Cognitive, Affective, & Behavioral Neuroscience

When humans learn under conditions of uncertainty, they dynamically adjust how they prepare for and respond to feedback. In navigating uncertain environments, the brain minimizes error by continuously refining internal models via memory updating (MU). Feedback is critical for MU, and anticipatory neural mechanisms shape how feedback is processed, likely reflecting learned environmental certainty. However, the literature has largely focused on post-feedback activity, leaving pre-feedback certainty-related mechanisms less understood. The present study aims to address this gap by examining how certainty modulates anticipatory states, preceding feedback and subsequent MU. We examined oscillatory activity prior to performance feedback in a reanalysis of EEG data previously published by Hassall and colleagues (2023). Twenty-one participants (16 female, Mage = 25.81 years) predicted the strength of cartoon characters with varying predictability levels which were learned through exposure. Feedback on prediction accuracy was presented via an animated rising bar. Results revealed that theta power is modulated by accumulative feedback. Linear mixed-effects models revealed an interaction between predictability-related certainty and learning stage: in late learning, higher performance was associated with increased pre-feedback alpha and beta power for low-certainty trials, whereas in early learning, higher performance was associated with decreased beta power. These learning-related modulations in alpha and beta power suggest that initial learning is marked by adaptable exploratory processing. Subsequent learning exhibited increased alpha-mediated inhibition and beta-related anticipatory activity for lower certainty trials, indicative of dynamic strategy refinement and selective engagement of task-relevant information. These results demonstrate that certainty shapes preparatory oscillatory activity associated with MU.

The willingness to exert cognitive effort is essential but is constrained by the subjective cost of effort. Although effortful tasks are often avoided, positive bias about ones own performance may help sustain engagement with cognitive demands. Here, participants completed an effort-based decision-making task and reported trial-by-trial predictions of their own performance, allowing us to quantify performance prediction error (PPE) as the discrepancy between subjective and objective accuracy. The results showed that PPE was predominantly positive and increased with effort level, indicating greater overestimation under higher cognitive demands. Using a computational model, we show that choices were best explained by a learning model in which rewarded trials accompanied by positive PPE decreased subsequent sensitivity to effort. A confidence-based control model did not provide a better account of choices, suggesting that this effect was better captured by positive performance bias than by confidence alone. Our findings provide a computational account of how biased self-evaluation may attenuate the subjective cost of cognitive effort and extend the positive bias literature to the task need for cognitive effort.

Goal-directed behavior often requires sustained effort across a sequence of interdependent decisions, yet the determinants of persistence in such contexts remain poorly understood. Here, we investigated how individuals regulate persistence in a novel sequential effort-based task in which they controlled an avatar through successive checkpoints to reach a final goal and could make repeated attempts following failure. At each attempt, participants could choose either to persist in the same task or to disengage toward an easier but less rewarding alternative. We found that decisions to persist or disengage were jointly shaped by multiple interacting factors. Disengagement increased with task difficulty and lower skill level. It also increased with repeated attempts and time-on-task, indexing fatigue, and with accumulated errors, indexing lack of progress. Conversely, proximity to the goal promoted persistence and shaped decision dynamics by reducing choice conflict during persistence decisions and increasing hesitation during disengagement near the goal. Notably, clearing the first checkpoint produced a sharp increase in persistence, suggesting that early success plays a pivotal role. Furthermore, persistence reflected both retrospective and prospective evaluations of effort, with prior investment promoting commitment and anticipated effort reducing it. Finally, disengagement was preceded by short-term performance decline but not by gradual increases in decision conflict, suggesting relatively abrupt strategy shifts following repeated failures. Together, these findings provide a comprehensive account of persistence in sequential effortful tasks, showing that decisions to persist or disengage are jointly shaped by multiple factors related to fatigue, (lack of) progress, goal proximity, and early success.

I ntroduction: Prospective memory (PM) deficits in children with attention-deficit/hyperactivity disorder (ADHD) significantly impact academic and daily functioning. Through two experiments, this study investigated how cognitive load and encoding strategies modulate PM performance. Methods: Experiment 1 included 43 children (21 ADHD, 22 typically developing) who completed an n-back task under high and low cognitive load. Experiment 2 included 44 children with ADHD who were randomly assigned to either a standard encoding group or an implementation intention encoding group, also completing the n-back task under both load conditions. Results: Experiment 1 showed that children with ADHD had significantly lower PM accuracy than typically developing peers. Signal detection analysis revealed that this deficit stemmed from a more conservative response bias rather than impaired perceptual sensitivity. Unexpectedly, PM accuracy and perceptual sensitivity were higher under high cognitive load than low load for both groups. Experiment 2 demonstrated that implementation intention encoding significantly enhanced PM accuracy and perceptual sensitivity in children with ADHD, with stable effects across load conditions and no interference with ongoing task performance. Discussion: These findings indicate that PM deficits in children with ADHD reflect a conservative response strategy rather than an inability to detect target cues. Implementation intention encoding provides an effective, load-independent cognitive strategy for enhancing PM performance. These results offer novel insights into the cognitive mechanisms underlying PM deficits in ADHD and provide evidence-based guidance for targeted interventions.

Fairness decisions often integrate affective responses within a social context, yet emotion regulation in this literature has been largely studied as a self-directed process rather than an interpersonal one. We examined how individual differences in other-directed emotion regulation--measured with the Emotion Regulation of Others and Self (EROS) scale--relate to behavioral and neural responses during fairness decisions in 138 adults completing a variant of the Ultimatum Game with human and computer partners during fMRI. Behaviorally, participants who more strongly endorsed worsening others emotions rejected unfair offers more frequently, and this tendency interacted with offer fairness to amplify rejection of unfair offers. At the neural level, the left anterior insula tracked offer unfairness more strongly in social versus nonsocial contexts, consistent with sociality modulating the neural encoding of fairness. Right dlPFC activation during socially unfair offers was greater among individuals who preferred to improve others emotions. Connectivity analyses revealed that social fairness sensitivity predicted stronger amygdala-orbitofrontal and amygdala-dmPFC coupling; the latter was further amplified among individuals higher in other-directed emotion worsening. Together, these findings identify interpersonal emotion regulation as an understudied source of variation in the affective and prefrontal systems supporting fairness-based social decisions.

Learning in adulthood is embedded in everyday social life, in which periods of psychosocial stress alternate with recovery. The autonomic nervous system regulates how the body responds to environmental demands, yet individuals differ markedly in this regulation. It remains unknown whether such individual differences in bodily regulation modulate the ability to learn probabilistic patterns from sensory input. Here, we investigated statistical learning of probabilistic patterns in speech streams in a six-hour experiment incorporating psychosocial stress and recovery to approximate everyday conditions. Sixty-five adults were exposed to novel speech streams in high- and low-stress contexts, with learning assessed immediately after exposure and following a rest period. Heart rate variability was recorded throughout the experiment to capture individual differences in autonomic reactivity to stress and recovery. From these measures, we constructed composite proxies of sympathetic (SNS) and parasympathetic (PNS) nervous system reactivity. Individuals with congruent SNS-PNS reactivity--either jointly high or jointly low--showed superior statistical learning outcomes across stress contexts. SNS reactivity preferentially supported encoding, whereas PNS reactivity supported consolidation. Moreover, the effect of SNS activation during speech exposure on statistical learning depended on individuals SNS reactivity profiles. These findings demonstrate that individual differences in bodily regulation are tightly linked to the ability to learn statistical dependencies in stressful environments. Overall, the findings highlight the essential role of brain-body-environment interactions in statistical learning.

Flow state, characterized by optimal engagement and performance, represents a key concept in understanding human performance and cognitive resource allocation. Grounded in Csikszentmihalyis and Sherrys flow theory and the Limited Capacity Model of Motivated Mediated Message Processing (LC4MP), this study investigated physiological and neural correlates of flow state during a simulated driving task under different music conditions and difficulty levels. Using a 2 x 3 factorial design with 20 participants, this study examined self-selected versus non-self-selected music across three difficulty levels, testing the relationship between task switching, cognitive resource allocation, and flow state. Physiological measures included heart rate and EEG (alpha/theta power) using a 4-channel Muse 2 headband, alongside a self-report measure of flow experience. Hierarchical linear modeling revealed significant physiological changes during self-selected music: heart rate decreased ({beta} = -5.15, p < .001), while alpha ({beta} = 5829.77, p < .001) and theta power ({beta} = 7637.24, p < .001) increased. Task difficulty also showed significant effects, with heart rate decreasing during hard ({beta} = -6.70, p < .001) and moderate ({beta} = -3.40, p = .001) conditions. In particular, while physiological measures showed robust changes, the self-reported flow state did not reach significance. Task switching rates showed significant decreases during self-selected music ({beta} = -0.86, p < .001) and hard difficulty ({beta} = -0.61, p < .001), supporting the LC4MP frameworks predictions regarding cognitive resource allocation. These findings demonstrate how task switching and cognitive resource allocation relate to flow state induction. The results highlight the importance of multimodal measurement approaches and demonstrate that personal relevance through music selection and task difficulty significantly influence physiological and neural responses during performance. Future research should employ more comprehensive measurement approaches to better capture the complexity of flow-related neural activity and its relationship to task switching and cognitive resource allocation.

Curiosity, a key driver of exploration and learning, is reinforced by reward-related neurochemical systems, yet the role of the opioidergic system in modulating this behavior remains unclear. Music, as a highly rewarding stimulus, offers a unique context to investigate the neurochemical basis of curiosity, particularly the unexplored role of opioids in music-driven exploration. To fill this gap, we performed a double-blind within-subject pharmacological design, in which 26 participants received, in two different sessions, either a placebo or the opioid antagonist naltrexone. During each session, participants engaged in a music exploration/exploitation trade-off paradigm designed to assess their willingness to pay for exploring unfamiliar electronic music. Using logistic regression mixed-effects models, we found that while naltrexone did not affect overall curiosity ratings, it significantly reduced exploratory behavior in states of heightened curiosity. These findings suggest that the opioidergic system plays a critical role in regulating the relationship between curiosity and exploration, particularly in the context of novel and rewarding stimuli like music. Overall, the present research provides new and compelling evidence on the important relationship between curiosity and exploration and its regulation with the opioidergic neurotransmitter subsystem. Significance StatementThe present research aimed to advance our understanding of the neurochemical mechanisms underlying curiosity and information seeking. In our study, we employed a pharmacological design to examine the role of the opioidergic system in music-related exploration. Using a novel music exploration/exploitation paradigm, we found that while naltrexone, an opioid antagonist, did not affect baseline curiosity ratings, it markedly reduced exploratory behavior during high-curiosity states in the presence of potential monetary losses. These results provide new evidence that opioidergic modulation plays a critical role in regulating curiosity-driven exploration. This new evidence might be relevant in the future for better understanding how neurochemical systems shape learning, motivation, and affective responses in complex cognitive domains such as music.

Subthreshold depression is associated with significant functional impairment and elevated risk of major depressive disorder. A negative self-concept may disrupt the implicit positive association evoked by ones own face, impairing incidental encoding of self-relevant information. Whether subthreshold depression involves a selective deficit in encoding self-face identity remains unclear. The attribute amnesia paradigm is well suited to address this question because it can dissociate attentional selection from working memory encoding. Using this paradigm, we examined the issue across two experiments. Experiment 1 employed nonsocial stimuli (animal drawings) and confirmed an intact attribute amnesia effect in subthreshold depression (n = 30) comparable to healthy controls (n = 30), ruling out a generalized encoding deficit. Experiment 2 replaced targets with faces (self or other) and revealed a selective enhancement of the attribute amnesia effect for self-face identity in subthreshold depression. Specifically, on the surprise trial, accuracy for self-face identity dropped to near-chance levels in the subthreshold depression group, whereas no such deficit emerged for other-faces or in controls. Encoding recovered rapidly once explicit memory expectations were introduced, indicating intact basic encoding capacity. These findings suggest that subthreshold depression is associated with a specific impairment in incidentally encoding self-face identity. This impairment likely stems from a negative self-concept that weakens self-face salience under incidental encoding conditions. By capturing this selective encoding failure, the present study reveals that the self-processing deficit in subthreshold depression can arise at the gating stage between attention and working memory consolidation.

It has been proposed that bilinguals have better executive function (EF) arising from the constant selection of one language while inhibiting the other, and gray matter has been found to differ in bilinguals in regions linked to EF (frontal-parietal and subcortical structures). Attention Deficit Hyperactivity Disorder (ADHD) is associated with poorer EF and neuroanatomical differences underlying EF. Given the EF advantage in bilinguals, we investigated whether a bilingual experience affects EF performance and brain structure differentially in those with ADHD. Using the Adolescent Brain and Cognitive Development Study, we compared early Spanish-English bilinguals and English-speaking monolinguals with and without ADHD. ANOVAs for the Flanker, Working Memory, and Card Sort Tasks revealed no main effects of Language Experience (Bilingual versus Monolingual), a main effect of Diagnostic Group for Card Sort (ADHD worse than Controls), and no interaction effects on performance for any task. ANOVAs for gray matter volume (GMV) revealed a main effect of Language Experience in many regions, a main effect of Diagnostic Group in some regions, but no interactions. GMV in left thalamus was affected by both ADHD and bilingualism, but the effect of ADHD was not significantly diminished or enhanced by the dual-language experience. For cortical thickness, there was a main effect of Language Experience in several regions, no main effect of Diagnostic Group, and no interactions. Taken together, bilingualism has some impact on EF performance, a strong impact on neuroanatomy, but there was no disproportionate impact by bilingualism on the differences caused by ADHD for any measure. Research HighlightsExecutive function and brain structure differ in ADHD and in bilinguals, prompting the need to investigate interactive effects. Bilingualism did not disproportionately affect performance differences in ADHD for executive function, nor for gray matter volume or for cortical thickness differences in ADHD. Gray matter volume was less in ADHD than non-ADHD, as well as greater in bilinguals than monolinguals in the left thalamus, but without interaction effect. These independent effects indicate that the brain basis of ADHD is not impacted by a dual-language experience.

Pleasurable urge to move to music is often referred to as groove. Although previous studies have shown an association between the supplementary motor area (SMA) and the groove experience, its causal role remains unclear. Here, we investigated whether the SMA is causally involved in groove experience during music listening using repetitive transcranial magnetic stimulation. Fifteen healthy participants completed three sessions on separate days: excitatory stimulation (intermittent theta burst stimulation; iTBS) over the SMA, inhibitory stimulation (continuous theta burst stimulation; cTBS) over the SMA, and sham stimulation (iTBS or cTBS) over the vertex. After each stimulation session, participants listened to five high-groove and five low-groove musical excerpts and rated urge-to-move and pleasure on a 0-100 scale. Heart rate was additionally recorded as an exploratory physiological measure during music listening. Linear mixed-effects models (LMM) showed that pleasure ratings, but not urge-to-move ratings, were higher following both iTBS and cTBS compared with sham stimulation. In exploratory LMMs, reduced log-transformed heart rate variability (HRV) significantly predicted higher pleasure ratings. These findings suggest that SMA stimulation modulates the pleasurable component of the groove experience, likely via network-level mechanisms rather than a simple linear relationship between SMA excitability and pleasure. They also raise the possibility that reduced parasympathetic activity, reflected by lower HRV, mediates the stimulation-related increase in musical pleasure. Future studies should investigate the causal roles of other brain regions as well as clarify the directionality between autonomic changes and the groove experience.

Singing is an innate human behaviour present across cultures and the lifespan. Despite lacking direct biological advantages, its ubiquity suggests that it is intrinsically rewarding. This research aimed to investigate the underlying factors that explain variability in sensitivity to deriving reward and enjoyment from natural singing in the general population. In Study 1 (n = 606), an initial pool of items describing daily, non-professional singing behaviours were administered to an international adult sample. Exploratory factor analysis revealed a unidimensional structure of 20 items with acceptable model fit, organized into five facets representing distinct domains of singing-related rewards: 1) pleasure and emotional evocation, 2) social singing reward, 3) singing frequency, 4) mood regulation through singing, and 5) inattentional singing during routine tasks. In Study 2 (n = 430), confirmatory factor analysis in a new sample supported this structure. When both samples were combined (n = 1036), the unidimensional model defined by these five facets showed acceptable to excellent goodness-of-fit indices, supporting the conceptualization of singing reward as a multidimensional construct with differentiated facets. This led to the Barcelona-Aarhus Natural Singing Engagement Questionnaire (BANSEQ), which demonstrated excellent reliability ( = .94) and population-level stability. Study 3 (n = 1036) tested the convergent validity of BANSEQ with measures of music reward and engagement and identified sociodemographic and psychological correlates across the five facets of singing reward. Overall, these findings characterize the sources of individual differences in the hedonic experience of natural singing and propose BANSEQ as a robust psychometric tool for its assessment in the general population.

Response inhibition, the ability to suppress contextually inappropriate actions, is a cornerstone of cognitive control and is commonly assessed using paradigms such as the go/no-go task. However, traditional go/no-go paradigms rely on binary outcomes such as commission errors, which offer limited insight into the dynamic, graded behavioral adjustments underlying successful stopping. The present study developed a novel mouse-tracking go/no-go paradigm with a dynamic start to capture inhibitory processes during ongoing execution. Twenty-three healthy young adults completed the task in two sessions separated by approximately one week to evaluate the test-retest reliability of standard behavioral measures (error rates and reaction times), and three kinematic features: path length, mean velocity, and mean acceleration. Results revealed robust differences between go and no-go trials across all measures. Successful inhibition was characterized by significantly shorter path lengths and reduced mean velocity and acceleration compared to go trials. Critically, all measures demonstrated moderate-to-good test-retest reliability across sessions, with intraclass correlation coefficients ranging from .75 to .85 for go trials and from .59 to .83 for no-go trials. These findings establish construct validity and psychometric reliability of the current mouse-tracking go/no-go paradigm. The demonstrated stability of these measures provides the methodological foundation for their use in cross-sectional, longitudinal, and intervention research targeting inhibitory control.

Visual working memory (vWM) is often linked to conscious experience and visual imagery, but it is typically described as a system that stores separate, independent items. These assumptions are difficult to reconcile, given the unified nature of conscious experience. Here, we test the hypothesis that vWM relies on at least two distinct representations: an underlying, unconscious memory trace and a consciously accessible, integrated representation. A total of 216 participants performed a change-detection task, in which they rated their perceptual awareness of the memory display during the maintenance interval. Critically, we manipulated the statistical properties of the displays (average item size and size variability) to probe sensitivity to unified ensemble-level structure. Results revealed a dissociation between subjective and objective measures. Perceptual awareness increased for displays with larger, more variable items, whereas objective performance improved for displays with smaller, less variable items. Despite this difference, subjective awareness still predicted performance, and even incorrect responses showed consistent biases rather than random guesses. Importantly, individual differences in imagery vividness (VVIQ) were selectively associated with subjective awareness and estimation bias, but not with objective correctness. These precision biases were further shaped by display statistics, suggesting that multiple representations can guide behavior. Together, our findings support a reinterpretation of vWM performance in which task responses can draw on both unconscious and consciously accessible representations. One possible explanation for these behavioral patterns is that subjective experience reflects integrated, ensemble-like representations, while objective performance depends more strongly on item-specific information. Public significance statementsWorking memory allows us to temporarily hold and use information, and differences in this ability are closely linked to broader cognitive skills such as intelligence. This study shows that these differences may not depend only on how much information people can store, but also on how they experience it: some individuals appear to rely more on consciously accessible, image-like representations, especially when memory is uncertain or prone to error. By demonstrating that subjective experience and the vividness of imagery can shape behavior independently of objective accuracy, these findings suggest that how we use memory may be as important as how much we can store, with implications for understanding individual differences in cognition.

The thalamus is essential for learning, dynamically engaging with other subcortical and cerebral cortex regions throughout the learning process. Here, the thalamus serves as a critical connector hub and synchroniser within the thalamocortical system of the brain. However, whilst higher order thalamic nuclei are known to be particularly important for this process, the exact contributions of individual higher order and first order thalamic nuclei, alongside their individual involvement with cortical networks and subcortical regions, remains unexplored within the initial phase of learning. In light of this, we analysed fMRI data obtained within a paradigm which is designed to examine initial learning processes within feedback-driven stimulus-response learning, in order to explore thalamic contributions. We investigated dynamic learning-related functional connectivity alterations between various thalamic nuclei with other subcortical regions and cortical networks. Our results show that the initial phase of learning was associated with: (1) decreasing functional connectivity between thalamic nuclei and frontoparietal and cingulo-opercular networks, (2) increasing functional connectivity between thalamic nuclei with default mode and salience networks, (3) decreasing functional connectivity between thalamic nuclei and the putamen, and (4) decreasing functional connectivity amongst higher order thalamic nuclei. Furthermore (5) these dynamic alterations were associated primarily by mediodorsal thalamus. Altogether, these results indicate that higher order thalamic nuclei play a crucial role within initial learning and in the generation of novel goal-directed behaviour. This was demonstrated through enhanced functional connectivity with selected cortical networks which drive goal-directed behaviour, alongside decreased functional connectivity with striatal regions which drive motor selectivity.

Pig vocalizations convey information about the emotional states of individuals, varying with arousal and valence. Studies show that different call types reflect distinct emotional contexts and social interactions for the receivers. However, little is known about the brain mechanisms behind the perception of conspecifics vocalizations. This study used BOLD fMRI to explore how pigs brains respond to emotionally varied vocalizations, with the aim to identify activity in regions linked to emotion, reward, and social processing. Eight healthy 2-month-old pigs underwent auditory brainstem response (ABR) testing and BOLD fMRI to assess brain responses to pig vocalizations with different hedonic valence. Sounds were delivered via MRI-compatible earphones, and imaging was performed on a 1.5T scanner. Data were analyzed using voxel-based and ROI-based statistics in SPM12 with small volume correction (SVC). Due to hearing anomalies or MRI artefacts, only 5 pigs were included in the final analysis. Functional MRI revealed that vocalizations activated regions of the auditory pathway and the left amygdala (pFWE at peak < 0.05 after SVC for all), with specific differences between positive and negative sounds. Clusters of activated voxels covering part of hippocampal areas, caudate nuclei and putamen were found with both positive and aversive vocal sounds. Limbic regions, including the amygdala and insula (p<0.05), as well as the right hippocampus after SVC (pFWE = 0.015) were uniquely engaged during the perception of negative conspecific vocalizations, indicating distinct processing based on emotional valence. This study shows for the first time that piglets brain can process and differentiate emotional vocalizations from other pigs, even under general anesthesia. Positive and negative vocal sound playbacks activated distinct brain regions related to hearing, emotion and reward. These findings highlight pigs cognitive and emotional processing of vocal cues. This study is part of a wider research program aimed at developing the fMRI protocol with acoustic stimulation in juvenile pigs.

Summary paragraphA hallmark of learning is the need for sensory stimuli (Ginns, 2015; McGraw et al., 2009; Reinwein, 2012; Spence, 1950) so that learning is fundamentally based on sensory input signals affecting behaviour, physiology, and neurology. If behavioural measures of learning can be causally linked to physiological and neurological variables, a broader understanding of the mechanisms related to learning in schools, learning disabilities, and learning and health issues may emerge (McGraw et al., 2009). Despite decades of research on the physiological/neurological variable of sympathetic activation, learning, and achievement (Horvers et al., 2021), any causal relation remains unclear (Cowley et al., 2014; Mason et al., 2020; Pijeira-Diaz et al., 2016; Sung et al., 2023; Yu et al., 2024) and issues with instrument validation remain (Costantini et al., 2023; Hu et al., 2024; Milstein & Gordon, 2020; Van Der Mee et al., 2021). Here we investigate the effect of sensory input on sympathetic activation by using validated instruments for skin conductance measurement (Batista et al., 2019) and whether sympathetic activation is connected to learning in a cognitive laboratory context and an ecologically valid classroom context. In both contexts, we found a physiological variable which correlated with learning and that sensory input affected this variable while student movement did not. These sensory inputs varied depending on the different instructional activities the students participated in. Together, these findings bring us one step closer to a model linking sensory input to behavioural, physiological, and neurological variables.

Time perception difficulties are frequently reported in Autism Spectrum Disorder, yet empirical findings remain inconsistent. A key methodological limitation is the failure to separate perceptual sensitivity from decision-making strategies. We applied Signal Detection Theory (SDT) to a subsecond duration discrimination task (100 and 500 ms) in 65 non-clinical adults varying in autistic traits, assessed via the Autism-Spectrum Quotient (AQ) and a Principal Component Analysis (PCA) of its subscales. Autistic traits did not predict reduced perceptual sensitivity (d'): temporal discrimination remained intact across the full autism-trait continuum, with Bayesian analyses providing converging evidence against a perceptual deficit. Instead, a PCA-derived cognitive component -- combining heightened Attention to Detail with reduced Imagination -- was systematically associated with a shift in decision bias (c). Individuals with this profile showed a graded attenuation of standard-based anchoring, with ordinal position progressively filling the gap. This shift operated consistently across both temporal scales, as confirmed by trial-level generalized linear mixed modelling, and reflects a quantitative redistribution of anchoring weight rather than a categorical switch in strategy. These findings reframe temporal "rigidity" in ASD not as a perceptual deficit, but as a suboptimal yet internally consistent decision-making style favouring within-trial information over accumulated representational knowledge. Lay AbstractMany autistic people report difficulties with time in daily life, but scientists have long disagreed on whether this reflects a genuine perceptual problem. This study found that autistic traits do not impair the basic ability to judge duration. Instead, people with more autistic traits tend to rely on which event came first, rather than accumulating experience across trials to refine their judgments -- a less effective but internally consistent strategy.

This study examined the utility of HRV detrended fluctuation analysis alpha-1 (DFA1) to assess readiness-to-train and exercise durability under varying acute training loads. Nineteen trained cyclists completed two 20-minute time-trials (TT) under rested and fatigued conditions. DFA1 was measured during a standardized warm-up (WU), 20-min TT, and standardized cool-down (CD). Power output (PO) and DFA1 responses were compared across conditions, and associations with performance and fitness (W/kg) were examined. DFA1 values declined with increasing WU and CD exercise intensity (p<0.001) and were significantly attenuated following the 20-min TT (p<0.001). While DFA1 profiles did not differ significantly between rested and fatigued conditions, lower pre-TT DFA1 was associated with reduced TT performance (p=0.022; r=0.55), suggesting relevance to training readiness. Additionally, an 18% decline in DFA1 between 10- and 20-min during the TT (p=0.031), and lower post-TT values at matched intensities were observed (p<0.001), indicating physiological perturbation from the 20-min TT. Fitter participants exhibited lower DFA1 values during the 20-min TT (p<0.001; r=-0.77), suggesting a greater capacity to sustain physiological stress. While DFA1 is responsive to exercise intensity and stress, offering potential to assess training readiness and durability, more robust fatigue protocols are needed to validate DFA1 as training load monitoring tool.

Confirmation bias impacts judgments and decisions across a range of domains including finance, policy and science. Here we examine whether explicitly labelling information as true or false disrupts a core underlying computational mechanism that can generate this pervasive bias - asymmetric learning. Human participants (Study 1: N=47; Study 2: N=57) completed a 2 alternative forced choice (2AFC) task previously used to test for the presence of confirmation bias. Participants made choices between pairs of options that could win or lose money and received either factual or counterfactual feedback after each choice. We introduced a key novel feature into the task - providing explicit cues that signalled to participants whether feedback they had seen was true (verified) or false (debunked). Learning in response to feedback was attenuated under false compared to true labels but was present under both. Fitting participants choices to computational models enabled us to examine how sensitivity to the feedback varied as a function of both the label (true/false) and confirmation (confirmatory/disconfirmatory). This revealed a distinct pattern of learning rates typical of confirmation bias (enhanced learning from positive prediction errors for chosen options and from negative prediction errors for unchosen options) in response to both true and false labels. The findings highlight how confirmation bias plays an important role in the effectiveness of interventions designed to verify true and/or debunk false claims. Verification is less likely to succeed when information disconfirms prior beliefs. Conversely, debunking false claims is unlikely to succeed when the information confirms ones prior beliefs.