Nathaniel J. Blanco

Exploratory decision-making as a function of lifelong experience, not cognitive decline

Older adults perform worse than younger adults in some complex decision-making scenarios, which is commonly attributed to age-related declines in striatal and frontostriatal processing. Recently, this popular account has been challenged by work that considered how older adults’ performance may differ as a function of greater knowledge and experience, and by work showing that, in some cases, older adults outperform younger adults in complex decision-making tasks. In light of this controversy, we examined the performance of older and younger adults in an exploratory choice task that is amenable to model-based analyses and ostensibly not reliant on prior knowledge. Exploration is a critical aspect of decision-making poorly understood across the life span. Across 2 experiments, we addressed (a) how older and younger adults differ in exploratory choice and (b) to what extent observed differences reflect processing capacity declines. Model-based analyses suggested that the strategies used by the 2 groups were qualitatively different, resulting in relatively worse performance for older adults in 1 decision-making environment but equal performance in another. Little evidence was found that differences in processing capacity drove performance differences. Rather the results suggested that older adults’ performance might result from applying a strategy that may have been shaped by their wealth of real-word decision-making experience. While this strategy is likely to be effective in the real world, it is ill suited to some decision environments. These results underscore the importance of taking into account effects of experience in aging studies, even for tasks that do not obviously tap past experiences.

Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

HighlightsLaser study of category learning, a fundamental aspect of human cognition.Transcranial infrared laser stimulation was directed at the lateral prefrontal cortex.Prefrontal rule‐based learning was substantially improved by the laser stimulation.Striatal information‐integration learning was not affected by the laser stimulation.Transcranial infrared laser showed potential as a form of cognitive enhancement. Abstract This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non‐invasive form of brain stimulation that shows promise for wide‐ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short‐term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus‐response associations. Participants (n = 118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures—a rule‐based structure optimally learned by the reflective system, or an information‐integration structure optimally learned by the reflexive system. We found that prefrontal rule‐based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298) = 5.117, p = 0.024), while information‐integration learning did not show significant group differences (treatment X block interaction: F(1, 288) = 1.633, p = 0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning.

Does category labeling lead to forgetting

What effect does labeling an object as a member of a familiar category have on memory for that object? Recent studies suggest that recognition memory can be negatively impacted by categorizing objects during encoding. This paper examines the “representational shift hypothesis” which argues that categorizing an object impairs recognition memory by altering the trace of the encoded memory to be more similar to the category prototype. Previous evidence for this idea comes from experiments in which a basic-level category labeling task was compared to a non-category labeling incidental encoding task, usually a preference judgment (e.g., “Do you like this item?”). In two experiments, we examine alternative tasks that attempt to control for processing demands and the degree to which category information is explicitly recruited at the time of study. Contrary to the predictions of the representational shift hypothesis, we find no evidence that memory is selectively impaired by category labeling. Overall, the pattern of results across both studies appears consistent with well-established variables known to influence memory such as encoding specificity and distinctiveness effects.

Framing matters: Effects of framing on older adults’ exploratory decision-making.

We examined framing effects on exploratory decision-making. In Experiment 1 we tested older and younger adults in two decision-making tasks separated by one week, finding that older adults’ decision-making performance was preserved when maximizing gains, but it declined when minimizing losses. Computational modeling indicates that younger adults in both conditions, and older adults in gains maximization, utilized a decreasing threshold strategy (which is optimal), but older adults in losses were better fit by a fixed-probability model of exploration. In Experiment 2 we examined within-subject behavior in older and younger adults in the same exploratory decision-making task, but without a time separation between tasks. We replicated the older adult disadvantage in loss minimization from Experiment 1 and found that the older adult deficit was significantly reduced when the loss-minimization task immediately followed the gains-maximization task. We conclude that older adults’ performance in exploratory decision-making is hindered when framed as loss minimization, but that this deficit is attenuated when older adults can first develop a strategy in a gains-framed task.

To not settle for small losses: evidence for an ecological aspiration level of zero in dynamic decision-making

This work aimed to investigate how one’s aspiration level is set in decision-making involving losses and how people respond when all alternatives appear to be below the aspiration level. We hypothesized that the zero point would serve as an ecological aspiration level where losses cause participants to focus on improvements in payoffs. In two experiments, we investigated these issues by combining behavioral studies and computational modeling. Participants chose from two alternatives on each trial. A decreasing option consistently gave a larger immediate payoff, although it caused future payoffs for both options to decrease. Selecting an increasing option caused payoffs for both options to increase on future trials. We manipulated the incentive structure such that in the losses condition the smallest payoff for the decreasing option was a loss, whereas in the gains condition the smallest payoff for the decreasing option was a gain, while the differences in outcomes for the two options were kept equivalent across conditions. Participants selected the increasing option more often in the losses condition than in the gains condition, regardless of whether the increasing option was objectively optimal (Experiment 1) or suboptimal (Experiment 2). Further, computational modeling results revealed that participants in the losses condition exhibited heightened weight to the frequency of positive versus negative prediction errors, suggesting that they were more attentive to improvements and reductions in outcomes than to expected values. This supports our assertion that losses induce aspiration for larger payoffs. We discuss our results in the context of recent theories of how losses shape behavior