Attentional mechanisms of the date/delay effect in intertemporal choice: An eye-tracking study.

Temporal discounting refers to the tendency to discount future rewards as a function of time until receipt of rewards. The discount rate can be reduced by experimentally manipulating time framing, an example being the date/delay effect: Specifically, if time until receipt of the reward is presented as a date (e.g., August 21, 2022) rather than as a delay (e.g., 136 days), temporal discounting is reduced. While this effect has been replicated several times, its underlying cognitive mechanisms are not well understood. Therefore, we used eye tracking to examine the role of attention in the date/delay effect. Participants completed both a delay and date condition of the Monetary Choice Questionnaire, while eye movements were recorded (N = 54). Results revealed a successful replication of the date/delay effect (p < .001, gav = 0.48). Eye tracking showed that participants compared time attributes (relative to reward attributes) more and fixated them longer in the date compared to the delay condition. Moreover, the absolute difference in reward values of choice options was more predictive of choosing the delayed reward in the date compared to the delay condition. Finally, explorative correlations revealed a stronger date/delay effect in participants who paid more attention to time than reward attributes in the delay condition and who used a more integrative search strategy. Our findings suggest that the date manipulation causes participants to weight rewards more strongly in their decision process than in the delay condition, ultimately reducing temporal discounting. Computation of time intervals in the date condition could possibly reflect an adaptation lowering the date/delay effect. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Hypocretin-1 receptor antagonism improves inhibitory control during the Go/No-Go task in highly motivated, impulsive male mice.

RATIONALE: Motivation and inhibitory control are dominantly regulated by the dopaminergic (DA) and noradrenergic (NA) systems, respectively. Hypothalamic hypocretin (orexin) neurons provide afferent inputs to DA and NA nuclei and hypocretin-1 receptors (HcrtR1) are implicated in reward and addiction. However, the role of the HcrtR1 in inhibitory control is not well understood. OBJECTIVES: To determine the effects of HcrtR1 antagonism and motivational state in inhibitory control using the go/no-go task in mice. METHODS: n = 23 male C57Bl/6JArc mice were trained in a go/no-go task. Decision tree dendrogram analysis of training data identified more and less impulsive clusters of animals. A HcrtR1 antagonist (BI001, 12.5 mg/kg, per os) or vehicle were then administered 30 min before go/no-go testing, once daily for 5 days, under high (food-restricted) and low (free-feeding) motivational states in a latin-square crossover design. Compound exposure levels were assessed in a satellite group of animals. RESULTS: HcrtR1 antagonism increased go accuracy and decreased no-go accuracy in free-feeding animals overall, whereas it decreased go accuracy and increased no-go accuracy only in more impulsive, food restricted mice. HcrtR1 antagonism also showed differential effects in premature responding, which was increased in response to the antagonist in free-feeding, less impulsive animals, and decreased in food restricted, more impulsive animals. HcrtR1 receptor occupancy by BI001 was estimated at ~ 66% during the task. CONCLUSIONS: These data indicate that hypocretin signalling plays roles in goal-directed behaviour and inhibitory control in a motivational state-dependant manner. While likely not useful in all settings, HcrtR1 antagonism may be beneficial in improving inhibitory control in impulsive subpopulations.

Association of temporal discounting with transdiagnostic symptom dimensions.

Temporal discounting (TD), the tendency to devalue future rewards as a function of delay until receipt, is aberrant in many mental disorders. Identifying symptom patterns and transdiagnostic dimensions associated with TD could elucidate mechanisms responsible for clinically impaired decision-making and facilitate identifying intervention targets. Here, we tested in a general population sample (N = 731) the extent to which TD was related to different symptom patterns and whether effects of time framing (dates/delay units) and monetary magnitude (large/small) had particularly strong effects in people scoring higher on specific symptom patterns. Analyses revealed that TD was related to symptom patterns loading on anxious-depression and inattention-impulsivity-overactivity dimensions. Moreover, TD was lower in the date than the delay version and with higher magnitudes, especially in people scoring higher on the inattention-impulsivity-overactivity dimension. Overall, this study provides evidence for TD as a transdiagnostic process across affective and impulsivity-related dimensions. Future studies should test framing interventions in clinical populations characterized by impulsivity.Preregistration: This research was preregistered at https://osf.io/fg9sc .

The date/delay effect in intertemporal choice: A combined fMRI and eye-tracking study.

Temporal discounting, the tendency to devalue future rewards as a function of delay until receipt, is influenced by time framing. Specifically, discount rates are shallower when the time at which the reward is received is presented as a date (date condition; e.g., June 8, 2023) rather than in delay units (delay condition; e.g., 30 days), which is commonly referred to as the date/delay effect. However, the cognitive and neural mechanisms of this effect are not well understood. Here, we examined the date/delay effect by analysing combined fMRI and eye-tracking data of N = 31 participants completing a temporal discounting task in both a delay and a date condition. The results confirmed the date/delay effect and revealed that the date condition led to higher fixation durations on time attributes and to higher activity in precuneus/PCC and angular gyrus, that is, areas previously associated with episodic thinking. Additionally, participants made more comparative eye movements in the date compared to the delay condition. A lower date/delay effect was associated with higher prefrontal activity in the date > delay contrast, suggesting that higher control or arithmetic operations may reduce the date/delay effect. Our findings are in line with hypotheses positing that the date condition is associated with differential time estimation and the use of more comparative as opposed to integrative choice strategies. Specifically, higher activity in memory-related brain areas suggests that the date condition leads to higher perceived proximity of delayed rewards, while higher frontal activity (middle/superior frontal gyrus, posterior medial frontal cortex, cingulate) in participants with a lower date/delay effect suggests that the effect is particularly pronounced in participants avoiding complex arithmetic operations in the date condition.

Financial Advisers' and Key Informants' Perspectives on the Australian Industry-Led Moratorium on Genetic Tests in Life Insurance.

INTRODUCTION: Genetic discrimination (GD) in the context of life insurance is a perennial concern in Australia and internationally. To address such concerns in Australia, an industry self-regulated Moratorium on Genetic Tests in Life Insurance was introduced in 2019 to restrict life insurers from using genetic test results in underwriting for policies under certain limits. Financial advisers (FAs) are sometimes engaged by clients to provide financial advice and assist them to apply for life insurance. They are therefore well-placed to comment on GD and the operation of the Moratorium. Despite this, the financial advising sector in Australia has yet to be studied empirically with regards to GD and the Moratorium. This study aims to capture this perspective by reporting on interviews with the financial advising sector. METHODS: Ten semi-structured qualitative interviews were conducted with FAs and key informants and were analysed using thematic analysis. CONCLUSION(S): Participants' level of awareness and understanding of the Moratorium varied. Participants reported mixed views on the Moratorium's effectiveness, how it operates in practice, and perceived industry compliance. Participants also provided reflections on Australia's current approach to regulating GD, with most participants supporting the concept of industry self-regulation but identifying a need for this to be supplemented with external oversight and meaningful recourse mechanisms for consumers. Our results suggest that there is scope to increase FAs' awareness of GD, and that further research, consultation, and policy consideration are required to identify an optimal regulatory response to GD in Australia.

Not so smart? "Smart" drugs increase the level but decrease the quality of cognitive effort.

The efficacy of pharmaceutical cognitive enhancers in everyday complex tasks remains to be established. Using the knapsack optimization problem as a stylized representation of difficulty in tasks encountered in daily life, we discover that methylphenidate, dextroamphetamine, and modafinil cause knapsack value attained in the task to diminish significantly compared to placebo, even if the chance of finding the optimal solution (~50%) is not reduced significantly. Effort (decision time and number of steps taken to find a solution) increases significantly, but productivity (quality of effort) decreases significantly. At the same time, productivity differences across participants decrease, even reverse, to the extent that above-average performers end up below average and vice versa. The latter can be attributed to increased randomness of solution strategies. Our findings suggest that "smart drugs" increase motivation, but a reduction in quality of effort, crucial to solve complex problems, annuls this effect.

Harnessing Computational Complexity Theory to Model Human Decision-making and Cognition.

A central aim of cognitive science is to understand the fundamental mechanisms that enable humans to navigate and make sense of complex environments. In this letter, we argue that computational complexity theory, a foundational framework for evaluating computational resource requirements, holds significant potential in addressing this challenge. As humans possess limited cognitive resources for processing vast amounts of information, understanding how humans perform complex cognitive tasks requires comprehending the underlying factors that drive information processing demands. Computational complexity theory provides a comprehensive theoretical framework to achieve this goal. By adopting this framework, we can gain new insights into how cognitive systems work and develop a more nuanced understanding of the relation between task complexity and human behavior. We provide empirical evidence supporting our argument and identify several open research questions and challenges in applying computational complexity theory to human decision-making and cognitive science at large.

Individuals with problem gambling and obsessive-compulsive disorder learn through distinct reinforcement mechanisms.

Obsessive-compulsive disorder (OCD) and pathological gambling (PG) are accompanied by deficits in behavioural flexibility. In reinforcement learning, this inflexibility can reflect asymmetric learning from outcomes above and below expectations. In alternative frameworks, it reflects perseveration independent of learning. Here, we examine evidence for asymmetric reward-learning in OCD and PG by leveraging model-based functional magnetic resonance imaging (fMRI). Compared with healthy controls (HC), OCD patients exhibited a lower learning rate for worse-than-expected outcomes, which was associated with the attenuated encoding of negative reward prediction errors in the dorsomedial prefrontal cortex and the dorsal striatum. PG patients showed higher and lower learning rates for better- and worse-than-expected outcomes, respectively, accompanied by higher encoding of positive reward prediction errors in the anterior insula than HC. Perseveration did not differ considerably between the patient groups and HC. These findings elucidate the neural computations of reward-learning that are altered in OCD and PG, providing a potential account of behavioural inflexibility in those mental disorders.

Task-independent metrics of computational hardness predict human cognitive performance.

The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of cognitive tasks using a set of task-independent metrics related to the computational resource requirements of individual instances of a task. We then examine the relation between those metrics and human behavior and find that they predict both time spent on a task as well as accuracy in three canonical cognitive tasks. Our findings demonstrate that performance in cognitive tasks can be predicted based on generic metrics of their inherent computational hardness.

Individual Differences in Intertemporal Choice.

Intertemporal choice involves deciding between smaller, sooner and larger, later rewards. People tend to prefer smaller rewards that are available earlier to larger rewards available later, a phenomenon referred to as temporal or delay discounting. Despite its ubiquity in human and non-human animals, temporal discounting is subject to considerable individual differences. Here, we provide a critical narrative review of this literature and make suggestions for future work. We conclude that temporal discounting is associated with key socio-economic and health-related variables. Regarding personality, large-scale studies have found steeper temporal discounting to be associated with higher levels of self-reported impulsivity and extraversion; however, effect sizes are small. Temporal discounting correlates negatively with future-oriented cognitive styles and inhibitory control, again with small effect sizes. There are consistent associations between steeper temporal discounting and lower intelligence, with effect sizes exceeding those of personality or cognitive variables, although socio-demographic moderator variables may play a role. Neuroimaging evidence of brain structural and functional correlates is not yet consistent, neither with regard to areas nor directions of effects. Finally, following early candidate gene studies, recent Genome Wide Association Study (GWAS) approaches have revealed the molecular genetic architecture of temporal discounting to be more complex than initially thought. Overall, the study of individual differences in temporal discounting is a maturing field that has produced some replicable findings. Effect sizes are small-to-medium, necessitating future hypothesis-driven work that prioritizes large samples with adequate power calculations. More research is also needed regarding the neural origins of individual differences in temporal discounting as well as the mediating neural mechanisms of associations of temporal discounting with personality and cognitive variables.

Reward motivation and cognitive flexibility in tau null-mutation mice.

The reduction of tau or hyperphosphorylated tau (p-tau) has been proposed as a therapeutic strategy for Alzheimer's disease (AD) and frontotemporal dementia (FTD). Cognitive decline and sleep-wake dysregulation seen in AD and FTD patients are mimicked in transgenic and null-mutation mouse models of tauopathy. Alterations in the reward system are additional symptoms of AD and FTD. However, the role of tau in reward processes is not well understood. The present study aimed to examine reward and reward-motivated cognitive processes in male and female tau knockout (tau-/-) and wild-type mice using progressive ratio and reversal learning tasks. Tau-/- mice were heavier, ate more in the home cage, and reached criterion in operant lever training faster than wild-type mice. Tau-/- mice had a higher breakpoint in progressive ratio but were unimpaired in reversal learning or reward sensitivity. These data indicate that tau loss of function alters reward processing. This may help to explain aberrant reward-related behaviors in tauopathy patients and highlights a potentially important area for consideration in the development of anti-tau therapies.

Effective brain connectivity at rest is associated with choice-induced preference formation.

Preferences can change as a consequence of making hard decisions whereby the value of chosen options increases and the value of rejected options decreases. Such choice-induced preference changes have been associated with brain areas detecting choice conflict (anterior cingulate cortex, ACC), updating stimulus value (dorsolateral prefrontal cortex, dlPFC) and supporting memory of stimulus value (hippocampus and ventromedial prefrontal cortex, vmPFC). Here we investigated whether resting-state neuronal activity within these regions is associated with the magnitude of individuals' preference updates. We fitted a dynamic causal model (DCM) to resting-state neuronal activity in the spectral domain (spDCM) and estimated the causal connectivity among core regions involved in preference formation following hard choices. The extent of individuals' choice-induced preference changes were found to be associated with a diminished resting-state excitation between the left dlPFC and the vmPFC, whereas preference consistency was related to a higher resting-state excitation from the ACC to the left hippocampus and vmPFC. Our results point to a model of preference formation during which the dynamic network configurations between left dlPFC, ACC, vmPFC and left hippocampus at rest are linked to preference change or stability.

Monetary feedback modulates performance and electrophysiological indices of belief updating in reward learning.

Belief updating entails the incorporation of new information about the environment into internal models of the world. Bayesian inference is the statistically optimal strategy for performing belief updating in the presence of uncertainty. An important open question is whether the use of cognitive strategies that implement Bayesian inference is dependent upon motivational state and, if so, how this is reflected in electrophysiological signatures of belief updating in the brain. Here, we recorded the EEG of participants performing a simple reward learning task with both monetary and nonmonetary instructive feedback conditions. Our aim was to distinguish the influence of the rewarding properties of feedback on belief updating from the information content of the feedback itself. A Bayesian updating model allowed us to quantify different aspects of belief updating across trials, including the size of belief updates and the uncertainty of beliefs. Faster learning rates were observed in the monetary feedback condition compared to the instructive feedback condition, while belief updates were generally larger, and belief uncertainty smaller, with monetary compared to instructive feedback. Larger amplitudes in the monetary feedback condition were found for three ERP components: the P3a, the feedback-related negativity, and the late positive potential. These findings suggest that motivational state influences inference strategies in reward learning, and this is reflected in the electrophysiological correlates of belief updating.

Uncertainty and computational complexity.

Modern theories of decision-making typically model uncertainty about decision options using the tools of probability theory. This is exemplified by the Savage framework, the most popular framework in decision-making research. There, decision-makers are assumed to choose from among available decision options as if they maximized subjective expected utility, which is given by the utilities of outcomes in different states weighted with subjective beliefs about the occurrence of those states. Beliefs are captured by probabilities and new information is incorporated using Bayes' Law. The primary concern of the Savage framework is to ensure that decision-makers' choices are rational. Here, we use concepts from computational complexity theory to expose two major weaknesses of the framework. Firstly, we argue that in most situations, subjective utility maximization is computationally intractable, which means that the Savage axioms are implausible. We discuss empirical evidence supporting this claim. Secondly, we argue that there exist many decision situations in which the nature of uncertainty is such that (random) sampling in combination with Bayes' Law is an ineffective strategy to reduce uncertainty. We discuss several implications of these weaknesses from both an empirical and a normative perspective. This article is part of the theme issue 'Risk taking and impulsive behaviour: fundamental discoveries, theoretical perspectives and clinical implications'.

Defining Compulsive Behavior.

Compulsive tendencies are a central feature of problematic human behavior and thereby are of great interest to the scientific and clinical community. However, no consensus exists about the precise meaning of 'compulsivity,' creating confusion in the field and hampering comparison across psychiatric disorders. A vague conceptualization makes compulsivity a moving target encompassing a fluctuating variety of behaviors, which is unlikely to improve the new dimension-based psychiatric or psychopathology approach. This article aims to help progress the definition of what constitutes compulsive behavior, cross-diagnostically, by analyzing different definitions in the psychiatric literature. We searched PubMed for articles in human psychiatric research with 'compulsive behavior' or 'compulsivity' in the title that focused on the broader concept of compulsivity-returning 28 articles with nine original definitions. Within the definitions, we separated three types of descriptive elements: phenomenological, observational and explanatory. The elements most applicable, cross-diagnostically, resulted in this definition: Compulsive behavior consists of repetitive acts that are characterized by the feeling that one 'has to' perform them while one is aware that these acts are not in line with one's overall goal. Having a more unified definition for compulsive behavior will make its meaning precise and explicit, and therefore more transferable and testable across clinical and non-clinical populations.

Separating Probability and Reversal Learning in a Novel Probabilistic Reversal Learning Task for Mice.

The exploration/exploitation tradeoff - pursuing a known reward vs. sampling from lesser known options in the hope of finding a better payoff - is a fundamental aspect of learning and decision making. In humans, this has been studied using multi-armed bandit tasks. The same processes have also been studied using simplified probabilistic reversal learning (PRL) tasks with binary choices. Our investigations suggest that protocols previously used to explore PRL in mice may prove beyond their cognitive capacities, with animals performing at a no-better-than-chance level. We sought a novel probabilistic learning task to improve behavioral responding in mice, whilst allowing the investigation of the exploration/exploitation tradeoff in decision making. To achieve this, we developed a two-lever operant chamber task with levers corresponding to different probabilities (high/low) of receiving a saccharin reward, reversing the reward contingencies associated with levers once animals reached a threshold of 80% responding at the high rewarding lever. We found that, unlike in existing PRL tasks, mice are able to learn and behave near optimally with 80% high/20% low reward probabilities. Altering the reward contingencies towards equality showed that some mice displayed preference for the high rewarding lever with probabilities as close as 60% high/40% low. Additionally, we show that animal choice behavior can be effectively modelled using reinforcement learning (RL) models incorporating learning rates for positive and negative prediction error, a perseveration parameter, and a noise parameter. This new decision task, coupled with RL analyses, advances access to investigate the neuroscience of the exploration/exploitation tradeoff in decision making.

Hard Decisions Shape the Neural Coding of Preferences.

Hard decisions between equally valued alternatives can result in preference changes, meaning that subsequent valuations for chosen items increase and decrease for rejected items. Previous research suggests that this phenomenon is a consequence of cognitive dissonance reduction after the decision, induced by the mismatch between initial preferences and decision outcomes. In contrast, this functional magnetic resonance imaging and eye-tracking study with male and female human participants found that preferences are already updated online during the process of decision-making. Preference changes were predicted from activity in left dorsolateral prefrontal cortex and precuneus while making hard decisions. Fixation durations during this phase predicted both choice outcomes and subsequent preference changes. These preference adjustments became behaviorally relevant only for choices that were remembered and were in turn associated with hippocampus activity. Our results suggest that preferences evolve dynamically as decisions arise, potentially as a mechanism to prevent stalemate situations in underdetermined decision scenarios.SIGNIFICANCE STATEMENT Most theories of decision-making assume that we always choose the best option available, based on a set of stable preferences. However, what happens for hard decisions when the available options are preferred equally? We show that in such stalemate situations, decision-makers adjust their preferences dynamically during the process of decision-making, and these preference adjustments are predicted by a left prefrontal-parietal network. We also show that eye movements during decision-making are predictive of the magnitude of the upcoming value change. Our results suggest that preferences are dynamic, adjusted every time a hard decision is made, prompting a re-evaluation of existing frameworks of decision-making.

Health warnings promote healthier dietary decision making: Effects of positive versus negative message framing and graphic versus text-based warnings.

Food product health warnings have been proposed as a potential obesity prevention strategy. This study examined the effects of text-only and text-and-graphic, negatively and positively framed health warnings on dietary choice behavior. In a 2 × 5 mixed experimental design, 96 participants completed a dietary self-control task. After providing health and taste ratings of snack foods, participants completed a baseline measure of dietary self-control, operationalized as participants' frequency of choosing healthy but not tasty items and rejecting unhealthy yet tasty items to consume at the end of the experiment. Participants were then randomly assigned to one of five health warning groups and presented with 10 health warnings of a given form: text-based, negative framing; graphic, negative framing; text, positive framing; graphic, positive framing; or a no warning control. Participants then completed a second dietary decision making session to determine whether health warnings influenced dietary self-control. Linear mixed effects modeling revealed a significant interaction between health warning group and decision stage (pre- and post-health warning presentation) on dietary self-control. Negatively framed graphic health warnings promoted greater dietary self-control than other health warnings. Negatively framed text health warnings and positively framed graphic health warnings promoted greater dietary self-control than positively framed text health warnings and control images, which did not increase dietary self-control. Overall, HWs primed healthier dietary decision making behavior, with negatively framed graphic HWs being most effective. Health warnings have potential to become an important element of obesity prevention.

The neural encoding of information prediction errors during non-instrumental information seeking.

In a dynamic world, accurate beliefs about the environment are vital for survival, and individuals should therefore regularly seek out new information with which to update their beliefs. This aspect of behaviour is not well captured by standard theories of decision making, and the neural mechanisms of information seeking remain unclear. One recent theory posits that valuation of information results from representation of informative stimuli within canonical neural reward-processing circuits, even if that information lacks instrumental use. We investigated this question by recording EEG from twenty-three human participants performing a non-instrumental information-seeking task. In this task, participants could pay a monetary cost to receive advance information about the likelihood of receiving reward in a lottery at the end of each trial. Behavioural results showed that participants were willing to incur considerable monetary costs to acquire early but non-instrumental information. Analysis of the event-related potential elicited by informative cues revealed that the feedback-related negativity independently encoded both an information prediction error and a reward prediction error. These findings are consistent with the hypothesis that information seeking results from processing of information within neural reward circuits, and suggests that information may represent a distinct dimension of valuation in decision making under uncertainty.

The anticipation and outcome phases of reward and loss processing: A neuroimaging meta-analysis of the monetary incentive delay task.

The processing of rewards and losses are crucial to everyday functioning. Considerable interest has been attached to investigating the anticipation and outcome phases of reward and loss processing, but results to date have been inconsistent. It is unclear if anticipation and outcome of a reward or loss recruit similar or distinct brain regions. In particular, while the striatum has widely been found to be active when anticipating a reward, whether it activates in response to the anticipation of losses as well remains ambiguous. Furthermore, concerning the orbitofrontal/ventromedial prefrontal regions, activation is often observed during reward receipt. However, it is unclear if this area is active during reward anticipation as well. We ran an Activation Likelihood Estimation meta-analysis of 50 fMRI studies, which used the Monetary Incentive Delay Task (MIDT), to identify which brain regions are implicated in the anticipation of rewards, anticipation of losses, and the receipt of reward. Anticipating rewards and losses recruits overlapping areas including the striatum, insula, amygdala and thalamus, suggesting that a generalised neural system initiates motivational processes independent of valence. The orbitofrontal/ventromedial prefrontal regions were recruited only during the reward outcome, likely representing the value of the reward received. Our findings help to clarify the neural substrates of the different phases of reward and loss processing, and advance neurobiological models of these processes.