Testing a locus coeruleus-norepinephrine account of working memory, attention control, and fluid intelligence

Abstract

The current set of studies examined the relations among working memory capacity, attention control, fluid intelligence, and pupillary correlates of tonic arousal regulation and phasic responsiveness in a combined sample of over 1,000 participants in two different age ranges (young adults and adolescents). Each study was designed to test predictions made by two recent theories regarding the role of the locus coeruleus-norepinephrine (LC-NE) system in determining individual differences in cognitive ability. The first theory, proposed by Unsworth and Robison (2017a) posits two important individual differences: the moment-to-moment regulation of tonic arousal and the phasic responsiveness of the system to goal-relevant stimuli. The second theory, proposed by Tsukahara and Engle (2021a) argues that people with higher cognitive abilities have greater functional connectivity between the LC-NE system and cortical networks at rest. These two theories are not mutually exclusive, but they make different predictions. Overall, we found no evidence consistent with a resting state theory. However, phasic responsiveness was consistently correlated with working memory capacity, attention control, and fluid intelligence, supporting a prediction made by Unsworth and Robison (2017a). Tonic arousal regulation was not correlated with working memory or fluid intelligence, and only inconsistently correlated with attention control, which offers only partial support for Unsworth and Robison’s (2017a) second prediction. We offer an interpretation of these patterns and directions for future research.

EEG and pupillometric signatures of working memory overload

“…Several studies reported a correlation between pupil dilation and alpha suppression during aversive learning and resting state, suggesting a contribution of the LC‐NE system in alpha suppression (Dahl et al, 2022; Sharon et al, 2021). Individual differences in WM capacity and attention control have been hypothesized to be driven by the differences in NE expression supporting activity in the fronto‐parietal network, which is implicated in cognitive control (Robison et al, 2022; Unsworth & Robison, 2017). Similarly, others identified a link between pupil size and theta activity in cognitive control tasks (Dippel et al, 2017; Lin et al, 2018).…”

EEG and pupillometric signatures of working memory overload

“…Several studies reported a correlation between pupil dilation and alpha suppression during aversive learning and resting state, suggesting a contribution of LC-NE system in alpha suppression (Dahl et al, 2022; Sharon et al, 2021). Individual differences in WM capacity and attention control have been hypothesized to be driven by the differences in NE expression supporting activity in the fronto-parietal network, that is implicated in cognitive control (Robison et al, 2022; Unsworth & Robison, 2017). Similarly, others identified a link between pupil size and theta activity in cognitive control tasks (Dippel et al, 2017; Lin et al, 2018).…”

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

“…While the depth of encoding is indexed by pupil orienting constrictions and baseline pupil size (Galeano‐Keiner et al, 2023; Koevoet, Naber, et al, 2023), the maintenance of material is reflected by pupillary dilations (Beatty, 1982; Kahneman, 1973; Robison & Unsworth, 2019; Strauch, Wang, et al, 2022; Zhou et al, 2022). The prioritization of material is also accompanied by a pupil dilation response (Robison et al, 2023; Unsworth & Robison, 2018), but the direct link to behavior remains to be investigated. Beyond these more general pupil responses, the PLR provides even more finely grained item‐specific insights into VWM operations.…”

“…Beyond the insights that the PLR provides into the internal prioritization process (Hustá et al, 2019; Unsworth & Robison, 2017c; Zokaei et al, 2019), prioritizing material in VWM also evokes an effort/alerting related dilatory pupil response more generally (Figure 1; Robison et al, 2023; Unsworth & Robison, 2018)—likely mediated by phasic LC firing as during pupil dilations during maintenance. We speculate that not only the extent of the prioritization‐evoked PLR is linked to performance (Zokaei et al, 2019), but that this more general dilatory response also predicts subsequent behavior in terms of accuracy, speed and precision.…”

“…Following encoding, the information needs to be maintained, which elicits a pupil dilation (Beatty, 1982; Kahneman, 1973; Robison & Unsworth, 2019). When a specific piece of memorized material is prioritized, an additional pupil dilation can be observed (Robison et al, 2023; Unsworth & Robison, 2018). In sum, different pupillary signal components emerge over time and each of these provides insights into distinct operations of VWM.…”