Related Experiment Video
Updated: Apr 21, 2026
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
Published on: January 23, 2017
TVA-based assessment of attentional capacities-associations with age and indices of brain white matter microstructure
Thomas Espeseth1, Signe A Vangkilde2, Anders Petersen2
1Department of Psychology, University of Oslo Oslo, Norway ; Norwegian Centre for Mental Disorders Research (NORMENT), and KG Jebsen Centre for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital Oslo, Norway.
Abstract:
In this study the primary aims were to characterize the effects of age on basic components of visual attention derived from assessments based on a theory of visual attention (TVA) in 325 healthy volunteers covering the adult lifespan (19-81 years). Furthermore, we aimed to investigate how age-related differences on TVA parameters are associated with white matter (WM) microstructure as indexed by diffusion tensor imaging (DTI). Finally, we explored how TVA parameter estimates were associated with complex, or multicomponent indices of processing speed (Digit-symbol substitution, DSS) and fluid intelligence (gF). The results indicated that the TVA parameters for visual short-term memory capacity, K, and for attentional selectivity, α, were most strongly associated with age before the age of 50. However, in this age range, it was the parameter for processing speed, C, that was most clearly associated with DTI indices, in this case fractional anisotropy (FA), particularly in the genu and body of the corpus callosum. Furthermore, differences in the C parameter partially mediated differences in DSS within this age range. After the age of 50, the TVA parameter for the perceptual threshold, t 0, as well as K, were most strongly related to participant age. Both parameters, but t 0 more strongly so than K, were associated WM diffusivity, particularly in projection fibers such as the internal capsule, the sagittal stratum, and the corona radiata. Within this age range, t 0 partially mediated age-related differences in gF. The results are consistent with, and provide novel empirical support for the neuroanatomical localization of TVA computations as outlined in the neuronal interpretation of TVA (NTVA). Furthermore, the results indicate that to understand the biological sources of age-related changes in processing speed and fluid cognition, it may be useful to employ methods that allow for computational fractionation of these multicomponent measures.
