Communications Psychology

Confidence evaluates the likely accuracy of a current decision. However, to be maximally informative about accuracy, confidence judgments should incorporate information about ones broader decision tendencies, such as their propensity to favor specific alternatives. We distinguish bias-aware confidence, which considers such tendencies, from bias-blind confidence, which relies only on evidence available on the current trial. To adjudicate between bias-aware and bias-blind confidence, we identified a signature of bias-aware confidence: the down-weighting of confidence for alternatives that a participant is biased toward. We then used a large dataset (N = 200) spanning 4- and 8-choice digit-classification tasks to show that humans reliably exhibit this signature of bias-aware confidence. This effect was reduced under speed pressure and could not be explained by guessing. In contrast to the human results, artificial neural networks (ANNs) trained for object recognition lacked this signature of bias- aware confidence. Importantly, augmenting ANNs with a metacognitive module that allows confidence to take the networks biases into account led to the emergence of human-like bias- aware confidence. These findings show that human confidence incorporates not only information from the current trial but also longer-term decision tendencies, and that this capacity - absent in standard ANNs - can be conferred through specialized metacognitive mechanisms.

Healthy older adults are more susceptible to false memories than young adults. Traditional false memory paradigms leverage semantic overlap, shared meaning, to induce false memories, but experiences can also overlap temporally whereby they occur close together in time. Prior work shows that older adults have impaired episodic memory, memory for events within a spatiotemporal context, corresponding to an overall shift toward semantic memory and away from episodic memory across the lifespan. We hypothesize that compared to young adults, older adults rely more heavily on semantic versus episodic information, which promotes false memory. We collected behavioral data in young and older adults performing an old/new recognition memory task in which we manipulated the degree of semantic and temporal overlap between study words and included critical lures, unstudied words that semantically overlap with study words. We find that whereas young and older adults are similarly reliant on semantic relative to episodic information to support false memory, the two age groups differ in their reliance on semantic relative to episodic information to support true memory. These results suggest that differences in the orientation of attention -- toward semantic vs. episodic information -- may underlie age-related memory changes.

Where and how we move our eyes through a natural scene depends jointly on the scene and on the viewer. How the spatial and temporal organization of viewing changes across the lifespan, and whether those changes relate to memory, remains unclear. We recorded eye movements from a lifespan cohort (N = 179, ages 5-79) during free viewing of naturalistic scenes, then tested recognition across graded levels of image degradation. Characterizing each observer by how closely their viewing corresponded to that of age peers, young adults, and a stimulus-driven salience model, we found a developmental dissociation: consistency in where the eyes were directed increased monotonically with age, whereas consistency in how they moved -- saccade direction, length, and fixation duration -- followed an inverted-U peaking in young adulthood. Recognition sensitivity followed an inverted-U of the same form. Across all three reference frames, typicality in how the eyes moved, but not in their spatial targeting, predicted recognition.

Bayesian decision theory proposes that people make statistically rational decisions by combining prior knowledge with sensory information (likelihoods). This framework successfully explains many aspects of human behaviour. However, debate persists over whether people perform precise Bayesian computations (i.e., explicit Bayesian strategy) or rely on less demanding strategies - such as approximations or heuristics - that produce Bayesian-like behaviour (i.e., implicit Bayesian strategy). To address this, we examined people's sensitivity to metamers: different prior-likelihood combinations yielding identical optimal policies. An explicit Bayesian observer would show a temporary performance drop immediately after a switch of prior-likelihood combination, followed by recovery, reflecting prior updating. In two studies, we trained participants to estimate hidden target locations drawn from a Gaussian prior. On each trial, scattered dots provided likelihood information. Over time, participants learned the prior and combined it with likelihood information to infer target locations. We then covertly introduced an untrained prior-likelihood metamer. Unlike explicit Bayesian observers, participants' performance declined after the switch and persisted throughout the untrained pair presentation. This finding challenges strict Bayesian interpretations of task performance and suggests that participants rely instead on likelihood-sensitive strategy that is neither explicit Bayesian nor does it not fully integrate prior information. Our study demonstrates how metamer manipulations can distinguish behaviour that merely appears Bayesian, from behaviour genuinely produced by Bayesian computations, and calls for the use of metamers for ruling out alternative explanations of Bayesian-like behaviours.

Sleepiness is a leading proximate cause of drowsy-driving fatalities, medical errors and industrial accidents, yet it has resisted mechanistic prediction; although it arises from well-characterized sleep-wake physiology, it is experienced as a subjective state and has lacked a quantitative link to the underlying dynamics. We previously showed that subjective sleepiness maps linearly, with a protocol-invariant form, onto the signed distance H - H+ between the homeostatic pressure H and the circadian-modulated sleep-onset threshold H+. This single quantity predicts sleepiness accurately but is mechanistically ambiguous: the same value can arise either because H sits far from the boundary or because the threshold H+(t) has shifted with circadian phase, and these two origins call for entirely different interpretations and interventions. Here we resolve this ambiguity by decomposing H - H+ into two mechanistically separable axes-intensity and phase. The intensity axis is the time-averaged margin [<] H - H+[>], set by how far, on average, H sits from the sleep boundary: slowed homeostatic accumulation accounts for the paradoxically blunted sleepiness of older adults, and pharmacological suppression of H accounts for the dose-dependent alerting effect of caffeine. The phase axis is set by the circadian modulation of H+(t): under a forced-desynchrony protocol, in which the pacemaker free-runs and the homeostatic and circadian processes are experimentally decoupled, sleepiness tracks the circadian profile of H+(t) across all phases while the intensity mapping itself remains unchanged-a clean dissociation of the two axes. By resolving felt sleepiness into these two physiological degrees of freedom, this framework renders previously isolated phenomena-aging, caffeine and circadian misalignment-commensurable within a single theory and provides a physiologically interpretable basis for prospective fatigue-risk prediction. Author summaryWhy people feel sleepy after sleep loss, or at particular times of day, remains difficult to predict from physiology alone. Sleep and wake are shaped by two interacting processes: a daily circadian rhythm and a homeostatic pressure that builds during wakefulness. In earlier work, we linked subjective sleepiness ratings to a simple geometric quantity-how close sleep pressure sits to a circadian sleep-onset boundary. That link is useful, but ambiguous: the same distance can arise either because pressure itself has changed, or because the boundary has moved with circadian phase. Here we use a computational model of the sleep-wake switch, extended to include the wake-stabilizing orexin system, to separate these contributions into an intensity axis and a phase axis. We find that aging and caffeine mainly alter how large the average distance to the boundary becomes, whereas forced desynchrony mainly alters how that distance varies across circadian phase. This dissociation offers a compact way to interpret several otherwise separate observations within one quantitative picture, and a step toward more physiologically grounded fatigue-risk assessment.

Longitudinal animal experiments generate behavior that is individual, history-dependent, and sometimes affected by ordinary procedural irregularities, yet analyses commonly reduce such records to pooled averages or synchronous trial-level explanations. We introduce history-structured forecasting as an auditable framework for determining whether an animals own preceding behavior carries predictive information beyond current-trial context. We applied the framework to 213,990 events from rats performing an auditory duration-discrimination task, using leakage-safe chronological forward-chaining, explicit trivial baselines, and controls that reset, exchange, or disrupt behavioral history. A transparent gradient-boosted model achieved 51.7% four-class accuracy, exceeding last-action persistence (40.9%) and prefix-derived subject-modal prediction (37.2%); decline-class AUPRC was 0.525 against a prevalence baseline of 0.303. Validation showed that the predictive advantage depended predominantly on each animals short-range sequential action history rather than group-level history, subject identity alone, or reward/correctness features, and strengthened on genuine choice trials. Forecasting remained informative across all 23 labeled animals, including six with recoverable records affected by incorrect training programming. These results revise the interpretation of rewarded give-up behavior while demonstrating how recoverable irregular records can be retained in transparent robustness analyses. History-structured forecasting offers a reusable open-science strategy for extracting reproducible evidence from imperfect longitudinal animal records without creating an artificially clean cohort.

Everyday action perception unfolds in complex contexts, requiring coordinated processing from low-level visual information to higher-level inferences about action types and social interactions. Aging is accompanied by sensory and cognitive changes, raising the question of how these processes may be altered. Here, we combined action similarity judgments with analyses of time-resolved and source-localized brain activity measured with magnetoencephalography (MEG) to investigate age differences in action perception when younger and older adults viewed naturalistic actions. Using cross-validated variance partitioning within a multivariate representational framework, three key findings were uncovered. First, affective-communicative features predicted similarity judgments better than, and independent of, visual and action-related features in both age groups. Second, neural processes in both groups followed a hierarchy from visual to action-related and affective-communicative features and recruited similar functional regions. However, older adults showed delayed visual processing but earlier affective-communicative processing, indicating selective prioritization rather than uniform slowing of subprocesses. Third, when sensory uncertainty was increased through visual blurring, older adults showed hierarchical reorganization, with affective-communicative features emerging earlier than action-related features, whereas younger adults preserved the original hierarchy. Together, these findings unveil adapted information prioritization in healthy aging, whereby socially meaningful information increasingly guides action perception when sensory input becomes unreliable.

Metacognition is the ability to reflect on and evaluate our own cognitive processes. It is often altered in psychopathology. Yet, the computational mechanisms underlying these alterations remain unclear. In this work, we extend Hierarchical Gaussian Filter (HGF) models to jointly fit trial-by-trial predictions and confidence ratings in a predictive inference task, providing an individualised characterisation on metacognitive processing. Applying our cognitive computational model to a large subclinical open dataset (N=430), we are able to achieve, on average, excellent fit of prediction responses [Formula] and a moderate to good fit of confidence ratings [Formula]. Analysis of experimental change-points revealed that our model accurately captures confidence self-reports dynamics around these change-points. Posterior parameter estimates reveal a negative effect of sensory input prediction errors and a positive effect of sensory input prediction precision on confidence ratings, respectively. In addition, we replicate state-of-the-art findings related to compulsivity as measured by a transdiagnostic factor score, such as inflated confidence and a decoupling of action updates (here, prediction errors) and confidence in compulsivity. These results demonstrate the robustness of our methodology and the potential of joint prediction-confidence modelling to uncover latent metacognitive alterations in psychopathology.

Learning in uncertain environments requires identifying the relevant associations between stimuli, actions, and outcomes and determining how strongly to update these associations. Although often treated separately, these components likely interact in the brain. We hypothesized that this interaction shapes individual learning rates according to cue-choice alignment and reward outcome, thereby improving discrimination between competing cues. We tested this hypothesis using a probabilistic learning task in which human participants predicted outcomes based on multiple cues and reward feedback. We measured gaze and manipulated cue saliency to assess and influence which cues were preferentially processed during choice and feedback. Computational modeling revealed that learning rates were selectively enhanced for cues supporting the chosen option after reward and for cues opposing it after no reward. This learning-rate asymmetry based on cue-choice alignment sharpened discrimination among predictive cues, increased robustness to noise, and improved performance. Moreover, differential gaze toward supporting and opposing cues predicted this asymmetry, which was causally altered by manipulating cue saliency. Together, our results suggest that attention provides a unifying mechanism for coordinating what we learn from with how much we learn, helping preserve distinctions among competing cues and bringing several learning asymmetries within a common framework.

Severe worry is a transdiagnostic syndrome associated with significant morbidity in older adults. In this study, we aim to infer worry-related mental states though brain activity timeseries. We acquired fMRI on two cohorts (N=116 and N=88), using an in-scanner worry induction and reappraisal task. We trained a recurrent long short-term memory (LSTM) neural network, using the first cohort as the train/validation and the second cohort as an independent test set. We predicted worry induction, reappraisal, and neutral states (area under the curve 0.89, 0.77, 0.91 for the test set and 0.78, 0.63, 0.81 for the independent set). The model was most accurate when participants reported high worry during the induction state. Dorsal attention network, and networks seeded on the anterior hippocampus, and supplementary motor area were most important for predicting worry states. The LSTM approach may have critical translational implications for identifying and treating severe worry in older adults.

The attentional blink is a well-known phenomenon illustrating the limitations of human attention: When two visual targets are presented in rapid succession, identification of the second target is often impaired. While the attentional blink is known to attenuate when targets share perceptual features or category membership, real-world objects are also linked through contextual associations, shaped by objects typically occurring within the same environments. Here, we devised an attentional blink experiment in which we orthogonally manipulated contextual and categorical relationships between the two targets while controlling for their perceptual similarity. As the key result, contextual associations facilitated identification of the second target but impaired identification of the first target. These findings suggest that contextual associations yield distinct benefits and costs for visual cognition, where enhanced attentional access to subsequent targets is traded off against increased interference between targets.

Newly acquired memories are initially fragile and are consolidated into long-term memory over time. Although consolidated memories were once thought to be resistant to interference, accumulating evidence shows that memory reactivation renders them transiently labile, making them susceptible to modification or interference before reconsolidation. Crucially, however, there is substantial variation in whether reactivated memories are disrupted by new information, remain protected from it, or even strengthened by it. The factors that guide this modification are largely unknown. To systematically investigate this, we examined motor memory interference using a classic A-B-A visuomotor rotation paradigm. Participants adapted to a 30-degree clockwise rotation (A) on Day1. On Day2, an interfering 30-degree counter-clockwise rotation (B) was introduced under varied conditions: directly without reactivation, after brief reactivation of A, after expression of A without feedback, or following a gradual transition from A to B. The final experiment used explicit contextual cues (a secondary follow-through target) to distinguish A and B trials. Contrary to the simple prediction that reactivation should increase vulnerability to interference, reactivating the original memory before introducing interference protected it, as evidenced by significant savings during relearning on Day3. In contrast, introducing interference directly, without reactivation, disrupted the original memory. This protection was consistent with a contextual-inference account: the large sensory prediction error experienced during the abrupt transition from A to B served as a latent contextual cue, signaling a new context and thereby shielding the original memory from being overwritten. Eliminating this prediction error through an immediate washout session with a similar error profile or through a gradual A-to-B transition abolished the protective effect and disrupted the original memory. Furthermore, when explicit contextual cues distinguished the two perturbations, memories were protected even in the absence of a salient prediction error. Our findings are consistent with a contextual inference account in which the fate of a consolidated memory, whether it is modified or protected, is shaped by the availability of explicit cues or latent signals such as sensory prediction error at the time when interference is introduced.

BackgroundThe Trail Making Test (TMT) is a widely used instrument for assessing executive functions due to its sensitivity. But, its traditional scoring, based solely on total completion time, limits its specificity by losing the rich behaviour required to complete the task, involving integrating visual search, motor planning and task switching. A computerised implementation of the TMT (cTMT) allows high-resolution cursor trajectories to be recorded, offering access to fine-grained features of the trajectory, while an online administration improves accessibility and statistical power. ObjectiveThis study aimed to extract high-resolution cursor trajectory features from an online cTMT and evaluate their capacity to predict individual differences in core executive functions, such as visual working memory (VWM), inhibitory control and age, using machine learning, as well as validating the feasibility of a fully online data acquisition pipeline as a basis for digital biomarkers. MethodsParticipants completed an online battery comprising the cTMT and three validation tasks: the Change Detection Task (CDT), the Stop-Signal Task (SST) and the Go/No-Go task (GNG). A total of 104 features (26 features x Part A/B x whole-trial/first-10-targets) were extracted from cursor trajectories, including trajectory profiles and segmentation into latent states: Search, Travel and Hesitation. Regression models were trained within a nested Leave-One-Out cross-validation framework with inner 10-fold hyperparameter tuning, feature selection and standardisation applied strictly within folds. Performance was assessed via mean absolute error (MAE), normalised error (MAE/SD) and permutation testing; SHapley Additive exPlanations (SHAP) were used to characterise feature importance. ResultscTMT features strongly predicted age across all models (p < .001), with MAEs roughly one-third lower than the targets dispersion, driven predominantly by distance-based "circuitousness" metrics from both parts. GNG accuracy and c-coefficient were both significantly predicted, but with a dissociated pattern: accuracy was best explained by Part B (alternation) metrics, whereas the c-coefficient was almost exclusively predicted by Part A (simple sequencing) metrics. SST response time (SSRT) was not significantly predicted by any model. VWM, characterised by the mean Cowan s K, was significantly predicted mainly by the more complex models, and involving state transitions and search phases in both Part A and B. ConclusionsMoving beyond completion time, cursor trajectory dynamics from an online cTMT provide a rich behavioural signal for predicting age, VWM capacity and distinct aspects of inhibitory control. The dissociation between Part A and Part B predictors supports differentiated cognitive processes within the TMT and positions the cTMT as a scalable, portable digital biomarker with promise for computational psychiatry and personalised neuropsychology.

Working memory is capacity-limited, but interactions with episodic memory may offset this constraint. We tested moment-by-moment contributions of episodic representations to working memory by combining the N-back and Mnemonic Similarity tasks. Thirty-one participants, undergoing eye-tracking, first encoded items in a one-back task, classifying them as "same" or "similar" to their predecessor. In a subsequent two-back task, mnemonic discrimination showed a graded, item-specific benefit of prior experience: performance was best for previously compared items, whereas recognition of identical repeats was unaffected. Successful discrimination of previously compared items was accompanied by greater pupil dilation, gradually emerging gaze patterns resembling those elicited by their similar pair-mate, and higher gaze-similarity between one-back and two-back target viewing. Diverging gaze patterns between pair-mates during one-back further predicted two-back discrimination. These findings challenge working memory's characterization as an isolated system, demonstrating how it recruits episodic computations - encoding distinct traces, predicting upcoming content, and reinstating it at retrieval.

Attention enables the prioritisation of task-relevant information, whether encountered in the external world or maintained as internal representations. While the mechanisms of attention have been extensively studied within perception and working memory, everyday cognition often confronts us with competing demands from both domains simultaneously. How attention is divided under such cross-domain demands remains poorly understood. Here, participants performed a combined perception and working-memory task in which an informative cue appeared between a working-memory display and a subsequent perceptual display. On most trials, this cue simultaneously indicated two items for prioritisation: either two encoded working-memory items or two upcoming perceptual items (within-domain attention), or one item from each domain (cross-domain attention). Combining behavioural measures with electroencephalography allowed us to characterise how dividing attention across domains shapes performance and neural activity relative to dividing attention within one domain. Behaviourally, we observed a striking asymmetry: perceptual performance benefited from cross-domain versus within-domain attention, whereas working-memory performance showed the opposite pattern. Mirroring this behavioural imbalance, time-resolved decoding revealed distinct cross-versus within-domain competition in both perception and working memory, suggesting that external and internal attention are neurally separable even when engaged simultaneously. This competition between domains was also evident in neural markers of spatial attentional orienting: while initially impaired during cross-domain attention, orienting progressively favoured external over internal information. Together, these findings show that when perception and working memory compete, attention is not divided evenly. Instead, cross-domain attention constitutes a distinct attentional state, with its own prioritisation dynamics and neural representation. Significance statementPerception and working memory are typically studied as separate targets of attention, yet real-world behaviour requires continuous negotiation between what is currently available in the external environment and what is held in mind. This study addresses how that negotiation unfolds when both sources of information become relevant at once. By directly comparing divided attention across versus within domains, we show that competition between perception and working memory is not neutral: it produces asymmetric behavioural consequences, distinct neural states, and a progressive bias in attentional prioritisation towards upcoming perceptual input. These findings suggest that cross-domain attention is not a balanced extension of within-domain attention, but a domain-biased prioritisation regime in which perception and working memory systematically trade off against each other.

Resting-state electroencephalography (rsEEG) yields robust indices of ageing, notably individual alpha peak frequency (iAPF), alpha power, and the aperiodic exponent. Whether these markers reflect stable traits or shift with cognitive exertion remains unresolved, with direct consequences for lifespan and clinical research. We parameterised periodic and aperiodic rsEEG activity before and after cognitive tasks in a lifespan cohort (N = 390, aged 20-70), a five-year longitudinal follow-up (N = 100), and an independent older-adult dataset completing a different task (N = 71). Across datasets, cognitive exertion produced lifespan-wide iAPF slowing and increase in associated power. Notably, aperiodic shifts were age-dependent, with post-task steepening of the exponent in younger adults that progressively flattened with advancing age, resulting in a stronger effect of age on post-task exponents. Our results demonstrate that widely used spectral metrics exhibit acute state-dependency and post-task recordings offer a promising translational framework for indexing individual differences in healthy ageing and pathology. Trial registrationClinicaltrials.gov: NCT05155397

Webers law is a rare quantitative regularity in psychology, yet its origins remain debated. Here we provide causal evidence that it arises from the more fundamental principle of efficient coding. This principle posits that representational resources are allocated according to stimulus frequencies: distributions skewed toward smaller stimuli thus result in discriminability decreasing with magnitude, as in Webers law. Skewing frequencies in the other direction--making large magnitudes more frequent than small ones--enabled us to invert this pattern, and to break Webers law. In discrimination tasks with three different sensory modalities, human subjects discriminability across stimuli was sensitive to the stimulus distribution, and this adaptation improved task performance. These findings establish efficient coding as a dynamic, organizing principle, explaining when and why Webers law holds.

Network measures of the ageing connectome are dominated by magnitude: connection strength and density decline, and the topological summaries built on them decline with them. Whether the geometry of the network follows the same course is not known, because the quantities in common use do not separate how strong a connection is from how it sits among the connections around it. We computed the Ollivier-Ricci curvature of every edge in structural connectomes from 307 participants spanning the adult lifespan, a quantity defined by optimal transport between the neighbourhoods of connected regions, and asked how it changes with age. The total geometric separation between within-network and between-network connections did not change across seven decades. Underneath that constancy, individual network pairs moved substantially and in opposite directions, gaining curvature around the salience and ventral attention system and losing it between the control and default mode networks. Curvature and connection strength reached half of their age-related variation almost four decades apart, and a small set of prefrontal nodes moved against the global trend. Ageing appears to conserve the local redundancy of the structural connectome in total while relocating it, on a timescale distinct from that of connection strength.

Response inhibition is a key control function that allows humans to perform safe, goal-directed behaviors. The dominant behavioral-computational model holds that response inhibition fails when the inhibition process is too slow to intercept unwanted movements. However, many have hypothesized that some inhibitory failures instead result from a failure to launch the inhibition process altogether. Since no method exists to identify individual trigger failure (TF) trials, they are hitherto a largely hypothetical phenomenon. We combined Bayesian process-mixture modeling with likelihood ratio testing and jackknife resampling to identify TF trials in 253 humans. We find that TF indeed represent a separate category from other inhibitory failures. Unlike other inhibitory failures, TF do not result from premature responses. Furthermore, TF lack a stop-signal P3 event-related potential, a neural index of response inhibition. Surprisingly, TF do not result from perceptual/attentional lapses. Thus, TF are a qualitatively distinct class of executive failure during response inhibition.

Navigating daily tasks requires working memory to retain information, formulate plans, and execute goal-directed actions. While frequent distractions may momentarily disrupt planned actions, individuals typically exhibit the cognitive resilience necessary to regroup and resume goal-directed behavior. How people adapt to these perturbations in dynamic environments remains unclear. To address this, we developed a working memory paradigm inspired by the arcade game Snake, in which participants navigated an agent to collect memorized targets while EEG and eye-tracking data were recorded. On each trial, participants encoded the location of one or two targets (apples), maintained them during a delay, and then guided a virtual agent (snake) to collect them. Critically, on 50% of trials, a secondary task introduced high-value novel targets that required immediate pursuit; these interruptions altered the agents spatial position, necessitating a re-evaluation of the original plan upon returning to the primary goal. Behaviorally, participants prioritized the target proximal to the agent and flexibly revised their collection order after distraction according to the agents updated position. Eye-movement analyses showed structured gaze sweeps during encoding that were consistent with efficient route planning. Representational similarity analyses of EEG data revealed that agent-centered object vectors were represented more strongly than absolute object locations during the delay. Following distraction, object vectors were recomputed relative to the agents new position, and representational strength was redistributed when the action plan was updated. Whereas neural representations were biased toward the distal, future-relevant target, gaze was preferentially directed toward the proximal, immediately relevant target, suggesting complementary roles for internal attention and external attention in multistep planning. During distraction, backward gaze sweeps revisited memorized target locations, indicating that replanning unfolded dynamically while the intervening task was still ongoing. These data demonstrate that prospective neural coding and attentional sampling coordinate to adapt behaviors to the shifting demands of goal pursuit in dynamic environments.