Differential impacts of healthy cognitive aging on directed and random exploration.

Deciding whether to explore unknown opportunities or exploit well-known options is a ubiquitous part of our everyday lives. Extensive work in college students suggests that young people make explore-exploit decisions using a mixture of information seeking and random behavioral variability. Whether, and to what extent, older adults use the same strategies is unknown. To address this question, 51 older adults (ages 65-74) and 32 younger adults (ages 18-25) completed the Horizon Task, a gambling task that quantifies information seeking and behavioral variability as well as how these strategies are controlled for the purposes of exploration. Qualitatively, we found that older adults performed similar to younger adults on this task, increasing both their information seeking and behavioral variability when it was adaptive to explore. Quantitively, however, there were substantial differences between the age groups, with older adults showing less information seeking overall and less reliance on variability as a means to explore. In addition, we found a subset of approximately 26% of older adults whose information seeking was close to zero, avoiding informative options even when they were clearly the better choice. Unsurprisingly, these "information avoiders" performed worse on the task. In contrast, task performance in the remaining "information seeking" older adults was comparable to that of younger adults suggesting that age-related differences in explore-exploit decision making may be adaptive except when they are taken to extremes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A divisive model of evidence accumulation explains uneven weighting of evidence over time.

Divisive normalization has long been used to account for computations in various neural processes and behaviours. The model proposes that inputs into a neural system are divisively normalized by the system's total activity. More recently, dynamical versions of divisive normalization have been shown to account for how neural activity evolves over time in value-based decision making. Despite its ubiquity, divisive normalization has not been studied in decisions that require evidence to be integrated over time. Such decisions are important when the information is not all available at once. A key feature of such decisions is how evidence is weighted over time, known as the integration kernel. Here, we provide a formal expression for the integration kernel in divisive normalization, and show that divisive normalization quantitatively accounts for 133 human participants' perceptual decision making behaviour, performing as well as the state-of-the-art Drift Diffusion Model, the predominant model for perceptual evidence accumulation.

Regulation of evidence accumulation by pupil-linked arousal processes.

Effective decision-making requires integrating evidence over time. For simple perceptual decisions, previous work suggests that humans and animals can integrate evidence over time, but not optimally. This suboptimality could arise from sources including neuronal noise, weighting evidence unequally over time (that is, the 'integration kernel'), previous trial effects and an overall bias. Here, using an auditory evidence accumulation task in humans, we report that people exhibit all four suboptimalities, some of which covary across the population. Pupillometry shows that only noise and the integration kernel are related to the change in pupil response. Moreover, these two different suboptimalities were related to different aspects of the pupil signal, with the individual differences in pupil response associated with individual differences in the integration kernel, while trial-by-trial fluctuations in pupil response were associated with trial-by-trial fluctuations in noise. These results suggest that different suboptimalities relate to distinct pupil-linked processes, possibly related to tonic and phasic norepinephrine activity.