Poorer White Matter Microstructure Predicts Slower and More Variable Reaction Time Performance: Evidence for a Neural Noise Hypothesis in a Large Lifespan Cohort

Journal of Neuroscience, vol. 43, pp. 3557–3566

Abstract

Most prior research has focused on characterizing averages in cognition, brain characteristics, or behavior, and attempting to predict differences in these averages among individuals. However, this overwhelming focus on mean levels may leave us with an incomplete picture of what drives individual differences in behavioral phenotypes by ignoring the variability of behavior around an individual's mean. In particular, enhanced white matter (WM) structural microstructure has been hypothesized to support consistent behavioral performance by decreasing Gaussian noise in signal transfer. Conversely, lower indices of WM microstructure are associated with greater within-subject variance in the ability to deploy performance-related resources, especially in clinical populations. We tested a mechanistic account of the “neural noise” hypothesis in a large adult lifespan cohort (Cambridge Centre for Ageing and Neuroscience) with over 2500 adults (ages 18-102; 1508 female; 1173 male; 2681 behavioral sessions; 708 MRI scans) using WM fractional anisotropy to predict mean levels and variability in reaction time performance on a simple behavioral task using a dynamic structural equation model. By modeling robust and reliable individual differences in within-person variability, we found support for a neural noise hypothesis (Kail, 1997), with lower fractional anisotropy predicted individual differences in separable components of behavioral performance estimated using dynamic structural equation model, including slower mean responses and increased variability. These effects remained when including age, suggesting consistent effects of WM microstructure across the adult lifespan unique from concurrent effects of aging. Crucially, we show that variability can be reliably separated from mean performance using advanced modeling tools, enabling tests of distinct hypotheses for each component of performance. SIGNIFICANCE STATEMENTHuman cognitive performance is defined not just by the long-run average, but trial-to-trial variability around that average. However, investigations of cognitive abilities and changes during aging have largely ignored this variability component of behavior. We provide evidence that white matter (WM) microstructure predicts individual differences in mean performance and variability in a sample spanning the adult lifespan (18-102). Unlike prior studies of cognitive performance and variability, we modeled variability directly and distinct from mean performance using a dynamic structural equation model, which allows us to decouple variability from mean performance and other complex features of performance (e.g., autoregression). The effects of WM were robust above the effect of age, highlighting the role of WM in promoting fast and consistent performance.

Authors 2

1. Ethan Michael McCormick Aachen Methodology and Statistics Department Institute of Psychology, Leiden University 2Methodology and Statistics Department

   Leiden University · Radboud University Medical Center · Radboud University Nijmegen · University of North Carolina at Chapel Hill · Donders Institute for Brain, Cognition and Behaviour

   Affiliation as printed

   Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands e.m.mccormick@fsw.leidenuniv.nl

   Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, North Carolina, 27599

   Methodology and Statistics Department, Institute of Psychology, Leiden University, 2333 AK Leiden, The Netherlands

   1Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands

   2Methodology and Statistics Department, Institute of Psychology, Leiden University, 2333 AK Leiden, The Netherlands

   3Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, North Carolina, 27599

2. Rogier Kievit

   University of Cambridge · Radboud University Medical Center · Radboud University Nijmegen · Donders Institute for Brain, Cognition and Behaviour · MRC Cognition and Brain Sciences Unit

   Affiliation as printed

   Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands

   MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom

   1Cognitive Neuroscience Department, Donders Institute for Brain, Cognition and Behavior, Radboud University Medical Center, 6525 GD Nijmegen, The Netherlands

   4MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge CB2 7EF, United Kingdom