A model comparison approach reveals individual variation in the scope and control of attention

Abstract

The maintenance capacity of working memory is known to be severely limited in scope. However, the reason this capacity varies across individuals remains unknown because it has proven difficult to estimate the maximum capacity of an individual's "scope of attention" (SoA) separate from their ability to achieve this maximum capacity due to temporary lapses in "attention control" (AC). The present study accomplished this separation by using a maximum likelihood framework to extract latent constructs representing SoA and AC from a whole-report version of the visual-array task. The results of two experiments (N = 145 and N = 189) showed that model fit was significantly greater when the model allowed both AC and SoA to vary across individuals relative to a model in which only AC was allowed to vary (and SoA was fixed). More importantly, the individual estimates of SoA and AC derived from this variable model suggested that (1) the observed range of SoA was found to be small across individuals, with 91% able to maintain a maximum of 3 or 4 items; (2) the consistency with which AC could be deployed was only weakly correlated with the magnitude of SoA; and (3) AC and SoA were both found to be significant predictors of fluid intelligence. Altogether, the present study clarified the nature of maintenance capacity and suggested that SoA and AC both need to be included in a mechanistic account of complex cognition.

Processing speed and executive attention as causes of intelligence.

“…10 Accordingly, both sampling theory and mutualism take a formative rather than a reflective view of g (see Borsboom et al, 2004). 22 control aspects (Hakim et al, 2020;Schor et al, 2020) and some have suggested differentiating attentional consistency and intensity (Unsworth & Miller, 2021). It is conceivable that different tasks may place a larger emphasis on one facet than the other, perhaps consistent with sampling theory.…”

Object-based encoding constrains storage in visual working memory.

“…To calculate the negative log-likelihood, we generated probability distributions at the specific combinations of parameter values via simulation (i.e., synthetic probability distributions). We simulated the number of objects successfully encoded based on a beta-binomial distribution previously demonstrated to explain performance on a WM whole-report task (see partial drop model in Hakim et al, 2020 NGIAM, LOETSCHER, AND AWH 4 and also in Schor et al, 2020Schor et al, , 2023. The beta-binomial distribution estimates the probability of successfully encoding an item from 0 to an individual's maximum capacity, K max .…”

“…Here, we examined this issue by using a whole-report procedure in which recall for all features of every to-be-remembered item was tested during each trial (Adam et al, 2015(Adam et al, , 2017Hakim et al, 2020;Schor et al, 2020). The key virtue of this approach is that it provides a richer picture of the distribution of successfully stored features across the six items in the memory array.…”

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

“…Occasionally, people experience lapses of attention, such as distraction by external or internal information (e.g., mind-wandering). Like most human traits, the capacity of working memory and the ability to control attention are normally distributed in the population (Schor et al, 2020 ). Both working memory capacity and attention control abilities range from weak to strong even in healthy young adults.…”