Biological Psychology

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

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

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

Flow, as defined by Mihalyi Csikszentmihalyi (1975), is a holistic sensation experienced when individuals are fully immersed in an activity, resulting in a mental state characterized by a diminished sense of self and altered perception of time. To investigate the global neural dynamics underlying flow, we employed EEG microstate analysis to capture the spatial and temporal properties of dominant transient global brain states (Lehmann et al., 1998). In a study involving 43 participants playing the video game Thumper for 25 minutes, we extracted three four-minute EEG segments from each session corresponding to reported experiences of flow, boredom, and frustration, as determined by self-reports and performance metrics. Across conditions, six distinct microstate topographies (A-F) accounted for most of the global variance. Given that reduced self-referential processing is a key feature of flow, we hypothesized that flow would modulate the properties of microstates C and E, which have been associated with brain regions resembling the default mode network (DMN). Compared to boredom and frustration, the flow condition showed significantly decreased global explained variance, mean duration, time coverage, and occurrence frequency of microstate E, as well as reduced mean duration and time coverage of microstate C. These findings suggest that microstates associated with self-referential processing are shorter and less frequent during flow than during boredom and frustration. This supports the notion that the flow experience modulates global brain dynamics, particularly within the DMN. Furthermore, our results align with previous research reporting reduced DMN activity during meditative and psychedelic states, reinforcing the idea of diminished self-awareness in such conditions.

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

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

Mental imagery is known to be accompanied by autonomic responses, traditionally viewed as merely downstream consequences of imagery. Recent theoretical work has challenged this view, proposing that mental imagery requires the integration of cortical sensory representations with ascending interoceptive signals supplied by the autonomic nervous system. These two views make opposite predictions: if autonomic activity is only a consequence of imagery, then the responsiveness of the autonomic nervous system should not predict imagery vividness. If instead autonomic input shapes the generation of mental images, individuals with greater autonomic responsiveness should experience more vivid imagery. The present study tested these competing predictions by examining whether individual differences in cardiac vagal reactivity (indexed by the magnitude of HRV change in response to a paced breathing manipulation) predict self-reported visual imagery vividness. Imagery vividness was assessed using the Vividness of Visual Imagery Questionnaire (VVIQ) at a separate time point from the paced breathing protocol, ensuring that any observed relationship between cardiac vagal capacity cannot reflect autonomic activation driven by imagery itself. The key result was that cardiac vagal reactivity (indexed by RMSSD change normalized by mean R-R interval), significantly predicted higher VVIQ scores (r = .30, p = .031). These findings demonstrate that vividness of mental imagery is not exclusively central in origin but also shaped by the capacity of the autonomic nervous system to enter a high-parasympathetic state. Imagery thus likely involves bidirectional autonomic-cortical interaction, with descending pathways triggering the intention to generate an image and ascending interoceptive signals contributing to its generation.

One of our sensory systems key functions is to detect threats in the environment. Sensory information eliciting negative emotions, such as fear or disgust, triggers instinctive avoidance reactions. This core survival mechanism is believed to be expressed as subtle non-conscious postural reactions, even when participants are instructed to stand still. Such avoidance behavior has mainly been studied using indirect measures that make participants aware of their posture (e.g. force-plate based methods) or measures that depend on explicit cognitive tasks, like moving a joystick to indicate an urge to approach or avoid the stimulus; experimental tasks with limited ecological validity and generalizability. Therefore, despite the importance of this basic survival strategy, its underlying mechanisms are still poorly understood. Here, we used a novel 3D-camera-based method allowing direct but implicit measures of postural reactions with high precision. Participants are aware that they are being filmed but, crucially, are not informed that distance measures are obtained. We assessed this ecologically valid measure of approach/avoidance responses in two different sensory modalities: olfaction and vision. Participants were standing upright while exposed to either olfactory or visual stimuli and verbally rating their perceived valence in each trial. In response to subjectively unpleasant odors and images, participants moved away from the stimulus source, as compared to pleasant stimuli. These results demonstrate a putative modality-independent early proxy for avoidance behavior in response to perceived negative valence. Considering its face validity and general applicability, this novel experimental method presents new possibilities for assessing non-conscious approach-avoidance responses in humans.

Conversations can feel effortlessly engaging or, conversely, difficult and unrewarding. Multiple factors contribute to the experienced quality and outcomes of a conversation, among them how interlocutors align with each other. The present study investigated speech-to-speech, brain-to-speech, and brain-to-brain coordination as markers of interpersonal alignment, examining their relationship with jointly perceived interaction quality and mutual affinity between conversational partners. Pairs of previously unacquainted participants (dyads) engaged in multiple short, free-form conversations on topics of varying interest while their vocal and neural activity were simultaneously recorded in a dual-EEG ("hyperscanning") setup. We analyzed interlocutors prosodic adaptation, neural speech tracking, and neural coordination during each conversation. At the speech-to-speech level, our findings reveal that partners with more positive mutual impressions became more similar in their volume and voice quality over the course of the experiment session, reflecting greater prosodic convergence. At the brain-to-speech level, we found no reliable effect of interaction quality on neural tracking of unfolding speech within any individual region, although topographical differences suggested relative modulation across scalp sites. Finally, at the brain-to-brain level, our findings show that higher perceived interaction quality enhanced inter-brain relationships across frequency bands (alpha and theta) and temporal dependencies (concurrent/near-instantaneous and recurrent/listener-lagging), with the strongest effects observed for concurrent alpha-band coupling. These findings suggest that distinct coordination processes are involved in how interlocutors experience an interaction and how they establish relational affinity, casting new light into the mechanisms that make a conversation worthwhile.

BackgroundEmotional and cognitive difficulties often co-occur in neurodevelopmental conditions. While transdiagnostic, dimensional approaches offer a more precise framework for understanding mental health than diagnostic categories, their neural correlates in youth with learning difficulties remain poorly understood. This study investigates associations between transdiagnostic mental health dimensions and resting-state functional connectivity in struggling learners. MethodsCross-sectional behavioural data from the Centre for Attention, Learning and Memory (CALM) for struggling learners (N = 378) was used to replicate a hierarchical model of mental health from the Conners Parent Rating Short Form, the Revised Childrens Anxiety and Depression Scale and the Strengths and Difficulties Questionnaire. Functional connectomes were derived from resting-state fMRI data (N = 67), and partial least squares regression related mental health dimensions to connectivity within and between large-scale brain networks. ResultsThe replicated model comprised a general p-factor, two broad domains (internalising and externalising), and three specific dimensions (specific internalising, neurodevelopmental and social maladjustment). Symptom severity was associated with two connectivity patterns: greater default mode network coupling to frontoparietal and attention networks, and reduced connectivity between visual and somatomotor systems. These effects were strongest for the neurodevelopmental and social maladjustment dimensions, respectively. ConclusionsThese findings align with population-level evidence linking mental health dimensions to brain network organization, extending it to struggling learners and offering new insight into the neural basis of mental health vulnerability in neurodevelopmentally at-risk youth.

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

BackgroundAttention-deficit/hyperactivity disorder (ADHD) has traditionally been conceptualized categorically, with efforts to identify disorder-specific neurobiological endophenotypes. However, dimensional models suggest that brain-behavior organization may follow developmental axes that cut across diagnostic boundaries. We tested whether neural dynamics and cortical excitability differentiate those with ADHD diagnoses from typically developing (TD) peers, and whether brain-behavior covariance aligns with diagnostic or developmental dimensions. MethodsWe studied 84 participants aged 8-17 years (51 ADHD, 33 TD). High-density electrophysiological (hdEEG) measures included task-free source-resolved data used to derive mean global brain fluidity (variance of dynamic functional connectivity) and region-specific cortical excitability. Behavioural measures included self- and parent-report questionnaires, cognitive control (CC) tasks, and neuropsychological tests. Partial least squares (PLS) assessed multivariate brain-behavior associations including age, followed by clustering based on latent component scores. ResultsGroup differences emerged in parent-report questionnaires and CC tasks, but not in neuropsychological measures. ADHD individuals showed higher mean global brain fluidity and increased cortical excitability. The excitability-fluidity relationship was network-dependent: higher excitability predicted higher fluidity in task-positive networks and lower fluidity in default-mode and salience networks, with no group effects. PLS identified a latent dimension linking neural metrics with age, verbal fluency, inhibitory control, and positive affect, but it did not distinguish ADHD from TD. Clustering revealed two neurodevelopmental profiles spanning both groups. ConclusionsWhile ADHD is associated with mean-level differences in neural dynamics, brain-behaviour organization follows a developmental neurocognitive-affective axis that transcends the diagnostic boundary. These findings support a dimensional framework for understanding neurobiological variation in neurodevelopmental conditions.

Ocular measures are increasingly used as non-invasive proxies of cognitive processes such as attention and listening effort. However, their interpretation in aging populations is complicated by concurrent changes in ocular physiology and oculomotor control, raising a critical question: to what extent do age-related differences in these measures reflect cognitive rather than other physiological factors? Here, we dissociate these contributions by characterizing ocular dynamics (resting and event-evoked) during passive fixation in younger (N = 98, 18-35 years) and older adults (N = 71, 60+ years). Aging is associated with pronounced alterations in pupil dynamics, including reduced baseline variability and slower, attenuated responses to both auditory and visual events. In contrast, microsaccade dynamics did not correlate with aging. Across measures, ocular responses showed moderate-to-high within-subject stability across blocks, and factor analysis in the older cohort revealed separable components reflecting instantaneous pupil responsivity, sustained pupil responsivity, and microsaccade dynamics, with additional variance associated with sensory decline and age-related changes in pupil dynamics. Together, these findings demonstrate a clear dissociation: pupil-based metrics are strongly influenced by aging, whereas microsaccades remain comparatively stable across age groups. This dissociation provides a principled basis for interpreting ocular indices in aging research and highlights the need to account for baseline physiological differences when inferring cognitive processes from eye-based measures.

In a single-blind randomized controlled trial, we investigated the effectiveness of real-time fMRI neurofeedback delivered in 7 runs over three sessions across two weeks in N = 65 patients with alcohol use disorder. The intervention targeted modulation of ventral striatal cue reactivity to alcohol-related cues as well as enhancement of prefrontal control mechanisms in the right inferior frontal gyrus. The study design incorporate three experimental groups that either were instructed to downregulate a ventral striatum signal, upregulate the right inferior frontal gyrus, or upregulate negative functional connectivity between these two structures. In two active control groups participants were instructed to either up- or downregulate the primary auditory cortex. We did not find an effect of ventral striatal downregulation or negative connectivity feedback, and a reduced striatal activation in the right inferior frontal gyrus upregulation group was accompanied by concurrent lower activation in the target structure, suggesting that our intended modulation approaches were not effective. Identified problems that might have contributed to this unexpected outcome might have been the use of continuous feedback presentation that potentially confuses regulation target and reward processing in the ventral striatum, counterintuitive regulation directions, a lack of explicit strategy guidance and transparency about the targeted process, and generally the difficulty to recruit a sufficient number of eligible voluntary participants for a well-powered study with a complex design. These insights emphasize the complex challenges of real-time fMRI neurofeedback interventions for the treatment of substance use disorders and could provide guidance for the development of more effective future approaches.

Understanding speech in noisy environments (SPIN) is an important everyday ability, and engaging in musical activities has been proposed as a factor that may support this ability. However, the cognitive mechanisms underlying a potential musical advantage in SPIN perception remain unclear. Here we investigated whether musical sophistication is associated with better SPIN perception in a large population-based sample, and whether this relationship is mediated by auditory working memory (AWM), verbal working memory (VWM), or non-verbal intelligence. We recruited 203 participants and measured SPIN perception at both word and sentence levels. Musical sophistication was assessed using the Goldsmiths Musical Sophistication Index (Gold-MSI). AWM was measured using delayed matching of tone frequency or the modulation rate of amplitude modulated white noise, VWM was based on backward digit span task, and non-verbal intelligence used matrix reasoning. Mediation analyses revealed that AWM fully mediated the relationship between musical sophistication and SPIN perception, whereas VWM showed no mediation effect. Non-verbal intelligence showed a partial mediating effect. Additional control analyses using structural equation modelling revealed that the indirect effect through AWM remained significant after accounting for age, hearing thresholds, and non-verbal intelligence. Together, these findings suggest that individuals with greater musical sophistication demonstrate better daily life listening abilities, and that superior auditory working memory may be the key cognitive mechanism underlying this advantage.

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

Background and Objectives In ADHD, a heterogeneous neurodevelopmental condition, behavioral and motor manifestations may reflect multiple inefficient or perturbed inhibitory systems. To evaluate Transcranial Magnetic Stimulation (TMS) evoked cortical silent period (CSP) duration, an indicator of GABA(B) receptor-mediated inhibition in motor cortex, as a potential biomarker of Attention-Deficit/Hyperactivity Disorder (ADHD) in children. Method We retrospectively analyzed TMS data, obtained using both round and figure-of-8 coils, from three cross-sectional studies conducted in 8- to 12-year-old children with ADHD (n=79; 10.7 +/- 1.5 years old) and age-and-sex-matched typically developing controls (n=96; 10.5 +/- 1.4 years old). Results Median CSP was 32% shorter in ADHD (p=0.02). Regression analysis demonstrated a relationship between shorter CSP and both lower active motor thresholds (p < 0.0001) and more severe hyperactivity symptom rating (p = 0.026). Test-retest CSP measures in 83 children showed moderate reliability (intraclass correlation 0.77 [ADHD], 0.75 [controls]). Conclusion TMS-evoked CSP may be a useful biomarker in future investigations of ADHD subtypes, domains of impaired function, or treatment outcomes.

RationaleCholinergic signalling is critical for attentional control and signal detection, yet the contribution of specific acetylcholine receptor (AChR) subtypes remains poorly understood. Although the 7 nicotinic AChR (nAChR) holds promise as a target for cognition-enhancing therapy, clinical findings to date have been inconsistent. ObjectiveTo investigate the effects of putative cognitive enhancing drugs, including those targeting cholinergic transmission and 7 nAChRs on a visual signal detection task (SDT). MethodsMale and female Sprague Dawley rats were trained on an SDT. Cholinergic transmission was probed systemically with nicotinic and muscarinic receptor antagonists (mecamylamine and scopolamine), a cholinesterase inhibitor (galantamine), an M4-AChR positive allosteric modulator (PAM; VU0467154), an 7 nAChR antagonist (MLA), an 7 nAChR PAM (CCMI), and an 7 nAChR partial agonist (SSR-180,711). Dopaminergic transmission was probed using the catechol-O-methyltransferase (COMT) inhibitor, tolcapone. A novel, trial-level signal detection theory-based generalised linear mixed-effects model (SDT-GLMM) was used to index response bias and perceptual sensitivity (d'), the latter reflecting subjects ability to discriminate signal from noise. ResultsMecamylamine profoundly impaired SDT performance across all measures. Galantamine significantly improved d' at moderate doses but not when a distractor was present. MLA uniquely produced dose-dependent improvements in d' that were preserved under distraction. In contrast, positive allosteric modulation and agonism of 7 nAChRs impaired task performance. Scopolamine, VU0467154, and tolcapone had no consistent or interpretable effects on signal detection. ConclusionsThis work demonstrates that 7 nAChR modulation bidirectionally and dose-dependently regulates perceptual sensitivity, irrespective of attentional distraction. These findings have implications for targeted cognitive enhancement in disorders of attention.

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

Meditation has been associated with improvements in attention, emotional regulation, and mental well-being, motivating increasing interest in objective methods for assessing meditative states. In this study, we investigate whether EEG-based machine learning can reliably distinguish between multiple meditation styles and mind-wandering states. EEG data were recorded from experienced meditators performing three meditation styles, Shamatha, Vipassana, and Metta, together with an eyes-closed mind-wandering condition. EEG signals were preprocessed to remove artifacts, and features were extracted from frequency, time-frequency, and time domains. Classification was evaluated using both intra-subject and inter-subject strategies with multiple machine learning classifiers. Results demonstrate high intra-subject classification accuracy across meditation-versus-mind-wandering and meditation-style comparisons, indicating strongly discriminative subject-specific neural signatures. In contrast, inter-subject performance decreased substantially, particularly for distinguishing meditation styles, suggesting considerable inter-individual variability in meditation-related EEG patterns. Furthermore, temporal analysis revealed that classification performance increase over time, indicating that the neural distinctions between meditation states become increasingly pronounced over time. Additionally, t-SNE visualization showed clear within-subject clustering but increased overlap across subjects, explaining the reduced inter-subject generalization. Overall, these findings highlight the potential of EEG-based machine learning for personalized assessment and monitoring of meditative states while emphasizing the challenges of developing subject-independent meditation classification systems.