Frontiers in Human Neuroscience

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.

Facial perception is a central feature of everyday social encounters and a rich source of emotional information. Classic functional magnetic resonance imaging (fMRI) studies of emotional facial processing used static photos emotional expression to identify regions of the brain showing univariate differences in response magnitudes between different emotional categories. However, there has been much less work identifying how the brain represents dynamic emotional facial expression and the factors that drive the similarity among these representations. In the current study, incorporated dynamic facial expression stimuli and representational similarity analysis to compare three competing hypothesized models of similarity of each of the stimuli presented: action being made, valence of the expression, and the identity of the person being perceived. Participants were shown short videos of fourteen volunteer actors making positive or negative facial expressions directed either toward or away from the camera. Activation patterns were compared against competing models on a trial-by-trial basis using a full multilevel modeling approach. Results showed that the identity of the person in the video was a greater predictor of brain responses similarity than the action or valence across widely distributed brain systems, particularly in the default mode network and lower-level visual processing regions. This suggests that the specific identity of the stimulus being perceived is a central driver of neural response similarity during perceptual encoding in dynamic facial processing.

ObjectiveAdults with knee osteoarthritis often experience movement-evoked pain (MEP), and that pain has the potential to alter gait mechanics and influence disease progression. However, the associations between MEP and gait biomechanics have only been assessed in typical lab settings. Gait mechanics differ in the lab compared to in the real-world, thus it is unknown whether these associations between pain and gait translate to real-world settings. Therefore, this study aimed to measure concurrent changes in MEP and gait mechanics across three days of typical real-world activity. DesignSeventeen participants with self-reported physician-diagnosed symptomatic knee osteoarthritis wore inertial measurement units on their more symptomatic limbs thigh and shank, as well as on both feet for three days of typical activity. Participants were sent 5 automated text messages a day and were instructed to complete a short 3-5 minute walk and self-report their MEP via a Numeric Rating Scale (0-10) during each of the walks. A random coefficients model was used to determine how gait speed, stride length, and knee and ankle range of motion was related to changes in pain intensity. ResultsThe average MEP experienced during the instructed walks was 1.4 {+/-} 1.3 with individual participant average pain intensities ranging from 0 to 4.8. Greater MEP was associated with a 2.7{degrees} decrease in knee range of motion per unit increase in pain (95% CI [-4.8 -0.5], p = 0.02). Seven of the seventeen participants never reported a pain level of 0. Speed, stride length, and ankle range of motion did not differ by pain intensity. ConclusionsIncreases in MEP were associated with decreases in knee range of motion. A 2.7{degrees} decrease in knee range of motion in response to a 1-unit change in pain is meaningful as 5{degrees} is generally considered the threshold for a meaningful difference in joint angles. With a change in pain intensity of 2 being common with daily activity, individuals may be experiencing meaningful changes in knee joint angles regularly. With gait mechanics being associated with disease progression, these daily acute fluctuations in pain may be influencing disease progression rates.

BACKGROUND: Dual task walking requires simultaneous management of cognitive and motor demands and is associated with changes in gait and cortical activation. However, the relationship between task related cortical recruitment and dual task related gait adjustments in healthy young adults remains unclear. This study aimed to investigate the effects of dual tasking on gait performance and cortical activation, and to examine the association between changes in cortical activity and dual-task costs. METHODS: This cross sectional study included 33 healthy young adults. Participants performed three conditions: single task walking, cognitive single task (verbal fluency), and dual task walking. Each condition was repeated 10 times using a repeated short block design with randomized trial presentation. Gait performance was assessed using an instrumented walkway, and cortical activation was measured using functional near infrared spectroscopy. Dual task costs were calculated for gait and cognitive outcomes. Statistical analysis included repeated measures analysis of variance (ANOVA) and Wilcoxon signed rank tests, with false discovery rate correction for multiple comparisons. Associations between changes in cortical activation and dual task costs were examined using correlation analyses. RESULTS: Dual task walking resulted in significant changes in gait, including reduced speed, step and stride length, and increased base of support, stance, and double support (all p < 0.05), while cognitive performance remained unchanged. Dual tasking was associated with increased cortical activation in left prefrontal and motor related regions. Greater increases in cortical activation were associated with lower dual task costs across most gait parameters, with significant correlations observed in the left dorsolateral prefrontal cortex (r {approx} 0.42 to 0.47 for speed and stride length; p < 0.05). Double support showed a distinct pattern, suggesting a specific temporal adjustment within the gait cycle. CONCLUSIONS: Dual task walking in young adults is associated with coordinated behavioral and cortical adaptations. Increased cortical recruitment is linked to reduced motor interference, suggesting that broader engagement of cortical networks may contribute to performance under cognitive motor load.

Chronic pelvic pain (CPP) affects up to 26% of women worldwide. While its pathophysiology is poorly understood, disturbances in body perception have been identified in various similar chronic musculoskeletal disorders. The Fremantle Perineal Awareness Questionnaire (FrePAQ) is a novel tool designed to specifically assess disturbed body perception in the pelvic region, but its structural validity and reliability require formal evaluation. Methods: Patient partners with lived experience contributed to study design. Participants with (n=417 and without (n=277) chronic pelvic pain completed the FrePAQ at baseline, as well as one week later. We assessed the validity and reliability of the FrePAQ following COSMIN guidelines for Classical Test Theory. Results: The validated FrePAQ comprises a two factor model, with a six item Distress & Disconnection (D&D) subscale and a two item Size & Shape (S&S) subscale. Confirmatory analysis showed excellent fit (CFI = .988; RMSEA = .048) and measurement invariance between diagnostic groups. Internal consistency was high (cronbach alpha = .838 CPP, .819 controls). Test retest reliability was high for D&D (ICC = .863) and acceptable for S&S (ICC = .695). FrePAQ scores showed a weak to moderate correlation with pain scores (r = .234 to .255), psychological distress (r = .226 to .443), and functional impact (r = .172 to .295), particularly for the D&D subscale. Conclusion: The FrePAQ is a reliable and valid instrument to measure perineal perceptual disturbances in CPP. Future research will evaluate the tools potential to support phenotyping and guide individualised interventions. Improved understanding of body perception disturbance in CPP can enhance diagnosis and treatment precision.

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.

PurposeParkinsons disease (PD) is a neurodegenerative disease that affects motor control but can also influence sensory perception. Changes in vision and proprioception are well-documented but less is known about how PD alters auditory perception, particularly perception of speech acoustic properties. The current study examined perception of speech rate and intensity in PD and the relationship of auditory perception to disease severity. MethodPeople with PD were compared to age- and hearing-matched controls using perceptual tasks focused on discrimination and learning of speech rate and intensity. For rate discrimination, speech, non-speech, and visual stimuli were included to determine whether performance differences for PD participants and controls were specific to speech. Disease severity was assessed using the MDS-Unified Parkinsons Disease Rating Scale (MDS-UPDRS) and the relationship to performance on perceptual discrimination and learning tasks was evaluated. ResultsPeople with PD performed significantly worse than controls in the rate discrimination task for all types of stimuli. There were no significant group differences for intensity discrimination. However, participants with greater PD disease severity demonstrated significantly poorer intensity discrimination accuracy. Performance on learning tasks utilizing rate and intensity manipulations did not differ between PD and control participants and was unrelated to PD disease severity. ConclusionsPeople with PD had difficulty discriminating rate differences across speech, non-speech, and visual stimuli, indicating that challenges with rate perception are not limited to speech. The relationship between intensity discrimination and disease severity suggests common dopaminergic networks between motor symptoms and auditory perception in PD.

IntroductionFunctional magnetic resonance imaging (fMRI) is widely used to study neural processes of behavior, but evaluations of test-retest reliability (TRR) of task-related blood-oxygen-level-dependent (BOLD) responses are scarce for many cognitive tasks. Such information is particularly important for longitudinal and intervention research. The ability to learn associations between choices and outcomes across decision stages is crucial for daily behavior. We assessed the measurement reliability of behavioral performance and fMRI BOLD signals during value-based sequential decision making to evaluate the TRR of task-relevant regions for future research on non-invasive brain stimulations. MethodsTwenty healthy adults (22 to 40 years) completed two task-fMRI sessions that were at least 2 weeks apart. During scanning, participants performed two variants of a three-stage Markov decision task with conditions varied in temporal contingency (immediate vs. delayed) and magnitude of choice outcomes (high vs. low). Both sessions were conducted under sham tDCS via a focal 3 x 1 montage targeting left dorsolateral prefrontal cortex (DLPFC). The TRR was assessed using intraclass correlation coefficients (ICC) with a two-way mixed-effects consistency model for decision performance and task-related fMRI signals at voxel-wise level and summarized in key regions defined by the extended Human Connectome Project atlas (HCPex). ResultsDecision performance was lower with delayed than immediate outcomes (p < 0.001). Higher outcome magnitude improved performance (p < 0.001). Decision performance increased across learning bins (p < 0.001). The behavioral TRR was in the moderate to good level (ICC(3,1) = 0.742 for accuracy; ICC(3,1) = 0.801 for reaction time). At the whole-brain level, contrasting brain activities in delayed with immediate condition revealed suprathreshold cluster peaks in several frontal-parietal (e.g., bilateral orbitofrontal, bilateral dorsolateral prefrontal, and medial parietal cortices) and striatal regions (e.g., bilateral putamen). Voxel-wise ICCs revealed variable but partly good-to-excellent TRR across task-relevant regions, with stronger reliability in several striatal, orbitofrontal, and left dorsolateral prefrontal parcels, and more variable reliability across anterior cingulate and medial prefrontal parcels. ConclusionThese results from a 2-session tDCS sham-sham stimulation study establish the validity of using the three-stage Markov decision task in future studies about intervention effects on the frontal-parietal-striatal network.

Empathy, a key element of social interaction, involves both cognitive and affective processes and is commonly investigated through measures such as empathic accuracy and affective physiological synchrony. While physiological synchrony offers a continuous measure of affective processes, empathic accuracy typically relies on discrete self-reports, leaving their temporal relationship largely unexplored. Advancing this line of research requires datasets that integrate time-continuous self-reports with physiological signals, yet such datasets--particularly those focusing on the empathizee--remain limited. To fill this gap, we present EMPAC (Empathy Measurement: Physiological, Affective, and Cognitive), a multimodal dataset constructed. To create empathy-eliciting stimuli, professional actors performed emotionally intense, pseudo-autobiographical narratives while their physiological signals (e.g., ECG, EDA) and continuous self-reported emotional states were recorded. We then conducted two observer experiments using these video recordings. In Experiment 1, to validate the stimuli as empathy-eliciting materials, observers continuously rated emotional intensity without being informed of the specific emotion portrayed, following the protocol of previous studies on time-series empathic accuracy. Yet this approach sometimes revealed a gap between the emotion category portrayed by the target and that perceived by the observers. In Experiment 2, we introduced a revised procedure in which the target emotion category was disclosed prior to viewing, revealing that specifying the target emotion led to a different relationship between individual empathy traits and empathic accuracy than observed in Experiment 1. EMPAC thus provides a rich, temporally aligned resource for investigating empathy dynamics in naturalistic settings and for evaluating methodological variations in empathic accuracy paradigms.

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.

Background: Low-intensity focused ultrasound (LIFU) is an emerging noninvasive neuromodulation technique capable of targeting deep cortical and subcortical structures with high spatial precision. In healthy human volunteers, LIFU has demonstrated a favorable safety and tolerability profile across multiple studies. However, its safety and tolerability in clinical populations remains poorly characterized, representing a critical barrier to clinical translation. Here, we prospectively evaluate the safety and tolerability of LIFU targeting the left dorsal anterior insula (dAI) in patients with fibromyalgia (FM). Methods: In a single-blind, sham-controlled, within-subjects crossover design, 13 individuals with FM (43.1 +/- 13.2 years; 12 female) received 10 minutes of active LIFU (500 kHz, 1 kHz PRF, 36% duty cycle, 4.2 W/cm2 Isppa; 100 x 1-second pulse trains with a 5-second inter-train interval) targeting the left dorsal anterior insula (dAI) or sham on separate visits. Safety was evaluated through neuroradiological review of post vs. pre LIFU FLAIR MRI, quantitative voxel-wise FLAIR analysis, and patient report of symptoms (ROS). Tolerability was assessed using an experience assessment. Efficacy of the LIFU intervention was assessed using quantitative sensory testing (QST) including temporal summation of pain (TSP) and conditioned pain modulation (CPM). Results: Neuroradiological review identified no new evidence of edema, microhemorrhage, acute ischemia, or white matter injury on post-LIFU structural imaging. Quantitative FLAIR analysis using contralateral-mirror-referenced relative FLAIR (rFLAIR) showed no significant within-subject change in the stimulated beam volume (delta rFLAIR = 0.002 +/- 0.025, t(12) = 0.30, P = 0.769, Cohen's dz = 0.08). No serious adverse events were documented and ROS indicated no change due to LIFU sonication. Participants rated the procedure as comfortable and could not distinguish active from sham LIFU. LIFU did not result in statistically significant changes for TSP (p = 0.797) or CPM (p = 0.465). Conclusions: Ten minutes of LIFU targeting the left dAI was safe and well tolerated in individuals with FM, with no neuroradiological or quantitative MRI evidence of tissue effects and no serious adverse events. Blinding was preserved, and participants rated the procedure as comfortable. Although no significant changes were observed in experimental pain measures, these findings support the feasibility of targeting deep salience and pain amplification circuitry with LIFU in patients with FM and provide a foundation for adequately powered efficacy trials.

Remote instruction is increasingly used to teach complex sensorimotor skills, yet conventional audio-video communication poorly conveys the fine-grained attentional cues that support expert guidance. This study tested whether real-time bidirectional gaze sharing enhances remote transfer of piano performance skill by restoring joint visual attention between teacher and learner. Twenty-seven conservatory-level pianists were randomly assigned either to a group, in which teacher and learner gaze positions were visualized during online instruction, or to a group receiving otherwise identical instruction without gaze cues. We recorded eye movements with wearable eye trackers and evaluated piano performance using a high-resolution key-motion sensing system. Real-time gaze sharing increased learners gaze-pattern similarity to a teacher, which was not evident in the control group. A parallel effect was observed for head-movement similarity. Critically, gaze sharing also reduced variability of the key-descending velocity at the moment of finger-key contact for the right-hand landing after a leap, a feature associated with unstable key-striking velocity. These findings exhibit that gaze information is not merely an auxiliary communication cue but a timing-critical coordination channel for remote motor instruction. By augmenting video-mediated pedagogy with shared attentional dynamics, the proposed system offers a framework for transmitting tacit, high-dexterity skills across distance.

BackgroundElectroencephalographic (EEG) studies attempting to characterise the neural signature of meditation typically rely on contrasts with passive rest or comparisons among practitioners based on experience. However, these approaches rarely include active control states and seldom establish the reliability and robustness of identified quantitative EEG features. Consequently, the validity of proposed neurophysiological markers of meditative state remains uncertain. The present study addressed these limitations by using a reliability-informed, multi-session within-subject design to characterise distinct state-dependent EEG dynamics in experienced meditators from the Brahmakumaris Rajayoga tradition. MethodsThirty long-term meditators underwent repeated EEG recordings over two days, comprising two meditation sessions per day. Each meditation block was flanked by rest periods, with a cognitive task between sessions to reduce carryover effects. We quantified broadband spectral power, aperiodic slope and intercept, and nonlinear dynamical measures, including detrended fluctuation analysis (DFA), Higuchi fractal dimension, and permutation entropy (PE), across meditation, rest, and task conditions. ResultsCompared with both rest and task states, meditation was associated with increased theta-alpha power, an elevated aperiodic intercept, and systematic modulation of nonlinear indices (DFA, Higuchi, PE). Further meditative core features demonstrated high inter-session test-retest reliability, strong inter-individual consistency, stability across guided and silent meditation states, and were not moderated by years of meditative experience. ConclusionThe present framework identifies a reproducible neurodynamic core of meditation, distinct from passive and active control states, spanning spectral, aperiodic, and nonlinear EEG domains in long-term meditators. These findings enhance the construct validity and measurement reliability of meditation-specific neural markers.

BackgroundTheta-frequency transcranial alternating current stimulation (tACS) over prefrontal cortex has been proposed to modulate working memory (WM), yet behavioral effects are often inconsistent. One potential source of variability is the tACS phase during stimulus presentation. ObjectiveWe tested whether behavioral performance during WM depends on the phase of prefrontal theta-tACS. MethodsTwenty participants completed two sessions of prefrontal 4 Hz tACS in a within-subject design, receiving active and sham stimulation in separate sessions. Participants performed a visuospatial change detection task (CDT) and a verbal N-back task. Stimulation effects on overall accuracy and reaction time were analyzed. Subsequently, phase-specific analyses related stimulation phase at task-relevant stimulus presentation to behavioral performance using circular regression models. Preferred phases across participants were tested using Rayleigh tests. ResultsNo significant overall effects of active compared with sham tACS on accuracy or reaction time were observed in either task. However, phase-specific analyses revealed stronger phase-dependent modulation of reaction time during active tACS compared with sham. In the CDT, this effect was present across difficulty levels, whereas in the N-back task it was observed only in the 3-back condition. No reliable phase-dependent effects were observed for accuracy. Preferred phases varied across participants and did not cluster around a common phase. ConclusionsPrefrontal theta-tACS can modulate WM performance in a phase-dependent manner even in the absence of average behavioral effects. The observation of phase-dependent reaction-time modulation across visuospatial and verbal WM tasks suggests that stimulation phase may be a relevant source of variability across cognitive domains.

Mental rotation in 3D is a key cognitive skill involving dynamic spatial transformations, for which pronounced individual differences have been documented. Here we ask whether individual differences in 3D abilities can be explained by analogous differences in 2D abilities. 3D mental-rotation was assessed by the Vandenberg & Kruse Mental Rotation Test (3D-MRT) and examined for association with performance and underlying electrocortical mechanisms during a 2D letter rotation task. Participants (N=40) first completed the MRT and then performed a computerized 2-D letter rotation task in which they had to identify whether letters were oriented in a standard or a mirrored direction (parity judgment) when rotated at 0{degrees}, 60{degrees}, 120{degrees}, and 180{degrees} while EEG was recorded. Reaction times (RTs) and error rates increased with angular disparity. The angular disparity effect on RT was smaller for mirrored letters. Low, relative to high, 3D-MRT scoring participants showed more pronounced accuracy declines at higher rotation angles. An EEG Event Related Potential (ERP) known as the Rotation-Related Negativity (RRN) became more pronounced with increasing angular disparity. High 3D-MRT scores were associated with a stronger RRN response at central-parietal sites. In addition, the ERP-P3b wave was more pronounced at central-parietal sites for low 3D-MRT scorers, independent of angular disparity. It is concluded that 3D rotational ability is positively associated with 2D mental rotation performance, and more strongly with enhanced recruitment of neural visual-spatial cortical representations than with enhanced recruitment of more general cognitive resources.

PurposeTo examine speech iconicity for shape in aphasia, we compared iconicity ratings from people with aphasia to those from neurologically intact individuals and evaluated how iconicity relates to phonological and semantic processing profiles in aphasia. MethodEleven people with aphasia and 11 age- and gender-matched neurologically intact participants rated how rounded or pointed 50 auditory pseudowords sounded using a 5-point scale. Ratings from participants with aphasia were compared to predicted iconicity ratings derived from reference ratings from prior work and to ratings from neurologically intact participants. For each participant with aphasia, correlations between individual ratings and predicted ratings were related to measures of phonological and semantic processing. ResultsRatings from people with aphasia were significantly correlated with both the predicted ratings and the ratings from neurologically intact participants. The strength of the correlation between individual ratings and predicted ratings did not differ significantly between groups, although there was a trend toward weaker correlations in the aphasia group. There were indications that greater language impairment was associated with greater disruption of iconicity ratings; in particular, deficits in phonological segmentation and semantic processing were associated with reduced sensitivity to shape iconicity. ConclusionThese findings suggest that sensitivity to shape iconicity is preserved in individuals with aphasia to varying degrees. The specific nature of language impairment appears to play an important role in determining iconicity processing in aphasia.

BackgroundResting-state functional imaging is increasingly used to understand how cortical networks modulate and respond to pain. Awake imaging with a minimally invasive approach is key to observe the natural state of the brain. As migraine with aura, a common headache disorder, can be experimentally modeled by cortical spreading depressions (CSD) in rodents, it is essential to understand the impact of CSD on functional connectivity and network topology to find imaging cues of trigeminovascular activation and headache. MethodsWe used awake widefield intrinsic optical-signal imaging (IOSI) on optically cleared windows to non-invasively characterize the impact of CSDs on bihemispheric resting-state static and dynamic functional connectivity patterns and network topology. A subset of mice was chronically treated with amitriptyline to examine the effect of susceptibility to CSD on connectivity. After baseline imaging, CSD was triggered optogenetically and confirmed by laser speckle contrast imaging. A group of mice received intraperitoneal naproxen after CSD to suppress headache. IOSI was repeated at 30 minutes, 60 minutes, 4 hours, and 24 hours after CSD. The mouse grimace scale was scored at each time point for behavioral headache documentation. ResultsWe observed time-dependent changes in resting-state functional connectivity that were reversed by naproxen. Amitriptyline, a prophylactic migraine medication, decreased susceptibility to CSD and modified resting-state functional connectivity differently than controls. Network analysis with graph-theoretical methods revealed barrel and retrosplenial cortices as potential key players in trigeminal pain processing after CSD. Dynamic functional connectivity analysis demonstrated functional connectivity states, with fractional occupancy and mean dwell time of these states showing distinct CSD and pain-modulated states. A support vector machine was utilized to predict CSD-mediated dynamic connectivity changes in controls. ConclusionOur results bring insight into potentially headache-associated changes in resting-state cortical functional connectivity after CSD and how this functional reorganization is influenced by acute and chronic medications for migraine.

The proliferation of gambling advertising has intensified concerns regarding its influence on vulnerable populations, yet the neural mechanisms underlying cue-reactivity to these stimuli remain underexplored in ecologically valid settings. This study protocol proposes a novel methodological framework to investigate prefrontal cortical responses to gambling advertisements in individuals with varying degrees of gambling experience. Materials and methods: This cross-sectional study will recruit 44 participants, divided into a clinical group (individuals with high-frequency gambling or gambling disorder) and a matched control group. Neural activity will be recorded using fNIRS while participants view gambling-related, neutral, violent, and sexual stimuli. Secondary measures include validated scales for gambling severity (SOGS), impulsivity, sensation seeking, and alexithymia. Data analysis will primarily utilize inter-subject correlation (ISC) to quantify neural synchronization and multiband frequency decomposition to capture dynamic affective processing. Advanced preprocessing, including short-channel regression, will be applied to ensure signal robustness. Discussion: By combining portable neuroimaging with a data-driven ISC approach, this study aims to identify objective neural markers of gambling vulnerability. The findings will provide novel insights into the idiosyncratic processing of commercial stimuli, potentially informing public health policies and the development of more effective evidence-based regulations for gambling marketing.

Brain stimulation is increasingly recognized as an effective and important therapeutic intervention for many brain diseases. Distance between the scalp and other brain regions is a pivotal variable for neurostimulation planning and the development of new techniques, but alterations in the distance between the scalp and other regions in brain diseases are largely unknown. In this study, we developed an automatic pipeline to calculate scalp-to-region distance (SRD) values from T1 MR images and applied it to a total of 1382 participants, including patients with autism spectrum disorder (ASD), Parkinsons disease (PD), Alzheimers disease (AD), and cognitively normal controls (CNs). Cloud points were uniformly sampled on the automatically extracted scalp surface and cortex surface, on which the point-wise distance maps were generated. The brain was then coregistered with the BCI-DNI atlas, and SRD value for each brain region was extracted. Analysis of covariance (ANCOVA) was performed for SRD in each brain region, with age and sex as covariates. Compared with CNs, ASD patients showed widespread SRD decreases across the brain with prominent involvement of the frontal lobe, especially the orbitofrontal cortex and adjacent regions. In contrast, in AD patients, significantly increased SRD values were observed in various regions of the frontal gyrus. No significant SRD alteration was found in PD patients after correction. The automatic SRD calculation pipeline and the different patterns of SRD alterations in these diseases might be helpful for future neurostimulation planning in clinical practice. HighlightsO_LIAutomatic pipeline enables scalp-to-region distance (SRD) measurement, facilitates brain stimulation planning. C_LIO_LIASD patients show widespread SRD decreases, especially in the orbitofrontal cortex and adjacent regions. C_LIO_LIAD patients present increased SRD in the frontal gyrus and decreased SRD in the parahippocampal gyrus. C_LI

BackgroundTranscranial magnetic stimulation (TMS) over the primary motor cortex (M1) elicits motor-evoked potentials (MEPs), a neurophysiological marker of corticospinal excitability. Ongoing brain activity at the time of stimulation, such as the phase and power of the sensorimotor mu rhythm (8-13 Hz), has a significant impact on MEP amplitudes. However, it remains unclear whether these endogenous excitability states also influence the consistency of MEP amplitudes across repeated trials. ObjectivesWe investigated whether instantaneous mu dynamics modulate not only the magnitude but also the consistency of corticospinal responses to TMS. MethodsTwenty-nine healthy participants received 1200 single TMS pulses over the left M1 during simultaneous EEG recording. Trials were stratified based on pre-stimulus mu power, phase, and interhemispheric M1-M1 functional connectivity. Brain-state-resolved MEP variability was quantified using the coefficient of variation (CV) within subsets of trials defined by similar pre-stimulus mu dynamics. ResultsTrial subsets characterized by high mu power or high M1-M1 functional connectivity were associated with reduced MEP variability, indicating more consistent corticospinal output. In contrast, the mu phase did not significantly influence response consistency. Brain-state-resolved MEP variability showed greater stability across sessions compared to MEP variability estimated from random trial subsampling. ConclusionsPre-stimulus mu dynamics shape not only magnitude but also consistency of corticospinal responses to TMS. We show that corticospinal response consistency reflects a structured, brain-state-dependent property of the sensorimotor network. These findings contribute to our mechanistic understanding of brain-state-dependent neuromodulation and may be leveraged to reduce variability and improve efficacy to TMS. HighlightsO_LIOngoing sensorimotor mu dynamics shape both magnitude and consistency of MEPs. C_LIO_LITrial subsets characterized by high mu power were associated with reduced MEP variability. C_LIO_LIMu phase modulated MEP amplitude but did not influence MEP consistency. C_LIO_LIBrain-state-resolved estimates of MEP variability were more reliable across sessions. C_LIO_LIFuture TMS protocols may reduce effect variability by targeting stable excitability states. C_LI