Working memory (WM) is vulnerable to interferences, especially from task interruptions that redirect the focus of attention to secondary tasks. Here, we used a visuospatial WM task to investigate how the modality and cognitive domain of interruptions affect performance. Twenty-eight participants memorized orientations of colored bars and reported one after a retrospective cue. During the maintenance phase, interrupting tasks varying in modality and cognitive domain occurred: visual arithmetic, auditory arithmetic, or visuospatial discrimination. Interruptions generally impaired memory performance, with the visuospatial discrimination task, which included low-level sensory feature overlap, causing the greatest decline. Further, target orientation's proximity to the horizontal axis was a good predictor in recall error, which showed a significant interaction only with visuospatial interruptions. EEG data showed reduced theta activity and weaker alpha/beta suppression to the retrospective cue following interruptions. After the visuospatial interruption, stronger posterior alpha asymmetries emerged, reflecting greater attentional demands for reorienting attention to the interrupted task. These results highlight that overlapping features between primary and interrupting tasks critically influence WM interference.

Aperiodic neural activity has been reliably shown to be reduced among older adults, and these reductions are associated with age-related cognitive decline. These results suggest that aperiodic activity, as measured by the spectral exponent, might be a viable electrophysiological biomarker for cognitive aging. However, this has not been tested longitudinally, within participants, during normal aging. Here, we used a longitudinal cohort to test whether changes in aperiodic activity between two sessions, approximately 5 years apart, track behavioral change across two domains: sustained attention (Psychomotor Vigilance Test) and executive function (modified Simon task). We found that aperiodic activity declined within individuals after the interval, independent of age at baseline. This within-person change tracked concurrent changes in reaction times during visual attention but was not associated with changes in any Simon task measure. Within a resampling framework, the aperiodic-PVT association was stable across cohort resamples and independently fitted partitions, though it was not confirmed in a small, frozen held-out set. These findings suggest the longitudinal decline in aperiodic activity specifically tracks sustained-attention processing speed rather than general cognitive aging, supporting its potential as a domain-specific biomarker of attentional aging in neurotypical populations.

Selective attention allows us to prioritize or retrieve task-relevant features and items from working memory. However, previous work has largely relied on unisensory paradigms, leaving open the question of how attentional mechanisms act on audiovisual working memory representations. Here, using an EEG-based audiovisual delayed-match-to-sample task, we investigate whether attention to audiovisual working memory contents operates on the level of individual unisensory features or bound cross-modal objects. On each trial, participants memorized an audiovisual item. At test, they were randomly presented with either an auditory, visual, or an audiovisual probe stimulus and indicated whether the latter matched their working memory content. Compared with recalling the entire audiovisual object, recall of unisensory visual or auditory features resulted in poorer behavioral performance and elevated midfrontal theta power. Multivariate pattern analyses (MVPA) showed that task-irrelevant feature representations were retrieved in both auditory and visual probe trials, consistent with object-based retrieval. Moreover, these results shed light on the representational structure underlying cross-modal feature storage in working memory, suggesting that audiovisual features are stored as bound objects and that attentional selection of individual object features in one modality spreads to cross-modal object features in another modality. In task conditions where such incidental recall of task-irrelevant features is detrimental to task performance, this places greater demands on cognitive control mechanisms. ### Competing Interest Statement The authors have declared no competing interest.

Background and objective Selective auditory attention enables listeners to focus on a target speaker while suppressing concurrent sounds. To assess the ecological validity of virtual reality for studying spatial attention, the present study investigated cognitive and neural mechanisms in both real and virtual laboratory environments. Method Participants completed a selective spatial attention task in both real and virtual environments under auditory-only and audio-visual conditions while EEG was recorded. Speech stimuli were presented from different locations in both azimuth and depth. In each trial, two simultaneous speech stimuli originated from different locations. Each stimulus included a target or distractor word (plus visual patterns in the audio-visual condition) followed by a numeral. Participants indicated whether the numeral at the target location was odd or even, ignoring the competing numeral. Results Performance was slower and less accurate in the virtual environment, with auditory-only stimulation, and in depth-only trials, suggesting slower accumulation of sensory evidence, as confirmed by drift-diffusion modeling. Early sensory ERPs (P1, N1) were largely stable across conditions, whereas P2 amplitudes were modulated by environment, stimulation, and spatial configuration. Spatial configuration also strongly influenced amplitudes of the contingent negative variation, which were largest with azimuth-only stimuli. Importantly, these effects were consistent across environments and largely independent of visual cues and significant cross-environment correlations were observed for all behavioral and neurophysiological measures. Conclusion These findings suggest that, despite additional perceptual and cognitive demands indicated by reduced performance and slower evidence accumulation, virtual reality captures key mechanisms of selective attention.

Electroencephalography (EEG) is commonly used in neuroscience to study cognitive and emotional processes, often showing functional lateralization. Alpha asymmetries are frequently interpreted as a reverse marker of functional asymmetries in cognitive activation. However, the role of motor activity versus cognitive demands in driving EEG asymmetries remains unclear. To explore this, we analyzed resting-state and task-based EEG asymmetry from 610 healthy adults (ages 20-70) from the Dortmund Vital Study (ClinicalTrials.gov: NCT05155397). Participants completed three tasks with increasing hand involvement and cognitive demands: Psychomotor Vigilance, Simon, and Stroop tasks. Timepoint (pre-stimulus vs. post-stimulus vs. resting-state) had the strongest impact, especially in the alpha and theta bands, with notable differences between resting-state and task-related asymmetries. Non-right-handers exhibited more dynamic shifts in asymmetry, while right-handers showed more stable lateralization patterns. Correlations between frequency bands, electrode pairs, and tasks revealed strong interhemispheric coupling in frontal and weaker coupling in central regions. Frontal post-stimulus asymmetry correlated more strongly than resting-state or pre-stimulus. Findings suggest that EEG asymmetry is a dynamic process influenced by cognitive and/or motor activity and perceptual processes mediated by frontoparietal circuits, with implications for interpreting EEG biomarkers in both research and clinical settings. This study offers reference standards in EEG asymmetry research.

Regular physical activity has the potential to improve a person's physical and cognitive performance. This is relevant for traffic safety and car driving, for example, when coping with complex driving situations. This study investigated whether physical activity in form of regular bicycle use has a positive effect on driving performance in older adulthood and on changes in performance over time. Longitudinal data on the development of driving behavior over a period of around six years were analyzed from 260 participants aged between 67 and 78 years at the baseline measurement. The influences of self-reported bicycle use on driving performance during an approximately 45-min driving simulation as well as on the development of driving performance was analyzed. In addition, EEG-based neurocognitive correlates of mental states while driving were explored from a subgroup of 145 participants. Regular bicycle use was not associated with better driving per se, but it was associated with less deterioration in driving behavior over the observation period. Regular bicycle use was also associated with a lower level of mental workload while driving, as suggested by lower EEG theta power. There were no associations with other physical activity (such as walking or fitness training), the participants' age, or their annual mileage. The results suggest that regular cycling as a combination of physical activity and active traffic participation is associated with maintaining driving competence in old age.

White matter microstructure is a candidate neurobiological substrate underlying individual differences in fluid intelligence, potentially through differences in neural information transfer. Investigating the association between white matter microstructure and fluid intelligence requires precise modeling of these microstructural properties across the brain. Yet, it remains unclear whether MRI-derived markers of white matter microstructure generalize across tracts to support latent modeling approaches. Therefore, our primary objective was to derive measurement models for markers of white matter integrity (fractional anisotropy, FA), neurite density (intra-neurite volume fraction, INVF), and myelin content (magnetization transfer ratio, MTR) across 52 tracts (HCP-1065 atlas) grouped into ten functional clusters. We investigated data of N = 365 individuals (age range: 18−74) drawn from two independent samples (Dortmund Vital Study: 𝑁 = 150, Clinicaltrials.gov: NCT05155397; Mainz Network Study: 𝑁 = 215). Confirmatory factor analyses consistently favored hierarchical bifactor models, capturing both a general factor per marker and orthogonal hemisphere-specific factors, independent of participants’ age. The general factors FA and MTR of the favored measurement models were significantly associated with fluid intelligence, assessed with matrix reasoning tests, FA: 𝛽 = 0.26, 𝑝 < .001 and MTR: 𝛽 = 0.25, 𝑝 = .017. When controlling for age, the association of fluid intelligence with FA remained significant, 𝛽 = 0.14, 𝑝 < .043, while the association with MTR was no longer significant, 𝛽 = 0.11, 𝑝 = .328. These findings establish anatomically informed measurement models for white matter microstructure and provide a scalable framework for investigating the biological underpinnings of cognitive abilities.

White matter microstructure is a candidate neurobiological substrate underlying individual differences in fluid intelligence, potentially through differences in neural information transfer. Investigating the association between white matter microstructure and fluid intelligence requires precise modeling of these microstructural properties across the brain. Yet, it remains unclear whether MRI-derived markers of white matter microstructure generalize across tracts to support latent modeling approaches. Therefore, our primary objective was to derive measurement models for markers of white matter integrity (fractional anisotropy, FA), neurite density (intra-neurite volume fraction, INVF), and myelin content (magnetization transfer ratio, MTR) across 52 tracts (HCP-1065 atlas) grouped into 10 functional clusters. We investigated data of N = 365 individuals (age range: 18-74 years) drawn from two independent samples (Dortmund Vital Study: N = 150, Clinicaltrials.gov: NCT05155397; Mainz Network Study: N = 215). Confirmatory factor analyses consistently favored hierarchical bifactor models, capturing both a general factor per marker and orthogonal hemisphere-specific factors, independent of participants' age. The general factors FA and MTR of the favored measurement models were significantly associated with fluid intelligence, assessed with matrix reasoning tests, FA: β = 0.26, p < .001 and MTR: β = 0.25, p = .017. When controlling for age, the association of fluid intelligence with FA remained significant, β = 0.14, p < .043, while the association with MTR was no longer significant, β = 0.11, p = .328. These findings establish anatomically informed measurement models for white matter microstructure and provide a scalable framework for investigating the biological underpinnings of cognitive abilities.

Binaural localization of an acoustic source entails two tasks: estimation of the direction of arrival (DOA) and of its distance. While DOA estimation primarily benefits from interaural cues, distance estimation strongly relies on the characteristics of the reverberant room, the receiver and the source. In order to train a robust binaural distance estimator, extensive data generation, augmentation, and regularization are essential. In this work, we investigate training strategies that integrate multi-task and contrastive learning via additional loss terms to improve robustness with respect to unseen acoustic environments. Since real-world data is scarce, we train a convolutional recurrent neural network on data generated by an auditory virtual environment which also incorporates multiple sets of head-related transfer functions. Our results show that a high emphasis on both the contrastive loss and the auxiliary task loss improves generalization to unseen synthetic and real-world datasets.

Personality traits describe stable differences in how people think, feel and behave, and how they interact with and experience their social and physical environments1,2. Many questions remain unanswered about associations between DNA and personality traits, such as their robustness, their generalizability and the biological and social pathways through which they act. Here we meta-analyse data across 46 cohorts comprising 611,037 to 1.14 million participants with European-like and African-like genomes for genome-wide association studies (GWAS) of the Big Five personality traits (extraversion, agreeableness, conscientiousness, neuroticism and openness to experience), and data from up to 50,725 participants for within-family GWAS. We identify 1,260 lead genetic variants associated with personality, including 824 novel variants3. Common genetic variants explain a moderate 4.8-9.3% of the variance in measures of each trait, and 9.3-13.3% among instruments with typical measurement reliability. Genetic associations with personality are highly consistent but not identical across geography, reporter (self versus close other), age group and measurement instrument, and we find minimal spousal assortment for personality in recent history. In contrast to many other social and behavioural traits4,5, within-family GWAS and polygenic index analyses indicate that genetic associations with personality are minimally confounded by the shared family environment. Polygenic prediction, genetic correlation and Mendelian randomization analyses indicate that personality traits have widespread, potentially causal associations with consequential behaviours and life outcomes. Overall, we find that the genetic architecture of personality is robustly generalizable, minimally confounded and widely relevant to human experience.

IntroductionThe ability to perceive spatial changes is crucial for everyday life. However, the effects of age on multisensory integration in spatial change detection are still less researched. Here, we investigated whether audio-visual stimulation enhances spatial change detection compared to auditory-only processing, and whether older adults benefit more from multisensory stimulation than younger adults.MethodsIn an active oddball task, younger and older participants had to detect spatial changes in azimuth (in the horizontal plane) or distance (in the depth dimension). Stimuli were presented as auditory-only or audio-visual (spatially congruent). Behavioral performance and event-related potentials indexing sensory processing (P1, N1, P2), automatic change detection (mismatch negativity), attention orienting (P3a), and evaluation (P3b) were measured.ResultsDetection accuracy was higher for azimuth than distance changes in auditory-only conditions, but this difference was reduced with audio-visual stimulation. Older adults showed comparable behavioral performance to younger adults across both conditions, with no additional benefit from multisensory input. However, older adults exhibited enhanced early sensory processing (larger N1, P2 amplitudes), reduced MMN differentiation between azimuth and distance deviations, and later evaluative processing that was primarily modulated by spatial dimension and stimulation modality. Thus, age-related neural differences were component-specific and depended on spatial dimension and stimulation modality.DiscussionTaken together, audio-visual integration facilitated spatial change detection, particularly in the depth dimension. While older adults maintained behavioral performance possibly through compensatory neural mechanisms involving enhanced attentional allocation, the use of multisensory stimuli for spatial change detection appears to be largely preserved in aging.

Objective: To investigate whether EEG asymmetries are primarily driven by cognitive or motor processes, and to establish normative patterns across different task conditions. Methods: We analyzed resting-state and task-related EEG asymmetry data from 610 healthy adults aged 20 to 70, from the Dortmund Vital Study (ClinicalTrials.gov: NCT05155397). Participants completed three tasks with increasing cognitive and motor demands: Psychomotor Vigilance, Simon, and Stroop tasks. EEG asymmetries were examined during pre-stimulus, post-stimulus, and resting-state across multiple frequency bands. Results: Timepoint had the strongest impact on EEG asymmetry, particularly in alpha and theta bands, with significant differences between resting-state and task-related conditions. Age had minimal effect on asymmetry patterns. Non-right-handers displayed more dynamic shifts in asymmetry, while right-handers maintained more stable lateralization. Correlations of asymmetry indexes revealed strong interhemispheric coupling in frontal and weaker connectivity in central regions. Post-stimulus frontal asymmetries showed stronger correlations compared to resting-state and pre-stimulus, highlighting dynamic, task-specific lateralization. Conclusions: EEG asymmetry is not static but dynamically modulated by task engagement and stimulus novelty. Significance: This study highlights EEG asymmetry as a dynamic biomarker of brain function, offers standards in EEG-asymmetry research, and may serve as a reference for clinical and non-clinical studies.

Interruptions are widespread in working life and increase the risk of errors. Older adults are usually more affected than younger ones, which is attributed to age-related changes in the cognitive processes needed to cope with interruptions, especially with respect to attentional control and working memory. Here, we investigated whether the benefits of prolonged or self-determined timing when dealing with interruptions, which we found in a previous study, become more pronounced with age. Twenty-eight younger (18-30 years) and 31 older participants (55-70 years) performed a retrospective cue (retro-cue)-based working memory task, in which the orientations of a set of colored bars had to be remembered and retrieved in response to a retro-cue. This primary task was randomly interrupted with an arithmetic task presented before the retro-cue, with the time after the interruption and before the retro-cue being either short (500 ms), long (1,500 ms), or self-determined. Interruptions impaired performance, and the older group performed overall worse than the younger group. Especially the older group benefited from that flexibility, which led to an improvement in performance up to the level of the younger group. Accordingly, the electroencephalography in the flexible condition showed an equally strong α activity in both groups at the time of the retro-cue, suggesting an improvement in the retrieval of task-relevant information from working memory. Overall, the study shows that in work situations in which interruptions cannot be avoided, flexibility in resumption following these interruptions can help older employees to compensate for age-related changes in cognitive abilities. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Chronotype represents individual differences in circadian preferences that influence sleep-wake patterns, cognitive performance, and clinical outcomes across the lifespan. Given its growing relevance for clinical research and application, efficient and reliable chronotype assessment is essential. However, widely used tools like the Morningness-Eveningness-Questionnaire (MEQ) rely on composite scores, despite methodological concerns about multidimensionality and unequal item contributions. Addressing this limitation, the current study applied machine learning techniques to enhance theoretical understanding and empirical precision in chronotype assessment. Using the German MEQ in the Dortmund Vital Study (ClinicalTrials.gov NCT05155397), a prospective cohort study on healthy cognitive aging, we identified item-level predictive hierarchies and response patterns distinguishing morning, neutral, and evening types. Item 19 ("Which chronotype do you think you are?") demonstrated exceptional predictive utility, showing threefold greater importance than any other item. This metacognitive self-assessment appears to capture relatively accurate chronotype identification rooted in lived experience. Chronotype-specific analyses revealed distinct predictive patterns across types, each relying on different item combinations for optimal classification. Partial dependence analysis identified non-linear response patterns including sigmoid curves, threshold effects, and plateau regions. A six-item combination achieved robust overall classification, potentially reducing assessment burden by 70%. Overall, this research advances chronotype assessment by uncovering non-linear and heterogeneous classification mechanisms to circadian preference. The findings provide evidence-based foundations for developing abbreviated screening tools for primary care consultations, large-scale epidemiological studies, and clinical contexts. An open-access R tutorial ensures reproducibility and facilitates adaptation across diverse populations and assessment instruments, supporting widespread implementation in research and practice.

Background: Exhaustion and depersonalization are the core symptoms of the occupational burnout. However, burnout is not an all-or-nothing phenomenon, but can occur in a milder to moderate form in otherwise healthy employees. In the last two decades hair cortisol concentrations (HCC) were increasingly related to the cumulative effect of psychosocial stress at work. We analyzed data of the Dortmund Vital Study (Clinicaltrials.gov: NCT05155397) to explore the relationship of HCC and burnout symptoms. Moreover, we asked whether the HCC - burnout association was moderated by work ability, chronic stress, neuroticism, depressive symptoms, and stress-related immunological biomarkers such as T cell concentration, CD4/CD8 cell ratio, and proinflammatory cytokines TNF- alpha, IL-6, and IL-18. Methods: Burnout was assessed by the Oldenburg Burnout Inventory (OLBI), and the Maslach Burnout Inventory (MBI-D) in 196 working adults aged between 20 and 65 years (mean age 42.2 years). Several self-reported variables and biomarkers were collected. Results: The results showed an association between HCC and the burnout measures. A series of moderator analyses revealed that the association between HCC and burnout symptoms was substantial for low work ability, high chronic stress level, high neuroticism level, and mild to moderate depressive symptoms. Immunological markers moderated the HCC - burnout association for high concentrations of T cells, low CD4/CD8 ratio and low IL-6, IL-18 and TNF-alpha concentrations. These interactions were moderated by age showing the largest impact in middle-aged to older individuals. Conclusions: The present findings shed light on the complex interaction between burnout symptoms and work ability, chronic stress, personality, and the endocrinological and immunological responses across the working lifespan. These parameters should be considered when assessing the risk for developing burnout and validating the diagnosis of burnout. Trial registration: ClinicalTrials.gov NCT05155397; https://clinicaltrials.gov/ct2/show/NCT05155397.

Interactive communication (IC), i.e., the reciprocal exchange of information between two or more interactive partners, is a fundamental part of human nature. As such, it has been studied across multiple scientific disciplines with different goals and methods. This article provides a cross-disciplinary and selective primer on contemporary IC integrating psychological mechanisms with speech signal, acoustic and media-technological constraints in theory, measurement, and applications. First, we outline theoretical frameworks that account for verbal, nonverbal, and multimodal aspects of IC, including distinctions between face-to-face and computer-mediated communication. Second, we summarize key methodological approaches, including behavioral, cognitive, and experiential measures of communicative synchrony and acoustic signal quality. Third, we discuss selected applications, applications in which speech transmission, signal enhancement, mediated dialogue, and real-time coordination are central, namely assistive listening technologies, conversational agents, and social VR, alongside ethical considerations. Taken together, this primer highlights how human capacities and technical systems jointly shape IC, consolidating concepts, findings, and challenges that have often been discussed in separate lines of research.

Working memory supports goal-directed behavior by maintaining task-relevant information. However, a growing number of studies shows that task-irrelevant features can interfere with the recall of task-relevant information. While this phenomenon is well documented in unisensory contexts, it remains unclear whether and how task-irrelevant information persists in multisensory working memory. Here, we examine the role of cross-modal binding by tracking the dynamic neural representation of audio-visual objects under varying selective attention conditions, using an EEG-based audio-visual delayed-match-to-sample task. Participants attended to either auditory or visual features (selective attention), or to both features (conjunction) of two sequential audio-visual items and subsequently compared those task-relevant features to an audio-visual probe. Further, to investigate the influence of bottom-up factors on cross-modal binding, we manipulated spatial congruency by presenting both features from either the same or from disparate positions. Behaviorally, task-irrelevant features interfered with performance even under selective attention, consistent with automatic cross-modal binding and encoding into working memory. Condition-level representational similarity analysis (RSA) showed that EEG activity patterns under selective attention more closely resembled those of conjunction trials than unisensory trials, indicating that task-irrelevant features were incorporated into multisensory object-level representations. This conjunction-similarity persisted in attend-visual trials, but declined over time in attend-auditory trials, reflecting partial filtering of task-irrelevant orientations. Crucially, activity patterns never shifted fully towards an auditory-only profile, indicating that irrelevant visual features were not fully excluded. Overall, these results demonstrate the persistence of task-irrelevant information in multisensory working memory and offer critical insights into how attentional processes shape its representational architecture.