Frontiers in Human Neuroscience

Visual wayfinding is essential for safe navigation but remains poorly characterized in people with ultra-low vision (ULV). Because assessing complex environments in the real world carries safety risks, this study utilized a calibrated virtual reality (VR) platform to safely quantify navigation. Participants with ULV, normal vision (NV), and simulated ULV (sULV) completed tasks across three environments (street crossing, cafeteria, and metro station) of increasing complexity to determine which metrics best capture task difficulty. Navigation metrics included motion onset latency, walking speed, path efficiency, and turn deviation derived from head position data. Participants with ULV showed longer onset latency, slower walking speed, reduced path efficiency, and greater turn deviation compared with NV, while sULV showed intermediate performance. These metrics successfully reflected increasing task difficulty across environments, with the metro station posing the greatest challenge. Path efficiency consistently detected differences between environments across groups, whereas turn deviation provided insight into complex tasks. Findings indicate that diverse virtual environments capture distinct aspects of navigation that cannot be safely studied in the real world, and trajectory-based metrics capture navigation behavior more effectively than conventional measures. VR-based assessment offers a useful approach for evaluating functional navigation and guiding rehabilitation strategies in profound vision loss.

Virtual reality (VR) interaction remains largely dependent on explicit motor input, limiting seamless and adaptive interaction. This study investigated whether electroencephalography (EEG)-based passive brain-computer interfaces (BCIs), combined with eye gaze, can decode interaction intent directly from its underlying neurophysiological correlates during dynamic VR gameplay. We operationalized interaction intent as comprising two components: affordance-related evaluation, indicating whether an attended object affords interaction, and approach-avoidance evaluation, indicating the directional tendency of interaction toward desirable or undesirable outcomes. Twenty-three participants completed a VR game with two calibration sessions and one online BCI session. Offline analyses showed above-chance decoding of the binary approach-avoidance decision classification across all actionable trials, with a grand-average accuracy of 66.28% across participants. This decoding transferred to online closed-loop gameplay, where grand-average accuracy remained above chance at 69.64%. Category-level analyses further revealed substantial variability in classification separability. For approach-avoidance-related classifications, accuracy reached 80.84% for the most distinct pairing between clearly valenced reward and punishment categories, but dropped to near chance at 59.03% for the more context-dependent pairing with ambiguous motivational valence. Affordance-related classifications between non-actionable and actionable item categories were consistently high, ranging from 77.76% to 83.50%. User Experience questionnaire results showed that, despite limitations leading to perceived loss of control and reduced ease of use, participants found the BCI-based interaction paradigm itself more fun than the controller baseline. To our knowledge, this is the first demonstration of real-time EEG decoding of interaction intent during dynamic VR gameplay, contributing toward intuitive user-adapted interfaces driven by physiological signals in immersive environments.

Background: Chronic pain affects hundreds of millions worldwide and remains a major clinical challenge, despite numerous available treatments. Advances in brain imaging offer a promising path toward identifying neural signatures of chronic pain, potentially enhancing diagnosis and guiding treatment. However, while a core set of brain regions, including the insula, cingulate, and somatosensory cortices, has been repeatedly implicated, findings regarding other regions and connectivity patterns involved remain inconsistent, with limited robust replication. Objective: To address these gaps, the present work characterizes resting-state functional connectivity and gray matter volume differences between chronic pain patients and pain-free controls. Methods: In this secondary analysis of publicly available data, anatomical and resting-state functional MRI were analyzed from 56 patients with chronic knee pain due to osteoarthritis and 20 pain-free controls. Group comparisons used Network-Based Statistic (NBS) and Bayesian multivariate regression models, controlling for demographic covariates. Results: In the pain group, about 75% of parcellated brain regions exhibited increased functional connectivity compared to controls. The 30 highest degree centrality regions in the NBS network were concentrated in regions consistent with prior pain neuroimaging findings. Additionally, chronic pain patients exhibited reduced gray matter volume (-3.98%; SD 1.2%) across 33% of parcellated brain regions, including key regions implicated in pain processing. Conclusions: These findings demonstrate widespread functional and anatomical neural alterations in chronic pain, revealing a global pattern of reorganization extending beyond previously reported network-pair effects. Characterizing such alterations may contribute to ongoing efforts to identify neuroimaging markers of chronic pain, with potential translational relevance.

PurposeSpeech perception is a fundamental part of everyday communication that relies on more than simple identification of words and sentences. Attention and listening engagement both contribute to speech perception, while representing distinct aspects of the listening experience. Attention is typically associated with cognitive focus, whereas listening engagement additionally involves cognitive and affective immersion in sound. Despite their importance, these states remain difficult to disentangle, behaviorally and physiologically. Both have been linked to interpersonal synchronization (the synchronization of biobehavioral signals across individuals), raising questions about what this synchronization actually reflects. MethodIn this study, we disentangled attention and listening engagement by independently manipulating both factors within a single experiment. Thirty participants listened to two simultaneously presented streams of meaningful speech and were instructed to focus on only one. Both attended and unattended stimuli were designed to be either engaging or non-engaging. Neural activity was recorded using EEG, while physiological responses were measured using heart rate and electrodermal activity. ResultsInterpersonal synchronization was computed from neural and bodily signals, alongside a self- report measure of listening engagement and auditory attention decoding (AAD), a neural measure of selective attention. Interpersonal synchronization of all three modalities significantly predicted listening engagement, whereas neural interpersonal synchronization was the only measure that significantly predicted attention. These findings suggest that attention is primarily driven by cognitive processes represented in the brain, while listening engagement additionally involves affective processes that are more strongly reflected in bodily responses. ConclusionsOverall, this study demonstrates that different forms of interpersonal synchronization reflect distinct dimensions of the listening experience and supports interpersonal synchronization as a potential objective marker of listening engagement.

Neurofeedback (NF) is a promising method for helping individuals overcome choking under pressure. Identifying relevant neural biomarkers is crucial for developing effective NF. In this exploratory study, we aimed to investigate changes in prefrontal hemodynamic signals associated with golf-putting performance under psychological pressure using functional near-infrared spectroscopy. Participants engaged in a one-on-one golf-putting task against an experimenter, with monetary rewards introduced to induce psychological pressure. This manipulation successfully elicited psychological pressure, leading to impaired performance in some participants. Based on performance changes between the practice and competition sessions, participants were categorized into a non-choking group (performance improved) and a choking group (performance declined). Statistical analysis revealed significantly greater increases in prefrontal activation from practice to competition in the non-choking group than in the choking group, especially in the left superior frontal gyrus. Furthermore, moderate but statistically nonsignificant negative correlations were observed between changes in activation in this region and changes in putting error, indicating that greater activation increases tended to accompany less performance deterioration or greater performance improvement. These exploratory findings suggest that the left superior frontal gyrus warrants further investigation as a candidate biomarker for NF interventions aimed at mitigating choking under pressure.

Background: Chronic pain is a multidimensional condition that often persists despite conventional treatment and adversely affects multiple domains of daily life. Music listening has emerged as a promising non-pharmacological intervention, with accumulating evidence supporting its beneficial effects on pain and associated psychological outcomes. However, despite growing evidence of efficacy, the translation of music listening into routine clinical practice remains limited, partly because intervention reporting has received comparatively little attention. Objective: To evaluate the effectiveness of music listening interventions for chronic pain and systematically assess the methodological quality and completeness of intervention reporting to identify barriers to reproducibility and clinical implementation. Methods: Systematic searches were conducted in PubMed, Cochrane Library, CINAHL, and Web of Science through June 2025, with no date restrictions on publication. Randomized controlled trials involving adults with chronic pain receiving music listening interventions were included. Two independent reviewers screened studies, extracted data, and assessed risk of bias. Intervention reporting was evaluated using the TIDieR checklist, and a random-effects meta-analysis was performed for pain intensity outcomes. Results: Ten RCTs involving 538 participants were included. Music listening interventions varied substantially in delivery, duration, and music selection procedures, reflecting considerable heterogeneity in intervention design. Most studies reported significant improvements in pain and psychological outcomes. Meta-analysis of eight trials (10 effect estimates), demonstrated a moderate reduction in pain intensity (SMD = -0.53, 95% CI: -0.96 to -0.11, p = 0.014; I2 = 76.2%). Although intervention rationale and procedures were generally well described, reporting of intervention modifications, treatment fidelity, and adherence was frequently incomplete. These reporting deficiencies may compromise reproducibility and limit translation into clinical practice. Conclusions: Music listening appears to be a safe, accessible, and scalable non-pharmacological intervention for chronic pain management, with benefits extending beyond pain reduction to psychological wellbeing, quality of life, and functioning. However, incomplete reporting of key intervention components may limit reproducibility and hinder clinical implementation. Future trials should adopt standardized and transparent reporting standards to facilitate implementation into clinical practice.

Nonduality is a foundational but conceptually elusive notion across several contemplative traditions. Nondual traditions challenge the assumption that a subject-object structure characteristic of ordinary experience is an intrinsic feature of conscious awareness. However, little remains known about the neurocognitive mechanisms associated with such experiential state. Here, we investigated how Open Presence (OP) meditation, a form of non-dual mindfulness practice, modulates bodily self-representation and large-scale brain functional organization. We combined the Full-Body Illusion Experience (FBIE), a virtual reality paradigm manipulating bodily self-processing, with resting-state functional connectivity gradient analyses in expert meditators (>10,000 hours of practice) and meditation novices. We hypothesized that OP would attenuate bodily self susceptibility as measured by FBIE and increase large-scale integration of functional brain networks, consistent with prior findings linking reduced self-boundaries and ego-dissolution to increased connectome integration. Seventy-five participants (28 experts, 47 novices) underwent fMRI scanning during OP meditation. Brain network organization was assessed using connectivity gradients and network dispersion/ eccentricity metrics. Group differences were evaluated using bootstrap statistics and support vector classification. Compared with novices, expert practitioners showed reduced global network eccentricity during OP, particularly within dorsal attention, ventral attention, and frontoparietal networks, suggesting greater large-scale integration of functional networks. These neural patterns were positively correlated with FBIE self-report measures and negatively with cognitive defusion scores, a construct thought to reflect reduced self-grasping toward thoughts and mental contents. Together, these findings suggest that nondual meditation is associated with alterations in self-representation and increased large-scale functional integration, providing candidate neural markers of nondual awareness.

ObjectivesStroke commonly impairs proprioception and motor function, yet the cortical sensory processes underlying these impairments remain poorly understood. Prior electrophysiological studies have primarily focused on the average magnitude of unilateral cortical sensory responses to vibration, potentially overlooking distributed and trial-to-trial features of sensory processing that may be functionally relevant to proprioceptive processing and motor performance. We therefore aimed to characterize bilateral cortical sensory responses to determine their relationships with proprioceptive and motor function. MethodsEEG was recorded from forty-six individuals with chronic stroke during a rapid, passive, vibrotactile stimulation paradigm applied to the left and right fingertips. Somatosensory evoked potentials (SEPs) and event-related desynchronization (ERD) were quantified. Finger proprioceptive performance was assessed using a passive, robotic, finger crossing identification task, while motor function was evaluated using the Box and Block Test, Fugl-Meyer Assessment, and Nine Hole Peg Test. Associations with function were assessed using (i) unilateral sensory response magnitude at the contralateral parietal cortex and (ii) somatosensory decoder performance, defined as the accuracy with which a decoder identified the location of the stimulated hand (i.e. paretic vs. non-paretic) from combined bihemispheric response patterns. The association between these responses and proprioceptive ability and motor function was assessed. These associations were further evaluated jointly across multiple motor function measures using an exploratory analysis leveraging nonlinear dimensionality reduction and clustering. ResultsVibrotactile stimulation of the paretic hand elicited ipsilesional SEP and ERD that were reduced in magnitude compared to stimulation of the non-paretic hand. Both decreased SEP magnitude and reduced sensory decoder performance were associated with greater finger proprioceptive error. Unlike unilateral responses, the somatosensory decoders performance was also strongly associated with motor function, explaining approximately 22.5% of the variance in motor performance. Dimensionality reduction and clustering across multiple motor assessment scores showed distinct subgroups, that showed significant differences in sensory decoding. ConclusionsThe hemispheric distribution and discriminability of cortical sensory responses are functionally relevant markers of sensorimotor integrity after stroke. Assessing relative lateralization of somatosensory responses for each hand, rather than the magnitude of dominant contralateral responses alone, may better capture the reliability of sensory processing after stroke, as well as the distributed cortical reorganization supporting sensorimotor function. These findings support the potential value of a novel decoding-based neurophysiological measure for sensory-driven rehabilitation, biomarker development, and patient stratification.

Emotions are dynamic experiences that unfold over time, yet most affective neuroscience studies have relied on static stimuli and laboratory-based EEG systems. This study examined whether emotional valence and arousal can be reliably decoded using a consumer-grade wearable EEG device in naturalistic contexts. Forty-three participants viewed video clips designed to elicit four core affect categories including high-arousal positive, low-arousal positive, high-arousal negative, and low-arousal negative, while EEG signals were continuously recorded. Multivariate analyses, including classification, multidimensional scaling (MDS), and intersubject correlation (ISC), were employed to assess affective representation and neural synchrony. Behavioral data demonstrated robust classification of both valence and arousal, whereas EEG data yielded consistent above-chance classification of valence but less stable decoding of arousal, particularly in within-participant analyses. MDS revealed that both behavioral and EEG responses were primarily organized along the valence dimension, with weaker separation along arousal. ISC analyses further indicated frequency- and region-specific neural synchrony, with stronger alignment in left and temporal electrodes, though overall ISC values were modest, likely reflecting the brief duration of stimuli. Taken together, these findings suggest that valence is more stably represented in both subjective and neural domains, whereas arousal may require time-resolved or longer-duration approaches for reliable decoding. This work demonstrates the feasibility and limitations of employing wearable EEG for theory-driven affective neuroscience, underscoring its potential for scalable and ecologically valid emotion research beyond laboratory settings.

Perception and sensation are not synonymous. Rather, perception is a process whereby sensory input is organized and interpreted in a behaviorally relevant way based on memory, experience, and context. One specific framework that is commonly invoked to explain perception is that of Bayesian inference. This framework casts perception as a probabilistic process whereby imprecise sensory data are combined with prior knowledge (prior) to determine what is consciously perceived (the posterior probability), which reflects the brains best guess as to the cause(s) of the sensory data. A striking behavioral example of how prior information can influence perception is seen in studies in which degraded speech is rendered intelligible by presenting information about the speech content in advance. Neurophysiological studies of this phenomenon have primarily focused on how it affects neural indices of low-level sensory encoding. The size of any reported effects on these indices tends to be much smaller - and much less consistent - than the notably large effects on perception that come with prior information. In the present study, we recorded EEG from 27 healthy adult participants (16 female) as they listened to degraded speech clips that were preceded by matching or mismatching text. Prior knowledge in the form of matching text led to a large perceptual pop-out effect when listening to degraded speech. Analyses of the resulting EEG revealed: 1) significant but relatively weak effects of prior information on EEG measures of the linguistic encoding of speech; and 2) a very large effect of prior information on an EEG signal that resembles a well-established neural index of perceptual evidence accumulation and that was strongly related to speech intelligibility ratings across participants. These EEG signals likely relate to separate components of a Bayesian inferential process during the predictive perception of degraded speech. As such, they have implications for understanding predictive perception more broadly and for future research on perceptual disturbances in clinical populations.

Muscle fatigue potentially interferes with proprioceptive afference from peripheral "movement sensors"-- the proprioceptors, which may hinder the crucial sensorimotor integration and thus locomotor performance. However, little is known about how muscle fatigue affects cortical processing of proprioceptive afference. Twenty-four healthy volunteers (30.7 {+/-} 6.5 yrs, 13 females) participated in the experiment, which included magnetoencephalography (MEG) recordings during ankle proprioceptive stimulation (2-Hz passive movements), and fatigue tasks comprised of isometric ankle plantar flexion. Corticokinematic coherence (CKC) between foot acceleration and MEG signals was examined before (PRE) and [~]3 min after (POST) the fatigue tasks to quantify the cortical proprioceptive processing. CKC peaked in the gradiometer pairs above the foot region of the primary sensorimotor (SM1) cortex in each participant. CKC strength did not show significant difference between PRE and POST at 2 Hz (0.30 {+/-} 0.12 vs. 0.30 {+/-} 0.14, p = 0.981) or its first harmonic at 4 Hz (0.38 {+/-} 0.14 vs. 0.37 {+/-} 0.13, p = 0.724). However, 4-Hz MEG power was [~]30% lower in POST than in PRE. Surprisingly, fatigue-induced bilateral increase of alpha and beta power was observed in SM1 hand regions during the movement stimulation. Our results indicated that the early processing of proprioceptive afference from the ankle joint was negligibly affected by muscle fatigue, or it recovered rapidly. The effects of muscle fatigue on the proprioceptive processing appear to extend beyond the primary somatotopic regions to bilateral SM1 neuronal networks. This cortical adaptation to muscle fatigue potentially preserves proprioceptive processing by modulating SM1 inhibitory neurons, offering a novel perspective for future research on proprioception.

Although dopaminergic therapies in Parkinson's disease primarily restore dopamine within nigrostriatal circuits, symptoms are better indexed by whole-brain dynamics than by local activity. In this manuscript, we hypothesize that L-Dopa therapy affects whole-brain dynamics alike, which in turn relate to clinical improvement. To test this hypothesis, we conducted a repeated-measures, source-reconstructed MEG study in 13 bradykinetic-dominant PD patients, recording resting-state cortical activity OFF medication and ~1 hour after levodopa administration (ON). We characterize brain dynamics using a microstate framework, in which transition probabilities between microstates are used to contrast pathological OFF-state dynamics with those in the ON-state. Microstate dynamics were stable within medication states but reconfigured by L-Dopa, with greater departures from the OFF-state pattern associated, at the individual level, with larger clinical improvements. Our results suggest that individualized changes in microstate dynamics may serve as a neurophysiological marker of dopaminergic responsiveness.

Theft, including shoplifting, extorts a pervasive societal and economic burden. However, the neurobehavioral mechanisms underlying recurrent theft remain sparsely understood. In this study, we investigated social cognition deficits in theft recidivists with kleptomania (TR+K) and instrumental theft recidivists without kleptomania (TR-K) compared to control subjects without criminal records (CT), for which the Social Norms Questionnaire (SNQ-22) to assess explicit moral knowledge, alongside the Dictator Game (DG) and Hawk-Dove Game (HDG) to evaluate discretionary and competitive resource allocation with others, respectively, were administered. Bayesian statistical analyses revealed that all groups demonstrated comparable social norm recognition in SNQ-22 and prosociality in the DG. However, distinct behavioral profiles emerged in specific contexts, such that TR+K exhibited more unfairness than CT and TR-K at discretionary resource allocations in the DG, whereas in the HDG, TR-K demonstrated more aggressive, resource-monopolizing responses, particularly when against an aggressive opponent, than CT and TR+K. These results suggest that theft recidivism may stem from contextual failures rather than general deficits in moral knowledge, which are distinct between TR+K rooted in the internal factor, such as heightened loss aversion, and TR-K characterized by impulsivity over the external factor, such as social conflicts with others.

Understanding the neural dynamics underlying expressive musical performance remains a major challenge at the intersection of neuroscience, music cognition, and computational modeling. While EEG studies of emotion have largely focused on passive exposure to affective stimuli, comparatively little research has examined oscillatory brain activity during active musical expression. The present single-subject study investigated whether band-limited EEG activity recorded during expressive piano performance by a professional concert pianist contains sufficient discriminative structure to support supervised multi-class classification of musically defined emotional categories. MethodsEEG was recorded from 128 scalp sites while a professional concert pianist performed emotionally characterized excerpts from Bach, Beethoven, and Chopin in a continuous naturalistic session. Musical excerpts had been previously categorized and perceptually validated according to emotional valence, tempo, energy/arousal, and tonal structure. From the continuous EEG recording, 180 non-overlapping 2-second artifact-free segments were extracted, yielding 30 segments for each emotional category. Mean spectral power was computed within theta (3.5-7.5 Hz), alpha (7.5-12.5 Hz), and high-beta (24-30 Hz) frequency bands across selected centro-parietal and posterior electrodes, resulting in 24 EEG-derived features per segment. Linear Support Vector Machine, Random Forest, and Gradient Boosting classifiers were evaluated using an 80/20 train-test split combined with 5-fold cross-validation. ResultsEEG-only classification achieved above-chance performance across models, with Random Forest yielding the highest accuracy (0.42), macro F1-score (0.414), and Cohens {kappa} (0.30), exceeding the theoretical chance level of 0.167. Feature importance analysis revealed distributed contributions across theta, alpha, and high-beta oscillatory activity, particularly over parietal and occipital regions, without evidence for a single dominant neural marker. Inclusion of an additional binary arousal-related feature substantially improved Random Forest performance (accuracy = 0.58; macro F1 = 0.579; {kappa} = 0.50), indicating that arousal organization contributed strongly to category separability within the classification framework. ConclusionsThese findings suggest that oscillatory EEG activity accompanying expressive musical action contains measurable statistical structure associated with emotionally differentiated performance states. Rather than identifying discrete neural correlates of emotion, the present results provide a computational characterization of distributed oscillatory dynamics emerging during expressive motor-acoustic interaction, extending affective EEG research beyond passive perception paradigms toward ecologically grounded musical performance contexts.

While extensive research has been conducted on emotion recognition from facial stimuli, it remains unclear how embodied emotional cues conveyed through body postures, gestures and actions (e.g., stick figures) compare with facial (human faces) and face-like symbolic representations (emoji faces) in shaping behavioral and neural responses. We employed a multimodal approach, combining behavioral measures (accuracy and reaction time) with electroencephalography (EEG) to examine the electrophysiological correlates of emotion recognition. Overall, sixty-six (equal number of males and females; 18-30 year old) participants identified positive, negative, and neutral emotions depicted in the three formats. Behavioral results showed significant effects of both emotion and format on accuracy and reaction time. Emoji faces were recognized with the highest accuracy and fastest reaction times, followed by stick figures and then human faces (p < .001, some comparisons p < .05). Thirty-four participants (17 males and 17 females) underwent EEG, which revealed distinct patterns of event-related potentials (ERPs). The Early Posterior Negativity (EPN) amplitude showed a significant overall effect of format. Post-hoc comparisons indicated that stick figures elicited greater (more negative) EPN amplitudes than human faces during positive emotion recognition (p = .003), and greater amplitudes than both emoji faces (p = .027) and human faces (p = .007) during negative emotion recognition. No significant differences were observed between emoji and human faces. N170 and Late Positive Potential (LPP) amplitudes did not reveal significant differences (all p > .05). Correlation analyses revealed no significant associations between ERP and behavioral measures. Thus, abstract, minimalistic representations like stick figures elicit enhanced early emotion-related processing despite similar early and later processing across formats. HighlightsO_LIEmotion recognition across realistic (human faces), symbolic (emoji faces) and embodied (stick figures) modalities were compared. C_LIO_LIEmotions were recognized fastest and most accurately in emoji faces format. C_LIO_LIStick figures format elicited significantly higher EPN compared to other two formats across positive and negative emotions. C_LIO_LINo significant differences were observed in terms of N170 and LPP. C_LIO_LIEmbodied, abstract emotional cues modulate automatic emotional appraisal, rather than initial sensory encoding and sustained cognitive evaluation. C_LI

The human face is central to social interactions, supporting the ability to interpret others mental states using theory of mind (ToM). We examined whether functional near-infrared spectroscopy (fNIRS) would reveal brain-activation differences between live and pre-recorded social conversations in brain regions implicated in ToM. Furthermore, we examined whether activation depended on the visual realism of a social partner - viewed as a human or an animated avatar. By one view, social interactions may be dependent on how natural the social partner appears; by another view, social interactions may depend only upon the attribution of responses to a real human regardless of visual appearance. Neural activation for pre-recorded compared to live interactions was prolonged, consistent with extended cognitive effort. Activation patterns in the right temporoparietal junction differed between interacting with humans versus avatars, along with a stronger preference for looking at the eyes when interacting with a human (vs. avatar), underscoring the social relevance of real faces. Findings highlight the importance of both live interactions and facial realism in shaping social-cognitive processing, a finding with relevance for optimizing online social interactions.

Introduction - Neurofeedback (NFB) has demonstrated efficacy in treating various disorders, often achieving substantial symptom reductions. Despite its effectiveness, a significant percentage of users (non-responders), fail to benefit from NFB. Addressing this issue, the study at hand investigates the role of NFB design on neuro-physiological responses. Method - event related potentials (ERPs) are examined in response to the application of different aesthetic principles in the context of NFB stimulus design. Drawing from Self-Determination Theory and ERP studies in the field of web design, 16 feedback stimuli were developed according to specific design principles. Stimulus design effects were inspected by means of ERPs allowing for the assessment of implicit and fast electroencephalogram (EEG) reactions. Results of n = 38 participants indicated distinct ERP response patterns at time window of interest 1 (TWOI-1; 100-200 ms) and TWOI-2 (200-300 ms), predicted by beholder-based liking and complexity of stimuli. The findings align with the proposed hypotheses suggesting that aesthetic evaluation of NFB stimuli occurs rapidly and implicitly. In response to the aesthetic vs. non-aesthetic categories, the findings were mixed. The results underscore the importance of further exploration of aesthetic design guidelines in the context of NFB applications. It is discussed how NFB aesthetics relate to Processing Fluency and Affective Prediction Error Theory, while the theoretical methodological issue of the Fixed Effect Fallacy is taken into consideration. The study contributes to the broader understanding of how design elements can affect therapeutic efficacy and engagement in NFB and Human Computer Interaction in therapeutic contexts in general.

The human brain undergoes profound changes from childhood to adulthood. These changes are foundational to cognitive, affective and social development, and measuring them is essential for identifying atypical development. A common approach consists of analyzing metrics derived from brain activity, such as spectral power, aperiodic activity and signal complexity. However, individual metrics are sensitive to external factors unrelated to development, contributing to inconsistent findings in the literature. Moreover, these metrics are not independent; they show some degree of intrinsic redundancy, which itself evolves across development. Here, we propose a novel approach that focuses on the relationships between neural features rather than their values, defining a "neural feature space" that captures the geometry of brain activity. We analyzed the neural feature spaces of children (4-12 years) and adults (30-45 years), based on 128-channel EEG recordings during naturalistic movie viewing. Specifically, we computed a range of spectral, aperiodic and complexity features and quantified pairwise distances between them using latent variable modeling. Neural feature spaces were significantly different between age groups. Notably, high frequency bands were less differentiated in children and distances between spectral and complexity features differed. Crucially, distances were highly stable across tasks, in contrast to feature values, which varied substantially. These findings suggest that the geometry of neural feature spaces provides robust, interpretable markers of neurodevelopment, offering a complementary approach to feature-based analyses.

Abstract Background: Non-specific chronic low back pain (NSCLBP) is associated with persistent pain, reduced health-related quality of life (HRQoL), and low-grade systemic inflammation. This study examined associations among changes in inflammatory biomarkers, pain intensity, and HRQoL following a 12-week aerobic exercise programme. Methods: This secondary analysis used data from a randomized controlled trial involving 41 participants with NSCLBP (intervention, n = 21; control, n = 20). Participants received either supervised aerobic exercise plus health education or health education alone for 12 weeks. Change scores for tumour necrosis factor-alpha (TNF-), interleukin-6 (IL-6), high-sensitivity C-reactive protein (hs-CRP), pain intensity, and HRQoL domains were analysed using correlation and multiple regression analyses. Results: Improvements in IL-6 (r = 0.434, p = 0.005) and hs-CRP (r = 0.444, p = 0.004) were significantly associated with improvements in pain intensity. No significant associations were observed between biomarker changes and HRQoL domains. Treatment allocation was the strongest independent predictor of improvement in physical HRQoL ({beta} = 0.492, p = 0.017) and pain intensity ({beta} = -0.512, p = 0.006). Conclusions: Improvements in IL-6 and hs-CRP were associated with reductions in pain intensity but not with improvements in HRQoL. Treatment allocation was the strongest predictor of clinical improvement, suggesting that mechanisms beyond systemic inflammation may contribute to the benefits of aerobic exercise in NSCLBP. Keywords: non-specific chronic low back pain; aerobic exercise; inflammation; interleukin-6; high-sensitivity C-reactive protein; pain intensity; health-related quality of life.

Dietary iron deficiency in the absence of anemia (IDNA) affects numerous people worldwide, with a wide range of negative effects on brain functioning and cognition. Although studies employing electroencephalography (EEG) have revealed a number of negative effects of IDNA in both the time- and frequency domains, to date there have been no attempts to characterize the effects of IDNA on the temporal dynamics of whole brain interactions. To address this issue, we applied multiscale entropy (MSE) analysis to resting-state EEG data collected from IDNA (n = 21) and iron sufficient (IS, n = 21) women. The MSE analysis on this data revealed that entropy was higher overall for the IS than the IDNA group, with significant differences appearing primarily at longer time scales and under right frontal and left and right parietal electrodes. These results suggest that IDNA may negatively affect long-distance interactions among brain regions and that this could conceivably be a source of diminished cognitive function and neural resilience in IDNA.