Interleaved Pro/Anti-saccade Behavior Across the Lifespan - Yep, Rachel; Smorenburg, Matthew L.; Riek, Heidi C.; Calancie, Olivia G.; Kirkpatrick, Ryan H.; Perkins, Julia E.; Huang, Jeff; Coe, Brian C.; Brien, Donald C.; Munoz, Douglas P. (Frontiers in Aging Neuroscience, 2022)
The capacity for inhibitory control is an important cognitive process that undergoes dynamic changes over the course of the lifespan. Robust characterization of this trajectory, considering age continuously and using flexible modelling techniques, is critical to advance our understanding of the neural mechanisms that differ in healthy aging and neurological disease. The interleaved pro/anti-saccade task (IPAST), in which pro- and anti-saccade trials are randomly interleaved within a block, provides a simple and sensitive means of assessing the neural circuitry underlying inhibitory control. We utilized IPAST data collected from a large cross-sectional cohort of normative participants (n=604, 5-93 years of age), standardized pre-processing protocols, generalized additive modelling, and change point analysis to investigate the effect of age on saccade behavior and identify significant periods of change throughout the lifespan. Maturation of IPAST measures occurred throughout adolescence, while subsequent decline began as early as the mid-20s and continued into old age. Considering pro-saccade correct responses and anti-saccade direction errors made at express (short) and regular (long) latencies was crucial in differentiating developmental and aging processes. We additionally characterized the effect of age on voluntary override time, a novel measure describing the time at which voluntary processes begin to overcome automated processes on anti-saccade trials. Drawing on converging animal neurophysiology, human neuroimaging, and computational modelling literature, we propose potential frontal-parietal and frontal-striatal mechanisms that may mediate the behavioral changes revealed in our analysis. We liken the models presented here to “cognitive growth curves” which have important implications for improved detection of neurological disease states that emerge during vulnerable windows of developing and aging.