TY - JOUR
T1 - Poorer White Matter Microstructure Predicts Slower and More Variable Reaction Time Performance
T2 - Evidence for a Neural Noise Hypothesis in a Large Lifespan Cohort
AU - Cambridge Centre for Ageing and Neuroscience
AU - McCormick, Ethan M.
AU - Kievit, Rogier A.
AU - Tyler, Lorraine K.
AU - Brayne, Carol
AU - Bullmore, Edward T.
AU - Calder, Andrew C.
AU - Cusack, Rhodri
AU - Dalgleish, Tim
AU - Duncan, John
AU - Henson, Richard N.
AU - Matthews, Fiona E.
AU - Marslen-Wilson, William D.
AU - Rowe, James B.
AU - Shafto, Meredith A.
AU - Associates, Research
AU - Campbell, Karen
AU - Cheung, Teresa
AU - Davis, Simon
AU - Geerligs, Linda
AU - Kievit, Rogier
AU - McCarrey, Anna
AU - Mustafa, Abdur
AU - Price, Darren
AU - Samu, David
AU - Taylor, Jason R.
AU - Treder, Matthias
AU - Tsvetanov, Kamen A.
AU - van Belle, Janna
AU - Williams, Nitin
AU - Assistants, Research
AU - Bates, Lauren
AU - Emery, Tina
AU - Erzinçlioglu, Sharon
AU - Gadie, Andrew
AU - Gerbase, Sofia
AU - Georgieva, Stanimira
AU - Hanley, Claire
AU - Parkin, Beth
AU - Troy, David
AU - Auer, Tibor
AU - Correia, Marta
AU - Gao, Lu
AU - Green, Emma
AU - Henriques, Rafael
AU - Allen, Jodie
AU - Amery, Gillian
AU - Amunts, Liana
AU - Barcroft, Anne
AU - Castle, Amanda
AU - Dias, Cheryl
N1 - Publisher Copyright:
Copyright © 2023 McCormick et al.
PY - 2023/5/10
Y1 - 2023/5/10
N2 - 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.
AB - 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.
KW - aging
KW - dynamic structural equation modeling
KW - lifespan
KW - reaction time
KW - white matter
UR - https://www.scopus.com/pages/publications/85159542130
U2 - 10.1523/JNEUROSCI.1042-22.2023
DO - 10.1523/JNEUROSCI.1042-22.2023
M3 - Article
C2 - 37028933
AN - SCOPUS:85159542130
SN - 0270-6474
VL - 43
SP - 3557
EP - 3566
JO - Journal of Neuroscience
JF - Journal of Neuroscience
IS - 19
ER -