Cognitive, Affective, & Behavioral Neuroscience

Working memory (WM) is a core cognitive function that supports goal-directed behavior by temporarily maintaining and manipulating information. One of the most widely used paradigms for investigating WM function is the N-back task, and numerous neuroimaging studies have examined load-dependent neural responses using a variety of analytical approaches. However, most previous studies have focused on low-to-moderate load ranges (primarily 0-3-back), and it remains unclear how whole-brain activity patterns reconfigure across a broader range of WM demands, including conditions approaching capacity limits. In the present study, we investigated behavioral performance and whole-brain activity patterns across an extended N-back task ranging from 0-back to 7-back. Behavioral analyses revealed that discrimination sensitivity (d') decreased nonlinearly with increasing WM load, whereas reaction time (RT) exhibited an inverted-U pattern, peaking at intermediate load conditions. To characterize load-dependent whole-brain activity patterns, we computed relative activation maps by subtracting the participant-wise mean activation map across all conditions from each condition-specific activation map. Spatial similarity analyses with the Yeo 7-network templates revealed that low-load conditions showed relatively high similarity to default mode network (DMN)-related patterns. Similarity to the dorsal attention network (DAN) and frontoparietal network (FPN) was maximal at intermediate load levels, indicating load-dependent changes in network similarity profiles. High-load conditions were characterized by partial re-emergence of DMN-related patterns, accompanied by reduced DAN/FPN similarity. In addition, semantic similarity analysis using Neurosynth-derived semantic maps revealed relatively high similarity to default mode-related and self-referential representations under low-load conditions. Intermediate-load conditions showed strong correspondence with working memory- and executive control-related representations, whereas high-load conditions exhibited increased similarity to salience-, aversive/interoceptive-, and inhibitory-control-related representations. Together, these findings suggest that increasing WM load is associated not merely with stronger activation, but with changes in whole-brain activity patterns accompanied by nonlinear changes in network similarity profiles across levels of cognitive demand. Furthermore, the relative activation map-based whole-brain pattern analysis used in this study may provide a useful approach for evaluating changes in whole-brain state representations associated with cognitive load.

Bayesian accounts of autism propose that perception is less influenced by prior expectations and more strongly driven by incoming sensory information in autistic than non-autistic individuals, with this altered balance cascading through the cognitive hierarchy to also influence higher cognitive functions. However, empirical support for these accounts remains mixed. Previous work has mostly tested these ideas in the context of objective environmental statistics, but recent work suggests that it may be subjective experience of structure, rather than structure itself, that shapes perceptual processing. Characterising these subjective experiences in autistic individuals is therefore crucial for understanding predictive processing in autism. In the present study, we thus examined subjective experience of statistical structure in autistic and non-autistic adults and tested how this experience relates to perceptual decisions. Participants were exposed to statistical regularities between action cues and visual stimuli (shapes), and we measured their speed and accuracy in reporting which shape they had seen. At the end of the study, participants were asked to estimate the probability and rate their surprise for each action-shape combination. Autistic and non-autistic participants showed similar subjective probability and surprise ratings and a comparable relationship between these ratings and perceptual decisions. Across participants, subjective ratings explained perceptual decisions better than objective structure. Together, these findings show that autistic and non-autistic adults experience statistical structure similarly, with these experiences exerting a similar influence on perceptual decisions - therefore suggesting that subjective experience plays a comparable role in predictive processing in autistic and non-autistic adults.

Disordered eating attitudes exist on a continuum that extends well below clinical diagnostic thresholds, yet the cognitive correlates of this non-clinical variation remain incompletely understood. Previous research linking executive functioning to disordered eating in non-clinical samples has relied almost exclusively on self-report questionnaire measures of executive function, which show weak correspondence with performance-based assessments. This methodological reliance leaves open the question of how objective executive performance relates to eating behavior across the spectrum. The present study addressed this gap by examining the association between performance-based measures of executive function and disordered eating attitudes in a non-clinical sample of 243 university students via an online experiment, using a dimensional approach consistent with the Research Domain Criteria framework. Participants completed established neurocognitive tasks covering three executive function domains: working memory was assessed with Digit Span and an N-back task, inhibitory control with a Go/No-Go task, and cognitive flexibility with the Card Sorting Task. Disordered eating attitudes were indexed using the EAT-26 total score and its subscales. A notable correlation was identified between cognitive flexibility and disordered eating attitudes, while working memory and inhibitory control exhibited no such association. Overall, our findings provide evidence for associations between executive functioning and disordered eating attitudes in a non-clinical sample.

Cognitive flexibility is an executive function that allows individuals to adjust behaviour in response to changing environmental demands. We assessed volitional switching under uncertainty, without rule-based learning, in the Change Your Mind task. Nineteen patients with obsessive-compulsive disorder (OCD), 19 patients with attention-deficit hyperactivity disorder (ADHD) and matched control participants (20 per group) completed the task whilst undergoing a functional MRI scan. The task was a two-alternative forced choice paradigm where each stimulus was presented twice successively, with spurious feedback following the first presentation. This allowed participants the opportunity to repeat or change their response. Participants with ADHD changed their response more frequently than controls following a previously correct response, associated with reduced accuracy on the second trial. This was accompanied with smaller differences between change and repeat trials in the superior frontal gyrus, paracingulate gyrus and frontal pole compared to controls. Participants with OCD did not differ from healthy controls in their performance but exhibited greater activity on both change and repeat trials in the pre- and postcentral gyri than controls. These results point to distinct neurobehavioural differences in patients with ADHD and OCD underlying what is often termed more broadly inflexible behaviour.

Cognitive flexibility is the ability to change the way of responding when the demands of the environment change. This study tested how cognitive flexibility develops across the lifespan. We used a new computerized task that gives a continuous score instead of just right or wrong answers. 221 healthy adults aged 18 to 71 completed the Continuous-score Probabilistic Reversal Learning Test (CPRLT). We calculated mean absolute error and adjusted error for rule-based learning, and fitted a Rescorla-Wagner model to estimate each persons learning rate (alpha) for reward-based learning. All three scores have one breakpoint, performance improved rapidly from childhood to young adulthood, then declined slowly. Rule-based learning peaked around age 20. Reward-based learning peaked earlier, around age 18. This suggests that reward-based learning matures before rule-based learning. The pattern fits with brain development: reward circuits mature earlier, while prefrontal regions for rule-based learning develop later. Our continuous measure captured this difference, which binary tasks would miss.

Children often outperform adults in probabilistic statistical learning tasks, yet the mechanisms underlying this developmental advantage remain poorly understood. Here, we used eye-tracking measures of belief updating to examine how children and adults acquire and update predictions in a probabilistic sequence-learning task. Using the standard (oculomotor) reaction time measure, children showed stronger statistical learning than adults, replicating previous behavioral findings while revealing a more detailed profile of developmental differences in statistical learning. Critically, children updated their predictions more frequently: they were less likely to repeat previous predictions and more likely to shift their expectations in response to new input. Adults, in contrast, showed greater persistence, tending to maintain prior predictions even when those predictions were inconsistent with the underlying statistical structure. Despite these pronounced differences in updating behavior, the processing and use of prediction errors were remarkably similar across age groups. These findings indicate that developmental differences in statistical learning do not primarily arise from how prediction errors are computed, but rather from how prior beliefs and incoming information are weighted during belief updating. Children's enhanced learning may therefore reflect reduced reliance on stable priors and greater sensitivity to current sensory evidence, supporting a more exploratory learning strategy. Adults, by contrast, appear to favor an exploitative strategy that stabilizes existing predictions but reduces flexibility in probabilistic environments. More broadly, the results suggest that developmental changes in statistical learning may reflect age-related differences in how readily learners revise their predictions in response to incoming evidence. By integrating sensitive oculomotor measures with analyses that probe the mechanisms underlying belief updating, the present study provides a more fine-grained account of how predictive learning changes across development and offers a framework for reconciling previously inconsistent developmental findings in statistical learning.

Humans make emotional facial expressions and have a cardiac response when they catch themselves in a mistake or receive feedback about task performance. We tested whether rats exhibit similar visceral responses in the context of metacognition. We assessed heart rate variability (HRV) and machine learning-detected facial expressions as female and male rats detected and stopped in-progress mistakes and received post-choice rewards or error cues. HRV increased during internally detected mistakes, as well as in response to external error cues for both sexes. Errors were associated with an HRV response when parasympathetic tone was higher, while rewards were associated with an HRV response when sympathetic tone was higher. We observed sex-specific effects of cardiac interoception on cognitive control over real-time action correction, in that low parasympathetic tone was associated with reduced ability to stop in-progress mistakes exclusively in females. Rats made facial expressions during mistake detection and in response to task feedback. Outcome-related facial expressions were valence-specific, in that the facial expression after error feedback was delayed relative to the post-reward facial expression. Our results suggest that rats have a visceral experience during metacognitive monitoring.

Language production requires the coordination of multiple cognitive processes. The ability to anticipate and override a habitual response in favor of a contextually-appropriate response are key subprocesses of cognitive control which enable speakers to communicate effectively. Word retrieval involves the co-activation of semantically related alternatives from which the speaker must select the appropriate target representation. Although cognitive control mechanisms have been proposed to contribute to resolving semantic interference during language production, the nature of these control processes remain unclear. Studies investigating the temporal dynamics of cognitive control during decision making tasks have led to a distinction between two operating processes: proactive control, initiated prior to the occurrence of conflict, and reactive control recruited after conflict is detected. We investigated the roles of proactive and reactive control in resolving interference between competing linguistic representations during word retrieval. We analyzed congruency sequence effects combined with delta-plot distributional analyses to dissociate potential adjustments in proactive versus reactive cognitive control in a picture-naming task manipulating semantic context compared to a minimally-linguistic Stroop-like paradigm. Reaction time distributional properties following semantically related trials revealed the engagement of proactive control in semantic interference resolution during word retrieval in the PWI task. In contrast, reactive inhibitory control was engaged in resolving semantic interference following low conflict trials. This distinction was not present in the minimally-linguistic task, which did not appear to engage adaptive control to the same extent. These findings demonstrate that both proactive and reactive cognitive control mechanisms contribute to language production, and are engaged dynamically, adjusting trial-by-trial to resolve semantic interference during word retrieval. In addition, our study provides important insight into the comparison of language with other cognitive domains and positions linguistic paradigms as being instrumental in the study of cognitive control dynamics.

Attentional control balances proactive suppression of predictable distractors with reactive suppression of unexpected ones. Yet, how internal states such as alertness shape this balance is unclear. Using pupillometry and eye tracking across two probability-cueing experiments (conducted in 2024) with varying distractor prevalence, we distinguished tonic (baseline pupil size across blocks) from trial-level pupil size fluctuations (trial-by-trial residual variability in pre-stimulus pupil size). With moderate prevalence, suppression of frequent-region distractors developed gradually, whereas high prevalence induced near-immediate suppression. Behavioral measures (e.g., reaction times) were closely linked to tonic and trial-level pupil size fluctuations. Critically, both alertness components jointly influenced control: during early learning, heightened trial-level pupil size increased distractor capture and reduced target fixations, whereas later on, suppression shifted to a proactive mode resilient to trial-level fluctuations. Under high prevalence, this shift occurred faster. Notably, higher trial-level pupil size generally accelerated first target selection. These findings show that tonic alertness and trial-level alertness fluctuations dynamically regulate reactive and proactive control during statistical learning. Impact StatementThis study shows that people become better at ignoring predictable distractions over time, but that this improvement depends not only on what they have learned about the task environment, but also on their current level of alertness. By combining eye tracking and pupil measures, we found that temporary increases in alertness can sometimes help people orient more quickly to relevant information, yet during earlier stages of learning they can also make attention more vulnerable to distracting events. These findings suggest that successful focus in complex environments depends on a dynamic interplay between learned expectations and moment-to-moment fluctuations in mental state, with implications for understanding sustained attention in settings such as monitoring, driving, and other tasks that require people to stay engaged while resisting distraction.

Studying chess experts helps researchers understand how intensive practice shapes thinking skills. Cognitive flexibility is the ability to adjust thoughts when rules or tasks change. Working memory is the ability to hold and use information over short periods. This study compared cognitive flexibility and working memory precision between adolescent chess players and non-players. Twenty-four professional chess players and twenty-five controls completed two novel behavioral tasks. Chess players showed better accuracy in both tasks than controls. They adapted more efficiently when rules changed during a continuous learning task. They also remembered facial expressions more precisely in a working memory task. Learning rates in the flexibility task did not differ between groups. These results indicate that chess expertise may improve rule-guided flexibility and visual working memory precision in adolescents.

Learning is typically understood as a process driven by prediction errors, when outcomes differ from expectations. Yet it remains unclear whether outcomes that perfectly match expectations are psychologically and computationally meaningful. Here, we tested whether zero prediction errors shape affect, belief updating, and neural feedback processing in human reinforcement learning. Participants repeatedly predicted rewards in environments varying in uncertainty, with a subset of trial outcomes manipulated to exactly match their predictions. Zero prediction errors produced the highest momentary happiness, and computational modeling showed that behavior was best explained by a model in which zero prediction errors induce a distinct latent belief state that guides subsequent updating, particularly under higher uncertainty and in individuals with greater intolerance of uncertainty. Outcome-locked EEG analyses further showed that zero prediction errors elicited distinct P3-like responses, with residual neural activity predicting attenuated updating after zero prediction errors but enhanced updating after standard prediction errors. These findings suggest that perfect predictions are not neutral, but informative events that actively shape affect, behavior, and neural feedback processing.

Attention abilities, that are critical for most real-life cognitive task, can vary greatly across individuals. A plethora of behavioral and neural metric are commonly utilized to quantify attention; however, these often yield inconsistent and non-replicable results, raising questions as to which measures reliably account for and capture individual differences. To address this tension, here we employed a within-subject cross-paradigm design and quantified both behavioral and EEG-based neural measures associated with attention functioning, to test which measures converged across a gradient of artificial and ecological tasks. We found Inter-Subject Correlation (ISC), which quantifies the similarity in the pattern of neural response across individuals, captured consistent individual differences across both an artificial (Auditory Oddball) and ecological (Attention to Speech) task, with some correlation with performance. Moreover, we found that P300 neural responses to surprising events were qualitatively similar across artificial and ecological tasks, supporting their generalization across contexts. Interestingly, traditional cognitive-behavioral measures of attention - both from speeded response-time tasks and self-report of ADHD symptoms (ASRS) were not correlated with each other nor did they explain variance in neural metrics, nor were they explained by variation in general cognitive abilities (working memory or fluid intelligence). While these results demonstrate the shortcomings of many established measures of attention to generalize across contexts, they also point to the potential of neural measures, and specifically ISC, to serve as reliable indicators of individual differences and to bridge the gap between artificial and ecological studies of attention functioning.

Anxiety has been linked to difficulty sustaining engagement with ongoing tasks, even when continued engagement would yield greater rewards, yet the underlying mechanisms remain unclear. Here we examined how trait anxiety shapes sequential foraging decisions using a patch-leaving task grounded in the Marginal Value Theorem (MVT), a normative framework for explore-exploit decisions previously used to reveal altered computations in conditions such as problem gambling and attention-deficit hyperactivity disorder. Across two independent cohorts, participants adjusted patch residence times according to environmental opportunity costs, indicating preserved sensitivity to task structure irrespective of anxiety levels. Despite this, individuals with higher trait anxiety consistently left patches earlier and accrued fewer rewards. Drift diffusion modeling revealed that these deviations arose from reduced reward-driven evidence accumulation, rather than impaired environmental sensitivity or altered learning: trait anxiety reliably reduced the drift rate governing continued exploitation, providing a computational account of premature disengagement. This effect remained robust after accounting for pupil-linked arousal and baseline stress biomarkers, including salivary -amylase and cortisol, which independently constrained decision dynamics. Together, these findings identify reduced reward-evidence accumulation as a core mechanism through which anxiety promotes premature disengagement from rewarding environments.

Audiovisual cues ("bells and whistles") are ubiquitous in commercial gambling products. Pairing wins with sound and light cues in laboratory-based gambling paradigms increases risky choice, but the neurocognitive basis of this effect is unclear. Here we compared patterns of neural activation using functional MRI in healthy volunteers (n = 31) while they performed a two-choice lottery task. Reward-paired cues were either present or absent in a mixed-block, event-related design. As predicted, participants made riskier choices on cued trials. Choice latencies were also longer when cues were present, particularly on trials following a win. Activity within the nucleus accumbens and orbitofrontal cortex was greater during the decision phase when participants made risky choices. Nucleus accumbens signal was also greater when participants were anticipating risky outcomes, and in response to risky wins. Contrary to our pre-registered hypotheses, cue condition did not alter patterns of activity across any task phase, in either of these a priori regions of interest. As such, cue-induced risky choice does not appear to be driven by altered representation of risk or value within this canonically reward-sensitive circuitry. Instead, exploratory analyses revealed that the anterior insula was selectively activated by cued, risky wins. Such activation may signal the saliency of these events, or their emotional impact, and may reflect one mechanism through which cue-induced craving develops in vulnerable individuals.

The ability to orient or attend to sensory events is generally greater in response to visual and auditory cues occurring together than in response to single-modality cues occurring alone. In such cases the perceptual fusion of cross-modal stimuli (multisensory integration) depends on low-level features (e.g., location, intensity) and follows well established principles. However, less is known about multisensory integration mechanisms when behavioral responses are less direct and require top-down control. Here we investigate this in human participants using an urgent multisensory choice task that effectively dissociates stimulus-driven and goal-driven contributions to performance based on their distinct temporal signatures. Task conditions varied the modality of the cues (auditory, visual, or both), their location (left or right), and the rule defining the correct choice (look toward or away from a given cue). When spatially coincident cues were associated with the same response rule ("look away"), we observed multisensory enhancement and performance remained close to a statistical expectation as the choice process unfolded. However, when spatially disparate cues were associated with different rules but the same target, one cue dominated performance and the other produced crossmodal capture, i.e., low-level competition. The results indicate that the efficacy of multisensory integration is dictated by the stimulus-and goal-driven signals produced by each cue, with all four factors rapidly interacting in accordance to the dynamics of spatial attention. Significance StatementAuditory and visual stimuli located near each other in space and time are typically bound into a single sensory percept that draws attention most effectively. However, it is unclear whether such "multisensory integration" occurs during behaviors that go beyond directly attending or orienting to cue stimuli and require top-down control. We investigated this using a novel task design with which stimulus-driven and goal-driven contributions to performance can be accurately identified. We found that multisensory enhancement depends not so much on the complexity of the requested cue-response associations, but rather on the timing and alignment of the stimulus-and goal-driven signals derived from each cue (auditory and visual) -- similar to the way that such signals dictate the allocation of spatial attention.

Ambiguity represents a form of uncertainty in which outcome probabilities cannot be explicitly learned, making decisions dependent on emotional states and cognitive biases. Early-life stress (ELS) increases the risk of adverse mental and physical health outcomes and alters affective processing and learning. ELS may thus affect how ambiguous information is processed, which may depend on interactions with adulthood stress (AS) and mechanistically on bioenergetic mechanisms mediated by top-down cognitive control systems within the prefrontal cortex (PFC). The present study investigated the effects of AS in rats exposed to early maternal separation (MS), a rodent model of ELS, on a task assessing cognitive bias, together with putatively accompanying alterations in PFC mitochondrial function. Cognitive bias was assessed using an ambiguous cue task (ACT) in MS and non-separated control rats tested at baseline and following repeated unpredictable mild stress during adulthood. MS did not affect baseline cognitive bias but increased response latencies. Following AS, control animals showed a significant negative shift in cognitive bias, whereas MS animals were resistant to this shift. MS was also associated with greater PFC mitochondrial respiratory capacity and uncoupling of oxidative phosphorylation following AS. These findings suggest that ELS is associated with a recalibrated phenotype that buffers against the affective consequences of later stress. Enhanced PFC mitochondrial bioenergetics may underlie this resilience, highlighting the importance of developmental context in shaping affective-cognitive responses to stress.

The ability to seek reward and avoid punishment is a fundamental survival instinct. In natural environments, however, the statistics of rewards and punishments can change independently of one another. In addition, individuals experiencing anxiety and depression may be selectively biased to process rewards and punishments differently. Here, we examine how humans adapt their behavior in such dynamic environments, using a task where cues are associated with independently changing probabilities of rewards (wins) and punishments (losses). We demonstrate that participants dynamically adjust their learning rates based on the relative volatility of each valence. Neuroimaging reveals that this behavioral flexibility is supported by valence-specific segregation of volatility signals within distinct subregions of the anterior cingulate cortex (ACC: perigenual and dorsal). Furthermore, individuals with higher levels of anxiety and depression exhibit a relative reduction in loss-volatility learning adaptation, accompanied by less distinct neural encoding of win and loss volatility in both ACC subregions. Together, our findings indicate that flexible adaptation to separate reward and punishment contingencies relies on distinct, valence-specific tracking of volatility within the prefrontal cortex. These findings suggest a potential computational and neuroanatomical framework for understanding maladaptive learning in affective disorders.

The perception of timing has been investigated across short and long timescales, with the latter usually underrepresented. Previous accounts of supra-second timing have often emphasised dedicated neural signals, yet whether timing performance over longer durations reflects specialised temporal mechanisms or domain-general neural excitability remains unclear. We examined this question in an interval reproduction task (2 to 4 s) using EEG, decomposing neural activity into oscillatory (alpha, theta) and aperiodic components and relating both to behavioural performance. At the neural level, separate analyses were performed on the interval encoding epoch and the following delay period. Time-resolved analyses revealed a coordinated decrease in posterior alpha power and aperiodic offset during interval encoding. In contrast, interval duration did not produce consistent modulation of oscillatory or aperiodic activity during the delay period, providing limited support for a workload-based account of time duration. Across participants, higher baseline alpha power and aperiodic offset were associated with better timing accuracy, whereas trial-by-trial fluctuations in aperiodic activity, and to a lesser extent alpha power, predicted single-trial reproductions. The results suggest that temporal behaviour in the supra-second range is shaped by domain-general neural activity sustaining goal-directed task engagement, with oscillatory and aperiodic dynamics serving as complementary indices of this broader excitability state.

Purpose Postprandial sedentary behavior is associated with negative health effects and constitutes a large part of daily life in modern society. This study investigated how the timing of physical activity after eating influences glucose levels, cerebral and muscle oxygenation, cognitive performance, and well-being during subsequent sitting. Methods In a four-armed randomized crossover trial, healthy adults consumed four standardized meals separated by 48-hour washout periods. Each meal was followed by 2 hours of sitting combined, in random order, with one of four interventions: (1) sitting only, (2) 15 minutes of moderate intensity cycling immediately after eating, (3) 15 minutes of cycling 20 minutes after eating, or (4) three workload-matched five-minute cycling bouts during sitting. Interstitial glucose (continuous glucose monitoring), cerebral and muscle oxygenation (Functional near infrared spectroscopy), cognitive performance (Stroop test), heart rate, blood pressure, and subjective ratings were assessed every 30 minutes. Data were analyzed using repeated-measures ANOVA. Results Twenty participants (mean age 27.1{+/-}10.3 years, 12 females) completed the study. Cycling immediately after eating reduced mean glucose levels during postprandial sitting, while both 15-minute cycling bouts increased cerebral oxygenation. All active conditions enhanced muscle oxygenation. Heart rate and arousal increased with delayed cycling and active breaks. No effects were observed for blood pressure, cognitive performance, focus, or well-being. Conclusion A short bout of physical activity immediately after eating reduces postprandial hyperglycemia and improves brain oxygenation during sitting, whereas delayed activity and brief breaks increase physiological activation without cognitive or perceptual benefits.

Cortisol, our stress hormone, exerts widespread influence on neural activity. However, its influence on the aperiodic component of the electroencephalography power spectrum remains to be investigated. Given individual differences in the capacity to cope with stress and adversity, it also remains unclear whether trait resilience moderates this relationship. Hence, the present study examined whether individual differences in trait resilience moderates the association between resting cortisol and aperiodic activity. Participants (N=145) completed various self-report questionnaires (e.g., trait resilience). Electroencephalography was recorded over a 20-minute baseline period, followed by salivary cortisol collection. The results revealed a significant moderating effect of trait resilience in the occipital scalp region. Specifically, higher cortisol concentration was associated with flatter 1/f slopes amongst individuals with low trait resilience, whereas this association was reversed amongst those with high trait resilience. Overall, our findings highlight the role of individual differences in trait resilience in shaping hypothalamic-pituitary-adrenal axis-related neural dynamics.