Clinical Neurophysiology

The balance perturbation-evoked N1 potential is a reliable cortical response during reactive balance control that is correlated to a variety of cognitive and motor functions. Although the supplementary motor area (SMA) has been identified as the primary source of the N1, it is less understood whether other brain regions contribute to N1 recorded at the scalp. We used source localization on electroencephalography (EEG) data from 25 younger adults recorded during backward whole-body perturbations during stance. We identified the sources that contribute to channel-based N1 recordings and quantified their impact on N1 amplitude and latency. In younger adults, N1 amplitudes can be explained by one single source in a central midline cortical region covering the SMA. When reconstructing N1 signals using backprojections with one versus all independent components (IC) identified as brain sources there was no difference in peak amplitudes and a small but significant difference in N1 peak latencies. Parallel brain sources thus deflect the time course of the N1, but not its magnitude. Brain areas associated with ICs contributing to the shift in N1 latency varied between participants. Our results emphasize the dominant influence of central cortical areas on the N1 response, informing hypothesizes regarding the nature of the signal and its functional role. Importantly, the extent and location of other cortical structures that influence N1 timing, such as parietal cortex areas and the anterior cingulate cortex, may further elucidate cortical contributions to balance. These markers could be crucial for the early detection of balance problems in clinical populations. NEW & NOTEWORTHYWe demonstrate that channel-level amplitudes of the balance perturbation-evoked N1 in younger adults primarily reflect neural activity originating from cortical central midline regions, particularly the SMA. In contrast, contributions from parallel active brain regions evoked by balance perturbations are indicated by an influence on N1 peak latencies. Our findings imply that the perturbation-evoked N1, unlike other evoked potentials, is not a mixture of multiple neural sources in younger adults.

BACKGROUNDTheta-gamma phase-amplitude coupled ({theta}{gamma}-PAC) oscillations in primary motor cortex (M1) have been shown to support motor skill acquisition. Past research has shown that driving gamma activity at the theta peak (TGP), but not the theta trough (TGT) using transcranial alternating current stimulation (tACS) enhances motor learning (Akkad et al., 2021). However, the neurophysiological mechanisms underlying this phase-specific effect remain unclear. METHODSIn a double-blind, sham-controlled, cross-over study, twenty-two healthy participants received 20 minutes of 75Hz/6Hz TGP-tACS, TGT-tACS, or sham stimulation over M1. We used paired-pulse transcranial magnetic stimulation (TMS) to assess GABAergic and NMDAR-mediated activity before, during, and after tACS. Outcome measures included short-interval intracortical inhibition at 1ms (SICI1ms; extrasynaptic GABAergic tone) and 2.5ms (SICI2.5ms; synaptic GABAA activity), intracortical facilitation at 12ms (ICF12ms; NMDAR activity), and motor evoked potential (MEP) amplitude (corticospinal excitability). RESULTSTGP-tACS selectively decreased SICI1ms, a putative marker of extrasynaptic GABAergic tone (main effect of Stimulation: p=.021), with significant differences between TGP and TGT during late stimulation (p=.047). No significant effects were observed on corticospinal excitability, synaptic GABAergic activity (SICI2.5ms), or NMDAR signalling (ICF12ms). CONCLUSIONSDriving theta-gamma oscillations at the theta peak using tACS specifically modulates extrasynaptic GABAergic tone in M1 without affecting corticospinal excitability or synaptic inhibition. Given that reductions in GABAergic signalling supports motor learning, these findings provide a neurophysiological mechanism for the phase-specific behavioural effects of {theta}{gamma}-PAC tACS and suggest a potential therapeutic approach for facilitating motor recovery after stroke. HighlightsO_LITheta-gamma peak tACS selectively reduces extrasynaptic GABA in human motor cortex C_LIO_LIOnly gamma at the peak, not trough, of theta stimulation modulates GABA C_LIO_LINo effects on corticospinal excitability, synaptic GABA, or NMDAR signalling C_LIO_LItACS-TMS reveals mechanism for phase-dependent motor learning effects C_LI

Interictal epileptiform discharges (IEDs) are pathological hypersynchronous bursts of electrical brain activity that occur between seizures in patients with epilepsy. IEDs are caused by transient brain states that are difficult to predict, making them a challenging neurophysiological and technological case for brain-state-dependent stimulation. Administering stimulation at IED onset may provide insight into the epileptic network and optimize neurostimulation therapies. Here, we assessed the feasibility of IED-triggered transcranial magnetic stimulation (TMS) in two children with self-limited epilepsy with centrotemporal spikes (SeLECTS), a common pediatric epilepsy in which IEDs emerge from the motor cortex. A convolutional neural network (CNN) was trained on the participants pre-recorded electroencephalography (EEG) data with IEDs annotated by an epileptologist. The CNN was integrated into an EEG-processing pipeline that classified EEG segments as "IED" or "non-IED" in real time. With this pipeline, TMS pulses were administered during IED or non-IED periods in an interleaved, randomized design. We stimulated both the motor cortex generating the IEDs and the contralateral motor cortex and tested the impact of IEDs on TMS-evoked potentials (TEPs). Our study demonstrated that TMS can be timed to IEDs and that there is a site-specific increase in TEP amplitude when stimulating during IEDs. Out of the TMS pulses aimed at an IED, 39% and 19% were successfully delivered during an IED for the two participants, respectively. For future research, we propose ways to address the methodological challenges of IED-timed TMS, enabling brain-state-dependent TMS for epilepsy research and treatment.

Genetic deletion or pharmacological blockade of P2X7 receptors (Rs) counteract status epilepticus (SE) in animal models of epilepsy. It is, however, unclear whether P2X7Rs are localized at astrocytes or neurons, and the reason for astrocytic atrophy arising in consequence of SE is also ambiguous. We conducted a combined morphological/electrophysiological study in order to investigate these issues. It has been shown that kainic acid (KA)-induced SE in mice led to the atrophy of hippocampal astrocytes and at the same time to the decrease of ezrin immunoreactivity and its co-expression with mCherry, whose synthesis has been initiated by the injection of a virus complex. mCherry expression in astrocytes enabled us to study changes in cell somata and processes brought about by KA-injection. Ezrin is a plasmalemmal-cytoskeleton linker; its grade of expression indicates changes in the existence/function of small peripheral astrocytic processes. Pretreatment of mice with the blood-brain barrier-permeable P2X7R antagonist JNJ-47965567 prevented the SE-induced damage of astrocytes. KA caused a potentiation of dibenzoyl-ATP (Bz-ATP) currents in astrocytes but not neurons of the hippocampus. This effect was also abolished by pre-treatment of mice with JNJ-47965567 before applying KA, although no similar changes occurred in hippocampal CA1 neurons. The measurement of spontaneous postsynaptic currents (sPSCs) and spontaneous excitatory postsynaptic currents (sEPSCs) indicated a presynaptic facilitation of neurotransmitter release by Bz-ATP. In conclusion, we suggest that astrocytic P2X7Rs are the primary target of ATP release from damaged CNS cells in the hippocampus which simultaneously causes damage to astrocytic somata and processes.

Short-interval intracortical inhibition (SICI) is the most widely used neurophysiological index of GABAergic inhibition in the human cortex. However, it is an indirect measure, inferring synaptic inhibition from suppression of peripherally recorded motor-evoked potentials (MEPs) elicited by transcranial magnetic stimulation (TMS). In the standard protocol, a subthreshold conditioning pulse suppresses the MEP evoked by a suprathreshold test pulse delivered 1-5 ms later. Interpretation is further complicated by temporal overlap with short-interval intracortical facilitation (SICF), reflecting excitatory interactions at interstimulus intervals of [~]1.5 and 2.7 ms. To overcome these limitations, we recorded immediate TMS-evoked EEG potentials (iTEPs; 1-10 ms post-stimulus) as a more direct measure of motor cortical activity in 16 healthy volunteers (20-35 years; 7 male). The conventional SICI protocol suppressed only later components of the iTEP, likely corresponding to late corticospinal volleys previously identified in epidural spinal recordings after suprathreshold TMS, while the earliest iTEP component was unaffected. Importantly, later iTEPs were suppressed to a similar extent whether conditioning-test intervals coincided with SICF peaks or troughs, and the magnitude of iTEP suppression correlated with concurrently recorded paired-pulse MEP suppression. SICI also reduced an early TEP component (N15; 10-20 ms), but paired-pulse N15 suppression showed a different dependence on stimulus intensity and did not correlate with MEP suppression. These findings demonstrate that SICI measured via MEPs does not reflect a global index of cortical GABAergic motor cortical inhibition but instead reflects inhibition within specific cortical circuits that can be investigated directly with iTEPs.

About half of patients who undergo epilepsy surgery for drug-resistant epilepsy have seizure recurrence, supporting the need for approaches that more accurately identify the epileptogenic zone, defined as the brain areas whose removal causes cessation of seizures. Altered network connectivity has emerged as a candidate biomarker of the epileptogenic zone, but how connectivity is altered in the epileptogenic zone remains uncertain, with prior studies reporting inconsistent results. We hypothesized that a difference in intrinsic versus extrinsic connectivity of the epileptogenic zone may explain prior discrepant findings. We studied a multicenter cohort of adult and pediatric patients who underwent intracranial EEG recording and brain stimulation as part of epilepsy surgery planning. We measured spontaneous connectivity using Pearson correlation and perturbational connectivity using stimulation evoked potentials, modeling the connectivity according to the location of contacts in relation to the seizure onset zone (SOZ) while controlling for inter-electrode distance. We analyzed 79 patients (37 adults, 42 children). For both adult and pediatric patients, resting connectivity was higher within compared to outside the SOZ, but resting connectivity between SOZ and non-SOZ contacts was reduced. Stimulation connectivity followed a similar pattern, with elevated within-SOZ connectivity but reduced connectivity between SOZ and non-SOZ. The results support the hypothesis that the epileptogenic zone is disconnected from the rest of the brain but intrinsically hyperconnected. This result helps reconcile prior inconsistencies across studies, aligns with the results of basic science studies, and suggests that future translational work should model this heterogeneous pattern to increase the yield of using connectivity to localize the epileptogenic zone.

BackgroundTemporal lobe epilepsy (TLE) often originates from focal hippocampal injury but progressively evolves into a bilateral epileptic network engaging both hippocampi and distributed cortical regions. A mechanistic understanding of how this network emerges, and whether early perturbation of specific nodes can alter its trajectory, is essential for developing network-level therapeutic strategies. ObjectiveWe used a kainate-induced rodent model of TLE to (1) characterize the spatiotemporal emergence of epileptic discharges during the latent phase, (2) determine how bilaterally synchronized events develop, and (3) test whether transient chemogenetic silencing of either the ipsilateral epileptogenic focus (EF) or the contralateral hippocampus (CH) modifies large-scale epileptogenesis. MethodsFreely moving mice were implanted with multi-site electrodes spanning bilateral hippocampal subfields (dentate gyrus, CA1, subiculum) and cortical regions (M2, Cg1, PrL, V1, entorhinal cortex). Longitudinal LFP recordings were performed every other day during the latent and early chronic phases following KA or saline injection. DREADD-based chemogenetic inhibition of glutamatergic neurons was applied between days 2-7 post-KA. Epileptiform events were quantified via spike rates, waveform metrics, high-frequency oscillations (HFOs), and short-latency interregional co-spiking ResultsEarly after KA, epileptic spiking emerged locally in the ipsilateral dentate gyrus and progressively organized into HFO-coupled discharges. Contralateral hippocampal recruitment followed a distinctive biphasic time course, characterized by transient early activation, subsequent suppression, and later re-emergence with increasing bilateral coactivation. Cortical regions gradually developed higher spike rates and enhanced DG-related co-spiking, indicating large-scale network integration. Ipsilateral silencing modified local spike composition but did not prevent global network progression, whereas contralateral silencing accelerated ipsilateral epileptogenesis and strengthened pathological HFO expression. ConclusionEpileptogenesis in the KA model reflects a transition from a focal hippocampal insult to a resilient, bilateral cortico-hippocampal network. Targeting a single hippocampal node--even at early latent stages--is insufficient to halt this progression, highlighting the need for network-level therapeutic strategies. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=116 SRC="FIGDIR/small/701979v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@171797dorg.highwire.dtl.DTLVardef@df13d3org.highwire.dtl.DTLVardef@18e9594org.highwire.dtl.DTLVardef@1fe68f8_HPS_FORMAT_FIGEXP M_FIG C_FIG

Background: High-dose high-intensity upper limb neurorehabilitation can lead to meaningful clinical gains even in chronic stroke, yet substantial variability in recovery remains unexplained. Identifying neurophysiological markers linked to neuroplasticity and recovery could provide mechanistic insights and guide personalised rehabilitation. Objective: To characterise stroke-related alterations in {beta}-activity during movement and neural activity at rest and explore associations between brain activity and changes in upper limb clinical outcomes in chronic stroke survivors undergoing three-week high-dose rehabilitation. Methods: Electroencephalography (EEG) was recorded during the three-week rehabilitation programme in 40 chronic stroke survivors participating in the Queen Square Upper Limb (QSUL) Programme, as well as in 26 healthy controls. Recordings were taken during passive movement of the affected and unaffected index fingers (~70 movements per hand) and at rest (~7 min). Clinical assessments included the Fugl-Meyer Upper Limb Assessment (FM-UE), reflecting impairment-level deficits, and the Chedoke Arm and Hand Activity Inventory (CAHAI-13), capturing real-world upper limb activity, to examine their differential relationships with movement-related {beta}-activity. Results: Stroke survivors showed significant improvements in FM-UE and CAHAI scores following the rehabilitation programme (Mean {Delta}: FM-UE = 7.5, CAHAI = 7.4), exceeding minimum clinically important differences. Compared to controls, stroke survivors exhibited less strong {beta}-event-related desynchronization/synchronization ({beta}-ERD/ERS) during passive movement of the affected and unaffected index finger, with effects lateralised to the lesioned hemisphere. No significant differences at rest were observed between stroke participants and healthy controls. Only improvements in CAHAI, but not FM-UE, were associated with stronger {beta}-ERD (more negative) and stronger {beta}-ERS (more positive) responses during passive movement. Conclusions: Stronger movement-related {beta}-activity is associated with improvements in upper limb activity following high-dose high-intensity neurorehabilitation, suggesting {beta}-activity as a potential marker of neuroplasticity.

BackgroundTranscranial magnetic stimulation (TMS) can entrain oscillatory brain activity, offering a promising approach to study motor-related neural oscillations such as beta rhythms. However, how TMS-induced corticospinal oscillations are generated, propagated, and related to endogenous activity remains unclear, partly due to limitations in brain recording techniques. Recording muscle activity provides an alternative and physiologically grounded window into corticospinal dynamics. MethodsWe investigated whether subthreshold TMS over the motor cortex induces corticospinal oscillatory activity detectable in muscles, and whether these responses share neural generators with endogenous beta rhythms. Single-pulse subthreshold TMS was applied over the motor cortex in healthy participants while electromyography (EMG) was recorded from tonically active muscles. Stimulation intensity, coil orientation, and stimulation site were systematically varied. Concurrent electroencephalography (EEG) was used to assess cortical responses and corticomuscular transmission. In additional experiments, advanced EMG techniques were employed to track motor neuron pools and characterize how TMS-evoked oscillations are transmitted at the motor unit level. ResultsTMS elicited a robust and short-latency increase in beta-band activity in the EMG. The analysis of the elicited muscle responses and the comparison of results across different TMS configurations indicate that the beta responses resulted from activation of inhibitory interneurons in the targeted primary motor cortex. Importantly, the characteristics of cortico-muscular coherence and beta projection to the muscles indicate that the elicited beta responses with TMS have same cortical sources as endogenously generated beta activity. ConclusionsThese findings demonstrate that muscle recordings provide a sensitive and physiologically meaningful readout of TMS-induced corticospinal beta oscillations.

BackgroundDistinguishing epilepsy from functional/dissociative seizures (FDS) is an ongoing diagnostic challenge. Misdiagnosis delays appropriate treatment and puts patients at significant risk. Quantitative analyses of clinical EEG offer a potential avenue for developing decision-support tools in the diagnosis of seizure disorders. Recent work using univariate features demonstrated that reliably identifying diagnostic traits in the presence of confounding factors remains challenging. However, diagnostic information might be available in multivariate features such as network-based measures. Using a well-controlled dataset, we run the first diagnostic accuracy study assessing the potential of multivariate resting-state EEG markers to directly discriminate between a diagnosis of epilepsy and one of FDS at the time when a diagnosis is suspected and prior to treatment initiation. MethodsThe dataset, previously examined in a published study, includes 148 age- and sex-matched individuals with suspected seizure disorders who were later diagnosed with non-lesional epilepsy (n=75) or FDS (n=73). Eyes-closed, resting-state EEG data used for the analyses were normal on visual inspection, and acquired while participants were medication-free. Functional network measures in the 6-9 Hz range were extracted and machine learning implemented to assess their predictive potential; different model configurations (including varying model types, dimensionality reduction methods, and approaches to enhance feature stability) were tested to identify the most promising approach for future translational implementations. ResultsNetwork measures derived from resting-state EEG discriminate between conditions at levels significantly above chance (maximum balanced accuracy: 67.5%). Their sensitivity to epilepsy (81.8%) is consistently higher than their sensitivity to FDS (53.3%). A systematic assessment of model choices indicates that improving the temporal stability of network features through epoch-wise averaging improves classification accuracy (62.6% to 67.5%). Multiple nonlinear model types succeed on the classification problem, with the three-best performing assigning a consistent diagnostic label to 77.5% of the individuals; however, model choice remains a strong determinant of overall classification accuracy. Dimensionality reduction did not provide a significant advantage in our models. ConclusionWe establish evidence for the clinical validity of selected network-based markers to discriminate between a diagnosis of non-lesional epilepsy and FDS prior to treatment initiation, highlighting the measures potential to support post-test probability estimation in the clinic. Our models, configured to optimise balanced accuracy, classified people with epilepsy more accurately than people with FDS, indicating that these measures are specific to epilepsy and should not be interpreted as markers of a positive diagnosis of FDS.

Accurate detection of interictal epileptiform discharges (IEDs) in electroencephalography (EEG) plays a crucial role in epilepsy diagnosis. Our work investigates the classification of IEDs using Artificial Neural Networks (ANNs) trained on EEG data represented in both signal and source space. Source waveforms were computed using equivalent current dipole models fitted using either a 1-parameter fixed-orientation or a 3-parameter projection approach, both localized to a single best-fit position during the rising flank of the IED. The ANN was trained on raw and feature-extracted versions of signal space and source space data. Feature extraction significantly improved performance across all domains. The highest accuracy (0.98) was achieved in signal space using Katz Fractional Dimension (KFD). In source space analyses, the 1-parameter and 3-parameter models achieved a maximum accuracy of 0.84, with statistical features performing best for the fixed-orientation model and KFD for the free orientation model. Additionally, annotations from three independent expert markers showed considerable variability, with ANN performance falling within the range of inter-expert agreement. These findings support the potential of ANN-based tools to assist expert evaluation in future clinical workflows.

Objective: Electrical brain stimulations (EBS) are central to epileptic network identification and functional mapping during stereo-electroencephalography (SEEG), yet stimulation frequencies remain empirical, and standardized across patients and brain regions, producing false negatives and false positives, and potentially compromising surgical outcome. We investigated theta-range EBS (7 Hz) in the temporal lobe, a prominent physiological frequency band in this region, and compared it with conventional 1-Hz and 50-Hz protocols. Methods: We analyzed 1,408 temporal EBS in 25 patients with drug-resistant epilepsy. Epileptic responses (afterdischarges, seizures) and clinical signs were assessed across the epileptic network and temporal structures (amygdala, hippocampus, neocortex, parahippocampal gyrus, white matter), and analyzed according to stimulation parameters (frequency, intensity, duration, total charge). Results: At matched intensity and duration, 7-Hz EBS were associated with a higher occurrence of afterdischarges and clinical signs than 1-Hz EBS in several temporal structures (e.g., parahippocampal epileptogenic zone: p=0.014). Effects on usual seizure induction were less consistent. Comparisons with 50 Hz showed no systematic significant differences, with responses observed at one or both frequencies depending on structure and outcome. When controlling for total charge, frequency-related differences were attenuated. Some effects were sporadically observed at both intermediate frequency and charge quantity. No adverse events occured. Significance: Theta-range stimulation modulates electrophysiological and clinical responses during SEEG mapping and may provide complementary information to conventional frequencies. These findings support exploring a broader range of stimulation frequencies, rather than relying solely on standard protocols.

BackgroundEpilepsy affects approximately 50 million individuals worldwide, with nearly one-third developing drug-resistant epilepsy (DRE). The centromedian nucleus of the thalamus (CM) and the brainstem are integral components of seizure-modulating networks and represent promising targets for neuromodulation. This study aimed to map structural connectivity between CM and specific brainstem nuclei using probabilistic tractography and to evaluate whether connectivity patterns correlate with seizure reduction following CM-stimulation MethodsDiffusion MRI data from 100 healthy subjects from the Human Brain Connectome database were analyzed to characterize CM-brainstem connectivity. Additionally, 11 patients with generalized DRE who underwent deep brain stimulation (DBS) or responsive neurostimulation (RNS) targeting CM were retrospectively studied. Volumes of tissue activated (VTAs) were used as tractography seeds, and connectivity strength was quantified as probability of connectivity (ProbC), corrected for distance. Two subanalyses were performed by dividing patients into two or three groups based on the threshold for seizure frequency reduction (SFR). ResultsIn the two-group analysis, responders (>50% SFR) exhibited significantly higher connectivity between VTAs and the nucleus of the solitary tract (NTS) compared with non-responders (<50% SFR), and NTS connectivity was the only parameter significantly correlated with seizure reduction (r=0.762, p<0.001). The three-group analysis confirmed that high responders (>50% SFR) had stronger NTS connectivity than both partial (SFR = 50%) and low responders (<50% SFR), who showed greater connectivity with raphe nuclei. ConclusionsCM-NTS structural connectivity may underlie therapeutic response to CM-neuromodulation, suggesting a potential shared mechanism with vagus nerve stimulation.

ObjectiveTo evaluate central and peripheral correlates of motor control using functional magnetic resonance imaging (fMRI) and surface electromyography (EMG), with a focus on the added value of EMG-informed analysis during movement of the lower limb in healthy controls. MethodsTwenty participants performed dorsi-/plantarflexion of the ankle (Ankle) and gait imagery (GI) in a block design during fMRI. Accelerometry (Acc) and surface EMG from tibialis anterior (TA) activity were recorded and included as regressors in five analysis models, either with or without temporal derivative (TD) to account for time shift in the task regressor. Voxel-wise analyses complemented by post-hoc region-of-interest (ROI) analyses were performed to compare the amount of variability explained by the models. ResultsInclusion of either Acc or EMG on top of the task regressor explained robustly fMRI signal variability in the primary sensorimotor cortices. On top of Acc, EMG additionally explained activation variability mainly in the contralateral thalamus and the secondary somatosensory cortex (S2). This effect was, however, mainly driven by spontaneous signal fluctuations at rest and during imagery. Comparisons between models with and without TD revealed consistent differences in the cerebellum and thalamus across tested models, suggesting that subcortical structures may involve transient signal changes when switching between movement and rest. ConclusionIncluding EMG in fMRI analysis enhances specificity in detecting motor-related brain activity and enables differentiation of spontaneous or unpredicted motor behavior. TD improved signal detection in the primary sensorimotor cortices, but may have a detrimental effect on signal detection in other, mostly subcortical regions, likely reflecting their different temporal signal dynamics.

Motor unit (MU) firing is affected by motoneuronal persistent inward currents (PICs), which heavily contribute to gain control of motor output. PICs are highly sensitive to inhibition; for instance, Ia reciprocal inhibition via antagonist muscle vibration drastically reduces discharge rate hysteresis ({Delta}F), an estimate of PIC magnitude. A direct link between sensitivity of PICs to inhibition and voluntary force control, however, has not been established. To determine whether force control is altered with inhibition of PICs, we recorded high-density surface EMG from the tibialis anterior, while 11 participants (5F; 6M) completed and isometric force reproduction task. Tendon vibration was applied to the agonist or antagonist muscle during the first (with visual feedback) or second contraction (without visual feedback) and participants were asked to match percieved effort across contractions, in an attempt to match neural drive to the motor pool. In support of our hypothesis, torque and MU firing rates were reduced when vibration was applied to the antagonist (torque: p < .0001; MU firing rate: p < .0001), but not agonist (torque: p = .9980; MU firing rate: p = .312) muscle tendon in the second contraction, compared to control. Conversely, when vibration was applied during the first contraction, opposite effects were observed. These results suggest that PICs play a role in the proprioceptive sense of force, offering a potential link between PICs and voluntary force control, which may be important for understanding and treatment of motor impairments. KEY POINTSO_LIMotoneuronal persistent inward currents amplify synaptic currents and therefore heavily contribute to motor output, however they are extremely sensitive to Ia reciprocal inhibition induced by muscle tendon vibration. C_LIO_LIWe show that modulation of PICs severely impacts human force sense using an effort-based force reproduction paradigm which enabled us to manipulate combinations of tendon vibration and visual feedback. C_LIO_LIThese findings provide a link between PICs and functional motor output, which may be important for understanding neurological impairments and informing rehabilitation strategies. C_LI

BackgroundAccumulating results suggest that reticulospinal tract (RST) excitability increases after stroke. While animal studies suggest this hyperexcitability may compensate for corticospinal tract (CST) damage, its role in motor function in people with stroke (PwS) remains debated. This study aimed to: (1) replicate findings of RST hyperexcitability in PwS using the StartReact paradigm, measuring acceleration of motor response to a startling auditory stimulus; (2) examine the relationship between RST hyperexcitability and motor impairments after stroke; and (3) explore whether RST hyperexcitability provides functional benefits in severely impaired PwS. MethodsForty-six PwS completed the StartReact paradigm and motor assessments (Fugl-Meyer, ARAT, grip strength, Modified Ashworth Scale). PwS were categorized into high StartReact effect and typical StartReact effect subgroups based on comparisons with a healthy control group (n=37). Severe impairment was defined as ARAT [&le;]10. ResultsPwS exhibited significantly greater StartReact effects than controls. The high StartReact effect subgroup showed worse motor function, weaker grip strength, and higher spasticity. Among severely impaired PwS, high StartReact effect was not associated with improved grip strength. ConclusionsThese findings confirm the existence of RST hyperexcitability after stroke and suggest it is associated with poorer motor outcomes, likely due to reduced cortical input to the brainstem. The absence of functional benefit in severely impaired individuals supports the interpretation that RST hyperexcitability is a maladaptive rather than a compensatory reaction to brain damage. These findings provide insight into the neurophysiological mechanisms underlying motor impairments after stroke and do no imply direct clinical or therapeutic applications.

BackgroundOscillations underpin a large spectrum of brain function. Brain oscillations are altered by neuromodulation approaches including deep brain stimulation (DBS), but a mechanistic understanding of the brain oscillation - DBS interaction is missing. DBS is predominantly used in the treatment of Parkinsons disease. DBS can induce or alter pre-existing narrow frequency band gamma oscillations at half the stimulation frequency. Such half-harmonic responses have been interpreted as entrainment of endogenous oscillations by an exogenous oscillator with an associated Arnold tongue structure. However, half-harmonic responses are not exhibited by all patients. MethodsHere, a Wilson-Cowan model of subcortical neuronal populations is used to set out a broad theoretical framework explaining the heterogeneity of observed responses. ResultsIn the absence of stimulation, the model exhibited either damped oscillations or self-sustained oscillations, depending on parameter values. Off-stimulation behaviour determined observed stimulation response. When oscillations were strongly damped, the only observed response was a driven oscillation at the stimulation frequency. When off-stimulation oscillations were weakly damped, additional half-harmonic responses occurred for sufficiently large amplitude stimulation. When self-sustained oscillations were present they were entrained by the stimulation frequency leading to harmonic, half-harmonic and many other subharmonic responses. Varying stimulation amplitude highlighted hysteresis with the onset and offset of half-harmonic responses appearing at different thresholds. Such two-threshold systems present challenges for adaptive control systems. ConclusionsThis framework captures observed heterogeneity and will help guide future therapeutic practices and the development of adaptive neuromodulation techniques for more effective promotion of physiological rhythms and suppression of abnormal rhythms.

BackgroundRespiration is a key central nervous system rhythm that modulates sensorimotor function in healthy individuals, but the neurophysiological mechanisms of volitional breathing-mediated sensorimotor modulation and its preservation in stroke patients remain unclear. This study aimed to characterize the effects of volitional fast inspiration on sensorimotor pathway excitability in healthy and stroke populations, and provide a mechanistic basis for respiratory-integrated post-stroke rehabilitation. MethodsA multimodal case-control neurophysiology study was conducted in 52 healthy volunteers (26 {+/-} 3 years, 30 males) and 44 first-ever subacute stroke patients (66 {+/-} 10 years, 30 males). Three complementary experiments assessed transcranial magnetic stimulation-induced motor-evoked potentials (MEPs), peripheral nerve stimulation-induced somatosensory-evoked potentials (SEPs), and functional electrical stimulation -evoked muscle force under three breathing conditions: volitional fast inspiration (IN), fast expiration (EX), and spontaneous breathing (CON). Two-way and one-way repeated measures ANOVA with Bonferroni post hoc tests were used for statistical analysis. ResultsVolitional fast inspiration significantly enhanced sensorimotor pathway excitability and muscle force generation in both groups. Volitional fast inspiration increased MEP amplitudes relative to spontaneous breathing and fast expiration (p {inverted exclamation} 0.05), with further amplification during active muscle contraction (p {inverted exclamation} 0.05). It also elevated SEP amplitudes in healthy parietal/frontal cortical regions and the stroke parietal cortex (p {inverted exclamation} 0.05). Synchronizing volitional fast inspiration with voluntary finger contraction increased muscle force evoked by functional electrical stimulation by 16-18% relative to spontaneous breathing (p {inverted exclamation} 0.05), with non-significant force gains at rest. ConclusionsVolitional fast inspiration bidirectionally enhances corticospinal transmission, somatosensory integration, and functional force generation in both healthy individuals and stroke patients, with preserved respiratory modulation in stroke-damaged neuropathways. By demonstrating preserved respiratory modulation in stroke-damaged neuropathways, our results provide mechanistic support for integrating controlled breathing into low-cost, non-invasive post-stroke rehabilitation paradigms.

When participants are engaged with auditory narratives, physiological and neural signals exhibit temporal correlations between subjects. The intersubject correlation (ISC) increases when attention is directed to the stories, suggesting that shared neural and bodily dynamics arise from a similar processing of the narratives. Identifying the factors that drive these common responses is clinically relevant for interpreting EEG ISC exhibited in unresponsive patients. In this study, we investigated whether the ISC of the EEG elicited by auditory narratives is driven by low-level acoustic (envelope, spectrogram) and/or higher-level linguistic information (word onset, word surprisal) in two groups of healthy participants during passive, attentive and distracted listening. We use temporal response functions (TRFs) for acoustic, and linguistic features to assess the contribution of each feature to the ISC, measured using correlated component analysis (CorrCA). TRFs derived for acoustic features explained a larger fraction of variance in the EEG than linguistic features and were the main contributors to the ISC. The attention-related increase in ISC was driven by all features. Importantly, word surprisal had an effect on ISC only during active story engagement, with timing and scalp distribution consistent with language processing. Notably, the linear responses captured by TRFs only explained a small amount of the overall ISC, suggesting that ISC is largely driven by nonlinear responses to the narratives. We propose that the combined use of ISC and TRFs has the potential to provide meaningful markers of language processing in patients with disorders of consciousness, and we suggest practical recommendations for their implementation.

Structured AbstractO_ST_ABSBackgroundC_ST_ABSAtrial fibrillation (AF) is maintained by complex dynamics, clinically characterised by bursting periods of organization and disorganization in intracardiac electrograms. We have previously postulated that cardiac conduction behaves like a critical system, where phase shift from organised rhythm to AF is a phase transition at the critical point. We thus hypothesized that using multifractal analysis of AF electrograms could potentially quantify non-stationary fluctuations, revealing novel mechanistic insights into the cardiac critical system and examine potential clinically relevant markers of AF dynamics, phenotype and treatment response. ObjectivesTo determine whether multifractal analysis of AF electrograms can (i) Distinguish paroxysmal (PAF0 and non-paroxysmal AF (NPAF), (ii) predict response to pharmacologic modulation, and (iii) identify imminent spontaneous termination, thereby acting as marker of proximity to criticality along complex system phase spectrum. MethodsWe analysed >1.4 million seconds of high-density bipolar electrograms from 106 patients (paroxysmal n{approx}52, non-paroxysmal n{approx}54) undergoing left atrial mapping with a 24-bipole HD-Grid catheter at standardized sites (RENEWAL AF-ANZCTR ACTRN12619001172190)). Multifractal analysis using the Wavelet Transform Modulus Maxima Method (WTMM) was applied to a burst-energy observable to derive log-normal multifractal parameters c (support dimension), c (spectrum location), and c2 (fluctuations). Hierarchical mixed-effects models accounted for channels nested within locations within patients. A flecainide sub-study (n=15) provided paired pre-/post-infusion recordings, and 27 spontaneous termination events in 15 patients were analysed using 60-s pre-termination windows. Spatial texture of c2 was quantified by variogram-derived correlation length and sill. ResultsAF electrograms exhibited robust multifractality confirming multifractal fluctuations as an intrinsic property of AF. Non-paroxysmal AF showed significantly reduced fluctuations versus paroxysmal AF (c2: {beta}=-0.01, p=0.001), indicating a paradoxical loss of fluctuations with disease progression. Flecainide selectively increased fluctuations in paroxysmal AF ({Delta}c2 = +0.04, p<0.01; {Delta}c = +0.06, p<0.01) but had no significant effect on fluctuations (c2) in non-paroxysmal AF, revealing phenotype-dependent drug response. Immediately prior to spontaneous AF termination, fluctuations increased significantly compared with sustained AF (c2: 0.198 vs 0.181, p=0.024). Spatial variogram analysis revealed heterogenous patterns in paroxysmal AF, whereas non-paroxysmal AF displayed a homogenised, flattened fluctuations landscape. ConclusionsAtrial fibrillation exhibits robust multifractal dynamics rather than random electrical activity. Reduced fluctuations characterizes non-paroxysmal AF, whereas higher fluctuations is observed in paroxysmal AF, during flecainide modulation, and immediately prior to spontaneous termination. These findings suggest that multifractal fluctuations (c2) reflects the dynamical state of AF and may serve as a quantitative biomarker of disease progression, pharmacologic responsiveness, and proximity to termination. CONDENSED ABSTRACTTAtrial fibrillation (AF) exhibits multifractal electrogram fluctuations that vary with disease stage, pharmacologic responsiveness, and proximity to spontaneous termination. In this study, multifractal fluctuations (c2) was higher in paroxysmal than non-paroxysmal AF, increased selectively with flecainide in paroxysmal AF, and rose immediately before spontaneous termination. These findings identify c2 as a quantitative marker of AF progression, and imminent reorganization. Clinically, multifractal analysis may enhance intra-procedural assessment of AF phenotype, guide drug selection, and improve recognition of transitions toward sinus rhythm, and connects AF with concepts of criticality and phase transitions.