December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Investigating the consistency of pupil-linked cognitive processes across multiple disparate tasks
Author Affiliations
  • Russell Cohen Hoffing
    DEVCOM Army Research Labs
  • Javier Garcia
    DEVCOM Army Research Labs
  • Jean Vettel
    DEVCOM Army Research Labs
  • Steven Thurman
    DEVCOM Army Research Labs
Journal of Vision December 2022, Vol.22, 3111. doi:
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      Russell Cohen Hoffing, Javier Garcia, Jean Vettel, Steven Thurman; Investigating the consistency of pupil-linked cognitive processes across multiple disparate tasks. Journal of Vision 2022;22(14):3111.

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      © ARVO (1962-2015); The Authors (2016-present)

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The pupillary response is influenced by both cognitive processes, such as arousal and attention, and non-cognitive processes, such as luminance. To study physiological markers of cognitive processing, researchers use luminance-matched stimuli to minimize the influence of non-cognitive factors on pupil response changes. As such, extant pupillometry research may be confounded by task-structure which limits its applicability to other contexts. To investigate whether commonly defined phasic (peak amplitude, peak latency) and tonic pupil (baseline) features generalize across contexts, we leveraged a unique longitudinal pupillometry data set that involved performance of mental arithmetic (MA), visual working memory (VWM), and psychomotor vigilance (PVT) tasks. Participants (N=30) completed these tasks on 8 separate sessions over the course of 16 weeks, allowing us to address a number of questions about the task-dependence of pupil features: (1) which pupil features are consistent across tasks? and (2) which pupil features show reliable relationships to behavior (response time (RT)) within and/or across tasks? Results showed that mean baseline pupil diameter was consistent across the three tasks, whereas task-evoked phasic features (peak amplitude and latency) were not consistent (i.e., they were highly task-specific). However, despite being uncorrelated from task-to-task, phasic features showed a strong positive relationship with behavioral RT’s both within and across the three tasks. Peak latency, in particular, tracked RT very closely for all three tasks: MA: mean RT 3.18s & mean latency 5.75s; VWM: RT 0.70s & latency 3.23s; PVT: RT 0.41s & latency 2.31s. Baseline pupil diameter was also significantly associated with mean RT such that higher baseline was predictive of faster responses. These findings suggest that peak amplitude and latency, while task-specific, reflect a common pupil-linked decision process, while baseline reflects more stable pupil-linked arousal processes that also contribute to performance.


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