Pupillometry shows the effort of auditory attention switching.

Successful speech communication often requires selective attention to a target stream amidst competing sounds, as well as the ability to switch attention among multiple interlocutors. However, auditory attention switching negatively affects both target detection accuracy and reaction time, suggesting that attention switches carry a cognitive cost. Pupillometry is one method of assessing mental effort or cognitive load. Two experiments were conducted to determine whether the effort associated with attention switches is detectable in the pupillary response. In both experiments, pupil dilation, target detection sensitivity, and reaction time were measured; the task required listeners to either maintain or switch attention between two concurrent speech streams. Secondary manipulations explored whether switch-related effort would increase when auditory streaming was harder. In experiment 1, spatially distinct stimuli were degraded by simulating reverberation (compromising across-time streaming cues), and target-masker talker gender match was also varied. In experiment 2, diotic streams separable by talker voice quality and pitch were degraded by noise vocoding, and the time alloted for mid-trial attention switching was varied. All trial manipulations had some effect on target detection sensitivity and/or reaction time; however, only the attention-switching manipulation affected the pupillary response: greater dilation was observed in trials requiring switching attention between talkers.

Temporal alignment of pupillary response with stimulus events via deconvolution.

Analysis of pupil dilation has been used as an index of attentional effort in the auditory domain. Previous work has modeled the pupillary response to attentional effort as a linear time-invariant system with a characteristic impulse response, and used deconvolution to estimate the attentional effort that gives rise to changes in pupil size. Here it is argued that one parameter of the impulse response (the latency of response maximum, t(max)) has been mis-estimated in the literature; a different estimate is presented, and it is shown how deconvolution with this value of t(max) yields more intuitively plausible and informative results.