Age effects on sex classification performance

Field: Neuroscience (Life Sciences)

Cognitive sex differences have repeatedly been examined both in behaviour and task-related functional magnetic resonance imaging (fMRI). More recently, machine-learning approaches have successfully been employed to predict the sex of a person from whole brain and regionally specific resting state (RS) functional brain connectivity patterns. Differentiating patterns of brain connectivity between the sexes are presumably based on biological factors as well as social influences and experiences ([2]). Thus, sex differences in brain connectivity might be modulated by age. The present study aimed to examine if brain regions that most reliably distinguish between males and females differ between younger and older participants. The RS connectome was extracted from fMRI data in a sub-sample of the enhanced Nathan Kline Institute-Rockland Sample (NKI-RS; [1]), in which males and females were matched for age (n = 380, 190 males, age range: 8 – 83). For each of 436 regions (ROIs), connectivity patterns were defined by the Pearson correlations between each ROI’s time course and the rest of the brain, which were then transformed to Fischer’s Z-scores. Regional connectivity patterns were used as features in a sex classification analysis, employing a non-linear support vector machine (SVM) approach that was conducted individually for each ROI. Excluding the median age range of 25 – 35, classification accuracies for each ROI were assessed separately for the young (n=166) and the old (n=168) part of the sample. For both groups, classification accuracies (Acc) were above chance for all ROIs across the brain (young: min Acc = 67.11%, old: min Acc = 60.71%). Across the whole brain, accuracies were significantly higher for the young (mean Acc: 74.21%; SD: 2.56%) then for the old group (mean Acc: 68.54%; SD: 2.91%; t = 36.78; p < 0.001). Regions displaying significantly higher sex classification accuracies for the young then for the old group ( χ2(1) > 4.73, p < 0.05) were located in the left inferior, middle, medial and orbital frontal gyrus, the right middle, superior and orbital frontal gyrus, left pre- and postcentral gyrus, as well as bilateral palladium and putamen. Functional decoding associated these areas with language functions, reward, memory, task-switching and inhibition. Our data show that regional RS brain connectivity can be used to reliably predict sex both in younger and older subjects. Lower accuracies in the older group indicate that brain connectivity patterns become less sex-specific in older as opposed to younger subjects. Most pronounced lower accuracies in lateral and medial frontal cortices indicate that frontal brain connectivity becomes more similar in older males and females. As the frontal cortex has often been associated with monitoring and control of behaviour and cognitive strategies, these findings might indicate that with aging, frontal cortex modulatory influences on other brain regions becomes more similar between the sexes, supporting compensatory sex-dependent processes that act to reduce cognitive sex differences ([3])[1] Nooner KB et al. Frontiers in neuroscience (2012) 6:152.[2] Jancke L. F1000Res (2018) 7.[3] de Vries GJ & Sodersten P. Horm Behav (2009) 55(5):589-596.