Tracking working memory maintenance with pupillometry

Unsworth, Nash; Robison, Matthew K.

doi:10.3758/s13414-017-1455-x

Cited by 49 publications

(53 citation statements)

References 82 publications

(143 reference statements)

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“…In general, people who experienced more fluctuations in arousal performed worse on the task, and people who allocated more attention to the items during the delay periods (and more consistently) performed better. All of these correlations replicate prior work measuring pretrial pupil diameter, task-evoked pupillary responses, intraindividual variability in these measures, and WM capacity (Unsworth et al , 2017b(Unsworth et al , 2018b.…”

Section: Combined Analyses -Individual Differencessupporting

confidence: 77%

“…These results demonstrate that pupil diameter can be used as a reliable index of the attention deployed toward maintaining information in WM. We have previously demonstrated that this is the case across a number of visual WM tasks (Unsworth & Robison, 2015, 2018b. However, the present set of experiments extends this work in two ways.…”

Section: Discussionsupporting

confidence: 61%

“…Other investigations have shown that pupil diameter dilates in response to tracking multiple objects (Alnaes et al, 2014), that pupil dilation at encoding distinguishes between highand low-strength memories (Papesh et al, 2012), and that pupil dilation at encoding is sensitive to the value of to-beremembered information in a value-directed remembering paradigm (Ariel & Castel, 2014). In our own work, we have demonstrated that the pupil can be used to index the storage of information in WM during a delay in a variety of WM task situations (Unsworth & Robison, 2018b), and that pupillometry can be used to measure individual differences in the allocation of attention to items in WM (Unsworth & Robison, 2015).…”

mentioning

confidence: 65%

“…Thus, the taskevoked response is measured as a change (i.e., dilation) from this baseline. In our first analysis, we ensured that the task-evoked pupil response appeared similar to prior examinations of visual WM using pupillometry (Unsworth & Robison, 2015, 2018b. A repeated-measures analysis of variance (ANOVA) with bin as a within-subjects factor indicated a significant main effect of bin (F(38, 1216) = 29.38, p < 0.01, partial η 2 = 0.48).…”

Section: Pupillometrymentioning

confidence: 96%

“…Our target sample size was 30 participants, which was based on our prior investigations of WM using pupillometry (Unsworth & Robison, 2018b). A sample of 34 participants from the human subjects pool at the University of Oregon completed the study in exchange for partial course credit.…”

Section: Participants and Proceduresmentioning

confidence: 99%

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Pupillometry tracks fluctuations in working memory performance

Robison

Unsworth

2018

Atten Percept Psychophys

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In 3 experiments, we examined fluctuations in working memory (WM) performance and associated changes in pretrial and task-evoked pupil diameter. Additionally, we examined whether particularly poor trials were accompanied by self-reports of off-task attentional states. The results demonstrated that task-evoked pupillary responses can be used to measure momentto-moment fluctuations in the success of WM maintenance during delay intervals. Further, when individuals reported being in an off-task attentional state, their WM performance suffered. Additionally, when probed directly after a particularly poor trial, participants reported being in an off-task attentional state more often than at random intervals throughout the task. So behavioral, subjective, and physiological data converged when people experienced WM failures. Although pretrial pupil diameter did not consistently differentiate between successful and unsuccessful trials, variability in pretrial pupil diameter accounted for a significant portion of variance in WM task performance. This effect persisted after controlling for mean task-evoked pupillary response and variability in task-evoked pupillary responses. Thus, one of the major reasons people varied in the consistency with which they utilized their WM system was variability in arousal. Such variability in arousal is potentially due to variation in the functioning of the locus coeruleus-norepinephrine (LC-NE) neuromodulatory system, and thus may underlie individual differences in WM capacity and attention control.

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Section: Combined Analyses -Individual Differencessupporting

confidence: 77%

Section: Discussionsupporting

confidence: 61%

mentioning

confidence: 65%

Section: Pupillometrymentioning

confidence: 96%

Section: Participants and Proceduresmentioning

confidence: 99%

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Pupillometry tracks fluctuations in working memory performance

Robison

Unsworth

2018

Atten Percept Psychophys

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Pupillometry tracks cognitive load and salience network activity in a working memory functional magnetic resonance imaging task

Fietz

Pöhlchen

Binder

et al. 2021

Human Brain Mapping

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The diameter of the human pupil tracks working memory processing and is associated with activity in the frontoparietal network. At the same time, recent neuroimaging research has linked human pupil fluctuations to activity in the salience network. In this combined functional magnetic resonance imaging (fMRI)/pupillometry study, we recorded the pupil size of healthy human participants while they performed a blockwise organized working memory task (N‐back) inside an MRI scanner in order to monitor the pupil fluctuations associated neural activity during working memory processing. We first confirmed that mean pupil size closely followed working memory load. Combining this with fMRI data, we focused on blood oxygen level dependent (BOLD) correlates of mean pupil size modeled onto the task blocks as a parametric modulation. Interrogating this modulated task regressor, we were able to retrieve the frontoparietal network. Next, to fully exploit the within‐block dynamics, we divided the blocks into 1 s time bins and filled these with corresponding pupil change values (first‐order derivative of pupil size). We found that pupil change within N‐back blocks was positively correlated with BOLD amplitudes in the areas of the salience network (namely bilateral insula, and anterior cingulate cortex). Taken together, fMRI with simultaneous measurement of pupil parameters constitutes a valuable tool to dissect working memory subprocesses related to both working memory load and salience of the presented stimuli.

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Revealing visual working memory operations with pupillometry: Encoding, maintenance, and prioritization

Koevoet,

Strauch,

Van der Stigchel

et al. 2023

WIRES Cognitive Science

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Pupillary dynamics reflect effects of distinct and important operations of visual working memory: encoding, maintenance, and prioritization. Here, we review how pupil size predicts memory performance and how it provides novel insights into the mechanisms of each operation. Visual information must first be encoded into working memory with sufficient precision. The depth of this encoding process couples to arousal‐linked baseline pupil size as well as a pupil constriction response before and after stimulus onset, respectively. Subsequently, the encoded information is maintained over time to ensure it is not lost. Pupil dilation reflects the effortful maintenance of information, wherein storing more items is accompanied by larger dilations. Lastly, the most task‐relevant information is prioritized to guide upcoming behavior, which is reflected in yet another dilatory component. Moreover, activated content in memory can be pupillometrically probed directly by tagging visual information with distinct luminance levels. Through this luminance‐tagging mechanism, pupil light responses reveal whether dark or bright items receive more attention during encoding and prioritization. Together, conceptualizing pupil responses as a sum of distinct components over time reveals insights into operations of visual working memory. From this viewpoint, pupillometry is a promising avenue to study the most vital operations through which visual working memory works.This article is categorized under: Psychology > Attention Psychology > Memory Psychology > Theory and Methods

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Tracking working memory maintenance with pupillometry

Cited by 49 publications

References 82 publications

Pupillometry tracks fluctuations in working memory performance

Pupillometry tracks fluctuations in working memory performance

Pupillometry tracks cognitive load and salience network activity in a working memory functional magnetic resonance imaging task

Revealing visual working memory operations with pupillometry: Encoding, maintenance, and prioritization

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