Clinical Neurophysiology

Background and Objectives Interictal spikes on intraoperative electrocorticography have been used to localize the epileptogenic zone but have limited specificity. We hypothesized that identifying spatially distributed, spike-associated very high-frequency activity (vHFA; 500-2,000 Hz) would improve the ability of spikes to localize the epileptogenic zone. We aimed to characterize spike-associated vHFA and to determine whether a seizure outcome prediction model incorporating vHFA could be externally validated across independent centers. Methods This retrospective two-center cohort study included patients with drug-resistant focal epilepsy who underwent electrocorticography and subsequent resection between January 2016 and May 2025. Spikes occurring across contacts within 50 ms were classified as co-occurring; all others were classified as isolated. We determined whether vHFA was associated with co-occurring spikes. We then assessed whether contacts enriched in vHFA-positive co-occurring spikes were more likely to be located within the resected region among seizure-free patients. Finally, we determined whether the rate of such spikes remaining outside the resection predicted seizure outcomes across the two centers. Results Among 56 patients (mean age: 21.2 years; 26 females), we identified 132,359 spikes, of which 1,925 were vHFA-positive. The vHFA peak preceded the associated spike peak by 8.0 ms (95%CI: 5.0-16.0). vHFA-positive spikes were more likely to be classified as co-occurring, even after adjustment for anatomy and inter-electrode distance (OR: 3.43; 95%CI: 2.82-4.17). Among the 35 seizure-free patients, contacts with higher rates of vHFA-positive co-occurring spikes were more likely to be resected (OR: 11.92 per occurrence/min; 95%CI: 5.62-25.32). This association was stronger than that observed for all spikes (OR: 1.09 per occurrence/min; 95%CI: 1.06-1.11). Twenty patients experienced postoperative seizure recurrence; a higher proportion of vHFA-positive co-occurring spikes in preserved areas was associated with recurrence (OR: 3.22 per 0.01 increase in proportion; 95%CI: 1.14-9.12). In bidirectional cross-center validation, models incorporating vHFA-positive co-occurring spikes yielded areas under the receiver operating characteristic curves of 0.80 and 0.69, with better performance when the model was developed using the larger sample. Discussion Spike-associated vHFA may identify a biologically meaningful subset of interictal spikes involved in propagation across the epileptogenic zone. vHFA-positive co-occurring spikes may represent a generalizable intraoperative biomarker of the epileptogenic zone.

Objective: We developed a patient-specific framework to determine which information about interictal epileptiform discharges (IEDs) can be recovered from scalp EEG, separating temporal localization (where) from event-specific intracranial waveform reconstruction (what). Methods: Six subjects from a public simultaneous high-density scalp EEG and intracranial EEG (iEEG) dataset were analyzed using patient-specific dual-branch convolutional-attention models integrating waveform/topographic and time-frequency representations. For the where task, a 640-ms scalp EEG segment was divided into eight 80-ms bins, and the model predicted the bin containing the intracranial IED peak. For the what task, a 250-ms peak-centered iEEG waveform was represented as a fixed patient-specific template plus an event-specific residual predicted from scalp EEG. Direct scalp-input controls and event-clustered bootstrap confidence intervals were used to distinguish scalp-dependent information from template-driven performance. Results: Where accuracy varied markedly across subjects (0.080-0.984), with an unweighted subject-level mean of 0.333 versus a chance level of 0.125; 95% confidence intervals were above chance level in three of six subjects. Input-control analyses supported a scalp-dependent contribution in subjects with successful localization. For the what task, mean waveform correlation was 0.752 for the model and 0.754 for the fixed patient-specific template (mean difference, -0.002), while residual correlations were generally modest (-0.020 to 0.378). Conclusion: Scalp EEG contained recoverable temporal information in some subjects, but event-specific single-contact morphology was not consistently recovered beyond the patient-specific template. Separating temporal localization from template-based waveform reconstruction provides a more stringent framework for evaluating noninvasive-to-intracranial inference and reduces conflation of prior-driven similarity with input-dependent reconstruction.

ObjectiveThe current International League Against Epilepsy (ILAE) guidelines for Lennox-Gastaut syndrome (LGS) mandate the presence of generalized paroxysmal fast activity (GPFA) on EEG. However, GPFA is not necessarily restricted to LGS and has been described in, among others, idiopathic generalized epilepsies. A clear definition for GPFA is currently lacking, hampering research into its utility as a diagnostic or treatment biomarker. Here, we assessed expert agreement in the interpretation of GPFA to explore feasibility of a consensus-based definition. MethodsWe internationally distributed a two-part survey on GPFA to EEG experts. First, participants completed thirteen questions gauging their preferred clinical and EEG criteria for GPFA, including duration, frequency, amplitude and topography. Second, participants classified the presence versus absence of GPFA in eleven EEG clips, while blinded to clinical context, from patients with LGS, other epilepsies, and physiological variants. Results162 respondents, predominantly from North America and Europe, completed the survey. 87% considered GPFA to also occur in epilepsies other than LGS. Considerable heterogeneity was present on defining duration, spectral frequency, amplitude and topographic distribution of GPFA. Particularly poor agreement was seen for lower limits of duration and frequency, with no single response option receiving a majority consensus (36% and 30% agreement, respectively). Similarly, the degree of agreement on interpretations was highly variable across real-world EEG clips. SignificanceMarked discrepancies exist in the EEG identification and clinical interpretation of GPFA, undermining its utility as a potential biomarker in research and clinical trials of LGS and other epilepsies. The findings also highlight the need to establish a consensus-based and eventually evidence-informed definition to formally operationalize the clinical and EEG criteria for GPFA. Key pointsO_LIGeneralized paroxysmal fast activity (GPFA) is variably defined in the literature, limiting its utility as a diagnostic or treatment biomarker C_LIO_LIIn this international survey (n = 162 respondents, 25 countries) we found limited agreement on GPFAs defining features and on interpretation of fast activity on EEG clips C_LIO_LI87% of respondents considered GPFA to occur in epilepsies other than Lennox-Gastaut syndrome C_LIO_LIPending further elucidation of the pathophysiology underlying GPFA or its computational characterization (i.e., to inform a biologically-or evidence-based definition), we underscore the need for an interim consensus-based definition C_LI

Based on the observation that in normal EEG rhythms, the low-voltage beta frequencies dominate in the anterior region while characteristic high(er)-amplitude slower rhythms manifest more posteriorly, we studied these gradients across normal subjects and patients with different monogenic epilepsies. From large data sets (long term records of 374 controls and 241 patients) we selected 60s eyes-open rest-EEG epochs to determine the spectral power of the EEG bands. To help manage the large data sets and facilitate analyses, we employed AI to preselect and assist in coding. While both preselection and coding was extensively verified and validated by the authors, which was a time-consuming effort, the AI contribution reduced the net effort of evaluating the large dataset. We developed a metric that reflects the anterior-posterior gradients of the beta rhythm and the so-called posterior dominant rhythm. Our results indicate that this simple gradient measure across 1-10 year-age groups may provide a robust quantitative biomarker of cerebral dysfunction in monogenic epilepsy. Because EEG is noninvasive, widely available, repeatable, and relatively inexpensive, such a biomarker could ultimately provide a practical means of assessing the cerebral effects of emerging targeted therapies across multiple genetic epilepsies.

Objective: Cortico-cortical evoked potentials (CCEPs) are used during intracranial EEG (iEEG) monitoring to probe effective connectivity and guide epilepsy surgery. However, the factors governing spatial distribution and variability of stimulation-evoked responses across patients remain incompletely understood, making it difficult to distinguish physiological variation from pathological responses. We aimed to develop interpretable models of CCEP responses that integrate normative and patient-specific features, and to assess how these relationships are influenced by distance, brain-state, and epileptogenicity. Methods: We analyzed single-pulse stimulation data from 34 patients with drug-resistant epilepsy undergoing stereo-EEG monitoring. Significant CCEP responses were defined using N1 peak amplitude. For each stimulation-response pair, we derived multimodal features capturing Euclidean distance, effective connectivity priors from F-TRACT, a published population atlas of CCEP response probabilities, normative structural connectivity and communication metrics, and patient-specific functional connectivity estimated from iEEG during baseline and pre-stimulation periods. Lasso-regularized logistic regression models were trained to predict response using leave-one-patient-out cross-validation, and feature importance was examined across spatial scales and seizure onset zone (SOZ) involvement. Results: Performance to predict stimulation-evoked responses improved with the integration of multiple feature domains, with the full model achieving the highest accuracy (median AUC = 0.84). Feature relevance varied with spatial scale: short-range responses were dominated by distance and normative priors, whereas long-range responses depended strongly on patient-specific functional connectivity, especially when measured from pre-stimulation periods. Prediction errors were significantly higher for stimulation-response pairs within the SOZ, indicating deviations from normative connectivity-response relationships in epileptogenic networks. Significance: CCEP responses reflect an interaction between spatial constraints, network architecture, and patient-specific brain state. Multimodal modeling of CCEPs provides a principled framework to interpret stimulation responses and may offer complementary markers for identifying epileptogenic networks during presurgical evaluation.

Background: Immediate transcranial evoked potentials (iTEPs) are ultra-early electroencephalographic responses elicited by single-pulse transcranial magnetic stimulation (TMS) of the primary motor cortical hand area (M1-HAND). Their characteristic latency, waveform, and sensitivity to short-interval intracortical inhibition suggest a close relationship to the cortical generators of indirect corticospinal volleys (I-waves). Here, we tested the hypothesis that iTEPs constitute a fundamental physiological response of human motor cortex and therefore generalize across motor representations, including the leg representation (M1-LEG). Methods: Single-pulse TMS was delivered over the motor cortical representation of the right tibialis anterior (TA) in 16 healthy volunteers. In a subset of participants (n=10), stimulus-response curves and paired-pulse short-interval intracortical inhibition (SICI) measures were obtained. Results: TMS of M1-LEG elicited reproducible iTEPs consisting of a slow positive deflection with superimposed high-frequency peaks with topographic maxima in electrodes adjacent to the stimulation site. M1-LEG iTEPs emerged close to active motor threshold and increased in prevalence and amplitude with increasing stimulation intensity. Paired-pulse stimulation produced consistent SICI of the second and third iTEP peaks. M1-LEG stimulation also evoked conventional later TEPs with latencies and polarities closely resembling those recorded after M1-HAND stimulation. Conclusions: TMS of the human M1-LEG elicits robust iTEPs that closely resemble those recorded from M1-HAND in their timing, intensity dependence, and sensitivity to intracortical inhibition. These findings indicate that iTEPs are not specific to M1-HAND but reflect a general physiological response of human motor cortex closely linked to corticospinal I-wave generation. This broadens their utility as a non-invasive probe of excitatory and inhibitory circuit dynamics throughout the human motor system.

Activity in the gamma frequency range (>30Hz) serves as a neural hallmark of stimulus encoding across multiple sensory modalities. Based on its distinct properties, this activity could be classified as broadband or narrowband oscillations. Visual stimuli, such as a grating, induce narrowband oscillations, which have shown promise as diagnostic markers for neurological disorders. However, such tasks are discomforting for the subjects. These can be made subject-friendly by swapping the stimulus for an auditory one; however, most auditory stimuli elicit a broadband activity. In search of an ideal candidate to induce auditory narrowband oscillations, we previously recorded responses to auditory gratings in electroencephalography (EEG) recordings (Gulati & Ray, 2024) using a passive listening paradigm. We observed a focal sustained broadband increase in high gamma activity (70-150Hz), which was not selective towards any stimulus attributes. Nevertheless, since EEG represents activity of a large population, it remained unclear whether observed activity represented a broadband increase or comprised multiple narrowband rhythms, and whether it was indeed untuned. To elucidate this, we recorded invasively from the regions on and around the superior temporal gyrus, closer to Heschl's gyrus of seven patients undergoing epilepsy resection surgery. Patients were either under anesthesia or fully awake while we presented auditory gratings through loudspeakers. We found a transient increase in broadband gamma activity (30-100Hz) followed by a sustained suppression of beta rhythm (14-28Hz). This broadband gamma was selective for slower spectro-temporal modulations. Our result compares the responses obtained across different recording scales and corroborates that auditory gratings produce broadband but not narrowband gamma activity.

Background: Aberrant basal ganglia activity is a key feature of the pathophysiology of dystonia, but evidence is predominantly based on adult cohorts. Neurophysiological signatures during development remain poorly characterised. Local field potentials (LFPs) recorded by bidirectional neurostimulators provide a direct measure of globus pallidus internus (GPi) activity. In a cross-sectional paediatric cohort, we investigated whether pallidal oscillatory, aperiodic and connectivity characteristics are associated with dystonia severity and whether these differ between genetic and acquired dystonias. Methods: We recruited 30 children and young adults (5-20 years) with medically refractory dystonia (genetic n = 10; acquired n = 20) who underwent bilateral GPi Deep Brain Stimulation (DBS) implantation. Ten minutes of pallidal LFPs were recorded using Medtronic Percept RC neurostimulators with stimulation off, before DBS activation and, where available, at 12 months. Spectral power, aperiodic exponent and interhemispheric pallidopallidal coherence were quantified across delta (1-4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and low-gamma (30-45 Hz) frequency bands. Linear mixed-effects models were implemented to establish whether LFP markers were predictive of dystonia severity, as measured by the Burke-Fahn-Marsden Dystonia Rating Scale (BFMDRS-Movement). Firths Bias-Reduced Logistic Regression assessed whether LFP markers were predictive of dystonia aetiology. Results: Spectral peaks were most consistently detected in the delta, beta, and low-gamma bands. Delta and low-gamma peak power significantly predicted dystonia severity. This association was independent of medication burden, structural GPi involvement, and dystonia aetiology. Theta and alpha peaks were detected less consistently, and their power was not associated with dystonia severity. Pallidopallidal coherence significantly predicted dystonia severity in interaction with medication load in all frequency bands. Low-gamma peak power was significantly lower in acquired than genetic dystonia, but the potentially confounding influence of dystonia severity could not be excluded. The aperiodic exponent was not associated with severity or aetiology. Conclusion: Pallidal LFP markers are associated with dystonia severity in children, with delta peak power, low-gamma peak power and pallidopallidal coherence reflecting clinically relevant features of disease expression. These findings highlight the potential of pallidal LFPs to characterise dystonia across the lifespan and motivate longitudinal studies of their developmental and clinical trajectories.

Background: Working memory, the cognitive ability to maintain and manipulate a finite amount of information, is fundamental in reasoning, learning, and decision-making. Working memory erodes in conditions from Alzheimer's disease to stroke to healthy aging. Transcutaneous auricular vagus nerve stimulation (taVNS) is a promising neuromodulation method for improving working memory. By stimulating the auricular branch of the vagus nerve, taVNS is thought to engage ascending arousal systems such as the locus coeruleus-norepinephrine (LC-NE) system. However, the physiological link between LC-NE system modulation via taVNS and improved working memory remains largely unknown. This mechanistic gap limits the rational optimization of the stimulation protocol and the identification of the cognitive functions and patient populations that are likely to benefit. Objective: We test two competing hypotheses for how taVNS may improve working memory: sensory amplification or enhancement of cortical efficiency. The sensory-amplification hypothesis predicts increased cortical responses to stimuli, whereas the cortical-efficiency hypothesis predicts reduced cortical responses. Methods: Twenty healthy adults completed N-back working memory tasks during three counterbalanced sessions: baseline, active vibrotactile taVNS (vtaVNS), and sham stimulation, while we simultaneously recorded electroencephalography, electrocardiography, eye-tracking, and behavioral responses. To study the effect of vtaVNS on neuronal activity, we also recruited 20 patients with epilepsy undergoing invasive monitoring. Of these, 19 fully completed the spatial working-memory task. We quantified cortical responses to visual stimuli using event-related potentials (ERPs) in scalp EEG and high-gamma activity in intracranial local field potentials. To examine prediction of the cortical-efficiency hypothesis, we further explored the effect of vtaVNS on distance to criticality and heartbeat-evoked potentials. Results: Active vtaVNS reduced both scalp-recorded visual ERP and high-gamma response in temporal cortices, relative to sham stimulation. Moreover, smaller visual event-related potentials were associated with successful encoding during the most demanding working-memory condition (i.e., 4-back task). Exploratory analyses showed that vtaVNS shifted cortical dynamics closer to criticality. Conclusion: Our results converge on the conclusion that vtaVNS does not uniformly amplify cortical responses to external stimuli. Instead, vtaVNS enhances cortical efficiency, supporting more effective allocation of cognitive resources between exteroceptive and mnemonic processes. These findings provide a framework for predicting when taVNS will be most beneficial and for optimizing stimulation protocols across cognitive and clinical applications.

Background: Tremor is a repetitive, oscillatory movement with multiple subtypes requiring accurate characterization for diagnosis and treatment. While frequency, amplitude, and context are routinely used to describe tremor, recent recommendations have emphasized oscillation shape and regularity. However, these descriptors lack strict operational definitions, and differences in how clinicians interpret them introduce inconsistency into tremor classification. Objective: We quantified inter-rater reliability for commonly used tremor descriptors and determined which objectively measured signal parameters: peak amplitude, peak frequency, and frequency variability best explained inconsistency in rater assessments. Methods: We developed the Tremor Waveform Morphology Questionnaire (TWMQ) and obtained standardized video recordings of 34 individuals with upper-extremity tremor performing rest, postural, and kinetic tasks, with simultaneous kinematic recordings using an inertial sensor. Movement disorder experts rated tremor presence, shape, symmetry, regularity, rhythmicity, and diagnosis. We assessed inter-rater reliability, cross-feature dependencies, and modeled the influence of objective signal parameters on each subjective rating. Results: Tremor presence and symmetry showed high agreement, whereas jerkiness, rhythmicity, amplitude stability, and clinical diagnosis showed lower reliability. Modeling revealed that peak amplitude primarily influenced judgments of tremor presence, jerkiness, and diagnosis, while frequency variability drove ratings of rhythmicity and amplitude stability. Conclusions: Morphology-based descriptors remain subjective, but disagreement systematically reflects measurable signal properties. Objective definitions based on peak amplitude and frequency variability may improve the reliability and reproducibility of tremor characterization.

Background: Software tools can support MRI diagnosis of focal cortical dysplasias (FCDs) - subtle, surgically-treatable lesions that underlie drug-resistant focal epilepsy (DRFE). MELD-graph, a widely used open-source tool combining surface-based morphometry with a convolutional neural network, was developed using 1.5T and 3T MRI data. 7T MRI is increasingly used for lesion detection in DRFE. This study investigated whether MELD-graph is robust to domain shift at 7T. Methods: We collated paired 3T and 7T T1-weighted MRI, and FLAIR where available, from 23 patients with FCD (6 histologically-verified, 17 identified radiologically) and 39 healthy controls at four epilepsy centres. Manual lesion labels were used as ground truth. MELD-graph was run on 3T images, on 7T images with the default pipeline, and on 7T images with adaptations for 7T MRI (SPM bias-field correction, SynthStrip skull-stripping, sub-millimetric FreeSurfer reconstruction), with and without ComBat harmonisation. FCD detection performance and surface morphometry features were compared. Results: Sensitivity for FCD detection was 65% (15/23) at 3T, 48% (11/23) for 7T default and 52% (12/23) for 7T adapted, with Combat harmonisation. Among radiologically 3T-negative patients, 2/8 were detected at 3T and 3/8 at 7T; and among histologically confirmed FCD, 3/6 at 3T and 1/6 at 7T. Specificity was significantly lower at 7T (default 39%, adapted 45%) than 3T (76%). False-positives predominantly occurred in the basal temporal lobes. ComBat harmonisation improved specificity in all conditions and largely compensated for field-strength dependent differences in surface morphometry features. Adding FLAIR at 7T increased false-positive predictions. Conclusion: Sensitivity is comparable but specificity of MELD-graph is lower at 7T compared to 3T. Adaptations for 7T MRI can reduce segmentation errors but do not significantly improve FCD detection, while harmonisation improves performance. The adapted pipeline is released open-source. 7T MELD-graph outputs may inform radiologist review in challenging cases but require cautious interpretation.

Childhood absence epilepsy (CAE), the most common childhood epilepsy syndrome, is associated with bursts of generalized thalamocortical spike-wave discharges and cognitive impairment, yet the physiological mechanisms linking disease activity, treatment, and cognition remain unclear. Sleep spindles, generated by thalamocortical circuits, are associated with cognitive function and may be disrupted by epileptic activity. Here, we retrospectively studied 87 EEGs from 53 children with active and resolved CAE and 87 age- and sex-matched controls to evaluate sleep spindle activity across disease states and its association with antiseizure medication (ASM) exposure. We found that children with active CAE had reduced spindle rates across all cortical regions compared to those with resolved CAE and controls, with the largest reduction in the frontal region, where epileptic spike activity was also most prominent. Spindle rate was inversely correlated with epileptic spike rate, consistent with a shared thalamocortical circuitry. The association between ASM exposure and spindle rate varied by disease state. In active CAE, treated children had higher spindle rates than untreated children. In resolved CAE, treated children had lower spindle rates than untreated children. In contrast, ASM-related differences in spike rate were more limited, although a medication-specific reduction was observed in active CAE. These findings support sleep spindle rate as a candidate physiological marker of disease state and ASM exposure in children with CAE. Given the established role of sleep spindles in memory consolidation, these findings support testing of whether spindle disruption provides a mechanistic link between epileptic thalamocortical activity and cognitive vulnerability in CAE.

BackgroundThe balance between excitatory and inhibitory neuronal signalling (E/I balance), proposed as a key mechanism controlling neuronal activity, is disrupted in many neurodevelopmental conditions. One such condition is Neurofibromatosis Type 1, a monogenic neurodevelopmental disorder characterised by increased inhibitory tone. While previous research suggests that E/I balance may be altered in infancy, it is unknown whether E/I balance remains altered during adolescence in NF1. Here we investigated this question using the aperiodic exponent of the resting electroencephalogram (EEG) power spectrum, a proposed electrophysiological index of E/I balance. MethodThe aperiodic exponent of the EEG power spectrum ( 1/f) was estimated for 16 adolescents with NF1 diagnosis aged 11-16, and 16 age- and sex-matched neurotypical controls. General linear models (GLM) were fit to estimate effects of NF1 diagnosis, age and their interaction on aperiodic exponent. We also estimated the peak dominant frequency and power in oscillatory activity of the EEG signal and fitted the same structure of GLM models. Cognitive assessments across domains of memory, executive function and attention were also analysed with GLM to examine brain-cognition associations. ResultsThe NF1 group had higher aperiodic exponent compared to neurotypical controls, but the aperiodic exponent was not associated with cognitive performance. After accounting for aperiodic activity, the NF1 group also had lower dominant oscillatory frequency than the control group. There was no significant interaction between NF1 diagnosis and age on PAF. There were no group differences in peak alpha power. ConclusionsWe demonstrate for the first time that the alterations to aperiodic activity in NF1 are consistent with the proposed mechanism of increased inhibitory tone. These findings show the potential of this paradigm for future pharmacological and brain stimulation trials investigating treatment-related changes in cortical function.

Background: Dopamine replacement reshapes subthalamic activity in Parkinson's disease, but whether this response reflects anatomically organized network reconfiguration remains unclear. Objectives: To determine whether levodopa preferentially reorganizes dorsal subthalamic spectral activity and cortico-subthalamic directionality. Methods: Twelve participants undergoing bilateral subthalamic deep brain stimulation contributed 30 contacts (14 dorsal, 16 ventral). Recordings obtained OFF and ON medication underwent spectral parameterization and multiband state-space analysis. Simultaneous electroencephalography in six participants enabled assessment of directional cortico-subthalamic coupling using the phase slope index. Results: Levodopa suppressed beta power more strongly dorsally than ventrally (-2.473 versus -0.120 dB; p=0.0438). Dorsal theta power increased, with a trend toward an increase after baseline normalization (p=0.07). Dorsal contacts exhibited greater theta-beta (+5.904 versus +1.610 dB; p=0.006) and gamma-beta (+2.516 versus +0.384 dB; p=0.0188) state-space shifts, principally driven by beta suppression. Gamma changes did not differ regionally. Concurrently, dorsal low-beta and beta interactions shifted toward cortical leading at selected electrodes, whereas ventral responses were less consistent. Conclusions: Levodopa produces a topographically organized subthalamic response, combining preferential dorsal beta suppression with altered cortico-subthalamic directionality. These findings position contact anatomy as a key consideration in characterizing dopaminergic network responses and motivate clinical validation of spatially informed multiband biomarkers for adaptive stimulation.

Objective. Intermittent theta burst stimulation (iTBS) is a repetitive transcranial magnetic stimulation (rTMS) protocol used in clinical settings to alleviate symptoms of psychiatric disorders. Although the pulse parameters currently used in iTBS have remained unchanged since the first treatments, recent controllable TMS devices allow for the personalization of pulse shape and duration, opening the possibility of testing the efficacy of other pulse parameters in modulating corticospinal excitability (CSE). Methods. In a repeated-measures design, changes in CSE were induced by the administration of iTBS over the left primary motor cortex under three different conditions: long bidirectional pulse (L-Bi), long quasi-unidirectional pulse (L-QU), and a control short quasi-unidirectional pulse (S-QU). We assessed TMS-induced motor evoked potentials before and up to 70 minutes after iTBS. We hypothesized that L-QU pulses would induce greater facilitation than other conditions. Results. A mixed linear model showed that all conditions induced increased MEPs compared to baseline. However, the L-Bi pulse led to a larger and more sustained MEP increase than both unidirectional pulses, while the S-QU pulse appeared less effective in modulating CSE. We observed large within- and between-subject variability in responsiveness to the iTBS protocols. Conclusion. These results suggest that L-Bi pulses in iTBS protocols are more potent than unidirectional pulses in inducing CSE changes in the cortex of healthy adults. The individual variability in response to iTBS and the potential clinical relevance of these findings are discussed.

EEG-based machine-learning studies of attention-deficit/hyperactivity disorder (ADHD) are vulnerable to optimistic performance estimates when feature selection or model choice is informed by data outside the training fold. We compared expert-reconstructed, large language model (LLM)-guided and full-space feature strategies under leakage-controlled subject-level validation in a frozen cohort of 77 children (45 ADHD, 32 controls) represented by 1,185 gamma-free EEG features. Four classifiers (SVM, GMM, random forest [RF] and XGBoost) were evaluated with nested leave-one-subject-out cross-validation (LOOCV), with all data-dependent operations restricted to outer-training subjects. Across 100 repetitions of stratified 10-fold cross-validation, RF/expert achieved mean accuracy 62.8% (SD 3.5%; empirical 95% interval 55.8% -- 69.5%), mean balanced accuracy 62.3% and mean AUC-ROC 0.618. The corresponding LOOCV point estimate was 71.4% accuracy and 71.0% balanced accuracy (AUC-ROC 0.673). GMM/expert achieved the highest AUC-ROC (0.699), indicating metric-dependent model ranking. The expert-reconstructed strategy achieved the highest accuracy and balanced accuracy for every classifier, whereas the LLM-guided strategy showed no consistent advantage over the full feature space. Pairwise classifier differences were not significant after Holm correction. A pre-specified 200 V artifact gate reduced RF/expert accuracy to approximately 55.8%, below the 58.4% no-information rate; this drop may reflect removal of artifact-related signal and/or reduced epoch counts leading to noisier feature estimates. These findings support cautious benchmarking and external validation rather than claims of algorithmic or LLM superiority. Keywords: ADHD; electroencephalography; machine learning; benchmarking; feature engineering; subject-level validation; nested cross-validation; random forest; clinical prediction

Visual prostheses have targeted early structures in the visual pathway, including the retina, optic nerve, lateral geniculate nucleus, and visual cortex, to generate visual percepts. Stimulation of higher-order visual regions, which may better encode complex visual features, remains relatively unexplored. We tested whether electrical stimulation of the medial and inferior pulvinar elicits visual percepts in a patient with medically refractory epilepsy undergoing invasive seizure monitoring with intracranial electroencephalography. Bipolar stimulation (30 biphasic pulses, 0.5 ms per phase, 3 mA, 1 Hz) was delivered between adjacent pulvinar contacts while eye movements were tracked. Stimulation of different electrode pairs elicited visual percepts at distinct retinotopic locations (p = 0.010). Stimulation also altered cortical activity, producing an early power increase followed by gamma desynchronization in occipital and parietal regions (p < 0.001) and beta desynchronization in the lateral temporal region (p < 0.01). These findings suggest that pulvinar stimulation can generate visual percepts and modulate distributed cortical networks, supporting further investigation of the pulvinar as a target for vision restoration.

Cortical proprioceptive processing to passive movements can be quantified with evoked and induced responses in magnetoencephalographic (MEG) signals. We examined how intensity of proprioceptive stimulation (i.e., tendon-tap evoked movement) scales cortical processing of proprioceptive afference from the knee joint, and whether it affects stimulus-to-stimulus response variability. Twenty-one healthy volunteers (28.2{+/-}5 yr, 10 females) underwent a total of 100 right patellar tendon taps (5.0--6.0s inter-stimulus interval) evoked by a novel MEG-compatible stimulator under higher and lower intensity conditions. Strength of cortical evoked and induced MEG and electromyographic responses from the vastus lateralis and medialis muscles were quantified, and their variability were assessed using a matched sliding-window coefficient of variation (CoV). Higher intensity stimulation elicited significantly stronger cortical evoked (~11%) and induced (~17% for beta suppression and ~18% for beta rebound) responses, and muscular response (~27%) than lower intensity stimulation (p<0.05). The stimulus intensity did not affect response variability, with comparable CoV values between higher and lower intensity condition (p>0.05), but the muscular responses showed greater variability than the cortical ones in both intensity conditions (CoV: ~30% vs. ~10%, p<0.001). In addition, the variability in cortical and muscular responses were not significantly correlated (p>0.05). Our results indicate that patellar tendon-tap intensity scaled cortical and muscular response gain, but did not measurably alter response variability. The distinct variability profiles of cortical evoked fields and stretch-reflex muscular response suggest that proprioceptive afference evoked by tendon-tap is transformed differently across cortical and spinal levels.

Significance: There is potential for generative artificial intelligence (AI) to perform "full stack" academic publishing, including comprehensive manuscript fabrication, "peer"-review, and editorial decision making. This study evaluated the benefits and cautions in using AI for full stack academic publishing in clinical research about seizures. Methods: Three epileptologists each selected 1 published manuscript in Epilepsia and produced an AI-fabricated manuscript about seizures. AI tools were then used to perform "peer"-review and make editorial decisions with minimal human supervision. The rates of identifying AI-fabricated manuscripts and editorial decisions among the epileptologists was analyzed, and epileptologists' observations on how AI differed from typical human "peer"-review and editorial decisions was collected. Results: Four of 6 (67%) pairs of AI-fabricated and human-generated manuscripts were correctly identified. Only 1 AI-fabricated manuscript was editorially rejected, whereas another had a subtle indicator of fabrication. When compared to human content, AI generated content was comprehensive, detailed, and based on the highest standard of academic publication. However, generated content was more verbose, used more structured responses, and more critical feedback. Conclusions: These results demonstrate that the quality of AI-fabricated manuscripts about clinical research in seizures was sufficiently high that the current methods of peer and editorial review could not easily distinguish fabricated content compared to human-written content. Moreover, AI review and editorial decisions were high quality and appeared reasonable in many cases. AI tools have matured to the point that there should be thoughtful policies that permit AI assistance but prohibit insufficiently supervised autonomous scientific submissions, reviews, and editorial decisions.

Background: High-definition transcranial alternating current stimulation (HD-tACS) is favored by the neurostimulation community for its precision and ability to influence neuronal dynamics. Yet, the exact mechanism by which the underlying brain structures are being affected remains unclear. We believe that the investigation of the aperiodic nature of the electroencephalograph (EEG) could shed light on the modulatory effects of HD-tACS. Methods: We analyzed the EEG of 9 participants during a compensatory tracking task (CTT) in two sessions, each with different HD-tACS protocols. Every session consisted of an initial period of no stimulation, followed by 30 Hz HD-tACS in the left motor (M30) or frontal (F30) cortex. We then isolated the aperiodic component of the EEG and calculated its spectral slope {beta}. Results and Discussion: {beta} decreased during F30 mainly in the right frontal cortex, indicating a shift towards higher frequencies and an increase of the excitatory/inhibitory balance. Additionally, we found that despite the long monotonus task the accuracy of the participants did not decrease, which might be attributed to the ability of both M30 and F30 to sustain attention for prolonged time. Finally, the change of CTT accuracy during the stimulation correlated with the {beta} of specific channels before the stimulation. This indicates the potential of {beta} to be used as a screening biomarker in future studies. In conclusion, we showed the ability of HD-tACS to alter EEG aperiodic dynamics and paved the way for future exploration of such dynamics in the field.