Biology subjects

Denison, T.

Publications and source records attributed to Denison, T..

At least 19 recordsLinked to original sources

bioRxiv2026

Spinal Recurrent Inhibition Shapes the Dynamics of TMS-induced Motor-Evoked Potentials: A Computational Modeling Study

Motor-evoked potentials (MEPs) recorded via surface electromyography (EMG) from peripheral muscles following transcranial magnetic stimulation (TMS) of the motor cortex reflect the integrity of the entire corticospinal pathway and are widely used in both basic neuroscience and clinical practice. However, the relative contributions of spinal and peripheral mechanisms to the observed MEP waveform remain poorly understood, partly because computational models that capture individual MEP characteristics are lacking. Here, we present a biologically plausible and computationally efficient model of the descending motor pathway, spanning the spinal cord and hand muscles, that can be fitted to individual MEP waveforms across a range of TMS intensities. The model successfully reproduces individual MEP waveforms, accounting for approximately 90% of the observed variance in waveforms across 10 healthy participants. Crucially, we demonstrate that recurrent inhibition of Renshaw cells in the spinal cord is indispensable for reproducing the fine temporal structure of MEP waveforms, even when input-output curve fitting appears adequate without it. Beyond waveform reproduction, the fitted model provides interpretable estimates of latent neural dynamics and subject-specific pathway parameters, including motor neuron size distribution, synaptic receptor balance, axonal conduction delay, and hand muscle refractoriness, that are consistent with known biological ranges. These results suggest that individual MEP waveforms, when analyzed using a biologically grounded model, carry substantially more information about spinal and peripheral motor pathway integrity than conventional amplitude-based measures alone.

neuroscience↗

bioRxiv2026

Why Speech Motor Blocks Emerge in a Communicative Context: An Active Inference Model of Stuttering

Adults who stutter can speak fluently when speech is not addressed to another person, but stuttering emerges when they aim to convey information to a listener. The value of the information being conveyed to the listener also affects the likelihood of stuttering. Why should the mere absence of a listener neutralise a profound motor deficit, and why does a word's predictability affect whether it is spoken fluently? To resolve this socio-motor paradox, we develop a computational model of stuttering within an active inference architecture. The model represents the communicative context, including whether a listener is present and whether the agent is speaking or listening. It was designed around two candidate mechanisms for stuttering, a prior for silence and rigid phoneme sequencing precision. Using both, the model produced fluent private speech and more stuttering-like events during social speech. In the same parameter regime, the model also showed more stuttering-like events on words with higher information value, and produced a word-length effect, in which disfluency increased with longer words. To our knowledge, this is the first model of stuttering to generate both the private speech and the information-value effect from inferred communicative context. By representing the listener as a hidden state that makes the sensory consequences of resuming speech ambiguous, the model offers a computational link between social cognition and speech-motor instability, and suggests that speech fluency depends on whether the speaker believes anyone is present. Clinically, it may offer testable hypotheses and a route to personalising treatment, since the same overt severity can arise from different combinations of parameters.

neuroscience↗

bioRxiv2026

Device-embedded accelerometry complements neural signals for tracking parkinsonian motor states

Adaptive deep brain stimulation (aDBS) relies on physiological biomarkers to infer motor state and guide therapeutic stimulation in Parkinsons disease. However, neural biomarkers may themselves be altered by stimulation, potentially limiting their utility for closed-loop control. We address this limitation by testing whether DBS device-embedded accelerometers can accurately track Parkinsonian motor state across stimulation conditions. We analysed over 1,900 hours of chronic recordings of subthalamic nucleus (STN), sensorimotor cortical and device-embedded accelerometry signals acquired before and during continuous STN stimulation, alongside continuous wearable assessments of bradykinesia and dyskinesia. Across stimulation conditions, accelerometry-derived features robustly tracked motor symptom severity and outperformed neural features for symptom decoding. Mechanistically, total STN beta power - a widely used biomarker for aDBS - proved less informative because it conflates periodic and aperiodic neural processes with opposing relationships to motor state. Under active stimulation, periodic beta activity showed reduced coupling to symptom severity, whereas STN aperiodic activity, cortical periodic activity and cortico-subthalamic coherence remained comparatively stable. Together, these findings demonstrate that neural and behavioural biomarkers exhibit differential robustness during deep brain stimulation and identify device-embedded accelerometry as a robust behavioural biomarker of motor state, motivating its use in next-generation adaptive DBS systems.

bioengineering↗

bioRxiv2026

A learning-evoked slow-oscillatory architecture paces population activity for offline reactivation across the human medial temporal lobe

Memory processing requires the coordinated engagement of neuronal populations across distributed brain networks and across time. How such coordination is organized in the human medial temporal lobe (MTL) remains unclear. Here, we show that MTL population activity is dynamically structured by a transient slow-oscillatory architecture that emerges during online learning to promote offline consolidation and later recall. Using intracranial recordings that combine single-neuron spiking activity and local field potentials in human participants, we find that mnemonic engagement evokes on-demand slow-oscillatory bursts in the hippocampus. These hippocampal bursts synchronize gamma-band patterns across MTL regions, defining discrete coordination events that pace cross-regional coactivity motifs during learning. These learning-time population motifs are then selectively reactivated during hippocampal ripples in post-learning rest, and the strength of their reactivation predicts subsequent recall accuracy. Together, these findings identify a multi-scale coordination mechanism that links distributed population activity across learning, consolidation, and recall in humans.

neuroscience↗

bioRxiv2026

A cardiac pulse signal affects local field potentials recorded from deep brain stimulation electrodes across clinical targets

ObjectiveMany deep brain stimulation (DBS) systems sense local field potentials (LFPs) for patient monitoring or closed-loop therapy (CL-DBS). LFPs can be impacted by artifacts, including a recently discovered cardiac non-electrocardiographic pulse signal that can be visually masked by commercial device filters. We aimed to establish its prevalence across patient groups and brain areas, and to investigate its spectral impact. MethodsWe performed a cross-sectional analysis of LFPs recorded from the cranially mounted Picostim from the pedunculopontine nucleus in multiple systems atrophy patients, periacqueductal gray and sensory thalamus in chronic pain patients, and the centromedian thalamic nucleus (CMT) in paediatric epilepsy patients. For comparison, we analyse externalised recordings from the subthalamic nucleus in Parkinsons disease patients. The PulsAr algorithm was developed to detect and extract pulsatile signals, and we characterised contamination level and spectral content. ResultsThough not visually obvious in CMT, the pulsatile signal was algorithmically detected in all targets, with 33% of LFPs across targets classed as contaminated. Pulse signal power was similar across targets and may have been masked by higher endogenous activity in CMT. While its dominant frequencies were in the heartbeat range, the signal had spectral content extending up to >10Hz. ConclusionsA heart pulse signal affects LFP recordings from DBS leads across brain regions and patient groups. While masked by some device filters, spectral content can extend into higher (clinically relevant) frequencies. Researchers and clinicians should exercise caution when sensing lower LFP frequencies, especially for automated control of therapy in CL-DBS. HighlightsO_LIHistorically, electrocardiographic artifacts have been a major source of artifact affecting deep brain stimulation recordings, however pulsatile artifact is less well described. C_LIO_LIA cardiac pulse signal affects local field potentials recorded from deep brain stimulation electrodes across clinical targets. C_LIO_LIWe introduce an ECG-independent algorithm that detects and extracts this pulsatile signal. C_LIO_LIThe heart pulse signal looks like the intracranial pressure waveform and affects spectral frequencies above the heart rate range up to >10Hz. C_LIO_LIClinicians should incorporate screening and procedures to ensure accurate biomarker detection for clinical decision making. C_LI

bioengineering↗

bioRxiv2025

Dithering suppresses half-harmonic neural synchronisation to photic stimulation in humans

While entraining neural rhythms using brain stimulation has been suggested as a therapeutic mechanism to normalise brain activity in conditions such as depression, chronic pain, or Alzheimers disease, periodic stimulation can also inadvertently entrain brain rhythms at sub- and superharmonics of the stimulation frequency, which could lead to deleterious effects. Slightly jittering stimulation pulses (called "dithering") was previously proposed on the basis of mathematical modelling to selectively entrain a target neural rhythm while avoiding harmonic entrainment. In this study, we investigated the potential of dithering in humans. Using photic stimulation (light flicker) and EEG recordings in healthy participants, we showed that dithering suppresses half-harmonic synchronisation relative to perfectly periodic flicker, and more so than synchronisation at the stimulation frequency. This was also the case for a periodic condition with reduced stimulation amplitude, as predicted by theory. Furthermore, we demonstrated using synthetic data and modelling that the half-harmonic responses observed in participants cannot be explained by the super-position of evoked responses (even when modulated at the half-harmonic frequency), and are better matched by a minimal oscillator model. Our findings are consistent with half-harmonic EEG synchronisation in response to photic stimulation predom-inantly reflecting half-harmonic entrainment rather than the summation of evoked responses, and with dithering being an effective strategy to suppress subharmonic entrainment.

neuroscience↗

bioRxiv2025

Modulation of motor cortical theta and gamma oscillations using phase-targeted, closed-loop optogenetic stimulation of local excitatory and inhibitory neurons

Theta and gamma oscillations are prominent features of cortical local field potentials (LFPs) and stimulation of the motor cortex at these frequencies can enhance motor learning. Phase-targeted closed-loop stimulation could provide a more precise and effective method to modulate these oscillations, particularly if stimulation parameters could harness the dynamics of the specific circuit mechanisms underpinning the generation of these activities. To address this question, we defined the response of theta-and gamma-frequency oscillations in the motor cortex to closed-loop optogenetic stimulation of excitatory pyramidal neurons and inhibitory interneurons transfected with Channelrhodopsin-2 in awake, head-fixed RBP4-Cre (retinol-binding-protein-4) and PV-Cre (parvalbumin) mice, respectively. Phase-targeted blue-light pulses were delivered using the OscillTrack algorithm to track theta phase in the cortical LFP in real time and trigger stimulation at one of four target theta phases. Stimulation was delivered over a quarter of the target theta cycle, either as a single continuous pulse ("continuous" protocol) or three short pulses at gamma (75Hz) frequency ("gamma" protocol). Stimulation of both neuron types, using either stimulation protocol, modulated theta power in a phase-dependent manner, with continuous stimulation of excitatory cells leading to stronger modulation. Phase-dependent amplification during stimulation of excitatory vs inhibitory neurons was offset by 90{degrees}, in line with predictions from computational models. Open-loop replay of previously recorded closed-loop stimulation patterns did not elicit the same phase-specific effects, demonstrating the necessity of the closed-loop interaction to produce these effects. Stimulation of pyramidal neurons using the gamma protocol amplified gamma power, independently of target theta phase. These findings reveal phase-dependent amplification of cortical theta power can be induced by stimulation of local excitatory or inhibitory neurons, with a phase-offset likely resulting from circuit interactions. This approach can be used to inform the development of brain stimulation methods to modulate these activities more effectively in humans.

neuroscience↗

bioRxiv2025

Phasic and tonic pain serve distinct functions during adaptive behaviour

Pain drives self-protective behaviour, and evolutionary theories suggest it acts over different timescales to serve distinct functions. Whilst phasic pain provides a teaching signal to drive avoidance of new injury, tonic pain is argued to support recuperative behaviour, for instance by reducing motivational vigour. We test this hypothesis in an immersive virtual reality EEG foraging task where subjects harvested fruit in a forest: some fruit elicited brief phasic pain to the grasping hand, and this reduced choice probability. Simultaneously, tonic pressure pain to the contralateral upper arm was associated with reduced action velocities. This could be explained by a free-operant computational framework that formalises and quantifies the function of tonic and phasic pain in terms of motivational vigour and decision value, and model parameters correlated with physiological and neural responses. Overall, the results show how tonic and phasic pain subserve distinct objective motivational functions that support harm minimisation during ongoing adaptive behaviour.

neuroscience↗

bioRxiv2024

Prediction of pathological subthalamic nucleus beta burst occurrence in Parkinson's disease

The cortico-basal ganglia network in Parkinsons disease (PD) is characterized by the emergence of transient episodes of exaggerated beta frequency oscillatory synchrony known as bursts. Although it is well established that bursts of prolonged duration associate closely with motor impairments, the mechanisms leading to burst initiation remain poorly understood. Crucially, it is unclear whether there are features of basal ganglia activity which reliably predict burst onset. Current adaptive Deep Brain Stimulation (aDBS) approaches can only reactively deliver stimulation following burst detection and are unable to stimulate proactively to prevent burst onset. The discovery of predictive biomarkers could allow for such proactive stimulation, thereby offering potential for improvements in therapeutic efficacy. Here, using deep learning, we show that the timing of subthalamic nucleus (STN) beta bursts can be accurately predicted up to 60 ms prior to onset. Furthermore, we highlight that a dip in the beta amplitude - which is likely to be indicative of a phase reset of oscillatory populations occurring between 80-100 ms prior to burst onset - is a predictive biomarker for burst occurrence. These findings demonstrate proof-of-principle for the feasibility of beta burst prediction for DBS and provide insights into the mechanisms of burst initiation.

neuroscience↗

bioRxiv2024

Evoked Resonant Neural Activity Long-Term Dynamics can be Reproduced by a Computational Model with Vesicle Depletion

Subthalamic deep brain stimulation (DBS) robustly generates high-frequency oscillations known as evoked resonant neural activity (ERNA). Recently the importance of ERNA has been demonstrated through its ability to predict the optimal DBS contact in the subthalamic nucleus in patients with Parkinsons disease. However, the underlying mechanisms of ERNA are not well understood, and previous modelling efforts have not managed to reproduce the wealth of published data describing the dynamics of ERNA. Here, we therefore aim to present a minimal model capable of reproducing the characteristics of the slow ERNA dynamics published to date. We make biophysically-motivated modifications to the Kuramoto model and fit its parameters to the slow dynamics of ERNA obtained from data. We further validate the model against experimental data from Parkinsons disease patients by simulating variable stimulation and medication states, as well as the response of individual neurons. Our results demonstrate that it is possible to reproduce the slow dynamics of ERNA with a single neuronal population, and, crucially, with vesicle depletion as the key mechanism behind the ERNA frequency decay. We provide a series of predictions from the model that could be the subject of future studies for further validation. Author SummaryERNA is a high amplitude response to stimulation of deep brain structures, with a frequency over twice that of the frequency of stimulation. While the underlying mechanisms of ERNA are still unclear, recent findings have demonstrated its importance as the best indicator of which stimulation contact to select for DBS therapy in patients with Parkinsons disease. Previous modelling studies of ERNA focus on the immediate responses to stimulation (<200ms) and rely on interconnected neural structures and delays. Our work shows that the long-term (on the scale of one or more seconds) ERNA response to continuous stimulation can be modelled using a single neural structure. The proposed model also captures the long-term frequency and amplitude characteristics of ERNA with variable stimulation and medication paradigms. The key features of the model, in particular the depletion of vesicles carrying neurotransmitters between neurons by high-frequency stimulation, may provide insights into the underlying mechanisms of ERNA and inform future investigations into this neural response.

neuroscience↗

bioRxiv2023

Multi-night naturalistic cortico-basal recordings reveal mechanisms of NREM slow wave suppression and spontaneous awakenings in Parkinson's disease

BackgroundSleep disturbance is a prevalent and highly disabling comorbidity in individuals with Parkinsons disease (PD) that leads to worsening of daytime symptoms, accelerated disease progression and reduced quality of life. ObjectivesWe aimed to investigate changes in sleep neurophysiology in PD particularly during non-rapid eye movement (NREM) sleep, both in the presence and absence of deep brain stimulation (DBS). MethodsMulti-night (n=58) intracranial recordings were performed at-home, from chronic electrocorticography and subcortical electrodes, with sensing-enabled DBS pulse generators, paired with portable polysomnography. Four people with PD and one person with cervical dystonia were evaluated to determine the neural structures, signals and connections modulated during NREM sleep and prior to spontaneous awakenings. Recordings were performed both ON and OFF DBS in the presence of conventional dopaminergic replacement medications. ResultsWe demonstrate an increase in cortico-basal slow wave activity in delta (1-4 Hz) and a decrease in beta (13-31 Hz) during NREM (N2 and N3) versus wakefulness in PD. Cortical-subcortical coherence was also found to be higher in the delta range and lower in the beta range during NREM versus wakefulness. DBS stimulation resulted in a further elevation in cortical delta and a decrease in alpha (8-13 Hz) and low beta (13-15 Hz) power compared to the OFF stimulation state. During NREM sleep, we observed a strong inverse interaction between subcortical beta and cortical slow wave activity and found that subcortical beta increases prior to spontaneous awakenings. ConclusionsChronic, multi-night recordings in PD reveal opposing sleep stage specific modulations of cortico-basal slow wave activity in delta and subcortical beta power and connectivity in NREM, effects that are enhanced in the presence of DBS. Within NREM specifically, subcortical beta and cortical delta are strongly inversely correlated and subcortical beta power is found to increase prior to and predict spontaneous awakenings. We find that DBS therapy appears to improve sleep in PD partially through direct modulation of cortico-basal beta and delta oscillations. Our findings help elucidate a contributory mechanism responsible for sleep disturbances in PD and highlight potential biomarkers for future precision neuromodulation therapies targeting sleep and spontaneous awakenings.

neuroscience↗

bioRxiv2023

Bioelectronic Zeitgebers: targeted neuromodulation to re-establish circadian rhythms.

Existing neurostimulation systems implanted for the treatment of neurodegenerative disorders generally deliver invariable therapy parameters, regardless of phase of the sleep/wake cycle. However, there is considerable evidence that brain activity in these conditions varies according to this cycle, with discrete patterns of dysfunction linked to loss of circadian rhythmicity, worse clinical outcomes and impaired patient quality of life. We present a targeted concept of circadian neuromodulation using a novel device platform. This system utilises stimulation of circuits important in sleep and wake regulation, delivering bioelectronic cues (Zeitgebers) aimed at entraining rhythms to more physiological patterns in a personalised and fully configurable manner. Preliminary evidence from its first use in a clinical trial setting, with brainstem arousal circuits as a surgical target, further supports its promising impact on sleep/wake pathology. Data included in this paper highlight its versatility and effectiveness on two different patient phenotypes. In addition to exploring acute and long-term electrophysiological and behavioural effects, we also discuss current caveats and future feature improvements of our proposed system, as well as its potential applicability in modifying disease progression in future therapies.

bioengineering↗

bioRxiv2023

The effect of pulse shape in theta-burst stimulation: monophasic vs biphasic TBS

BackgroundIntermittent theta-burst stimulation (i)(TBS) is a transcranial magnetic stimulation (TMS) plasticity protocol. Conventionally, TBS is applied using biphasic pulses due to hardware limitations. However, monophasic pulses are hypothesised to recruit cortical neurons more selectively than biphasic pulses, thus yielding stronger plasticity effects. Monophasic and biphasic TBS can be generated using a custom-made pulse-width modulation-based TMS device (pTMS). ObjectiveUsing pTMS, we tested the hypothesis that monophasic iTBS would induce greater plasticity effects than biphasic, measured as induced changes in motor corticospinal excitability. MethodsIn a repeated-measures design, thirty healthy volunteers participated in three separate sessions, where monophasic and biphasic iTBS was applied to the primary motor cortex (M1 condition) or the vertex (control condition). Plasticity was quantified as changes in motor corticospinal excitability after versus before iTBS, by comparing peak-to-peak amplitudes of motor evoked potentials (MEP) measured at baseline and over 60 minutes after iTBS. ResultsBoth monophasic and biphasic M1 iTBS led to significant increases in MEP amplitude. As predicted, monophasic iTBS induced a significantly larger effect than biphasic iTBS (linear mixed effect model analysis: ({chi}2(1) = 7.48, p = 0.006), which persisted even after subtracting each individuals control (vertex) condition data from the M1 conditions ({chi}2(1) = 5.48, p = 0.019). ConclusionsIn this study, monophasic iTBS induced a stronger motor corticospinal excitability increase than biphasic within participants. This greater physiological effect suggests that monophasic iTBS may also have potential for greater functional impact, of interest for future fundamental and clinical applications of TBS.

neuroscience↗

bioRxiv2023

The Design of Brainstem Interfaces: Characterisation of Physiological Artefacts and Implications for Closed-loop Algorithms

Surgical neuromodulation through implantable devices allows for stimulation delivery to subcortical regions, crucial for symptom control in many debilitating neurological conditions. Novel closed-loop algorithms deliver therapy tailor-made to endogenous physiological activity, however rely on precise sensing of signals such as subcortical oscillations. The frequency of such intrinsic activity can vary depending on subcortical target nucleus, while factors such as regional anatomy may also contribute to variability in sensing signals. While artefact parameters have been explored in more standard and commonly used targets (such as the basal ganglia, which are implanted in movement disorders), characterisation in novel candidate nuclei is still under investigation. One such important area is the brainstem, which contains nuclei crucial for arousal and autonomic regulation. The brainstem provides additional implantation targets for treatment indications in disorders of consciousness and sleep, yet poses distinct anatomical challenges compared to central subcortical targets. Here we investigate the region-specific artefacts encountered during activity and rest while streaming data from brainstem implants with a cranially-mounted device in two patients. Such artefacts result from this complex anatomical environment and its interactions with physiological parameters such as head movement and cardiac functions. The implications of the micromotion-induced artefacts, and potential mitigation, are then considered for future closed-loop stimulation methods.

bioengineering↗

bioRxiv2022

Integrated human-machine interface for closed-loop stimulation using implanted and wearable devices

Recent development in implantable devices for electrical brain stimulation includes sensing and embedded computing capabilities that enable adaptive stimulation strategies. Applications include stimulation triggered by pathologic brain activity and endogenous rhythms, such as circadian rhythms. We developed and tested a system that integrates an electrical brain stimulation & sensing implantable device with embedded computing and uses a distributed system with commercial electronics, smartphone and smartwatch for patient annotations, extensive behavioral testing, and adaptive stimulation in subjects in their natural environments. The system enables precise time synchronization of the external components with the brain stimulating device and is coupled with automated analysis of continuous streaming electrophysiology synchronized with patient reports. The system leverages a real-time bi-directional interface between devices and patients with epilepsy living in their natural environment.

neuroscience↗

bioRxiv2022

How to entrain a selected neuronal rhythm but not others: open-loop dithered brain stimulation for selective entrainment

While brain stimulation therapies such as deep brain stimulation for Parkinsons disease can be effective, they have yet to reach their full potential across neurological disorders. Entraining neuronal rhythms using rhythmic brain stimulation has been suggested as a new therapeutic mechanism to restore neurotypical behavior in conditions such as chronic pain, depression, and Alzheimers disease. However, theoretical and experimental evidence indicate that brain stimulation can also entrain neuronal rhythms at sub- and super-harmonics, far from the stimulation frequency. Crucially, these counterintuitive effects can be harmful to patients, for example by triggering debilitating involuntary movements in Parkinsons disease. We therefore propose a principled approach to selectively promote rhythms close to the stimulation frequency, while avoiding potential harmful effects by preventing entrainment at sub- and super-harmonics. Our open-loop approach to selective entrainment, dithered stimulation, consists in adding white noise to the stimulation period. We theoretically establish the ability of dithered stimulation to selectively entrain a given brain rhythm, and verify its efficacy in simulations of uncoupled neural oscillators, and networks of coupled neural oscillators. Furthermore, we show that dithered stimulation can be implemented in neurostimulators with limited capabilities by toggling within a finite set of stimulation frequencies. Likely implementable across a variety of existing brain stimulation devices, dithering-based selective entrainment has potential to enable new brain stimulation therapies, as well as new neuroscientific research exploiting its ability to modulate higher-order entrainment.

neuroscience↗

bioRxiv2022

Sub-harmonic Entrainment of Cortical Gamma Oscillations to Deep Brain Stimulation in Parkinson's Disease: Predictions and Validation of a Patient-Specific Non-Linear Model

ObjectivesThe exact mechanisms of deep brain stimulation (DBS) are still an active area of investigation, in spite of its clinical successes. This is due in part to the lack of understanding of the effects of stimulation on neuronal rhythms. Entrainment of brain oscillations has been hypothesised as a potential mechanism of neuromodulation. A better understanding of entrainment might further inform existing methods of continuous DBS, and help refine algorithms for adaptive methods. The purpose of this study is to develop and test a theoretical framework to predict entrainment of cortical rhythms to DBS across a wide range of stimulation parameters. Materials and MethodsWe fit a model of interacting neural populations to selected features characterising PD patients off-stimulation finely-tuned gamma rhythm recorded through electrocorticography. Using the fitted models, we predict basal ganglia DBS parameters that would result in 1:2 entrainment, a special case of sub-harmonic entrainment observed in patients and predicted by theory. ResultsWe show that the neural circuit models fitted to patient data exhibit 1:2 entrainment when stimulation is provided across a range of stimulation parameters. Furthermore, we verify key features of the region of 1:2 entrainment in the stimulation frequency/amplitude space with follow-up recordings from the same patients, such as the loss of 1:2 entrainment above certain stimulation amplitudes. ConclusionOur results reveal that continuous, constant frequency DBS in patients may lead to nonlinear patterns of neuronal entrainment across stimulation parameters, and that these responses can be predicted by modelling. Should entrainment prove to be an important mechanism of therapeutic stimulation, our modelling framework may reduce the parameter space that clinicians must consider when programming devices for optimal benefit.

neuroscience↗

bioRxiv2021

Pulse-Width Modulation-based TMS mimics effects of conventional TMS on human primary motor cortex

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSObjectiveC_ST_ABSWe developed a novel transcranial magnetic stimulation (TMS) device to generate flexible stimuli and patterns. The system synthesizes digital equivalents of analog waveforms, relying on the filtering properties of the nervous system. Here, we test the hypothesis that the novel pulses can mimic the effect of conventional pulses on the cortex. ApproachA second-generation programmable TMS (pTMS2) stimulator with magnetic pulse shaping capabilities using pulse-width modulation (PWM) was tested. A computational and an in-human study on twelve healthy participants compared the neuronal effects of conventional and modulation-based stimuli. Main resultsBoth the computational modeling and the in-human stimulation showed that the PWM-based system can synthesize pulses to effectively stimulate the human brain, equivalent to conventional stimulators. The comparison includes motor threshold, MEP latency and input-output curve measurements. SignificancePWM stimuli can fundamentally imitate the effect of conventional magnetic stimuli while adding considerable flexibility to TMS systems, enabling the generation of highly configurable TMS protocols. HO_SCPLOWIGHLIGHTSC_SCPLOWO_LIThe PWM method promises the implementation of flexible neurostimulation C_LIO_LIPWM magnetic pulses were well tolerated by the participants without adverse events C_LIO_LIRMTs and MEPs were compared for PWM and conventional stimuli C_LIO_LIPWM-equivalent of conventional pulses has relatively similar effects on the cortex C_LIO_LIThe use of digital synthesis techniques to create novel patterns is a promising method for future neuromodulation C_LI

neuroscience↗