An examination of the effects of eye-tracking on behavior in psychology experiments.

Eye-tracking is emerging as a tool for researchers to better understand cognition and behavior. However, it is possible that experiment participants adjust their behavior when they know their eyes are being tracked. This potential change would be considered a type of Hawthorne effect, in which participants alter their behavior in response to being watched and could potentially compromise the outcomes and conclusions of experimental studies that use eye tracking. We examined whether eye-tracking produced Hawthorne effects in six commonly used psychological scales and five behavioral tasks. The dependent measures were selected because they are widely used and cited and because they involved measures of sensitive topics, including gambling behavior, racial bias, undesirable personality characteristics, or because they require working memory or executive attention resources, which might be affected by Hawthorne effects. The only task where Hawthorne effects manifested was the mixed gambles task, in which participants accepted or rejected gambles involving a 50/50 chance of gaining or losing different monetary amounts. Participants in the eye-tracking condition accepted fewer gambles that were low in expected value, and they also took longer to respond for these low-value gambles. These results suggest that eye-tracking is not likely to produce Hawthorne effects in most common psychology laboratory tasks, except for those involving risky decisions where the probability of the outcomes from each choice are known.

Effects of categorical and numerical feedback on category learning.

Real-world learning signals often come in the form of a continuous range of rewards or punishments, such as receiving more or less money or other reward. However, in laboratory studies, feedback used to examine how humans learn new categories has almost invariably been categorical in nature (i.e. Correct/Incorrect, or A/Not-A). Whether numerical or categorical feedback leads to better learning is an open question. One possibility is that numerical feedback could give more fine-grained information about a category. Alternatively, categorical feedback is more dichotomous, potentially leading to larger error signals. Here we test how feedback impacts category learning by having participants learn to categorize novel line stimuli from either numerical, categorical, or a combination of both types of feedback. Performance was better for categorical relative to the more variable numerical feedback. However, participants were able to learn to effectively categorize from numerical feedback, and providing larger numerical rewards for easier, more representative stimuli was more successful in promoting learning than providing larger rewards for harder to classify stimuli. Simulations and fits of a connectionist model to participants' performance data suggest that categorical feedback promotes better learning by eliciting larger prediction errors than numerical feedback.

Frequency effects in action versus value learning.

Recent work in reinforcement learning has demonstrated a choice preference for an option that has a lower probability of reward (A) when paired with an alternative option that has a higher probability of reward (C), if A has been experienced more frequently than C (the frequency effect). This finding is critical as it is inconsistent with widespread assumptions that expected value is based on average reward, and instead suggests that value is based on cumulative instances of reward. However, option frequency may also affect instrumental reinforcement of choosing A during training, which may then transfer to choice on AC trials. This study therefore aimed to assess the contribution of action reinforcement and option value to the frequency-effect across 2 experiments. In both experiments we included an additional test phase in which participants were asked to rate the likelihood of reward for each choice option, a response that should be unaffected by action reinforcement. In Experiment 1, participants completed the original choice training phase. In Experiment 2, participants were presented with each option individually, thus removing reinforcement of choice during training. Single cue training reduced the strength of the preference for A compared to choice training, suggesting a contributing role of action reinforcement. However, frequency effects were still evident in both experiments. We found that the pattern of reward likelihood ratings was consistent with the pattern of choice preferences in both experiments, suggesting that action reinforcement may also influence judgements about the likelihood of receiving reward. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Neural regions associated with gain-loss frequency and average reward in older and younger adults.

Research on the biological basis of reinforcement-learning has focused on how brain regions track expected value based on average reward. However, recent work suggests that humans are more attuned to reward frequency. Furthermore, older adults are less likely to use expected values to guide choice than younger adults. This raises the question of whether brain regions assumed to be sensitive to average reward, like the medial and lateral PFC, also track reward frequency, and whether there are age-based differences. Older (60-81 years) and younger (18-30 years) adults performed the Soochow Gambling task, which separates reward frequency from average reward, while undergoing fMRI. Overall, participants preferred options that provided negative net payoffs, but frequent gains. Older adults improved less over time, were more reactive to recent negative outcomes, and showed greater frequency-related activation in several regions, including DLPFC. We also found broader recruitment of prefrontal and parietal regions associated with frequency value and reward prediction errors in older adults, which may indicate compensation. The results suggest greater reliance on average reward for younger adults than older adults.

Hearing hooves, thinking zebras: A review of the inverse base-rate effect.

People often fail to use base-rate information appropriately in decision-making. This is evident in the inverse base-rate effect, a phenomenon in which people tend to predict a rare outcome for a new and ambiguous combination of cues. While the effect was first reported in 1988, it has recently seen a renewed interest from researchers concerned with learning, attention and decision-making. However, some researchers have raised concerns that the effect arises in specific circumstances and is unlikely to provide insight into general learning and decision-making processes. In this review, we critically evaluate the evidence for and against the main explanations that have been proposed to explain the effect, and identify where this evidence is currently weak. We argue that concerns about the effect are not well supported by the data. Instead, the evidence supports the conclusion that the effect is a result of general mechanisms that provides a useful opportunity to understand the processes involved in learning and decision making. We discuss gaps in our knowledge and some promising avenues for future research, including the relevance of the effect to models of attentional change in learning, an area where the phenomenon promises to contribute new insights.

Preliminary effects of prefrontal tDCS on dopamine-mediated behavior and psychophysiology.

The ability to manipulate dopamine in vivo through non-invasive, reversible mechanisms has the potential to impact clinical, translational, and basic research. Recent PET studies have demonstrated increased dopamine release in the striatum after bifrontal transcranial direct current stimulation (tDCS). We sought to extend this work by examining whether bifrontal tDCS could demonstrate an effect on behavioral and physiological correlates of subcortical dopamine activity. We conducted a preliminary between-subjects study (n = 30) with active and sham tDCS and used spontaneous eye blink rate (EBR), facial attractiveness ratings, and greyscales orienting bias as indirect proxies for dopamine functioning. The initial design and analyses were pre-registered (https://osf.io/gmnpc). Stimulation did not significantly affect any of the three measures, though effect sizes were often moderately large and were all in the predicted directions. Additional exploratory analyses suggested that stimulation's effect on EBR might depend on pre-stimulation dopamine levels. Our results suggest that larger samples than those that are standard in tDCS literature should be used to assess the effect of tDCS on dopamine using indirect measures. Further, exploratory results add to a growing body of work demonstrating the importance of accounting for individual differences in tDCS response.

Rest-activity rhythms and white matter microstructure across the lifespan.

STUDY OBJECTIVES: The purpose of this study was to examine how rest-activity (RA) rhythm stability may be associated with white matter microstructure across the lifespan in healthy adults free of significant cardiovascular risk. METHODS: We analyzed multi-shell diffusion tensor images from 103 healthy young and older adults using tract-based spatial statistics (TBSS) to examine relationships between white matter microstructure and RA rhythm stability. RA measures were computed using both cosinor and non-parametric methods derived from 7 days of actigraphy data. Fractional anisotropy (FA) and mean diffusivity (MD) were examined in this analysis. Because prior studies have suggested that the corpus callosum (CC) is sensitive to sleep physiology and RA rhythms, we also conducted a focused region of interest analysis on the CC. RESULTS: Greater rest-activity rhythm stability was associated with greater FA across both young and older adults, primarily in the CC and anterior corona radiata. This effect was not moderated by age group. While RA measures were associated with sleep metrics, RA rhythm measures uniquely accounted for the variance in white matter integrity. CONCLUSIONS: This study strengthens existing evidence for a relationship between brain white matter structure and RA rhythm stability in the absence of health risk factors. While there are differences in RA stability between age groups, the relationship with brain white matter was present across both young and older adults. RA rhythms may be a useful biomarker of brain health across both periods of adult development.

Acute stress enhances tolerance of uncertainty during decision-making.

Acute stress has been shown to influence reward sensitivity, feedback learning, and risk-taking during decision-making, primarily through activation of the hypothalamic pituitary axis (HPA). However, it is unclear how acute stress affects decision-making among choices that vary in their degree of uncertainty. To address this question, we conducted two experiments in which participants repeatedly chose between two options-a high-uncertainty option that offered highly variable rewards but was advantageous in the long-term, and a low-uncertainty option that offered smaller yet more consistent rewards. The Socially Evaluated Cold Pressor Task (SECPT) was utilized to induce acute stress. Participants in Experiment 1 (N = 114) were exposed to either the SECPT or a warm-water control condition and then completed the decision-making under uncertainty task. Compared to the control condition, those exposed to the acute stress manipulation chose the high-uncertainty option that provided highly variable but larger rewards over the option that provided stable, smaller rewards. Experiment 2 (N = 95) incorporated a salivary cortisol measure. Results replicated the behavioral findings in Experiment 1 and demonstrated that the acute stress manipulation increased salivary cortisol. This work suggests that moderate acute stress is associated with tolerance of outcome variability in contexts that depend on learning to maximize rewards.

Blunted Reward Sensitivity and Trait Disinhibition Interact to Predict Substance Use Problems.

Reward deficit models of addiction posit weaknesses in reward sensitivity to be promotive of substance dependence, while the externalizing spectrum model views substance problems as arising in large part from a general disinhibitory liability. The current study sought to integrate these perspectives by testing for separate and interactive associations of disinhibition and reward dysfunction with interview-assessed substance use disorders (SUDs). Community and college adults (N = 199) completed a scale measure of trait disinhibition and performed a gambling-feedback task yielding a neural index of reward sensitivity, the 'Reward Positivity' (RewP). Disinhibition and blunted RewP independently predicted SUDs, and also operated synergistically, such that participants - in particular, men - with high levels of disinhibition together with blunted RewP exhibited especially severe substance problems. Though limited by its cross-sectional design, this work provides new information about the interplay of disinhibition, reward processing, and gender in SUDs and suggests important directions for future research.

Learning reward frequency over reward probability: A tale of two learning rules.

Learning about the expected value of choice alternatives associated with reward is critical for adaptive behavior. Although human choice preferences are affected by the presentation frequency of reward-related alternatives, this may not be captured by some dominant models of value learning, such as the delta rule. In this study, we examined whether reward learning is driven more by learning the probability of reward provided by each option, or how frequently each option has been rewarded, and assess how well models based on average reward (e.g. the delta model) and models based on cumulative reward (e.g. the decay model) can account for choice preferences. In a binary-outcome choice task, participants selected between pairs of options that had reward probabilities of 0.65 (A) versus 0.35 (B) or 0.75 (C) versus 0.25 (D). Crucially, during training there were twice the number of AB trials as CD trials, such that option A was associated with higher cumulative reward, while option C gave higher average reward. Participants then decided between novel combinations of options (e.g., AC). Most participants preferred option A over C, a result predicted by the Decay model, but not the Delta model. We also compared the Delta and Decay models to both more simplified as well as more complex models that assumed additional mechanisms, such as representation of uncertainty. Overall, models that assume learning about cumulative reward provided the best account of the data.

Acute stress improves long-term reward maximization in decision-making under uncertainty.

Acute stress influences reward-seeking tendencies and risky decision-making. However, it is unclear how acute stress influences decision-making in situations in which individuals must learn to either maximize long-term or immediate rewards from experience. Consequently, this study sought to investigate whether acute stress enhances salience of small, immediate or large, delayed rewards on decision-making under uncertainty. The Socially Evaluated Cold Pressor Task (SECPT) was used to induce acute stress. Participants in Experiment 1 (N = 50) were exposed to either the SECPT or a warm-water control condition and then completed a decision-making task in which participants needed to learn to forego immediate rewards in favor of larger delayed rewards. The results demonstrated that acute stress enhanced decisions that maximized long-term, large rewards over immediate, small rewards. Experiment 2 (N = 50) included an assessment of salivary cortisol. Results replicated the behavioral findings in Experiment 1 and demonstrated that the acute stress manipulation increased salivary cortisol, thus providing a potential physiological mechanism for these results. This work suggests that moderate acute stress can improve decision-making under uncertainty that depends on learning to maximize long-term rewards from experience.

Substance use is associated with reduced devaluation sensitivity.

Substance use has been linked to impairments in reward processing and decision-making, yet empirical research on the relationship between substance use and devaluation of reward in humans is limited. We report findings from two studies that tested whether individual differences in substance use behavior predicted reward learning strategies and devaluation sensitivity in a nonclinical sample. Participants in Experiment 1 (N = 66) and Experiment 2 (N = 91) completed subscales of the Externalizing Spectrum Inventory and then performed a two-stage reinforcement learning task that included a devaluation procedure. Spontaneous eye blink rate was used as an indirect proxy for dopamine functioning. In Experiment 1, correlational analysis revealed a negative relationship between substance use and devaluation sensitivity. In Experiment 2, regression modeling revealed that while spontaneous eyeblink rate moderated the relationship between substance use and reward learning strategies, substance use alone was related to devaluation sensitivity. These results suggest that once reward-action associations are established during reinforcement learning, substance use predicted reduced sensitivity to devaluation independently of variation in eyeblink rate. Thus, substance use is not only related to increased habit formation but also to difficulty disengaging from learned habits. Implications for the role of the dopaminergic system in habitual responding in individuals with substance use problems are discussed.

Examining the link between reward and response inhibition in individuals with substance abuse tendencies.

BACKGROUND: Substance use problems are often characterized by dysregulation in reward sensitivity and inhibitory control. In line with this representation, the goal of this investigation was to determine how substance abuse tendencies among university students affect incentivized response inhibition. Additionally, this study examined whether striatal dopamine moderates the impact of substance use on response inhibition performance. METHODS: The sample included ninety-eight university students. Participants completed this prospective experimental study at an on-campus laboratory. All participants completed substance abuse and disinhibition subscales of the Externalizing Spectrum Inventory-Brief Form. Using a within-subjects design, participants then performed the Stop Signal Task under both neutral (unrewarded) and reward conditions, in which correct response cancellations resulted in a monetary reward. Striatal tonic dopamine levels were operationalized using spontaneous eyeblink rate. RESULTS: The outcome measures were Stop Signal Reaction Time (SSRT) performance in the unrewarded and rewarded phases of the task. A hierarchical linear regression analysis, controlling for trait disinhibition, age, gender, and cigarette smoking status, identified an interactive effect of substance use and striatal dopamine levels on incentivized SSRT. Substance abuse tendencies were associated with slower SSRT and thus poorer inhibitory control under reward conditions among individuals with low levels of striatal dopamine (F = 7.613, p = .007). CONCLUSIONS: This work has implications for research examining advanced drug use trajectories. In situations in which rewards are at stake, drug users with low tonic dopamine may be more motivated to seek those rewards at the expense of regulating inhibitory control.

Model-based fMRI reveals dissimilarity processes underlying base rate neglect.

Extensive evidence suggests that people use base rate information inconsistently in decision making. A classic example is the inverse base rate effect (IBRE), whereby participants classify ambiguous stimuli sharing features of both common and rare categories as members of the rare category. Computational models of the IBRE have posited that it arises either from associative similarity-based mechanisms or from dissimilarity-based processes that may depend on higher-level inference. Here we develop a hybrid model, which posits that similarity- and dissimilarity-based evidence both contribute to the IBRE, and test it using functional magnetic resonance imaging data collected from human subjects completing an IBRE task. Consistent with our model, multivoxel pattern analysis reveals that activation patterns on ambiguous test trials contain information consistent with dissimilarity-based processing. Further, trial-by-trial activation in left rostrolateral prefrontal cortex tracks model-based predictions for dissimilarity-based processing, consistent with theories positing a role for higher-level symbolic processing in the IBRE.

A Case of Divergent Predictions Made by Delta and Decay Rule Learning Models.

The Delta and Decay rules are two learning rules used to update expected values in reinforcement learning (RL) models. The delta rule learns average rewards, whereas the decay rule learns cumulative rewards for each option. Participants learned to select between pairs of options that had reward probabilities of .65 (option A) versus .35 (option B) or .75 (option C) versus .25 (option D) on separate trials in a binary-outcome choice task. Crucially, during training there were twice as AB trials as CD trials, therefore participants experienced more cumulative reward from option A even though option C had a higher average reward rate (.75 versus .65). Participants then decided between novel combinations of options (e.g, A versus C). The Decay model predicted more A choices, but the Delta model predicted more C choices, because those respective options had higher cumulative versus average reward values. Results were more in line with the Decay model's predictions. This suggests that people may retrieve memories of cumulative reward to compute expected value instead of learning average rewards for each option.

Gender differences in preference for reward frequency versus reward magnitude in decision-making under uncertainty.

Extensive research has focused on gender differences in intertemporal choices made from description in which participants must choose from multiple options that are specified without ambiguity. However, there has been limited work examining gender differences in intertemporal choices made from experience in which the possible payoffs among choice alternatives are not initially known and can only be gained from experience. Other work suggests that females attend more to reward frequency, whereas males attend more to reward magnitude. However, the tasks used in this research have been complex and did not examine intertemporal decision-making. To specifically test whether females are more sensitive to reward frequency and males are more sensitive to reward magnitude on intertemporal decisions made from experience, we designed a simple choice task in which participants pressed a response button at a time of their own choosing on each of many trials. Faster responses led to smaller, but more frequent rewards, whereas slower responses led to larger, but less frequently given rewards. As predicted, females tended to respond quicker for more certain, smaller rewards than males, supporting our prediction that women attend more to reward frequency whereas men attend more to reward magnitude.

Better late than never (or early): Music training in late childhood is associated with enhanced decision-making.

Decision-making is critical to everyday life. Here we ask: to what extent does music training benefit decision-making? Supported by strong associations between music training and enhanced cross-domain skills, we hypothesize that musicians may show decision-making advantages relative to non-musicians. Prior work has also argued for a "critical period" for cross-domain plasticity such that beginning music training early enhances sensorimotor brain regions that mature early in life. Given that brain regions supporting decision-making begin maturing late in childhood, we hypothesized that an advantage in decision-making may only be present in musicians who began music training later in childhood. To test this hypothesis, young adults who began music training before and after 8 years of age (early-trained musicians, ET; late-trained musicians, LT, respectively) and non-musicians (NM) performed a decision-making task. We found a decision-making advantage in LT relative to ET and NM. To better understand the mechanism of the LT advantage, we conducted computational modeling on participant responses and found that LT were less biased by recent outcomes and incorporated longer strings of outcomes when deciding among the choice options. These results tentatively suggest that music training may confer decision-making enhancements, and carry strong implications for the utility of music training in childhood.

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.

Striatal Dopamine, Externalizing Proneness, and Substance Abuse: Effects on Wanting and Learning during Reward-Based Decision Making.

We examined whether striatal dopamine moderates the impact of externalizing proneness (disinhibition) on reward-based decision-making. Participants completed disinhibition and substance abuse subscales of the brief form Externalizing Spectrum Inventory, and then performed a delay discounting task to assess preference for immediate rewards along with a dynamic decision-making task that assessed long-term reward learning (i.e., inclination to choose larger delayed versus smaller immediate rewards). Striatal tonic dopamine levels were operationalized using spontaneous eyeblink rate. Regression analyses revealed that high disinhibition predicted greater delay discounting among participants with lower levels of striatal dopamine only, while substance abuse was associated with poorer long-term learning among individuals with lower levels of striatal dopamine, but better long-term learning in those with higher levels of striatal dopamine. These results suggest that disinhibition is more strongly associated with the wanting component of reward-based decision-making, whereas substance abuse behavior is associated more with learning of long-term action-reward contingencies.

Dopaminergic Genetic Polymorphisms Predict Rule-based Category Learning.

Dopaminergic genes play an important role in cognitive function. DRD2 and DARPP-32 dopamine receptor gene polymorphisms affect striatal dopamine binding potential, and the Val158Met single-nucleotide polymorphism of the COMT gene moderates dopamine availability in the pFC. Our study assesses the role of these gene polymorphisms on performance in two rule-based category learning tasks. Participants completed unidimensional and conjunctive rule-based tasks. In the unidimensional task, a rule along a single stimulus dimension can be used to distinguish category members. In contrast, a conjunctive rule utilizes a combination of two dimensions to distinguish category members. DRD2 C957T TT homozygotes outperformed C allele carriers on both tasks, and DARPP-32 AA homozygotes outperformed G allele carriers on both tasks. However, we found an interaction between COMT and task type where Met allele carriers outperformed Val homozygotes in the conjunctive rule task, but both groups performed equally well in the unidimensional task. Thus, striatal dopamine binding may play a critical role in both types of rule-based tasks, whereas prefrontal dopamine binding is important for learning more complex conjunctive rule tasks. Modeling results suggest that striatal dopaminergic genes influence selective attention processes whereas cortical genes mediate the ability to update complex rule representations.