Give me a break! Unavoidable fatigue effects in cognitive pupillometry.

Pupillometry has a rich history in the study of perception and cognition. One perennial challenge is that the magnitude of the task-evoked pupil response diminishes over the course of an experiment, a phenomenon we refer to as a fatigue effect. Reducing fatigue effects may improve sensitivity to task effects and reduce the likelihood of confounds due to systematic physiological changes over time. In this paper, we investigated the degree to which fatigue effects could be ameliorated by experimenter intervention. In Experiment 1, we assigned participants to one of three groups-no breaks, kinetic breaks (playing with toys, but no social interaction), or chatting with a research assistant-and compared the pupil response across conditions. In Experiment 2, we additionally tested the effect of researcher observation. Only breaks including social interaction significantly reduced the fatigue of the pupil response across trials. However, in all conditions we found robust evidence for fatigue effects: that is, regardless of protocol, the task-evoked pupil response was substantially diminished (at least 60%) over the duration of the experiment. We account for the variance of fatigue effects in our pupillometry data using multiple common statistical modeling approaches (e.g., linear mixed-effects models of peak, mean, and baseline pupil diameters, as well as growth curve models of time-course data). We conclude that pupil attenuation is a predictable phenomenon that should be accommodated in our experimental designs and statistical models.

Pupillometry reveals cognitive demands of lexical competition during spoken word recognition in young and older adults.

In most contemporary activation-competition frameworks for spoken word recognition, candidate words compete against phonological "neighbors" with similar acoustic properties (e.g., "cap" vs. "cat"). Thus, recognizing words with more competitors should come at a greater cognitive cost relative to recognizing words with fewer competitors, due to increased demands for selecting the correct item and inhibiting incorrect candidates. Importantly, these processes should operate even in the absence of differences in accuracy. In the present study, we tested this proposal by examining differences in processing costs associated with neighborhood density for highly intelligible items presented in quiet. A second goal was to examine whether the cognitive demands associated with increased neighborhood density were greater for older adults compared with young adults. Using pupillometry as an index of cognitive processing load, we compared the cognitive demands associated with spoken word recognition for words with many or fewer neighbors, presented in quiet, for young (n = 67) and older (n = 69) adult listeners. Growth curve analysis of the pupil data indicated that older adults showed a greater evoked pupil response for spoken words than did young adults, consistent with increased cognitive load during spoken word recognition. Words from dense neighborhoods were marginally more demanding to process than words from sparse neighborhoods. There was also an interaction between age and neighborhood density, indicating larger effects of density in young adult listeners. These results highlight the importance of assessing both cognitive demands and accuracy when investigating the mechanisms underlying spoken word recognition.