Heuristics in risky decision-making relate to preferential representation of information.

When making choices, individuals differ from one another, as well as from normativity, in how they weigh different types of information. One explanation for this relates to idiosyncratic preferences in what information individuals represent when evaluating choice options. Here, we test this explanation with a simple risky-decision making task, combined with magnetoencephalography (MEG). We examine the relationship between individual differences in behavioral markers of information weighting and neural representation of stimuli pertinent to incorporating that information. We find that the extent to which individuals (N = 19) behaviorally weight probability versus reward information is related to how preferentially they neurally represent stimuli most informative for making probability and reward comparisons. These results are further validated in an additional behavioral experiment (N = 88) that measures stimulus representation as the latency of perceptual detection following priming. Overall, the results suggest that differences in the information individuals consider during choice relate to their risk-taking tendencies.

The active time model of concurrent choice.

The following paper describes a steady-state model of concurrent choice, termed the active time model (ATM). ATM is derived from maximization principles and is characterized by a semi-Markov process. The model proposes that the controlling stimulus in concurrent variable-interval (VI) VI schedules of reinforcement is the time interval since the most recent response, termed here "the active interresponse time" or simply "active time." In the model after a response is generated, it is categorized by a function that relates active times to switch/stay probabilities. In the paper the output of ATM is compared with predictions made by three other models of operant conditioning: melioration, a version of scalar expectancy theory (SET), and momentary maximization. Data sets considered include preferences in multiple-concurrent VI VI schedules, molecular choice patterns, correlations between switching and perseveration, and molar choice proportions. It is shown that ATM can account for all of these data sets, while the other models produce more limited fits. However, rather than argue that ATM is the singular model for concurrent VI VI choice, a consideration of its concept space leads to the conclusion that operant choice is multiply-determined, and that an adaptive viewpoint-one that considers experimental procedures both as selecting mechanisms for animal choice as well as tests of the controlling variables of that choice-is warranted.

Loss, gain and choice difficulty in gambling patients: Neural and behavioural processes.

Impaired decision-making is often displayed by individuals suffering from gambling disorder (GD). Since there are a variety of different phenomena influencing decision-making, we focused in this study on the effects of GD on neural and behavioural processes related to loss aversion and choice difficulty. Behavioural responses as well as brain images of 23 patients with GD and 20 controls were recorded while they completed a mixed gambles task, where they had to decide to either accept or reject gambles with different amounts of potential gain and loss. We found no behavioural loss aversion in either group and no group differences regarding loss and gain-related choice behaviour, but there was a weaker relation between choice difficulty and decision time in patients with GD. Similarly, we observed no group differences in processing of losses or gains, but choice difficulty was weaker associated with brain activity in the right anterior insula and anterior cingulate cortex in patients with GD. Our results showed for the first time the effects of GD on neural processes related to choice difficulty. In addition, our findings on choice difficulty give new insights on the psychopathology of GD and on neural processes related to impaired decision-making in GD.

Learning to Choose: Behavioral Dynamics Underlying the Initial Acquisition of Decision-Making.

Current theories of decision-making propose that decisions arise through competition between choice options. Computational models of the decision process estimate how quickly information about choice options is integrated and how much information is needed to trigger a choice. Experiments using this approach typically report data from well-trained participants. As such, we do not know how the decision process evolves as a decision-making task is learned for the first time. To address this gap, we used a behavioral design separating learning the value of choice options from learning to make choices. We trained male rats to respond to single visual stimuli with different reward values. Then, we trained them to make choices between pairs of stimuli. Initially, the rats responded more slowly when presented with choices. However, as they gained experience in making choices, this slowing reduced. Response slowing on choice trials persisted throughout the testing period. We found that it was specifically associated with increased exponential variability when the rats chose the higher value stimulus. Additionally, our analysis using drift diffusion modeling revealed that the rats required less information to make choices over time. These reductions in the decision threshold occurred after just a single session of choice learning. These findings provide new insights into the learning process of decision-making tasks. They suggest that the value of choice options and the ability to make choices are learned separately and that experience plays a crucial role in improving decision-making performance.

Differential representation of sensory information and behavioral choice across layers of the mouse auditory cortex.

The activity of neurons in sensory areas sometimes covaries with upcoming choices in decision-making tasks. However, the prevalence, causal origin, and functional role of choice-related activity remain controversial. Understanding the circuit-logic of decision signals in sensory areas will require understanding their laminar specificity, but simultaneous recordings of neural activity across the cortical layers in forced-choice discrimination tasks have not yet been performed. Here, we describe neural activity from such recordings in the auditory cortex of mice during a frequency discrimination task with delayed report, which, as we show, requires the auditory cortex. Stimulus-related information was widely distributed across layers but disappeared very quickly after stimulus offset. Choice selectivity emerged toward the end of the delay period-suggesting a top-down origin-but only in the deep layers. Early stimulus-selective and late choice-selective deep neural ensembles were correlated, suggesting that the choice-selective signal fed back to the auditory cortex is not just action specific but develops as a consequence of the sensory-motor contingency imposed by the task.

Graded decisions in the human brain.

Decision-makers objectively commit to a definitive choice, yet at the subjective level, human decisions appear to be associated with a degree of uncertainty. Whether decisions are definitive (i.e., concluding in all-or-none choices), or whether the underlying representations are graded, remains unclear. To answer this question, we recorded intracranial neural signals directly from the brain while human subjects made perceptual decisions. The recordings revealed that broadband gamma activity reflecting each individual's decision-making process, ramped up gradually while being graded by the accumulated decision evidence. Crucially, this grading effect persisted throughout the decision process without ever reaching a definite bound at the time of choice. This effect was most prominent in the parietal cortex, a brain region traditionally implicated in decision-making. These results provide neural evidence for a graded decision process in humans and an analog framework for flexible choice behavior.

Differences in Discounting Behavior and Brain Responses for Food and Money Reward.

Most neuroeconomic research seeks to understand how value influences decision-making. The influence of reward type is less well understood. We used functional magnetic resonance imaging (fMRI) to investigate delay discounting of primary (i.e., food) and secondary rewards (i.e., money) in 28 healthy, normal-weighted participants (mean age = 26.77; 18 females). To decipher differences in discounting behavior between reward types, we compared how well-different option-based statistical models (exponential, hyperbolic discounting) and attribute-wise heuristic choice models (intertemporal choice heuristic, dual reasoning and implicit framework theory, trade-off model) captured the reward-specific discounting behavior. Contrary to our hypothesis of different strategies for different rewards, we observed comparable discounting behavior for money and food (i.e., exponential discounting). Higher k values for food discounting suggest that individuals decide more impulsive if confronted with food. The fMRI revealed that money discounting was associated with enhanced activity in the right dorsolateral prefrontal cortex, involved in executive control; the right dorsal striatum, associated with reward processing; and the left hippocampus, involved in memory encoding/retrieval. Food discounting, instead, was associated with higher activity in the left temporoparietal junction suggesting social reinforcement of food decisions. Although our findings do not confirm our hypothesis of different discounting strategies for different reward types, they are in line with the notion that reward types have a significant influence on impulsivity with primary rewards leading to more impulsive choices.

Autoshaped impulsivity: Some explorations with a neural network model.

This study evaluated the effect of delay and magnitude of reinforcement in Pavlovian contingencies, extending the understanding of the phenomenon of autoshaped impulsivity as described in Alcalá's thesis (2017) and Burgos and García-Leal (2015). The effects of adding a trace interval were analyzed on the maintained responses of impulsive choice, seen as the preference of a small and immediate reinforcer over a larger and delayed one, and the role of the contextual unit, as well as the inhibitory units according to the Diffuse Discrepancy Model. In the Simulation, the model with inhibitory units was used, trained in two signals with different delays and reinforcement magnitudes, and subsequently presented concurrently in choice tasks without reinforcement nor learning, using an ABA within-subject design. In general, the DD model successfully simulated the phenomenon of autoshaped impulsivity, consistent with studies from Alcalá's thesis (2017), Burgos and García-Leal (2015), and Picker and Poling (1982). It also predicted the elimination of this effect (autoshaped impulsivity) after introducing a trace interval. The observed results and their implications are discussed, as well as possible future studies with animals and humans.

Win-win or lose-lose: Children prefer the form of equality.

In middle childhood, children's sense of fairness further develops, they are willing to pay a cost to maintain equality. Win-win and lose-lose are two forms of equality. Win-win equality refers to both parties maximizing benefits, while lose-lose equality means both parties incurring the maximum loss. Win-win equality allows third party upholding fairness to gain more reputational benefits without the violator being punished, embodying the principle of "benefiting oneself without harming others". On the other hand, lose-lose equality is a more deterrent form of fairness with the violator getting punished, and the third-party might experience a situation of "effort without appreciation." However, the specific form of equality which school-aged children prefer still requires further exploration. Therefore, adopting the dictator game paradigm of third-party punishment, we design two experiments to investigate the fairness preference of first to fourth-grade children when acting as a third party and to clarify patterns of age-related changes. Study 1 (N = 111) explored children's preferred form of fairness under advantageous inequity conditions. Study 2 (N = 122) further examined children's fairness preferences in disadvantageous inequity situations. The findings suggest that when confronted with inequitable distributions, whether rooted in disadvantageous or advantageous inequity, children display a notable tendency to utilize third-party punishment to achieve an equal allocation. Meanwhile, this tendency strengthens as they progress in grade levels. Notably, children consistently manifest a preference for win-win equality, highlighting their inclination towards mutually beneficial outcomes.

Attribute latencies causally shape intertemporal decisions.

Intertemporal choices - decisions that play out over time - pervade our life. Thus, how people make intertemporal choices is a fundamental question. Here, we investigate the role of attribute latency (the time between when people start to process different attributes) in shaping intertemporal preferences using five experiments with choices between smaller-sooner and larger-later rewards. In the first experiment, we identify attribute latencies using mouse-trajectories and find that they predict individual differences in choices, response times, and changes across time constraints. In the other four experiments we test the causal link from attribute latencies to choice, staggering the display of the attributes. This changes attribute latencies and intertemporal preferences. Displaying the amount information first makes people more patient, while displaying time information first does the opposite. These findings highlight the importance of intra-choice dynamics in shaping intertemporal choices and suggest that manipulating attribute latency may be a useful technique for nudging.

The neural representation of metacognition in preferential decision-making.

Humans regularly assess the quality of their judgements, which helps them adjust their behaviours. Metacognition is the ability to accurately evaluate one's own judgements, and it is assessed by comparing objective task performance with subjective confidence report in perceptual decisions. However, for preferential decisions, assessing metacognition in preference-based decisions is difficult because it depends on subjective goals rather than the objective criterion. Here, we develop a new index that integrates choice, reaction time, and confidence report to quantify trial-by-trial metacognitive sensitivity in preference judgements. We found that the dorsomedial prefrontal cortex (dmPFC) and the right anterior insular were more activated when participants made bad metacognitive evaluations. Our study suggests a crucial role of the dmPFC-insula network in representing online metacognitive sensitivity in preferential decisions.

Optogenetic Inhibition of Rat Anterior Cingulate Cortex Impairs the Ability to Initiate and Stay on Task.

Our prior research has identified neural correlates of cognitive control in the anterior cingulate cortex (ACC), leading us to hypothesize that the ACC is necessary for increasing attention as rats flexibly learn new contingencies during a complex reward-guided decision-making task. Here, we tested this hypothesis by using optogenetics to transiently inhibit the ACC, while rats of either sex performed the same two-choice task. ACC inhibition had a profound impact on behavior that extended beyond deficits in attention during learning when expected outcomes were uncertain. We found that ACC inactivation slowed and reduced the number of trials rats initiated and impaired both their accuracy and their ability to complete sessions. Furthermore, drift-diffusion model analysis suggested that free-choice performance and evidence accumulation (i.e., reduced drift rates) were degraded during initial learning-leading to weaker associations that were more easily overridden in later trial blocks (i.e., stronger bias). Together, these results suggest that in addition to attention-related functions, the ACC contributes to the ability to initiate trials and generally stay on task.

Is impulsivity related to attentional bias in cigarette smokers? An exploration across levels of nicotine dependency and deprivation.

Research has largely focused on how attentional bias to smoking-related cues and impulsivity independently influence the development and maintenance of cigarette smoking, with limited exploration of the relationship between these mechanisms. The current experiments systematically assessed relationships between multiple dimensions of impulsivity and attentional bias, at different stages of attention, in smokers varying in nicotine dependency and deprivation. Nonsmokers (NS; n  = 26), light-satiated smokers (LS; n  = 25), heavy-satiated smokers (HS; n  = 23) and heavy 12-hour nicotine-deprived smokers (HD; n  = 30) completed the Barratt Impulsivity Scale, delayed discounting task, stop-signal task, information sampling task and a visual dot-probe assessing initial orientation (200 ms) and sustained attention (2000 ms) toward smoking-related cues. Sustained attention to smoking-related cues was present in both HS and LS, while initial orientation bias was only evident in HS. HS and LS also had greater levels of trait motor and nonplanning impulsivity and heightened impulsive choice on the delay discounting task compared with NS, while heightened trait attentional impulsivity was only found in HS. In contrast, in HD, nicotine withdrawal was associated with no attentional bias but heightened reflection impulsivity, poorer inhibitory control and significantly lower levels of impulsive choice relative to satiated smokers. Trait and behavioral impulsivity were not related to the extent of attentional bias to smoking-related cues at any stage of attention, level of nicotine dependency or state of deprivation. Findings have both clinical and theoretical implications, highlighting the unique and independent roles impulsivity and attentional bias may play at different stages of the nicotine addiction cycle.

Healthy adults favor stable left/right hand choices over performance at an unconstrained reach-to-grasp task.

Reach-to-grasp actions are fundamental to the daily activities of human life, but few methods exist to assess individuals' reaching and grasping actions in unconstrained environments. The Block Building Task (BBT) provides an opportunity to directly observe and quantify these actions, including left/right hand choices. Here we sought to investigate the motor and non-motor causes of left/right hand choices, and optimize the design of the BBT, by manipulating motor and non-motor difficulty in the BBT's unconstrained reach-to-grasp task. We hypothesized that greater motor and non-motor (e.g. cognitive/perceptual) difficulty would drive increased usage of the dominant hand. To test this hypothesis, we modulated block size (large vs. small) to influence motor difficulty, and model complexity (10 vs. 5 blocks per model) to influence non-motor difficulty, in healthy adults (n = 57). Our data revealed that increased motor and non-motor difficulty led to lower task performance (slower task speed), but participants only increased use of their dominant hand only under the most difficult combination of conditions: in other words, participants allowed their performance to degrade before changing hand choices, even though participants were instructed only to optimize performance. These results demonstrate that hand choices during reach-to grasp actions are more stable than motor performance in healthy right-handed adults, but tasks with multifaceted difficulties can drive individuals to rely more on their dominant hand.

Performance errors during rodent learning reflect a dynamic choice strategy.

Humans, even as infants, use cognitive strategies, such as exploration and hypothesis testing, to learn about causal interactions in the environment. In animal learning studies, however, it is challenging to disentangle higher-order behavioral strategies from errors arising from imperfect task knowledge or inherent biases. Here, we trained head-fixed mice on a wheel-based auditory two-choice task and exploited the intra- and inter-animal variability to understand the drivers of errors during learning. During learning, performance errors are dominated by a choice bias, which, despite appearing maladaptive, reflects a dynamic strategy. Early in learning, mice develop an internal model of the task contingencies such that violating their expectation of reward on correct trials (by using short blocks of non-rewarded "probe" trials) leads to an abrupt shift in strategy. During the probe block, mice behave more accurately with less bias, thereby using their learned stimulus-action knowledge to test whether the outcome contingencies have changed. Despite having this knowledge, mice continued to exhibit a strong choice bias during reinforced trials. This choice bias operates on a timescale of tens to hundreds of trials with a dynamic structure, shifting between left, right, and unbiased epochs. Biased epochs also coincided with faster motor kinematics. Although bias decreased across learning, expert mice continued to exhibit short bouts of biased choices interspersed with longer bouts of unbiased choices and higher performance. These findings collectively suggest that during learning, rodents actively probe their environment in a structured manner to refine their decision-making and maintain long-term flexibility.

Value Estimation versus Effort Mobilization: A General Dissociation between Ventromedial and Dorsomedial Prefrontal Cortex.

Deciding on a course of action requires both an accurate estimation of option values and the right amount of effort invested in deliberation to reach sufficient confidence in the final choice. In a previous study, we have provided evidence, across a series of judgment and choice tasks, for a dissociation between the ventromedial prefrontal cortex (vmPFC), which would represent option values, and the dorsomedial prefrontal cortex (dmPFC), which would represent the duration of deliberation. Here, we first replicate this dissociation and extend it to the case of an instrumental learning task, in which 24 human volunteers (13 women) choose between options associated with probabilistic gains and losses. According to fMRI data recorded during decision-making, vmPFC activity reflects the sum of option values generated by a reinforcement learning model and dmPFC activity the deliberation time. To further generalize the role of the dmPFC in mobilizing effort, we then analyze fMRI data recorded in the same participants while they prepare to perform motor and cognitive tasks (squeezing a handgrip or making numerical comparisons) to maximize gains or minimize losses. In both cases, dmPFC activity is associated with the output of an effort regulation model, and not with response time. Taken together, these results strengthen a general theory of behavioral control that implicates the vmPFC in the estimation of option values and the dmPFC in the energization of relevant motor and cognitive processes.

Prefrontal activity during IOWA Gambling Task in young adult women.

This study aims to investigate the relationships between personality traits of impulsivity, using the UPPS-P Impulsive Behaviour Scales shortened version, and prefrontal cortex (PFC) activity during the IOWA Gambling Task (IGT) in young adult women. The study included a sample of 83 young, healthy females (19.8 ± 1.4 years), who voluntarily took part in the study. Repeated measures analysis during the IGT revealed a significant increase in HbO (all p <.001; ηp2 >.31) and a decrease in Hbr (all p <.003; ηp2 >.08) in all prefrontal quadrants. This increase in oxygenation occurs primarily during the choice period under ambiguity (r =.23; p =.039). Additionally, there was a significant linear decrease in selecting the decks associated with a high frequency of losses (p <.001), while the favorable deck with low losses showed a linear increase (F = 12.96; p <.001). Notably, discrepancies were found between UPPS-P and IGT impulsivity ratings. The Lack of Perseverance and Lack of Premeditation scales from the UPPS-P were identified as significant predictors of HbO levels, mainly in the two quadrants of the left hemisphere's, lateral (adjusted R2 =.23; p <.001; f2 =.34) and rostral (adjusted R2 =.13; p <.002; f2 =.17). These findings suggest that young adult women predominantly adopt a punishment-avoidance strategy during IGT, exhibiting increased activation in the left hemisphere, especially during the task's initial phase characterized by ambiguity.

Pre-acquired Functional Connectivity Predicts Choice Inconsistency.

Economic choice theories usually assume that humans maximize utility in their choices. However, studies have shown that humans make inconsistent choices, leading to suboptimal behavior, even without context-dependent manipulations. Previous studies showed that activation in value and motor networks are associated with inconsistent choices at the moment of choice. Here, we investigated if the neural predispositions, measured before a choice task, can predict choice inconsistency in a later risky choice task. Using functional connectivity (FC) measures from resting-state functional magnetic resonance imaging (rsfMRI), derived before any choice was made, we aimed to predict subjects' inconsistency levels in a later-performed choice task. We hypothesized that rsfMRI FC measures extracted from value and motor brain areas would predict inconsistency. Forty subjects (21 females) completed a rsfMRI scan before performing a risky choice task. We compared models that were trained on FC that included only hypothesized value and motor regions with models trained on whole-brain FC. We found that both model types significantly predicted inconsistency levels. Moreover, even the whole-brain models relied mostly on FC between value and motor areas. For external validation, we used a neural network pretrained on FC matrices of 37,000 subjects and fine-tuned it on our data and again showed significant predictions. Together, this shows that the tendency for choice inconsistency is predicted by predispositions of the nervous system and that synchrony between the motor and value networks plays a crucial role in this tendency.

How do animals weigh conflicting information about reward sources over time? Comparing dynamic averaging models.

Optimal foraging theory suggests that animals make decisions which maximize their food intake per unit time when foraging, but the mechanisms animals use to track the value of behavioral alternatives and choose between them remain unclear. Several models for how animals integrate past experience have been suggested. However, these models make differential predictions for the occurrence of spontaneous recovery of choice: a behavioral phenomenon in which a hiatus from the experimental environment results in animals reverting to a behavioral allocation consistent with a reward distribution from the more distant past, rather than one consistent with their most recently experienced distribution. To explore this phenomenon and compare these models, three free-operant experiments with rats were conducted using a serial reversal design. In Phase 1, two responses (A and B) were baited with pellets on concurrent variable interval schedules, favoring option A. In Phase 2, lever baiting was reversed to favor option B. Rats then entered a delay period, where they were maintained at weight in their home cages and no experimental sessions took place. Following this delay, preference was assessed using initial responding in test sessions where levers were presented, but not baited. Models were compared in performance, including an exponentially weighted moving average, the Temporal Weighting Rule, and variants of these models. While the data provided strong evidence of spontaneous recovery of choice, the form and extent of recovery was inconsistent with the models under investigation. Potential interpretations are discussed in relation to both the decision rule and valuation functions employed.

Altruism, reciprocity, and probability: Examining relations through a discounting framework.

Probability and reciprocation have been implicated as key variables for understanding altruism and cooperation. Social discounting, which describes the decline in reward value as the recipient increases in social distance, has provided a framework through which to examine altruistic and cooperative choice. A previous study introduced reciprocal discounting as a way of studying perceived altruism from others (termed reciprocal altruism). But probability discounting has not yet been examined in relation to reciprocal discounting. In order to extend research on reciprocal discounting, the present study evaluated correlations between social, reciprocal, and probability discounting as well as relations between standard social distance (used in social discounting) and reciprocal social distance (the participant's perceived social distance placement on someone else's list) among 129 participants. Upon evaluation, the fit of median reciprocal discount rates to the hyperbolic form was replicated. A strong correlation between social and reciprocal discount rates and a moderate correlation between social and probability discount rates were found as well. Additionally, reciprocal and probability discount rates yielded moderate correlations while reciprocal and standard social distance analyses revealed more correspondence between reward values when persons were socially close (i.e., Person 1) or socially distant (i.e., Person 100). This study provides further evidence that reciprocation and probability likely impact altruistic choice while laying groundwork for further investigations into social distance.