Pupil-Linked Arousal Responds to Unconscious Surprisal

Abstract

Pupil size under constant illumination reflects brain arousal state, and dilates in response to novel information, or surprisal. Whether this response can be observed regardless of conscious perception is still unknown. In the present study, male and female adult humans performed an implicit learning task across a series of three experiments. We measured pupil and brain-evoked potentials to stimuli that violated transition statistics but were not relevant to the task. We found that pupil size dilated following these surprising events, in the absence of awareness of transition statistics, and only when attention was allocated to the stimulus. These pupil responses correlated with central potentials, evoking an anterior cingulate origin. Arousal response to surprisal outside the scope of conscious perception points to the fundamental relationship between arousal and information processing and indicates that pupil size can be used to track the progression of implicit learning.SIGNIFICANCE STATEMENT Pupil size dilates following increase in mental effort, surprise, or more generally global arousal. However, whether this response arises as a conscious response or reflects a more fundamental mechanism outside the scrutiny of awareness is still unknown. Here, we demonstrate that unexpected changes in the environment, even when processed unconsciously and without being relevant to the task, lead to an increase in arousal levels as reflected by the pupillary response. Further, we show that the concurrent electrophysiological response shares similarities with mismatch negativity, suggesting the involvement of anterior cingulate cortex. All in all, our results establish novel insights about the mechanisms driving global arousal levels, and it provides new possibilities for reliably measuring unconscious processes.

Keywords: ERPs; arousal; implicit learning; prediction error; pupil size; statistical learning.

Figure 1.

Experimental design. A, Each trial was composed of a series of displays containing a letter over-imposed on a fixation point. The letters changed every second. In the first experiment, participants underwent 2 sessions, with a different alphabet in each session (Alphabets I or II). Experiments 2 and 3 used only Alphabet I. B, Color-coded transition matrix for rare (red), frequent (blue), and same transitions (green). Notice that the same transition never occurred during the experiment. Right, A schematic example of the Markovian process driving the letter sequence. Each letter could transition to three other letters, two of which being frequent (47.5% chance) and one being rare (5% chance). Bottom, An example of sequence is provided, in which the rare transition is shown in red.

Figure 2.

Pupillary traces. All the panels show pupil responses after rare (red) and frequent (blue) transitions. The origin of the x-axis corresponds to the onset of the stimulus, whereas the y-axis has arbitrary units, pupil size being normalized with respect to the baseline (1 s before onset). Baseline correction was performed for visualization purposes, but was not applied during analysis. The small graph in the top right of each panel reports the IRF of each participants computed after each rare transitions, the signed maximum value of each IRF and the mean ± SE. of the maximum values. In all panels, it is possible to observe a periodic response in both conditions at 1 Hz, because of the stimulus onset. A and B show data from the first experiment, when attention is allocated respectively to the letter or to the fixation dot. C, Results from the second experiment, and (D) from the third one.

Figure 3.

Generative and familiarity tests. A, During a trial of the generative task, participants were asked to guess the next letter, following a transition. Letter duration and layout was the same as during the experiment. B, In the familiarity task, participants judged how familiar a transition was by rating it from 1 to 10. C, Results of the bias-corrected generative task: bar plots in blue/red show the mean percentage ± SE of times the participants chose the frequent/rare transition. The transitions that were chosen by the participants but never actually occurred are displayed in green (<5% of responses). The connected dots represent the percentage values for each subject in the frequent (blue) and rare (red) conditions. D, Mean ± SE of the rate of familiarity reveals that participants judged rare transitions (red) as more familiar than frequent ones (blue). Each pair of connected dots represents one subject. E, Positive correlation between the difference in the pupillary response between conditions (rare − frequent) and difference in the familiarity scores in each condition.

Figure 4.

Electrophysiological results. A, The topographies show the clusters of electrodes whose activity differed from baseline, regardless of the conditions; the left and right plots show the first and second time windows, respectively. Red/black dots represent electrodes included/excluded in/from the cluster. B, Grand average of ERP traces elicited by rare (red) and frequent (blue) transitions in the first (left plot), and second cluster (right plot). The subplot shows the mean difference ± SE between rare and frequent condition in the respective time windows. Dots represent subjects. C, Topography of the difference rare-frequent in the second clusters of electrodes. The effect involves mostly central regions. D, Scatter plots of ERP and pupil differences (rare − frequent) in the second cluster.