Journal of Neurophysiology

The aim of this study was to improve our understanding of muscle contractions in the arm as a function of hand orientation for grasp. While there have been several reports on arm kinematics for reach and grasp movements, little has been done at the muscular level. To this end, we analyzed the modulation of shoulder, elbow and hand muscles for a reach and grasp task involving a target in either horizontal or vertical orientation. We hypothesized that unlike what has been observed for kinematics, at the muscular level we would see less correlation between the three muscle groups. A decoding approach with Machine Learning revealed adaptation patterns that were not visible using classical methods. Reach-and-grasp has traditionally been treated as being made of two components - the reach and the grasp components. Our dynamic decoding approach revealed a more complex picture with very different dynamics in the shoulder and elbow muscle groups during reach. All muscle groups showed peak capacity for predicting hand orientation before the start of grasp and followed the ubiquitous proximo-distal organization. The patterns of muscular modulation for hand orientation were strongly perturbed by the eyes closed and slow movement conditions, potentially decreasing the available degrees of freedom for adaptation.

Practice enhances motor acuity, enabling movement execution with greater speed and accuracy. However, the learning principles underlying improvements in speed, accuracy, and efficiency remain less understood than those supporting motor skill acquisition and adaptation. Here, we examined motor execution in a skill-based practice task to characterize learning, retention, and generalization of motor acuity. Using a gamified two-dimensional racing task, right-handed participants controlled a stylus-driven car along a curved track as quickly and accurately as possible. Across two studies (N = 83 total, 54 females), participants completed 300 training laps on Session 1 and returned for Session 2 to assess retention and generalization to novel track configurations: one with altered spatial configuration (rotated track) and one requiring movement in the opposite direction of training (reverse track). Movement speed improved rapidly and showed robust, though incomplete, retention across sessions. Speed improvements generalized substantially to both novel tracks. Accuracy was high at training onset and showed strong retention. However, we do not observe offline gains between sessions. Notably, accuracy declined transiently for the novel track configurations, suggesting interference from prior training. Movement efficiency, indexed by path length, was retained and generalized to the rotated track. However, reversing movement direction impaired efficiency, revealing a movement direction effect. This effect persisted when training direction was reversed in a second study, with counterclockwise movements remaining slower and less efficient than clockwise movements. These findings show that practice produces durable and broadly transferable motor execution improvements, while inherent movement direction biases constrain how improvements generalize across contexts. New & NoteworthyThe learning principles underlying improvements in motor acuity remain less well understood than those governing other forms of motor learning. Prior work suggests that motor execution improvements show limited generalization. In contrast, the present findings demonstrate that execution-based practice can produce robust, transferable gains, while also revealing a key constraint: inherent movement direction biases that limit generalization. By characterizing learning, retention, and generalization, this work provides new insight into how motor acuity improvements compare with skill acquisition and adaptation.

Eye movement-related eardrum oscillations (EMREOs) appear to consist of a pulse of oscillation occurring in conjunction with saccades. However, this apparent pulse could occur either because there is an increase in energy at that frequency at the time of saccades (a true pulse), or because there is saccade-related phase resetting of ongoing energy at that frequency band, thus appearing like a pulse when averaged in the time domain across many trials. Here we conducted a spectral analysis at the individual trial level in humans performing a visually guided saccade task to determine whether the power at the EMREO frequency (30-45 Hz) is higher during saccades than during steady fixation. We found both an increase in sound power in the EMREO frequency band associated with saccades, i.e. sound pulses at the individual trial level, as well as, phase resetting at saccade onset/offset. While both factors contribute to the apparently pulse-like EMREO signal, phase resetting appears to be more prevalent across participants. The prevalence of phase resetting has implications for the underlying mechanism(s) producing EMREOs as well as functional consequences for how the ear might respond to incoming sound in an eye-position dependent fashion.

Mental fatigue is known to impair cognitive and motor performance, but its impact on motor learning remains unclear. This study examined how mental fatigue affects skill acquisition in a sequential finger-tapping task. Twenty-eight participants were assigned to either a mental fatigue group, which completed a thirty-minute Stroop task, or a control group, which watched a documentary of equivalent duration. Both groups then trained on the finger-tapping task across multiple practice blocks with brief rest periods. Overall motor skill improved similarly in both groups. However, mental fatigue altered the pattern of acquisition: participants in the fatigue group showed decreased performance during practice blocks, which was compensated by larger gains during inter-block rest periods. A strong negative correlation was observed between online decrements and offline improvements, indicating that greater declines during practice were associated with larger gains during rest. This study highlights the critical role of rest periods in maintaining learning under cognitively demanding conditions and provides insight into how internal states, such as mental fatigue, can selectively influence the expression of performance without compromising overall learning.

BackgroundHow does neuronal activity change as an animal transitions from being awake to a state of general anesthesia? Previous studies used C. elegans to investigate awake and anesthetized states, emergence from anesthesia, and to establish metrics characterizing how system-wide neuronal dynamics differ under these conditions. This study employs a new technique to image pan-neuronal activity in C. elegans continuously during induction of anesthesia with isoflurane. MethodsC. elegans worms expressing pan-neuronal nuclear RFP and cytosolic GCaMP6s were imaged with light sheet microscopy to measure single cell activity in the majority of neurons in the animals head during induction via isoflurane exposure. Stable concentrations of isoflurane were maintained throughout the experiment by measured flow vaporization of isoflurane into a specially designed gas enclosure compatible with the imaging system. Building on our previous work investigating emergence from anesthesia, we analyzed ensemble neuronal activity, spectrograms of frequency over time, and metrics of information flow between neurons. ResultsInduction of isoflurane anesthesia caused a progressive reduction in neuronal activity over the course of 40 minutes. Spectrograms indicated a loss of bulk signal power across all frequencies, notably in low frequencies too. State Decoupling and Internal Predictability were among the most useful metrics for discriminating the anesthetized state, demonstrating induction kinetics that are the inverse of emergence. However, each animal does not arrive at the anesthetized state at the same time; response times are highly individualized. ConclusionsInformation metrics of neurodynamic activity demonstrate that isoflurane induction results in a gradual increase in neuronal disconnection and disorganization. Thus, at the level of individual neuron connectivity and system dynamics, the induction of anesthesia in C. elegans nematodes is in essence the reverse of emergence. Induction however occurs more rapidly and shows marked variability between individuals. Future genetic studies will show which molecular targets define sensitivity to volatile anesthetics like isoflurane. Summary StatementIsoflurane-induced unconsciousness is a common phenomenon across species. Does the induction of anesthesia arise by distinct state transitions, or through gradual changes in system dynamics when activity is measured at the level of individual neurons?

After cervical spinal cord injury (cSCI), swallowing dysfunction is common and increases mortality via aspiration pneumonia. While these deficits have often been attributed to secondary damage from complications of injury management, there has recently been a greater appreciation for the modulatory role of spinal populations in swallow generation that are disrupted by injury. Here, we illustrate in a rodent model of cSCI that epidural spinal stimulation (ESS) of the phrenic motor nucleus at spinal segment C4 alters motor output at the hypoglossal motor nucleus through activation of excitatory ascending spinal pathways and inhibitory peripheral sensory feedback mechanisms. These findings highlight the importance of spinal-brainstem communication in shaping the motor program of swallow-related musculature and offer the potential for stimulation of the cervical spinal cord to be a therapeutic target for restoring swallowing function after injury. NEW & NOTEWORTHYIn two varying severity models of spinal cord injury, we demonstrate the effects of spinal cord stimulation at C4 on the distal hypoglossal motor nucleus. We show that despite being anatomically distant, electrical stimulation of the phrenic motor nucleus increases hypoglossal motor output through ascending spinal pathways and dampens it through peripheral pathways. These findings highlight the importance of spinal-brainstem communication and illustrate the ability of spinal stimulation to restore this communication after injury.

Spinal motoneuron (MN) pools behave as linear systems that transmit common synaptic input to muscles. However, MNs are biophysically heterogeneous and intrinsically nonlinear. How different MN subpopulations integrate and transmit high-frequency inputs remains poorly understood, partly because conventional analyses treat the MN pool as a single functional system rather than examining subpools with different firing rates. Here, we addressed this gap using a combination of computational simulations and human MN recordings. Simulations of MNs receiving a common synaptic input at varying frequencies showed that MNs firings become phase-locked to input oscillations when the input frequency approximates the neurons firing rate or its harmonics. We refer to this frequency-dependent synchronization as entrainment. Importantly, this subpool-specific effect was masked when MN activity was analysed at the whole-pool level. Because entrained MNs effectively sample the input at their firing instants, we developed a MN-firing locked method that uses individual MN firings as endogenous triggering events for peristimulus frequencygrams across the pool. In simulations, this method revealed entrainment-driven firing rate modulations across MN subpools. We then applied this MN-firing locked method to MNs decomposed from high-density surface electromyography recordings obtained during isometric contractions in healthy individuals. We found that faster-firing MNs exhibited larger transient firing rate increases, time-locked to slower MN activity. Furthermore, these modulations correlated with common input in the alpha and beta bands implicating high frequency common input as the driving source. Together, these findings demonstrate that MN nonlinearities generate heterogeneous, frequency-dependent dynamics that remain hidden in conventional pool-level analyses.

Successful goal-directed movements depend on the central nervous systems (CNS) ability to handle diverse physical interactions. The CNS is thought to handle different dynamical contexts through three mechanisms: (i) trial-by-trial adaptation when forces are predictable, (ii) a model-free robust control strategy, and (iii) online adaptation of feedback responses. While each has been studied independently, their relative contributions and the possibility that they are recruited to different extents across contexts is unknown. Here, we quantified all three strategies within the same individuals to examine how CNS exploits them under varying environmental conditions. Participants (19 female, 15 male) performed reaching tasks while interacting with robot-generated force-fields that were either consistent or varied unpredictably. Trial-by-trial adaptation was measured using standard force channels to isolate anticipatory compensation. Robust control was assessed through movement velocity and corrective force magnitude. Online adaptive control was quantified by the temporal alignment between commanded and measured forces within a movement. Results showed that participants improved anticipatory compensation in consistent environments and relied on both robust and online adaptation when perturbations were unpredictable. Crucially, markers of robust control dominated the early movement phase, whereas online adaptation dominated later corrections. This temporal dissociation was confirmed by electromyographic recordings. Markers of robust and online adaptive feedback strategies also statistically predicted participants ability to adapt across trials in consistent environments, revealing a common trait linking online control and adaptation. These findings reveal a rich and flexible combination of control mechanisms, offering a new framework for understanding the neurophysiological bases of reaching control. Significance StatementHuman reaching control is a complex behavior resulting from several mechanisms that orchestrate feedback responses to mechanical perturbations and adaptation to changes in the environment. Here we combine previously studied paradigms to highlight within the same groups of healthy volunteers that three major components are recruited to different extents dependent on the context: unpredictable environment promote concomitant use of robust control and online adaptation whereas predictable environments recruit standard adaptation based on anticipatory compensation. Remarkably, individuals adaptive capabilities correlated across consistent and inconsistent environments, suggesting a key involvement of adaptive mechanisms in both online control and trial-by-trial adaptation. Robust control, online adaptation, and anticipatory compensation are dissociable behaviorally, and are used to varying levels as a result of individual traits.

Neuromuscular reflexes elicited by sensory nerve stimulation provide valuable insights into neural motor control pathways. Analysis at the level of individual motor units (MUs) is feasible via electromyographic decomposition, but the factors shaping MU-specific reflex responses remain poorly understood. We investigated long-latency responses to cutaneous electrical stimulation in a large population of tibialis anterior MUs from nine healthy subjects during isometric ankle dorsiflexion at 10-30% of maximum voluntary contraction. Individual MU reflex responses differed markedly. Using 1000 stimulation pulses per trial, substantially more than the 150-300 typically reported in previous studies, provided more reliable estimates of cutaneous reflex characteristics. Across the motor pool, reflex magnitude increased with force level (p < 0.001) while excitation probability correlated significantly with MU recruitment threshold in 78% of subjects (p = 0.012). Furthermore, excitation probability increased systematically with contraction intensity (p < 0.001) for individually tracked MUs. Post-excitatory depression (PED) magnitude correlated significantly with excitation probability (r = 0.50, p < 0.001) of individual MUs. A targeted reflex-removal analysis, validated by MU simulations incorporating realistic excitation probabilities into ordinary firing patterns, reduced the PED by 84.2% in simulated data but only by 34.7% in recorded units. These findings suggest that the PED is a complex, hybrid phenomenon, resulting from synchronization-induced discharge resetting and additional independent inhibitory components. These findings demonstrate that MU-level reflex excitability to somatosensory input is influenced by state- and identity-dependent motor neuron characteristics, underscoring the importance of using sufficient stimulation pulses for reliable reflex measures and MU population analysis.

Receptive fields provide a concise description of the stimulus selectivity of visual neurons. But this stimulus selectivity is neither static nor linear, and these nonlinear effects are not well captured by standard linear or pseudo-linear receptive field models. At the same time, receptive field models incorporating nonlinear effects are largely empirical, and are not easily interpreted in terms of underlying cellular and synaptic mechanisms. Here we show that two nonlinear mechanisms in the primate outer retina shape neural responses and that these contribute significantly to responses to natural stimuli and to the retinal output signals. Incorporating these outer retinal nonlinearities into models for visual function will improve our ability to identify the mechanistic origin of specific features of downstream visual responses.

Anticipatory control organises motor output prior to predictable perturbations and is expressed in multi-digit tasks as anticipatory synergy adjustments (ASAs), which coordinate digit forces before movement onset. Whether such feedforward coordination depends on peripheral sensory input remains unclear. Carpal tunnel syndrome provides a model of altered median nerve afference with within-subject restoration following surgical decompression. We quantified ASA onset and amplitude in eleven individuals with carpal tunnel syndrome performing a multi-finger grasp-and-release task before and three weeks after decompression surgery. Postoperatively, sensory function improved, and total grip force decreased significantly across task phases, indicating more efficient force regulation. In contrast, ASA onset timing and amplitude were unchanged. Equivalence testing confirmed that pre- and post-operative ASA measures fell within predefined bounds of practical equivalence. These findings demonstrate a central-peripheral dissociation: feedback-mediated grip force scaling is sensory-dependent and rapidly recalibrates following afferent restoration, whereas feedforward synergy coordination remains stable despite months of degraded peripheral input. The preserved ASA suggests that central motor planning circuits maintain anticipatory coordination through efferent copy or cerebellar-mediated internal models that do not require continuous peripheral recalibration. This resilience may reflect the brains ability to maintain predictive motor planning despite chronic sensory degradation, with implications for understanding compensatory mechanisms in peripheral neuropathies and the limits of sensory-dependent motor adaptation.

Reaction time is a measure of the speed of our response to stimuli in the environment. Even for a well-trained task, a subjects reaction time varies. One source of this variability is internal state fluctuations (such as changes in arousal). There are few studies that systematically quantify the extent to which reaction time varies across different timescales and link this to measures of systemic physiology associated with arousal. In much of the literature, it is assumed but not demonstrated that behavioral and systemic measurements associated with arousal will be consistently linked because both estimate a common underlying arousal process. In this work, we examined this assumption by simultaneously measuring reaction time, heart rate, and pupil diameter in rhesus macaque monkeys performing several visual tasks over hours and across hundreds of sessions. We found a portion of the variability in reaction time could be linked to systemic physiological signatures of arousal on fast timescales from second to second and slower timescales from minute to minute. This link between reaction time and systemic physiology was also present for different biomarkers of arousal (heart rate and pupil). However, the strength of this relationship varied depending on the arousal biomarker. Our findings support the conclusion that there are multiple arousal mechanisms that act simultaneously to influence behavior and multiple timescales at which they operate.

Hierarchy in the brain emerges across spatial and temporal scales, enabling transformations from rapid sensory encoding to sustained cognitive control. Hierarchical gradients are well established in sensory systems. In contrast, the hierarchical organization of the primate motor cortex remains debated, partly due to its agranular architecture and the absence of clear laminar input-output projections, that obscures the distinction between feedforward and feedback pathways. In particular, the relative hierarchical position of the dorsal premotor cortex (PMd) and the primary motor cortex (M1) cannot be resolved from anatomy alone. To investigate their relative organization, we here adopted a multimodal approach using intrinsic timescales derived from both single-unit spiking activity (SUA) and local field potentials (LFPs) in macaques performing a delayed-match-to-sample reaching task. We found convergent evidence for inter-areal temporal hierarchy, with longer spiking timescales and smaller LFP aperiodic spectral exponents in M1. Across cortical depth, however, temporal organization depended on signal modality. LFP spectral exponents were significantly smaller in deep than superficial layers in both areas, and LFP-autocorrelation timescales were longer in deep layers in M1. In contrast, spiking activity did not show significant laminar differences in intrinsic timescales. Functionally, neurons with longer timescales exhibited more stable representations of the planned movement direction during motor preparation in PMd and slower temporal evolution of movement encoding during execution in both areas. In conclusion, multimodal temporal measures converge on the same hierarchical organization across these two motor areas, with M1 placed higher than PMd. Our study provides the first characterization of intrinsic spiking timescales across cortical layers in any cortical area and shows that laminar temporal organization depends on the neural signal analyzed. This divergence likely reflects their distinct physiological origins. Spikes capture neuronal output, whereas LFPs primarily reflect synaptic and dendritic population activity, potentially integrating differential contributions from apical and basal dendritic inputs.

Dysarthric speech severity assessment typically requires either trained clinicians or supervised machine learning models built from labelled pathological speech data, limiting scalability across languages and clinical settings. We present a training-free method (no supervised severity model is trained; feature directions are estimated from healthy control speech using a pretrained forced aligner) that quantifies dysarthria severity by measuring the degradation of phonological feature subspaces within frozen HuBERT representations. For each speaker, we extract phone-level embeddings via Montreal Forced Aligner, compute d scores along phonological contrast directions (nasality, voicing, stridency, sonorance, manner, and four vowel features) derived exclusively from healthy control speech, and construct a 12-dimensional phonological profile. Evaluating 890 speakers across10corpora, 5 languages for the full MFA pipeline (English, Spanish, Dutch, Mandarin, French) and 3 primary aetiologies (Parkinsons disease, cerebral palsy, amyotrophic lateral sclerosis), we find that all five consonant d features correlate significantly with clinical severity (random-effects meta-analysis rho = -0.50 to -0.56, p < 2 x 10^-4; pooled Spearman rho = -0.47 to -0.55 with bootstrap 95% CIs not crossing zero), with the effect replicating within individual corpora, surviving FDR correction, and remaining robust to leave-one-corpus-out removal and alignment quality controls. Nasality d decreases monotonically from control to severe in 6 of 7 severity-graded corpora. Mann-Whitney U tests confirm that all 12 features distinguish controls from severely dysarthric speakers (p < 0.001).The method requires no dysarthric training data and applies to any language with an existing MFA acoustic model (currently 29 languages) or a model trained from healthy speech alone. It produces clinically interpretable per-feature profiles. We release the full pipeline and phone feature configurations for six languages to support replication and clinical adoption. Author SummaryOne of the authors has lived with ALS for sixteen years. Bernard Muller, who built this entire analytical pipeline using only eye-tracking technology, has experienced the progression of the disease firsthand, including the dysarthric speech that comes with advancing ALS and the tracheostomy that followed. The problem this paper addresses is not abstract to him, and that shapes how the method was designed. We developed a method to measure how well a person with dysarthria can produce distinct speech sounds, without needing any recordings of disordered speech for training. Our approach works by analysing how a widely available AI speech model organises different sound categories -- such as nasal versus oral consonants, or voiced versus voiceless sounds -- and measuring whether those categories become harder to tell apart. We tested this on 890 speakers across 10 datasets in five languages, covering Parkinsons disease, cerebral palsy, and ALS. Because the method only needs healthy speech recordings to set up, it applies to any language with an existing acoustic model, currently covering 29 languages. The resulting profiles show clinicians which specific aspects of speech production are degrading, rather than providing a single opaque severity score. This could support remote monitoring of speech decline in neurodegenerative disease and enable screening in languages and settings where specialist assessment is unavailable.

This study examines the temporal dynamics of expressive piano performance by means of a quantitative analysis of motor timing in an elite pianist, with particular reference to stylistic contrasts between Baroque and Romantic repertoire. In line with kinematic models of expressive timing, which describe musical performance as reflecting principles of biological motion, we examined whether a common temporal structure underlies stylistically divergent executions. Despite marked differences in structural complexity and gesture density, both performances exhibited a shared low-frequency oscillatory pattern ([~]0.36 Hz) in beat-level timing variability. This infra-delta rhythmic modulation is consistent with the presence of an underlying motor timing scaffold and suggests a common temporal organization across expressive behaviors. These findings support the hypothesis that musical performance relies on a rhythmically structured control architecture, potentially shared with other complex motor activities such as speech and locomotion.

Stroke impairs dexterous hand use in daily activities, which may be due to compromised coordination complexity and diminished task-appropriate and individually-distinctive coordination (expressiveness). This loss of complexity and expressiveness, however, has not been elucidated, especially in spatiotemporal coordination. Here, we characterized spatiotemporal coordination in able-bodied and post-stroke hands during finger individuation. We quantified coordination complexity and expressiveness using principal component analysis (PCA) and linear discriminant analysis of 3D isometric forces from all five fingers. Paretic fingers showed reduced complexity (number of PCs) and expressiveness (task-, individual-, and group-specificity), which was associated with greater intrusion of flexor bias in the paretic hand. Higher-variance PCs were characteristic of tasks and groups, while both higher- and lower-variance PCs were characteristic of individual-specific coordination. These findings advance understanding of how stroke affects finger coordination complexity and expressiveness, and may inform the development of targeted therapies to improve task-relevant and individually distinctive coordination post-stroke.

Background: Spinal cord injury (SCI) is associated with widespread reorganisation of cortical sensorimotor circuits. Persistent complications such as spasticity and neuropathic pain suggest that homeostatic plasticity, which normally helps stabilise and constrain activity-dependent changes in sensorimotor circuits, may be disrupted after SCI. Homeostatic plasticity can be probed using repeated blocks of transcranial direct current stimulation (tDCS); in healthy individuals, two closely spaced excitatory blocks typically leads to an inhibitory response, reflected as a reduction in corticomotor excitability. Objective: To determine whether individuals with SCI show reduced homeostatic suppression of corticospinal excitability in response to repeated anodal tDCS, compared with healthy controls. Methods: Twenty adults with thoracic or below SCI and 20 healthy controls completed three counterbalanced sessions. Each session comprised two 10-minute blocks of 2 mA tDCS separated by 5 minutes, with the second block always being anodal tDCS over left primary motor cortex. The first block was either anodal, cathodal, or sham tDCS, yielding 3 condition types: anodal-anodal, cathodal-anodal, and sham-anodal. To assess corticomotor excitability, transcranial magnetic stimulation-evoked motor evoked potentials (MEPs) were elicited at baseline, after priming, and every 5 minutes for 60 minutes after the second block. The primary outcome was percent change in MEP amplitude from baseline. Results: In the anodal-anodal condition, the SCI group showed greater facilitation than controls over 0-30 minutes (estimate = 83.09, 95% CI 49.75 to 116.43, p < 0.001), suggestive of a weaker homeostatic response. The cathodal-anodal condition led to a significant overall facilitatory effect with no between-group difference, while the sham-anodal condition showed no change in MEP amplitude relative to baseline. Within the SCI group, exploratory subgroup analysis suggests that those with neuropathic pain and a traumatic injury showed greater facilitation in the anodal-anodal condition than those without these features, indicative of a weaker homeostatic response. Conclusions: SCI is associated with impairment in the homeostatic regulation of corticomotor excitability following repeated excitatory brain stimulation. Disrupted plasticity stabilisation may be relevant to persistent symptoms such as neuropathic pain.

BackgroundFlexibility and robustness of neuronal function are closely linked to degeneracy, the ability of distinct structural or parametric configurations to produce similar functional outcomes. At the cellular level, this often manifests as ion-channel degeneracy, in which multiple combinations of intrinsic conductances yield comparable electrophysiological phenotypes. MethodologyWe used a population-based, data-driven modelling framework to generate large ensembles of biophysically detailed CA1 pyramidal neuron models constrained by somatic electrophysiological features extracted from patch-clamp recordings in acute slices from early-birth rats. 10 reconstructed morphologies were incorporated, and model populations were analyzed using parameter correlation analysis, principal component analysis, and generalization tests to assess robustness, degeneracy, and morphology dependence of intrinsic properties. ConclusionsAcross the model population, similar somatic firing behaviours emerged from widely different combinations of intrinsic parameters, demonstrating robust two-level ion channel degeneracy both within and across morphologies. Each morphology occupied a distinct region of parameter space, indicating morphology-specific compensatory effects, while weak pairwise parameter correlations suggested distributed compensation rather than tight parameter dependencies. Even with a fixed morphology, multiple parameter subspaces supported comparable electrophysiological phenotypes. Generalization across morphologies was structure-dependent and non-reciprocal, with successful parameter similarity occurring preferentially between structurally similar neurons. Interestingly, to accurately simulate spike-frequency adaptation, it was important to retain some kinetic properties of the ion channel models as free parameters during optimization. Together, these findings show that dendrite morphology shapes the valid parameter space, and similar electrophysiology of CA1 pyramidal neurons arises from the interplay between structural variability and ion-channel diversity. This work highlights the importance of population-based modelling for capturing biological variability and provides insights into how neuronal robustness might be maintained despite substantial heterogeneity, and offers a scalable pipeline for generating biophysically realistic CA1 neuron populations for use in network simulations. Author summaryNeurons must reliably process information even though their internal components, such as ion channels and cellular shape, can vary widely from cell to cell. How stable behaviour emerges from such variability is a fundamental question in neuroscience. In this study, we explored this problem using detailed computer models of early-birth rat hippocampal CA1 pyramidal neurons, a cell type that plays a central role in learning and memory. Instead of building a single "average" neuron model, we created large populations of models that all reproduced key experimental recordings but differed in their internal parameters. We found that neurons with different shapes and different combinations of ion channels could nevertheless generate similar electrical activity. This phenomenon, known as ion channel degeneracy, allows neurons to remain functional despite biological variability or perturbations. Our results show that neuronal shape strongly influences which parameter combinations are viable, but that multiple solutions exist even for the same morphology. The population of models we provide offers a resource for future studies of early-birth CA1 pyramidal cell function and dysfunction.

Objective: To systematically evaluate the efficacy and safety of Deep Brain Stimulation (DBS) for the management of disabling tremor in patients with Multiple Sclerosis (MS) by synthesizing data from available clinical studies. Methods: This systematic review and meta analysis followed PRISMA 2020 guidelines and was registered with PROSPERO (CRD420261347426). A comprehensive search of PubMed, Scopus, Web of Science, and Embase was performed from database inception until December 2025 with no time or language limitation. A pre-post meta analysis design was used to estimate the pooled effect size using the Standardized Mean Change (SMC) between baseline and follow up tremor severity. Because most included studies were single arm cohorts and clinical heterogeneity was anticipated, a random effects model using the Restricted Maximum Likelihood (REML) estimator with the Hartung-Knapp adjustment was applied. Safety outcomes including hardware complications and postoperative infections were pooled using random effects meta analysis of proportions. Results: Thirteen studies including 131 patients met the eligibility criteria. Eight studies with adequate outcome data were included in the pooled efficacy analysis. DBS was associated with a significant reduction in tremor severity with an overall pooled SMC of 1.42 (95% CI 1.07 to 1.77). Statistical heterogeneity was minimal (I2 = 0.0%, p = 0.6300), although this finding should be interpreted cautiously given the limited number of studies and clinical variability in surgical targets, most commonly the ventral intermediate nucleus (VIM), and follow up duration ranging from months to more than 20 years. The pooled incidence of postoperative infection was approximately 7% with substantial heterogeneity across studies (I2 = 74.1%). The most frequently reported adverse events were stimulation related effects such as dysarthria and disequilibrium, which were generally reversible after adjustment of stimulation parameters. Overall methodological quality of included studies was predominantly moderate. Conclusion: Deep brain stimulation may provide meaningful tremor reduction in selected patients with disabling and medication refractory MS tremor, with a large pooled treatment effect (SMC = 1.42). Although complications such as postoperative infection (approximately 7%) and transient stimulation related adverse effects can occur, these events appear manageable in most cases. However, the current evidence base remains limited by small sample sizes, heterogeneous study designs, and variability in surgical targets and outcome reporting. Larger prospective studies with standardized tremor outcome measures and consistent reporting of safety outcomes are needed to better define the long term efficacy and optimal clinical role of DBS in patients with MS related tremor.

BackgroundTranscranial Magnetic Stimulation (TMS) studies identify the Resting Motor Threshold (RMT) to calibrate stimulation intensity. However, this procedure is time-consuming and subject to variability. We developed an automated procedure to improve the efficiency and standardization of RMT determination. New methodWe developed an algorithm that measures MEP amplitudes and automatically adjusts stimulation intensity to determine the RMT. Experiment 1 compared this automated method with the manual procedure in terms of reliability and equivalence. Experiment 2 developed a "Fast" automated process, assessing it against both the manual and initial automated procedures. ResultsAcross both experiments the automated approach demonstrated excellent test-retest reliability and strong agreement with the manual method (Intraclass Correlation Coefficients [&ge;]0.95), giving estimates of RMT statistically equivalent to those of manual measurements within {+/-}3% MSO, with the majority of comparisons within {+/-}2% MSO. Experiment 2 optimized the procedure, allowing empirical determination of the RMT in an average of <3 minutes with only 33-34 pulses. Comparison with existing methods RMT-Finder provides a reliable and time-efficient alternative to manual approaches. To the best of our knowledge RMT-Finder presents the first closed-loop feedback approach to identify the RMT without manual intervention. This procedure can improve standardization and reproducibility in TMS studies. ConclusionsAutomating RMT assessment allows rapid and highly reproducible assessment of this standard TMS measurement, making it viable for inclusion in routine clinical applications that require standardized procedures.