Reward learning and working memory: Effects of massed versus spaced training and post-learning delay period

The role of uncertain reward in voluntary task-switching as revealed by pupillometry and gaze

Cognitive flexibility, the brain's ability to adjust to changes in the environment, is a critical component of executive functioning. Previous literature shows a robust relationship between reward dynamics and flexibility: flexibility is highest when reward changes, while flexibility decreases when reward remains stable. The purpose of this study was to examine the role of uncertain reward in a voluntary task switching paradigm on behavior, pupillometry, and eye gaze. We used pupil dilation as a neuropsychological correlate of arousal and accumulated fixations on a region (i.e. dwell time) to measure oculomotor attention capture. Results during the cue phase showed that pupil dilation under a deterministic, but not a stochastic reinforcement schedule tracked arousal from the magnitude of reward. In addition, dwell time was increased for the eventual choice and dwell-time was reduced under high reward. Taken together, results show that arousal and attentional capture by reward depends to some extent on reward certainty. Turning to reward outcome, pupil dilation was highest (and average dwell time was lowest) following Error feedback compared to correct rewarded feedback. Overall results show that uncertain reward cues may alter pupil-linked arousal and attention as compared to certain reward, highlighting the role of uncertainty as an important modulator affecting attention and reward processing in environments that demand cognitive flexibility.

Enhancing learning experiences: EEG-based passive BCI system adapts learning speed to cognitive load in real-time, with motivation as catalyst

Computer-based learning has gained popularity in recent years, providing learners greater flexibility and freedom. However, these learning environments do not consider the learner's mental state in real-time, resulting in less optimized learning experiences. This research aimed to explore the effect on the learning experience of a novel EEG-based Brain-Computer Interface (BCI) that adjusts the speed of information presentation in real-time during a learning task according to the learner's cognitive load. We also explored how motivation moderated these effects. In accordance with three experimental groups (non-adaptive, adaptive, and adaptive with motivation), participants performed a calibration task (n-back), followed by a memory-based learning task concerning astrological constellations. Learning gains were assessed based on performance on the learning task. Self-perceived mental workload, cognitive absorption and satisfaction were assessed using a post-test questionnaire. Between-group analyses using Mann-Whitney tests suggested that combining BCI and motivational factors led to more significant learning gains and an improved learning experience. No significant difference existed between the BCI without motivational factor and regular non-adaptive interface for overall learning gains, self-perceived mental workload, and cognitive absorption. However, participants who undertook the experiment with an imposed learning pace reported higher overall satisfaction with their learning experience and a higher level of temporal stress. Our findings suggest BCI's potential applicability and feasibility in improving memorization-based learning experiences. Further work should seek to optimize the BCI adaptive index and explore generalizability to other learning contexts.

Learning and memory processes in behavioural addiction: A systematic review

Similar to addictive substances, addictive behaviours such as gambling and gaming are associated with maladaptive modulation of key brain areas and functional networks implicated in learning and memory. Therefore, this review sought to understand how different learning and memory processes relate to behavioural addictions and to unravel their underlying neural mechanisms. Adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we systematically searched four databases - PsycINFO, PubMed, Scopus, and Web of Science using the agreed-upon search string. Findings suggest altered executive function-dependent learning processes and enhanced habit learning in behavioural addiction. Whereas the relationship between working memory and behavioural addiction is influenced by addiction type, working memory aspect, and task nature. Additionally, long-term memory is incoherent in individuals with addictive behaviours. Consistently, neurophysiological evidence indicates alterations in brain areas and networks implicated in learning and memory processes in behavioural addictions. Overall, the present review argues that, like substance use disorders, alteration in learning and memory processes may underlie the development and maintenance of behavioural addictions.

Naturalistic reinforcement learning

Humans possess a remarkable ability to make decisions within real-world environments that are expansive, complex, and multidimensional. Human cognitive computational neuroscience has sought to exploit reinforcement learning (RL) as a framework within which to explain human decision-making, often focusing on constrained, artificial experimental tasks. In this article, we review recent efforts that use naturalistic approaches to determine how humans make decisions in complex environments that better approximate the real world, providing a clearer picture of how humans navigate the challenges posed by real-world decisions. These studies purposely embed elements of naturalistic complexity within experimental paradigms, rather than focusing on simplification, generating insights into the processes that likely underpin humans' ability to navigate complex, multidimensional real-world environments so successfully.

Promoting Empathy and Affiliation in Relationships (PEAR) study: protocol for a longitudinal study investigating the development of early childhood callous-unemotional traits

INTRODUCTION

Children with callous-unemotional (CU) traits are at high lifetime risk of antisocial behaviour. Low affiliation (ie, social bonding difficulties) and fearlessness (ie, low threat sensitivity) are proposed risk factors for CU traits. Parenting practices (eg, harshness and low warmth) also predict risk for CU traits. However, few studies in early childhood have identified attentional or physiological markers of low affiliation and fearlessness. Moreover, no studies have tested whether parenting practices are underpinned by low affiliation or fearlessness shared by parents, which could further shape parent-child interactions and exacerbate risk for CU traits. Addressing these questions will inform knowledge of how CU traits develop and isolate novel parent and child targets for future specialised treatments for CU traits.

METHODS AND ANALYSIS

The Promoting Empathy and Affiliation in Relationships (PEAR) study aims to establish risk factors for CU traits in children aged 3-6 years. The PEAR study will recruit 500 parent-child dyads from two metropolitan areas of the USA. Parents and children will complete questionnaires, computer tasks and observational assessments, alongside collection of eye-tracking and physiological data, when children are aged 3-4 (time 1) and 5-6 (time 2) years. The moderating roles of child sex, race and ethnicity, family and neighbourhood disadvantage, and parental psychopathology will also be assessed. Study aims will be addressed using structural equation modelling, which will allow for flexible characterisation of low affiliation, fearlessness and parenting practices as risk factors for CU traits across multiple domains.

ETHICS AND DISSEMINATION

Ethical approval was granted by Boston University (#6158E) and the University of Pennsylvania (#850638). Results will be disseminated through conferences and open-access publications. All study and task materials will be made freely available on lab websites and through the Open Science Framework (OSF).

The Devastating Effects of Sleep Deprivation on Memory: Lessons from Rodent Models

In this narrative review article, we discuss the role of sleep deprivation (SD) in memory processing in rodent models. Numerous studies have examined the effects of SD on memory, with the majority showing that sleep disorders negatively affect memory. Currently, a consensus has not been established on which damage mechanism is the most appropriate. This critical issue in the neuroscience of sleep remains largely unknown. This review article aims to elucidate the mechanisms that underlie the damaging effects of SD on memory. It also proposes a scientific solution that might explain some findings. We have chosen to summarize literature that is both representative and comprehensive, as well as innovative in its approach. We examined the effects of SD on memory, including synaptic plasticity, neuritis, oxidative stress, and neurotransmitters. Results provide valuable insights into the mechanisms by which SD impairs memory function.

Neural Index of Reinforcement Learning Predicts Improved Stimulus-Response Retention under High Working Memory Load

Human learning and decision-making are supported by multiple systems operating in parallel. Recent studies isolating the contributions of reinforcement learning (RL) and working memory (WM) have revealed a trade-off between the two. An interactive WM/RL computational model predicts that although high WM load slows behavioral acquisition, it also induces larger prediction errors in the RL system that enhance robustness and retention of learned behaviors. Here, we tested this account by parametrically manipulating WM load during RL in conjunction with EEG in both male and female participants and administered two surprise memory tests. We further leveraged single-trial decoding of EEG signatures of RL and WM to determine whether their interaction predicted robust retention. Consistent with the model, behavioral learning was slower for associations acquired under higher load but showed parametrically improved future retention. This paradoxical result was mirrored by EEG indices of RL, which were strengthened under higher WM loads and predictive of more robust future behavioral retention of learned stimulus-response contingencies. We further tested whether stress alters the ability to shift between the two systems strategically to maximize immediate learning versus retention of information and found that induced stress had only a limited effect on this trade-off. The present results offer a deeper understanding of the cooperative interaction between WM and RL and show that relying on WM can benefit the rapid acquisition of choice behavior during learning but impairs retention.SIGNIFICANCE STATEMENT Successful learning is achieved by the joint contribution of the dopaminergic RL system and WM. The cooperative WM/RL model was productive in improving our understanding of the interplay between the two systems during learning, demonstrating that reliance on RL computations is modulated by WM load. However, the role of WM/RL systems in the retention of learned stimulus-response associations remained unestablished. Our results show that increased neural signatures of learning, indicative of greater RL computation, under high WM load also predicted better stimulus-response retention. This result supports a trade-off between the two systems, where degraded WM increases RL processing, which improves retention. Notably, we show that this cooperative interplay remains largely unaffected by acute stress.

Anesthesia Resistant Memories in Drosophila, a Working Perspective

Memories are lasting representations over time of associations between stimuli or events. In general, the relatively slow consolidation of memories requires protein synthesis with a known exception being the so-called Anesthesia Resistant Memory (ARM) in Drosophila. This protein synthesis-independent memory type survives amnestic shocks after a short, sensitive window post training, and can also emerge after repeated cycles of training in a negatively reinforced olfactory conditioning task, without rest between cycles (massed conditioning—MC). We discussed operational and molecular mechanisms that mediate ARM and differentiate it from protein synthesis-dependent long-term memory (LTM) in Drosophila. Based on the notion that ARM is unlikely to specifically characterize Drosophila, we examined protein synthesis and MC-elicited memories in other species and based on intraspecies shared molecular components and proposed potential relationships of ARM with established memory types in Drosophila and vertebrates.