Journal of Cognitive Neuroscience

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.

Introduction: Decision making for selecting an object or a course of action from possible alternatives largely depends on our perceptual ability modulated by attention. When multiple stimuli appear close together in time, processing one stimulus can temporarily impair the processing of another due to temporal limitations of attention. Observers frequently fail to detect the second target (T2) presented within a few hundred milliseconds after the first target (T1) in a stream of stimuli, which is commonly known as attentional blink (AB). Existing theories attribute this perceptual lapse to T1 processing, distractor interference, or transient attentional gating; however, the computations underlying suppressive mechanism remains unresolved. We investigated whether pupil-size could reveal the underlying mechanisms of AB and predict conscious perception on a trial-by-trial basis. Methods: Pupil diameter and gaze locations were recorded using an infrared eye tracker. Machine learning techniques were used to classify trials when T2 was detected versus when it was not, after correct identification of T1, during an AB task from the pupil dynamics, which also yielded attentional episode (AE) associated with each element in the stream of visual stimuli when deconvolved. Results: Cross-validating classifiers achieved near-perfect accuracy not only in distinguishing but also predicting perceptual outcomes on a single-trial basis. AEs exhibited greater power when T2 was detected than when it was missed; the differential power in AEs on a logarithmic scale was highly synced with the differential pupil size. Conclusions: Collectively, these findings establish a framework for predicting attention-driven perceptual outcomes from pupil-dynamics at finer time-scale.

Past studies using transcranial magnetic stimulation have shown larger motor-evoked potentials when people observe someone lifting a heavy object than when they observe someone lifting a light one. This means that observers may engage their own motor system in proportion to the perceived effort. However, the different responses during the observation of light and heavy objects may have been influenced by predictable trial sequences within blocked presentation, making it unclear whether corticospinal excitability reflects online processing of kinematics or is affected by top-down expectations. In this Registered Report, 57 right-handed participants passively observed videos of a precision grip and lift of heavy and light objects while receiving a single-pulse TMS to the left primary motor cortex during the lift phase of the movement. Motor-evoked potentials were recorded from the right first dorsal interosseous muscle. The study compared two main observation contexts: a predictable trial sequence in which repeated videos of the same lifts were presented in a blocked order, and an unpredictable one in which videos were presented semi-randomly and participants could rely only on kinematic cues to perceive the weight of the lifted object. In both conditions, the same videos of lifts of equivalent-looking heavy and light objects were used and only the order of presentation differed. Contrary to our predictions, in the blocked (predictable) condition, there was no significant difference in MEPs elicited by light and heavy lifts. In the unpredictable condition, participants showed greater corticospinal excitability during the observation of the light lifts compared to the heavy lifts. This suggests that in the absence of predictable information, the corticospinal system was sensitive to the observed kinematics, but contrary to previous findings, its excitability varied inversely with the object weight.

Laboratory stress tasks are widely used to assess individual differences in acute stress reactivity, yet it remains unclear how these responses correspond to stress experienced in everyday life. Here, we combined the Montreal imaging stress task (MIST) with ecological momentary assessment (EMA) over three months to assess acute and everyday stress in 67 healthy women. Greater within-person variability in everyday stress, but not average stress levels, were associated with stronger overall stress-related brain responses (b = 0.73, p = .039), with a whole-brain association particularly evident in the bilateral caudate (rROI = .32, pcluster.FWE < .001). Greater everyday stress variability was also associated with stronger stress-related functional connectivity between the ventromedial prefrontal cortex (vmPFC) and parietal and posterior medial regions (pcluster.FWE < .001). We conclude that acute neural stress responses relate more closely to fluctuations in perceived stress than to how stressed an individual feels on average. This suggests that laboratory stress tasks capture acute stress responsivity that is distinct from average stress exposure, highlighting the importance of considering what these tasks measure when interpreting individual differences in acute stress responses.

During wakefulness, we are used to perceive the environment through our senses, act on it and take these inputs to update our experiences and build the perceptions. When the inputs are not longer accurate or structured, people would sometimes have hallucinatory experiences. Whether such experiences are associated with distinct patterns of thought, and how they relate to large scale brain dynamics, remains unclear. To address these questions, we combined experience sampling protocol with EEG recording during multimodal Ganzfeld, where participants were exposed to unstructured, uniform visual and auditory stimulation. Participants repeatedly reported the complexity of their visual experiences together with ongoing thoughts related to perceptual belief, prediction perception mismatch, active updating, and prior mentation. EEG microstates were extracted to characterize the temporal dynamics of large-scale brain networks. We found that visual complexity was related to all four dimensions, but partly distinct in simple and complex visual experiences. These phenomenological changes were accompanied by distinct, and often nonlinear, dynamics of large-scale brain networks involved in visual processing, salience detection, and internally directed cognition. It also indicates that this paradigm might be a valuable model for investigating the mechanisms underlying hallucinatory experiences in psychosis.

Museum visits typically follow curator-defined routes that constrain how visitors shape their own experience, yet choice is widely held to heighten engagement, autonomy, and enjoyment. Virtual reality (VR) offers a setting in which to study these processes because it combines ecological immersion with precise, continuous behavioral measurement. We investigated (i) whether VR- derived behavioral signals are associated with self-reported enjoyment during a virtual museum tour, and (ii) whether the level of agency afforded to visitors influences enjoyment. Forty-eight adults completed a room-scale, life-size VR tour (8 * 4 m) of seven paintings from the Tel Aviv Museum of Art, each accompanied by a synchronized audio guide. Synchronized gaze and head- position streams were logged continuously (50 Hz) and segmented into painting-level viewing episodes using a trial-and-tile pipeline that intersects each painting's trial interval with an empirically defined spatial window in front of the canvas. Participants were randomly assigned to one of three agency conditions, Active (choice before every artwork), Semi-Active (choice for the first three), or Passive (fixed route),while the artwork sequence was held identical. Self- reported enjoyment at the tour and painting levels did not differ reliably across agency conditions. Among VR-derived measures, gaze engagement during the audio guide showed the clearest (though modest) association with painting-level liking, whereas locomotion and pacing measures were weak and inconsistent predictors. Agency nonetheless reliably modulated several gaze- and time-based viewing measures. The findings reveal a dissociation between subjective enjoyment and the micro-structure of viewing, and establish a reusable framework for full-tour, painting-level behavioral analysis in immersive settings.

A dental AI system and a dentist reading the same radiographs form a paired comparison. Published comparative studies often report the two arms separately against a reference standard, leaving the joint pattern of correctness between them unavailable for secondary paired inference. We show what that omission costs. The accuracy difference remains exactly identified; its sampling variance does not, so the report contains the estimate and not its uncertainty. On a study of 282 units, two published accuracies are consistent with 38 distinct joint tables whose confidence intervals differ in width by a factor of 2.5. The consequence is a three-zone decision map rather than a single threshold: differences at or below 1.06 points are non-significant under every compatible table, differences at or above 6.03 points are significant under every compatible table, and in between the published numbers cannot decide. We then show the omission is repairable at negligible cost. One additional integer, the number of units both arms classify correctly, identifies the joint table exactly and restores standard paired inference. For a panel of readers the pairwise dependences must arise from one joint distribution, a constraint that binds once three readers are present; publishing each reader's joint-correct count against a single reference reader cannot widen and may tighten every pairwise bound, and in a 7-arm experiment reduced them by a median of 37% even for pairs excluding that reference. Where the integer was never published we give DentalPair-Cert, an interval with finite-sample coverage uniformly over every admissible within-unit AI-dentist dependence under the independent-sampling-unit model, certified in both the nuisance maximization and the inversion. Across 4,200,000 simulated comparisons an independence analysis falls to 74.5% coverage with 12.2% type-I error; in a purposive sample of 9 recent comparative studies, 1 reported a paired test on discordant units.

The olfactory and intranasal trigeminal systems interact closely, influencing chemosensory perception, yet the mechanisms underlying their interaction remain poorly understood and have been studied mainly in young adults. We aimed to characterize olfactory-trigeminal interactions in aging by comparing electrophysiological and behavioral responses under ipsilateral and contralateral olfactory-trigeminal co-stimulation, to determine the relative contributions of peripheral and central mechanisms. Using chemosensory event-related potentials and a localization task, 44 healthy older adults (66.3 {+/-} 4.6 years; 29 women) were tested under four conditions: pure trigeminal (carbon dioxide; CO2), pure olfactory (2-phenylethanol; PEA), ipsilateral co-stimulation (PEA+CO2 in the same nostril), and contralateral co-stimulation (PEA+CO2 in opposite nostrils). Ipsilateral, but not contralateral olfactory-trigeminal co-stimulation, improved trigeminal localization performance and induced larger late positive component amplitudes. Together, these findings suggest that olfactory-trigeminal interactions are driven primarily by peripheral rather than central mechanisms. This study also provides normative CSERP data for healthy older adults.

Kinaesthetic motor imagery (kMI) is widely used in sport to enhance motor performance by engaging cortical sensorimotor networks. Neurofeedback may further support kMI, but the optimal neural target to reinforce remains unclear. Maximal sensorimotor event-related desynchronisation (SMR-ERD) represents a relevant target as it may index sensorimotor cortex engagement, yet sport expertise has been associated with reduced SMR-ERD, potentially reflecting neural efficiency. The optimal neurofeedback target may therefore depend on sport expertise, movement expertise, and individual kMI ability. This study examined how these factors influence sensorimotor activity during kMI. We compared 17 basketball players (Experts) and 16 individuals without formal basketball training (Novices). kMI ability and frequency of use were assessed using questionnaires, while SMR-ERD was quantified using electroencephalography (EEG) during kMI. Participants imagined either a basketball-specific movement (Free throw), for which only Experts had extensive experience, or a generic movement (Box lifting), familiar to both groups. Experts reported greater kMI ability and more frequent kMI use than Novices. Only Experts exhibited significant and sustained SMR-ERD during kMI. Moreover, SMR-ERD was stronger in Experts than Novices specifically during Free throw kMI, corresponding to their movement of expertise. Nonetheless, within the Expert group, higher kMI ability was associated with reduced SMR-ERD. These findings suggest that sport expertise initially enhances voluntary recruitment of sensorimotor networks during kMI, whereas greater kMI ability may subsequently promote neural efficiency, resulting in reduced overall sensorimotor cortical activation. These results highlight the need to tailor kMI-based neurofeedback training to users' sport expertise and kMI ability levels.

Objectives: Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability by eliciting motor evoked potential (MEP)s in targeted muscles, with MEP characteristics such as magnitude and latency reflecting the physiological state of the pathways being stimulated. Although numerous studies have examined MEP reliability in upper extremity muscles, less is known about the reliability of this measurement across the lower extremity. We hypothesized that inter-session, test-retest reliability of MEPs recorded simultaneously from multiple lower-limb muscles, from a single TMS location, would differ by muscle, stimulation intensity, and quantification method. Materials and Methods: Ten healthy participants (5 males, 5 females) completed three TMS sessions separated by atleast one week. At each session, the stimulation hotspot was identified using a five-location virtual grid anchored at the vertex, with electromyography (EMG) recorded from all eight muscles of interest at each grid location; the grid location producing the largest and most consistent MEPs in the tibialis anterior (TA), the primary target muscle, was selected as the stimulation site and held constant across all three sessions. MEPs were then recorded bilaterally from the TA, soleus, rectus femoris, and biceps femoris muscles at two stimulation intensities (110% and 120% resting motor threshold (RMT)). MEP size was quantified using mean rectified magnitude and peak-to-peak amplitude, and inter-session reliability was assessed using intraclass correlation coefficients (ICC). Bland-Altman analysis was used to characterize the range of measurement variability across all eight muscles. Results: MEP size differed across sessions, and reliability varied by muscle, intensity, and quantification method. The highest reliability was observed in the right TA, the muscle used to establish the stimulation hotspot, using mean rectified magnitude at 120% RMT. Reliability was comparatively lower in the seven non-target muscles recorded from the same fixed stimulation site, indicating that MEP consistency was not uniform across the lower-limb musculature. Conclusions: MEP reliability in the lower extremity depends heavily on the muscle, stimulation intensity, and quantification method used, and is highest in the muscle for which the stimulation site was optimized. These findings support the interpretation that coil positioning targeted to a specific muscle yields more consistent responses in that muscle than in others recorded from the same fixed site, and underscore the importance of careful muscle selection and hotspot optimization when designing TMS protocols for longitudinal or clinical lower-limb research.

Intrinsic neural timescale (INT) quantifies the persistence of spontaneous neural dynamics and offers a principled metric for characterizing brain-wide temporal organization. Although a hierarchy of INTs has been established during rest, how task engagement reconfigures this organization and how it is constrained by the structural connectome (SC) remain poorly understood. Here, we systematically mapped whole-brain INT using high-resolution fMRI data from the Human Connectome Project during rest and seven tasks spanning working memory, gambling, motor, language, social, relational, and emotion domains. Task engagement induced robust, regionally heterogeneous changes in INT while largely preserving the brain-wide temporal hierarchy across cognitive states. SC-INT coupling remained strong but consistently decreased during tasks, indicating that anatomical architecture continues to constrain INT, although its influence is attenuated under task demands. To investigate these findings mechanistically, we employed a multiscale, whole-brain neuronal-network model, which revealed that INT increase and peak within a broad critical-like regime. Strong SC-INT coupling, as observed empirically, emerged in the subcritical regime, weakened progressively with increasing network excitability, and reversed in the supercritical regime. These results demonstrate that task engagement reconfigures INTs while maintaining their hierarchical organization, suggesting that both resting and task states operate largely within a common subcritical dynamical regime.

The gastric network, comprised of brain regions whose activity synchronizes with the stomach's slow-wave rhythm, offers a unique window into the brain-body interaction involved in interoceptive processing. While previous work has established the existence of this network, its intrinsic organization and temporal unfolding remain poorly understood. Here, we reanalyzed resting-state fMRI-electrogastrogram data from 43 healthy adults of both sexes to characterize the time-averaged architecture and time-varying reconfiguration of the gastric network. We identified regions exhibiting phase-locked synchronization with the stomach slow electrical rhythm (0.05 Hz) and characterized cortical parcels comprising this network. Time-averaged graph-theoretical analysis revealed a fixed unimodal organization of functional communities, with primary visual, default mode network (DMN) and dorsal attention regions emerging as the principal time-averaged hubs. Next, we applied edge-centric functional connectivity (eFC) to capture the network state during transient high-amplitude "bursts". Time-varying community detection revealed communities whose compositions formed integrative combinations of DMN, visual, attentional and control elements. Edge-derived hubs shifted away from primary visual dominancy in the time-averaged analysis, and were instead directed by DMN regions, suggesting that moments of heightened connectivity in the network are coordinated by multisensory integration rather than passive sensory processing. These findings demonstrate that the gastric network is not merely a time-averaged, sensory-bound system, but rather a flexible and dynamically reconfiguring interoceptive network whose organization is selectively coordinated by transient cofluctuation events. This work provides a comprehensive network analysis of gastric-brain coupling and reveals a temporally structured mode of interoceptive integration that may support adaptive physiological and cognitive regulation.

Across different modalities, signals play a core role in attracting mates and influencing mating success. In several non-human primate species, females produce calls during mating that are thought to promote male competition over receptive females. The extent to which social system characteristics modulate the function of copulation calls remains less clear. We studied copulation calls in wild Guinea baboons (Papio papio), who live in a multilevel society structured around units in which females associate and mate almost exclusively with a single male. We hypothesised that females use copulation calls as an indirect form of mate competition, with competition increasing in larger units. In addition, we hypothesised that females are more likely to mate again after calling. We analysed 6116 copulations between 2014 and 2025, involving 99 reproductively active females and 78 subadult and adult males. Females produced copulation calls in 72.7% of copulations, with large inter-individual variation. Neither unit size nor its interaction with the female's swelling size or the presence of simultaneously receptive females affected the probability of calling. A survival analysis with a subset of the data (2353 copulations) revealed no effect of calling on the latency to the next mating. Our results render the hypothesis that female Guinea baboons use calls in indirect mate competition unlikely. Yet, the probability of calling varied with sexual swelling size, suggesting that calls signal female fertility. Possibly, Guinea baboon copulation calls represent an evolutionary remnant, no longer under selective pressure, and can be considered index signals of female fertility.

In vertebrates, top-down visual attention is a cognitive process where internal goals modulate the tuning of peripheral sensory systems. This leads to increased perceived contrast to both goal-relevant objects and areas of the visual field that are attended. Such a system would also be beneficial to bees, enabling them to detect and recognise the most profitable flowers in their environment. We tested whether bumblebees possess a top-down attentional system resembling that seen in vertebrates. We trained two groups of bees to collect rewards under high contrast targets. To potentially induce a difference in attention while searching for the targets, one group received a higher concentration of sucrose rewards compared to the other. During tests, the targets were presented with a series of lower contrasts to measure the contrast sensitivity curves of the bees induced by the different learnt reward levels. We predicted a stronger effect of any attention-like process on contrast sensitivity in the high reward group. We also repeated this experiment with the neonicotinoid pesticide imidacloprid dissolved in the sucrose rewards to test whether this affects bee attention. Across all test contrasts, higher rewards significantly increased bee accuracy when locating targets, lowered contrast thresholds and reduced the latency to make first choices. Imidacloprid reduced bee accuracy but did not influence first choice latency. These results suggest that learnt floral rewards can influence bee behavioural contrast sensitivity in a manner resembling vertebrate top-down attention and that imidacloprid may modulate this through effects on their nervous system.

BACKGROUND: An individual's adaptation to threatening environments under uncertainty is reflected in stress responses. Predictability (the ability to anticipate events) and controllability (the ability to control outcomes) are central to how one adapts, yet their joint influence on aversive learning remains unclear. METHODS: Thirty healthy adults completed a probabilistic aversive learning task in which cue-outcome contingencies varied across levels of predictability and controllability, i.e. whether shock intensity depended on prediction accuracy. Prediction accuracy, reaction time, subjective stress ratings, and skin conductance responses were recorded throughout. Trial-wise learning dynamics were estimated using the Volatile Kalman Filter. RESULTS: Prediction accuracy reduced as environments became less predictable and negatively associated with higher learning rates across predictability levels, with the strongest relationship observed in highly predictable blocks. Skin conductance responses showed that moderately predictable environments elicited responses like those in highly predictable environments when accurate predictions reduced shock intensity, but resembled responses in unpredictable environments when shock intensity was uncontrollable. Model comparison revealed a double dissociation between subjective stress ratings and skin conductance responses. Subjective ratings were best explained by model-derived volatility when prediction accuracy determined shock intensity and by belief uncertainty when it was independent of prediction accuracy, whereas skin conductance responses showed the reverse pattern. Reaction times were best explained by belief uncertainty when predictions influenced shock intensity. Higher anxiety was associated with elevated learning rates in highly and moderately predictable blocks when predictions did not control shock intensity.

Anxiety-related traits (ARTs) have been linked to altered fear learning, but previous studies have typically examined different experimental phases and response systems, limiting the comparability of findings and the accumulation of consistent evidence. Here, we comprehensively examined associations between ARTs and fear conditioning across acquisition, extinction and renewal and across subjective, physiological and neural response systems in a well-powered sample (N = 267) using a two-day differential conditioning paradigm. ARTs were operationalized as a composite of trait anxiety, neuroticism, and intolerance of uncertainty and conditioned responding was assessed using skin conductance responses, fear-potentiated startle, US expectancy ratings, fear ratings, and functional magnetic resonance imaging. Higher ARTs were consistently associated with elevated subjective fear and US expectancy to both threat and safety cues during extinction and renewal, without corresponding elevations in physiological responding. At the same time, ARTs were not associated with threat-safety discrimination in subjective or physiological measures across phases, while neural associations were limited to reduced dorsal anterior cingulate cortex discrimination during early renewal. These findings suggest that ARTs are characterized by a CS unspecific cognitive bias toward heightened threat expectancy and evaluation rather than altered associative fear learning, highlighting the importance of distinguishing conditioned discrimination from general levels of responding across response systems.

Lesion Network Mapping (LNM) is a framework used for identifying symptom-related brain circuits by projecting lesion locations onto a normative connectome. Recent methodological investigations have raised concerns about the biological interpretation and specificity of the circuits derived using this method, with published LNM maps often showing high similarity across clinically unrelated conditions. Specificity testing has subsequently been put forward as the decisive step to ensure specificity to the symptom in question, accompanied by the argument that this step was not evaluated in the original methodological investigation. Yet, sensitivity testing, specificity testing, case-control LNM, permutation of group labels, and symptom-based LNM involve related operations on connectivity matrix C. We expand on specificity testing in LNM, clarify its relationship to other LNM steps and variants, and examine the persistent repetition among LNM specificity networks across studies. These considerations advance our understanding of the disease-specificity limitation of LNM and encourage the development of new methodological approaches for identifying brain circuits underlying psychiatric and neurological disorders.

Individuality is a defining feature of human biology. The functional network architecture of the human brain harbors person-specific qualities and forms individualized connectivity profiles that function as a neural fingerprint, both stable and unique across time. Here, using fMRI data from 431 Human Connectome Project participants, we examined whether neural individuality is more strongly exhibited in brain regions bearing signatures of recent human evolution. We calculated region-wise fingerprinting accuracy and associated it with four properties of evolutionary cortical organization: cortical expansion, myelin content estimate (T1w/T2w), human-specific gene-expression profiles, and functional homology to other primates. Across all four measures, neural individuality was strongest in cortical areas showing greater evolutionary novelty in humans, particularly frontoparietal control and default mode networks, and weaker in more conserved primary regions. Our findings connect evolutionary variation across species with stable functional variation among individuals.

Damage to the primary visual cortex causes loss of conscious vision, yet some patients retain the ability to respond to stimuli despite reporting no visual experience. Why similar lesions produce such different behavioral phenotypes remains unclear. While research to date has focused primarily on spared pathways that bypass V1, here we asked whether these divergent outcomes are also linked to the brain's intrinsic functional architecture. In the largest resting-state fMRI cohort of patients with unilateral V1 damage reported to date, we quantified information sharing between regions across cortical and subcortical parcels in blindsight-positive and blindsight-negative patients, as well as in age-matched healthy controls. Despite comparable lesions, the two patient groups displayed distinct hierarchical patterns on the cortex: B+ patients preserved a sensory-to-association organization as in healthy controls, whereas B- patients exhibited a marked flattening of this hierarchy. The effect was driven by abnormally low shared-information coupling within unimodal cortices and scaled continuously with single-subject behavioral blind-field detection performance. A thalamic region consistent with the pulvinar, linking the contralesional visual cortex and the frontal eye field, discriminated B+ from B- patients. These findings highlight the system-level consequences of V1 damage supporting blindsight, suggesting that the unimodal-transmodal axis might track not only global states of consciousness, but also whether sensory information can guide behavior without awareness.

Pouring a drink feels deceptively trivial, yet it requires guiding a boundary-free fluid into a vessel without spilling, overflowing, or toppling it -- a task at which robots remain notoriously brittle. How humans achieve this so effortlessly is unknown, as motor control has predominantly been studied in brief, highly constrained laboratory tasks, leaving the control principles underlying ecological tasks largely unknown. Here we measured continuous sensorimotor control during liquid pouring across various containers, vessels, and speed demands. Despite substantial variation in movement trajectories and durations, individuals maintained a strikingly invariant preferred fill level. Counterintuitively, fill level variability decreased at higher fill levels, and precision was maintained even under time pressure. A stochastic optimal control model combining a data-driven nonlinear approximation of flow dynamics with a cost that balanced individualised fill level, energy expenditure and flow-rate reproduced the behaviour. Humans thus pour optimally, given their sensorimotor limits and idiosyncratic notion of "full".