Predicting executive functioning from brain networks: modality specificity and age effects

Author:

Heckner Marisa K12ORCID,Cieslik Edna C12ORCID,Paas Oliveros Lya K12ORCID,Eickhoff Simon B12ORCID,Patil Kaustubh R12ORCID,Langner Robert12ORCID

Affiliation:

1. Institute of Neuroscience and Medicine (INM-7: Brain and Behaviour), Research Centre Jülich , 52425 Jülich , Germany

2. Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf , 40204 Düsseldorf , Germany

Abstract

Abstract Healthy aging is associated with structural and functional network changes in the brain, which have been linked to deterioration in executive functioning (EF), while their neural implementation at the individual level remains unclear. As the biomarker potential of individual resting-state functional connectivity (RSFC) patterns has been questioned, we investigated to what degree individual EF abilities can be predicted from the gray-matter volume (GMV), regional homogeneity, fractional amplitude of low-frequency fluctuations (fALFF), and RSFC within EF-related, perceptuo-motor, and whole-brain networks in young and old adults. We examined whether the differences in out-of-sample prediction accuracy were modality-specific and depended on age or task-demand levels. Both uni- and multivariate analysis frameworks revealed overall low prediction accuracies and moderate-to-weak brain–behavior associations (R2 < 0.07, r < 0.28), further challenging the idea of finding meaningful markers for individual EF performance with the metrics used. Regional GMV, well linked to overall atrophy, carried the strongest information about individual EF differences in older adults, whereas fALFF, measuring functional variability, did so for younger adults. Our study calls for future research analyzing more global properties of the brain, different task-states and applying adaptive behavioral testing to result in sensitive predictors for young and older adults, respectively.

Funder

Deutsche Forschungsgemeinschaft

National Institute of Mental Health

Helmholtz Portfolio Theme “Supercomputing and Modeling for the Human Brain,” the European Union’s Horizon 2020 Research and Innovation Programme

Publisher

Oxford University Press (OUP)

Subject

Cellular and Molecular Neuroscience,Cognitive Neuroscience

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