Individual differences in working memory impact the trajectory of non-native speech category learning.

What is the role of working memory over the course of non-native speech category learning? Prior work has predominantly focused on how working memory might influence learning assessed at a single timepoint. Here, we substantially extend this prior work by examining the role of working memory on speech learning performance over time (i.e., over several months) and leverage a multifaceted approach that provides key insights into how working memory influences learning accuracy, maintenance of knowledge over time, generalization ability, and decision processes. We found that the role of working memory in non-native speech learning depends on the timepoint of learning and whether individuals learned the categories at all. Among learners, across all stages of learning, working memory was associated with higher accuracy as well as faster and slightly more cautious decision making. Further, while learners and non-learners did not have substantially different working memory performance, learners had faster evidence accumulation and more cautious decision thresholds throughout all sessions. Working memory may enhance learning by facilitating rapid category acquisition in initial stages and enabling faster and slightly more careful decision-making strategies that may reduce the overall effort needed to learn. Our results have important implications for developing interventions to improve learning in naturalistic language contexts.

Neural underpinnings of ethical decisions in life and death dilemmas in naïve and expert firefighters.

When a single choice impacts on life outcomes, faculties to make ethical judgments come into play. Here we studied decisions in a real-life setting involving life-and-death outcomes that affect others and the decision-maker as well. We chose a genuine situation where prior training and expertise play a role: firefighting in life-threatening situations. By studying the neural correlates of dilemmas involving life-saving decisions, using realistic firefighting situations, allowed us to go beyond previously used hypothetical dilemmas, while addressing the role of expertise and the use of coping strategies (n = 47). We asked the question whether the neural underpinnings of deontologically based decisions are affected by expertise. These realistic life-saving dilemmas activate the same core reward and affective processing network, in particular the ventromedial prefrontal cortex, nucleus accumbens and amygdala, irrespective of prior expertise, thereby supporting general domain theories of ethical decision-making. We found that brain activity in the hippocampus and insula parametrically increased as the risk increased. Connectivity analysis showed a larger directed influence of the insula on circuits related to action selection in non-experts, which were slower than experts in non rescuing decisions. Relative neural activity related to the decision to rescue or not, in the caudate nucleus, insula and anterior cingulate cortex was negatively associated with coping strategies, in experts (firefighters) suggesting practice-based learning. This shows an association between activity and expert-related usage of coping strategies. Expertise enables salience network activation as a function of behavioural coping dimensions, with a distinct connectivity profile when facing life-rescuing dilemmas.

Gustatory cortex: Taste coding and decision making in one.

A new study reveals that, as mice learn a taste discrimination task, taste responses in gustatory cortex undergo plasticity such that they reflect taste identity and predict the upcoming decision in separate response epochs.

Making precise movements increases confidence in perceptual decisions.

Perceptual decision-making often lacks explicit feedback, making confidence in our choices pivotal for guiding subsequent actions. Recent studies have highlighted the role of motor responses in modulating decision confidence. Two competing mechanisms have been proposed to elucidate this phenomenon. The "fluency hypothesis" posits that the ease and smoothness of executing a motor response can serve as a cue to enhance retrospective confidence. Conversely, the "monitoring hypothesis" suggests that the extent of action monitoring during response selection may boost retrospective confidence, with heightened monitoring potentially offsetting response fluency. We conducted a pre-registered experiment to directly test these hypotheses. Participants engaged in a perceptual task involving the discrimination of Gabor patch orientation. Perceptual responses required high or low motor precision, manipulated by the size of target circles that participants had to reach with the computer mouse to provide a response. Contrary to the "fluency hypothesis", our results showed that, in trials requiring higher precision (utilizing small circles), participants reported higher confidence levels compared to trials with less demanding responses (involving larger circles). Importantly, this increase in confidence did not coincide with any change in perceptual accuracy. These findings align with the "monitoring hypothesis," suggesting that the degree of action monitoring during response execution can indeed influence retrospective decision confidence.

Contractualist tendencies and reasoning in moral judgment and decision making.

The social-contract tradition of Hobbes, Rousseau, Kant, and Rawls has been widely influential in moral philosophy but has until recently received relatively little attention in moral psychology. For contractualist moral theories, ethics is a matter of forming, adhering to, and enforcing (hypothetical) agreements, and morality is fundamentally about acting according to what would be agreed by rational agents. A recent psychological theory, virtual bargaining, models social interactions in contractualist terms, suggesting that we often act as we would agree to do if we were to negotiate explicitly. However, whether such contractualist tendencies (a propensity to make typically contractualist choices) and forms of reasoning (agreement-based cognitive processes) play a role in moral cognition is still unclear. Drawing upon virtual bargaining, we develop two novel experimental paradigms designed to elicit incentivized decisions and moral judgments. We then test the descriptive relevance of contractualism in moral judgment and decision making in five preregistered online experiments (n = 4103; English-speaking Prolific participants). In the first task, we find evidence that many participants show contractualist tendencies: their choices are "characteristically" contractualist. In the second task, we find evidence consistent with contractualist reasoning influencing some participants' judgments and incentivized decisions. Our findings suggest that a propensity to act as prescribed by tacit agreements may be particularly important in understanding the moral psychology of fleeting social interactions and coordination problems. By complementing the rich literature on deontology and consequentialism in moral psychology, empirical approaches inspired by contractualism may prove fruitful to better understand moral cognition.

C. elegans foraging as a model for understanding the neuronal basis of decision-making.

Animals have evolved to seek, select, and exploit food sources in their environment. Collectively termed foraging, these ubiquitous behaviors are necessary for animal survival. As a foundation for understanding foraging, behavioral ecologists established early theoretical and mathematical frameworks which have been subsequently refined and supported by field and laboratory studies of foraging animals. These simple models sought to explain how animals decide which strategies to employ when locating food, what food items to consume, and when to explore the environment for new food sources. These foraging decisions involve integration of prior experience with multimodal sensory information about the animal's current environment and internal state. We suggest that the nematode Caenorhabditis elegans is well-suited for a high-resolution analysis of complex goal-oriented behaviors such as foraging. We focus our discussion on behavioral studies highlighting C. elegans foraging on bacteria and summarize what is known about the underlying neuronal and molecular pathways. Broadly, we suggest that this simple model system can provide a mechanistic understanding of decision-making and present additional avenues for advancing our understanding of complex behavioral processes.

Difficulty sensitivity replaces reward sensitivity during adolescence: Task-related fMRI and functional connectivity during self-regulative learning choices.

AIM: We examined age-related differences in valuation and cognitive control circuits during value-based decision-making. METHODS: 13-year-olds (N = 25) and 17-year-olds (N = 22) made a metacognitive choice to be tested or not on an upcoming learning task, based on reward and difficulty associated with word-pairs. To investigate whether these determinants of subjective value are differently processed at different ages, we performed region-of-interest(ROI)-based analyses of task-related and functional connectivity data. RESULTS: We observed age-related differences in responsiveness of valuation structures (amygdala, ventral striatum, ventromedial prefrontal cortex) and caudate nucleus, with activity modulated by reward in 13-year-olds, while in 17-year-olds activity being responsive to difficulty. These accompanied age-related differences in functional connectivity between medial prefrontal and striatal/amygdala seeds. DISCUSSION: These results are in line with current views that sensitivity changes for reward and difficulty during adolescence are the result of a maturational switch in effort-related signalling in the cognitive control circuit, which increasingly regulates value-signalling structures.

The medial prefrontal cortex leaves the hippocampus when it prepares for the future.

Our memories help us plan for the future. In some cases, we use memories to repeat the choices that led to preferable outcomes in the past. The success of these memory-guided decisions depends on close interactions between the hippocampus and medial prefrontal cortex. In other cases, we need to use our memories to deduce hidden connections between the present and past situations to decide the best choice of action based on the expected outcome. Our recent study investigated neural underpinnings of such inferential decisions by monitoring neural activity in the medial prefrontal cortex and hippocampus in rats. We identified several neural activity patterns indicating awake memory trace reactivation and restructuring of functional connectivity among multiple neurons. We also found that these patterns occurred concurrently with the ongoing hippocampal activity when rats recalled past events but not when they planned new adaptive actions. Here, we discussed how these computational properties might contribute to success in inferential decision-making and propose a working model on how the medial prefrontal cortex changes its interaction with the hippocampus depending on whether it reflects on the past or looks into the future.

Decision-making under conditions of explicit risk and uncertainty in autistic and typically developing adolescents and young adults.

Adolescence has been characterized as a period of risky and possibly suboptimal decision-making, yet the development of decision-making in autistic adolescents is not well understood. To investigate decision-making in autism, we evaluated performance on 2 computerized tasks capturing decision-making under explicit risk and uncertainty in autistic and non-autistic adolescents/young adults ages 12-22 years. Participants completed the Game of Dice Task (32 IQ-matched participant pairs) to assess decision-making under explicit risk and the modified Iowa Gambling Task (35 IQ-matched pairs) to assess decision-making under uncertainty. Autistic participants overall made riskier decisions than non-autistic participants on the Game of Dice Task, and the odds of making riskier decisions varied by age and IQ. In contrast, the autistic group showed comparable levels of learning over trial blocks to the non-autistic group on the modified Iowa Gambling Task. For both tasks, younger autistic participants performed poorer than their non-autistic counterparts, while group differences diminished in older ages. This age-related pattern suggests positive development during adolescence on risk assessment and decision-making in autism but also implies differential developmental trajectories between groups. These findings also suggest differential performance by the risk type, with additional complex influences of IQ and fluid cognition, which warrants further investigations.

Forming cognitive maps for abstract spaces: the roles of the human hippocampus and orbitofrontal cortex.

How does the human brain construct cognitive maps for decision-making and inference? Here, we conduct an fMRI study on a navigation task in multidimensional abstract spaces. Using a deep neural network model, we assess learning levels and categorized paths into exploration and exploitation stages. Univariate analyses show higher activation in the bilateral hippocampus and lateral prefrontal cortex during exploration, positively associated with learning level and response accuracy. Conversely, the bilateral orbitofrontal cortex (OFC) and retrosplenial cortex show higher activation during exploitation, negatively associated with learning level and response accuracy. Representational similarity analysis show that the hippocampus, entorhinal cortex, and OFC more accurately represent destinations in exploitation than exploration stages. These findings highlight the collaboration between the medial temporal lobe and prefrontal cortex in learning abstract space structures. The hippocampus may be involved in spatial memory formation and representation, while the OFC integrates sensory information for decision-making in multidimensional abstract spaces.

Group vocal composition and decision-making during roost finding in Spix's disk-winged bats.

Theoretical work suggests that having many informed individuals within social groups can promote efficient resource location. However, it may also give rise to group fragmentation if members fail to reach consensus on their direction of movement. In this study, we investigate whether the number of informed individuals, exemplified by bats emitting calls from different roosts, influences group cohesion in Spix's disk-winged bats (Thyroptera tricolor). Additionally, we explore the role of signal reliability, quantified through signalling rates, in group consensus on where to roost. These bats use contact calls to announce the location of a roost site and recruit conspecifics. The groups they form exhibit high levels of cohesion and consist of both vocal and non-vocal bats, with vocal behaviour being consistent over time. Our findings revealed that an increase in the number of roosts broadcasting calls is strongly associated with the likelihood of groups fragmenting among multiple roosts. Additionally, we found that a majority of group members enter the roost with higher calling rates. This phenomenon can mitigate the risk of group fragmentation, as bats emitting more calls may contribute to greater group consensus on roosting locations, thereby reducing the likelihood of individuals separating and enhancing overall group cohesion. Our results highlight the potential costs of having too many information producers for group coordination, despite their established role in finding critical resources. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

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 neurocomputational link between defensive cardiac states and approach-avoidance arbitration under threat.

Avoidance, a hallmark of anxiety-related psychopathology, often comes at a cost; avoiding threat may forgo the possibility of a reward. Theories predict that optimal approach-avoidance arbitration depends on threat-induced psychophysiological states, like freezing-related bradycardia. Here we used model-based fMRI analyses to investigate whether and how bradycardia states are linked to the neurocomputational underpinnings of approach-avoidance arbitration under varying reward and threat magnitudes. We show that bradycardia states are associated with increased threat-induced avoidance and more pronounced reward-threat value comparison (i.e., a stronger tendency to approach vs. avoid when expected reward outweighs threat). An amygdala-striatal-prefrontal circuit supports approach-avoidance arbitration under threat, with specific involvement of the amygdala and dorsal anterior cingulate (dACC) in integrating reward-threat value and bradycardia states. These findings highlight the role of human freezing states in value-based decision making, relevant for optimal threat coping. They point to a specific role for amygdala/dACC in state-value integration under threat.

Cingulate microstimulation induces negative decision-making via reduced top-down influence on primate fronto-cingulo-striatal network.

The dorsolateral prefrontal cortex (dlPFC) is crucial for regulation of emotion that is known to aid prevention of depression. The broader fronto-cingulo-striatal (FCS) network, including cognitive dlPFC and limbic cingulo-striatal regions, has been associated with a negative evaluation bias often seen in depression. The mechanism by which dlPFC regulates the limbic system remains largely unclear. Here we have successfully induced a negative bias in decision-making in female primates performing a conflict decision-making task, by directly microstimulating the subgenual cingulate cortex while simultaneously recording FCS local field potentials (LFPs). The artificially induced negative bias in decision-making was associated with a significant decrease in functional connectivity from cognitive to limbic FCS regions, represented by a reduction in Granger causality in beta-range LFPs from the dlPFC to the other regions. The loss of top-down directional influence from cognitive to limbic regions, we suggest, could underlie negative biases in decision-making as observed in depressive states.

Prefrontal tDCS modulates risk-taking in male violent offenders.

Detrimental decision-making is a major problem among violent offenders. Non-invasive brain stimulation offers a promising method to directly influence decision-making and has already been shown to modulate risk-taking in non-violent controls. We hypothesize that anodal transcranial direct current stimulation (tDCS) over the right dorsolateral prefrontal cortex beneficially modulates the neural and behavioral correlates of risk-taking in a sample of violent offenders. We expect offenders to show more risky decision-making than non-violent controls and that prefrontal tDCS will induce stronger changes in the offender group. In the current study, 22 male violent offenders and 24 male non-violent controls took part in a randomized double-blind sham-controlled cross-over study applying tDCS over the right dorsolateral prefrontal cortex. Subsequently, participants performed the Balloon Analogue Risk Task (BART) during functional magnetic resonance imaging (fMRI). Violent offenders showed significantly less optimal decision-making compared to non-violent controls. Active tDCS increased prefrontal activity and improved decision-making only in violent offenders but not in the control group. Also, in offenders only, prefrontal tDCS influenced functional connectivity between the stimulated area and other brain regions such as the thalamus. These results suggest baseline dependent effects of tDCS and pave the way for treatment options of disadvantageous decision-making behavior in this population.

Visual social information use in collective foraging.

Collective dynamics emerge from individual-level decisions, yet we still poorly understand the link between individual-level decision-making processes and collective outcomes in realistic physical systems. Using collective foraging to study the key trade-off between personal and social information use, we present a mechanistic, spatially-explicit agent-based model that combines individual-level evidence accumulation of personal and (visual) social cues with particle-based movement. Under idealized conditions without physical constraints, our mechanistic framework reproduces findings from established probabilistic models, but explains how individual-level decision processes generate collective outcomes in a bottom-up way. In clustered environments, groups performed best if agents reacted strongly to social information, while in uniform environments, individualistic search was most beneficial. Incorporating different real-world physical and perceptual constraints profoundly shaped collective performance, and could even buffer maladaptive herding by facilitating self-organized exploration. Our study uncovers the mechanisms linking individual cognition to collective outcomes in human and animal foraging and paves the way for decentralized robotic applications.

Synergizing habits and goals with variational Bayes.

Behaving efficiently and flexibly is crucial for biological and artificial embodied agents. Behavior is generally classified into two types: habitual (fast but inflexible), and goal-directed (flexible but slow). While these two types of behaviors are typically considered to be managed by two distinct systems in the brain, recent studies have revealed a more sophisticated interplay between them. We introduce a theoretical framework using variational Bayesian theory, incorporating a Bayesian intention variable. Habitual behavior depends on the prior distribution of intention, computed from sensory context without goal-specification. In contrast, goal-directed behavior relies on the goal-conditioned posterior distribution of intention, inferred through variational free energy minimization. Assuming that an agent behaves using a synergized intention, our simulations in vision-based sensorimotor tasks explain the key properties of their interaction as observed in experiments. Our work suggests a fresh perspective on the neural mechanisms of habits and goals, shedding light on future research in decision making.

Continuous decision to wait for a future reward is guided by fronto-hippocampal anticipatory dynamics.

Deciding whether to wait for a future reward is crucial for surviving in an uncertain world. While seeking rewards, agents anticipate a reward in the present environment and constantly face a trade-off between staying in their environment or leaving it. It remains unclear, however, how humans make continuous decisions in such situations. Here, we show that anticipatory activity in the anterior prefrontal cortex, ventrolateral prefrontal cortex, and hippocampus underpins continuous stay-leave decision-making. Participants awaited real liquid rewards available after tens of seconds, and their continuous decision was tracked by dynamic brain activity associated with the anticipation of a reward. Participants stopped waiting more frequently and sooner after they experienced longer delays and received smaller rewards. When the dynamic anticipatory brain activity was enhanced in the anterior prefrontal cortex, participants remained in their current environment, but when this activity diminished, they left the environment. Moreover, while experiencing a delayed reward in a novel environment, the ventrolateral prefrontal cortex and hippocampus showed anticipatory activity. Finally, the activity in the anterior prefrontal cortex and ventrolateral prefrontal cortex was enhanced in participants adopting a leave strategy, whereas those remaining stationary showed enhanced hippocampal activity. Our results suggest that fronto-hippocampal anticipatory dynamics underlie continuous decision-making while anticipating a future reward.

Common neural dysfunction of economic decision-making across psychiatric conditions.

Adaptive decision-making, which is often impaired in various psychiatric conditions, is essential for well-being. Recent evidence has indicated that decision-making capacity in multiple tasks could be accounted for by latent dimensions, enlightening the question of whether there is a common disruption of brain networks in economic decision-making across psychiatric conditions. Here, we addressed the issue by combining activation/lesion network mapping analyses with a transdiagnostic brain imaging meta-analysis. Our findings indicate that there were transdiagnostic alterations in the thalamus and ventral striatum during the decision or outcome stage of decision-making. The identified regions represent key nodes in a large-scale network, which is composed of multiple heterogeneous brain regions and plays a causal role in motivational functioning. The findings suggest that disturbances in the network associated with emotion- and reward-related processing play a key role in dysfunctions of decision-making observed in various psychiatric conditions. This study provides the first meta-analytic evidence of common neural alterations linked to deficits in economic decision-making.

Ambush strategy enhances organisms' performance in rock-paper-scissors games.

We study a five-species cyclic system wherein individuals of one species strategically adapt their movements to enhance their performance in the spatial rock-paper-scissors game. Environmental cues enable the awareness of the presence of organisms targeted for elimination in the cyclic game. If the local density of target organisms is sufficiently high, individuals move towards concentrated areas for direct attack; otherwise, they employ an ambush tactic, maximising the chances of success by targeting regions likely to be dominated by opponents. Running stochastic simulations, we discover that the ambush strategy enhances the likelihood of individual success compared to direct attacks alone, leading to uneven spatial patterns characterised by spiral waves. We compute the autocorrelation function and measure how the ambush tactic unbalances the organisms' spatial organisation by calculating the characteristic length scale of typical spatial domains of each species. We demonstrate that the threshold for local species density influences the ambush strategy's effectiveness, while the neighbourhood perception range significantly impacts decision-making accuracy. The outcomes show that long-range perception improves performance by over 60%, although there is potential interference in decision-making under high attack triggers. Understanding how organisms' adaptation their environment enhances their performance may be helpful not only for ecologists, but also for data scientists, aiming to improve artificial intelligence systems.