML
Montandon
Department of Psychiatry, University of Geneva, Switzerland.
Cristelle
C
Rodriguez
Institute of Mathematics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
Stephan
S
Morgenthaler
Department of Psychiatry, University of Geneva, Switzerland.
Panteleimon
P
Giannakopoulos
Affidea CDRC - Centre Diagnostique Radiologique de Carouge, Switzerland; Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden; Department of Neuroradiology, University Hospital Freiburg, Germany; Faculty of Medicine of the University of Geneva, Switzerland.
Sven
S
Haller
Institute of Bioengineering, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Department of Radiology and Medical Informatics, University of Geneva, Geneva, Switzerland.
Dimitri
D
Van De Ville
D000368:Aged; D000369:Aged, 80 and over; D060825:Cognitive Dysfunction / Q000000981:diagnostic imaging / Q000503:physiopathology*; D063132:Connectome / Q000379:methods*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D057567:Memory, Long-Term / Q000502:physiology*
Cross-validation partial least square regression; Extreme value modeling; Functional brain connectivity; Long term memory; Medial temporal lobe; Mild cognitive impairment