Structural and functional MRI data differentially predict chronological age and behavioral memory performance [article]

Joram Soch, Anni Richter, Jasmin M Kizilirmak, Hartmut Schütze, Hannah Feldhoff, Larissa Fischer, Lea Knopf, Matthias Raschick, Annika Schult, Emrah Düzel, Björn H Schott
2022 bioRxiv   pre-print
Human cognitive abilities decline with increasing chronological age, with decreased explicit memory performance being most strongly affected. However, some older adults show "successful aging", that is, relatively preserved cognitive ability in old age. One explanation for this could be higher brain structural integrity in these individuals. Alternatively, the brain might recruit existing resources more efficiently or employ compensatory cognitive strategies. Here, we approached this question
more » ... testing multiple candidate variables from structural and functional neuroimaging for their ability to predict chronological age and memory performance, respectively. Prediction was performed using support vector machine (SVM) classification and regression across and within two samples of young (N = 106) and older (N = 153) adults. The candidate variables were (i) behavioral response frequencies in an episodic memory test, (ii) recently described fMRI scores reflecting preservation of functional memory networks, (iii) whole-brain fMRI contrasts for novelty processing and subsequent memory, (iv) resting-state fMRI maps quantifying voxel-wise signal fluctuation and (v) gray matter volume estimated from structural MR images. While age group could be reliably decoded from all variables, chronological age within young and older subjects was best predicted from gray matter volume. In contrast, memory performance was best predicted from task-based fMRI contrasts and particularly single-value fMRI scores, whereas gray matter volume has no predictive power with respect to memory performance in healthy adults. Our results suggest that superior memory performance in healthy older adults is better explained by efficient recruitment of memory networks rather than by preserved brain structure.
doi:10.1101/2022.03.24.485603 fatcat:cv2yxvsfs5arrbkm5ujvi7xzsa