Biology subjects

Neufeld, E.

Publications and source records attributed to Neufeld, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Accurate Hippocampal Electric Field Modeling for Electroconvulsive Therapy: Numerical Accuracy and Convergence

Accurate hippocampal electric field (E-field) prediction is important for individualized electroconvulsive therapy (ECT) dosing and emerging deep-brain stimulation approaches such as temporal interference. Because hippocampal fields are far weaker than those beneath the stimulation electrodes, they are highly sensitive to tissue interfaces, conductivity contrasts, and numerical discretization, so numerical error can rival the physical uncertainties of anatomy and conductivity. We investigate this numerical component of hippocampal dosimetry using individualized head models from eleven ECT patients. Identical head40 segmentations, comprising 40 tissue compartments including the bilateral hippocampi, were simulated with three independent numerical methods: a charge-based boundary-element fast multipole method (BEM-FMM), a voxel-based hexahedral finite-element solver, and a conformal tetrahedral finite-element solver. For each, resolution was increased systematically and convergence assessed from the average hippocampal E-field magnitude. At the highest attainable resolutions, the three methods agreed closely, differing by 6%-7% in the left hippocampus and 9%-12% in the right. At default or coarse resolutions, however, they disagreed by 28.8% on average and up to 50.3% in the right hippocampus. Numerical convergence should therefore be established before differences are attributed to anatomical or conductivity uncertainty, and independent-solver agreement provides a practical basis for reliable hippocampal dosimetry.

neuroscience↗

bioRxiv2026

Hippocampal stimulation timed to memory reactivation shapes human sleep oscillatory dynamics and consolidation

Memory consolidation during sleep depends on the precisely timed coordination of hippocampal reactivation with cortical slow oscillations and spindles. In humans this coupling has been characterised correlationally, while causal investigations have required intracranial stimulation in restricted patient cohorts or used non-invasive approaches targeting cortical regions, often obscuring the underlying sleep rhythms. Here we stimulated the human hippocampus during sleep for the first time, applying temporal interference stimulation to the left hippocampal head either concurrently with or prior to induced memory reactivation. Stimulation concurrent with reactivation reduced associative memory forgetting relative to mistimed stimulation and enhanced fast spindle amplitude, preserving the association between slow oscillation-spindle coupling and memory. This behavioural benefit was mediated by a distributed, left-lateralised set of spindle and coupling features. Non-invasively engaging deep hippocampal circuits during sleep offers both a means to probe human memory and a scalable basis for intervention where consolidation fails.

neuroscience↗

bioRxiv2026

BraiNN: A Modern Simulator for Clinically Feasible Personalized Whole-Brain Network Modeling

Personalized whole-brain modeling aims to transform treatment planning for neurological disorders by enabling patient-specific simulations of brain network dynamics. Neural mass models (NMMs) offer a tractable compromise between biophysical detail and computational cost and can be directly linked to macroscopic observables such as EEG. However, scaling NMMs to whole-brain networks with realistic connectivity, conduction delays, and cortical surface resolution--and fitting them to individual patient data--imposes computational demands that existing frameworks cannot meet at clinically relevant timescales. Here we introduce BraiNN, a JAX-based Python framework for large-scale neural mass modeling that achieves speedups of up to two to three orders of magnitude over existing tools by leveraging GPU/TPU-accelerated, XLA-compiled array computation. BraiNN combines a region-level Jansen-Rit network with a subject-specific cortical surface mesh of coupled neural mass models and biophysically grounded EEG forward modeling via reciprocity-based lead fields. Its fully differentiable computational graph enables a hybrid personalization pipeline that pairs Bayesian optimization for global parameter exploration with gradient-based refinement, completing EEG-driven spectral fitting of an eight-dimensional parameter space in approximately 2-3 hours on a single consumer GPU--compared to multiple days with conventional neural mass modeling software. Numerical verification against established benchmarks confirms that BraiNN faithfully reproduces canonical synchronization and bifurcation dynamics of Jansen-Rit networks. By reducing the time requirements for personalizing a high-detail whole-brain surface model from days to a few hours on consumer-grade hardware, BraiNN brings personalized brain network modeling closer to practical use in clinical contexts. We anticipate that BraiNN will serve as a foundation for patient-specific digital twins and EEG-guided neuromodulation planning.

neuroscience↗

bioRxiv2026

Resonance-driven enhancement of sleep spindles using thalamic temporal interference stimulation

Sleep spindles are hallmarks of non-rapid eye movement sleep and support memory consolidation yet remain difficult to modulate non-invasively. Combining computational modeling and human sleep recordings, we show that thalamus-targeted temporal interference stimulation (TIS) with a 5Hz envelope increases spindle density via subthreshold resonance in thalamocortical relay neurons. Our results demonstrate a mechanistic framework for the rational design of interventions to selectively augment sleep spindles.

neuroscience↗

bioRxiv2026

Virtual prototyping of non-invasive spinal cord electrical stimulation targeting upper limb motor function

Transcutaneous spinal cord stimulation (tSCS) applied over the cervical or lumbar spinal cord facilitates motor function after paralysis. However, emerging electrophysiological evidence indicates mechanistic differences between cervical and lumbar tSCS and across different cervical tSCS paradigms. To clarify these discrepancies, we developed and validated a multi-scale, whole-body computational model of tSCS-induced volume conduction, axonal recruitment, and synaptic transmission. Across 24 cervical and four lumbar tSCS paradigms, simulations showed that somatosensory afferents consistently exhibit lower stimulation thresholds than motor efferents. In turn, region-specific synaptic transmission differences may explain electrophysiological discrepancies between cervical and lumbar tSCS. Across cervical tSCS paradigms, substantial volume conduction and axonal recruitment differences were observed that explain electrophysiological discrepancies. Specifically, clinically-prevalent paradigms, including those with anodes placed over the clavicles or iliac crests, engaged peripheral nerves in addition to spinal roots. This effect was amplified by multiphasic waveforms, which introduced recruitment sites near the anodes. By integrating simulations with electrophysiological recordings in 14 able-bodied individuals, we investigated previously unexplored cervical tSCS paradigms on their capacity to recruit somatosensory afferents relative to motor threshold.

neuroscience↗

bioRxiv2025

Shaping a Collaborative, Sustainable, Accessible, and Reproducible Future for Computational Modeling

The o2S2PARC platform is an open-source, extensible, and scalable cloud-based platform developed in the context of the U.S. National Institutes of Health SPARC program to support collaborative, sustainable, FAIR (findable, accessible, interoperable, reusable) and reproducible computational modeling and analysis. This publication presents the main features of o2S2PARC, its underlying approaches and philosophy, innovative aspects of the developed technologies, while also drawing attention to its rapid adoption. The paper showcases a variety of applications and use cases enabled by the platform. These include hybrid electromagnetic-electrophysiology simulations of neural interfaces, personalized brain and spinal cord stimulation planning, in silico device safety assessments, the training and application of AI systems (e.g., for model-predictive control and medical image segmentation), hybridized surrogate modeling and multi-objective optimization in high-dimensional parameter spaces, sensitive and unbiased validation of measurement devices, and interactive data analysis as paper supplements.

neuroscience↗

bioRxiv2025

iCSD can produce spurious results in dense electrode arrays

Estimation of the current source density (CSD) is a commonly-used method to interpret local field potential (LFP) signals by estimating the location of the neural sinks and sources of current that give rise to the LFP. We show analytically that, when the inter-electrode spacing is small relative to the width of the current distribution, commonly used methods to estimate the CSD produces spurious results, calculating true sources as sinks and vice versa. By simulating a biologically-detailed subvolume of the rat somatosensory cortex with over 200,000 biophysically-detailed neurons, we show that, for high-density recording electrodes, the estimated CSD diverges from expected results, necessitating awareness and careful interpretation of CSD results.

neuroscience↗

bioRxiv2025

SpIC3D imaging: Spinal In-situ Contrast 3D imaging

High-definition visualization techniques are critical for understanding the neuroanatomy of the spinal cord, an essential structure for sensorimotor and autonomic functions, in both healthy and pathological conditions. Magnetic resonance imaging (MRI) is a common method for visualizing neural structures in 3D. However, techniques for spinal cord MRI have historically achieved limited visualization of rootlets and nerves, especially at lower spinal levels, due to their highly complex and compact organization. Here we developed a spinal in-situ contrast 3D imaging (SpIC3D) method that allows visualization of spinal compartments in fixed animal and human specimens with ultra-high resolution at various spinal levels. Using SpIC3D, we achieved quantification of neuronal cell density in dorsal root ganglia, multi-segment identification of individual rootlets and roots, and volumetric reconstruction of multiple spinal structures for computational modeling. SpIC3D provides a basis for accelerated spinal pathology characterization and personalized spinal cord stimulation treatments.

neuroscience↗

bioRxiv2024

Computational modeling reveals biological mechanisms underlying the whisker-flick EEG

Whisker flick stimulation is a commonly used protocol to investigate somatosensory processing in rodents. Neural activity in the brain evoked by whisker flicks produces a characteristic EEG waveform recorded at the skull, known as a somatosensory evoked potential. In this paper, we use in silico modeling to identify the neural populations that serve as sources and targets of the synaptic currents contributing to this signal (presynaptic and postsynaptic populations, respectively). The initial positive deflection of the EEG waveform is driven largely by direct thalamic inputs to Layer 2/3 and Layer 5 pyramidal cells, though interestingly, L5-L5 inhibition plays a modulatory role, reducing the amplitude and width of the deflection. This suggests that increasing thalamocortical connectivity and decreasing L5-L5 inhibition may be responsible for some of the changes observed in the EEG waveform over the course of development. The negative deflection is driven by a more complex mix of sources, including both thalamic and recurrent cortical connectivity. We demonstrate that small changes to the local connectivity of the circuit, particularly to perisomatic inhibitory targeting, can have an important impact on the recorded EEG, without substantially affecting firing rates, suggesting that EEG may be useful in constraining in silico neural models.

neuroscience↗

bioRxiv2024

Simulation Insights on the Compound Action Potential in Multifascicular Nerves

ObjectiveDevelop an efficient method for simulating evoked compound action potential (eCAP) signals from complex nerves to help optimize and interpret eCAP recordings; validate it through comparison with measured vagus nerve eCAP recordings; elucidate the subtle interplay giving rise to specific eCAP signal shapes and magnitudes. ApproachWe developed an extended reciprocity theorem approach to model neuron signals in heterogeneous environments, and use it to study analytically the single fibre action potential. We then established a semi-analytic model that also uses hybrid electromagnetic-electrophysiological simulations to model eCAP signals from complex nerves populated with heterogeneous fiber populations of fibers. A cuff electrode was used to measure activity induced by vagus nerve stimulation in in vivo porcine experiments; these measurements were compared with signals produced by the model. Main ResultsThe semi-analytic model produces signals that approximate the shape and amplitude of in vivo measurements. Partially activated fascicles contribute substantially to the signal, as eCAP contributions from smoothly varying fiber calibers in fully activated ones partially cancel. As a result, eCAP magnitude does not depend monotonically on the stimulation current and recruitment level. Because the eCAP is sensitive to the degree of activation in individual fascicles, and to the location of the recording electrodes with respect to individual fascicles, the contributions of different fascicles to the recorded eCAP signals vary significantly with changes in the shape and placement of the stimulus and the recording electrodes. SignificanceOur method can be used to rapidly assess new stimulation and recording setups involving complex nerves and neurovascular bundles, e.g., to maximize signal information content, for closed-loop control in bioelectronic medicine applications, and potentially to non-destructively reconstruct structural and functional nerve topologies through inverse problem solving.

neuroscience↗

bioRxiv2024

BlueRecording: A Pipeline for the efficient calculation of extracellular recordings in large-scale neural circuit models

As the size and complexity of network simulations accessible to computational neuroscience grows, new avenues open for research into extracellularly recorded electric signals. Biophysically detailed simulations permit the identification of the biological origins of the different components of recorded signals, the evaluation of signal sensitivity to different anatomical, physiological, and geometric factors, and selection of recording parameters to maximize the signal information content. Simultaneously, virtual extracellular signals produced by these networks may become important metrics for neuro-simulation validation. To enable efficient calculation of extracellular signals from large neural network simulations, we have developed BlueRecording, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. In particular, we implement a general form of the reciprocity theorem, which is capable of handling non-dipolar current sources, such as may be found in long axons and recordings close to the current source, as well as complex tissue anatomy, dielectric heterogeneity, and electrode geometries. To our knowledge, this is the first application of this generalized (i.e., non-dipolar) reciprocity-based approach to simulate EEG recordings. We use these tools to calculate extracellular signals from an in silico model of the rat somatosensory cortex and hippocampus and to study signal contribution differences between regions and cell types.

neuroscience↗

bioRxiv2024

Safety of Non-invasive Brain Stimulation in Patients with Implants: A Computational Study

ObjectiveNon-invasive brain stimulation (NIBS) methodologies, such as transcranial electric (tES) and magnetic stimulation are increasingly employed for therapeutic, diagnostic, or research purposes. The concurrent presence of active or passive implants can pose safety risks, affect the NIBS delivery, or generate confounding signals. A systematic investigation is required to understand the interaction mechanisms, quantify exposure, assess safety, and establish guidance for NIBS applications. ApproachWe used measurements, simplified generic, and detailed anatomical modeling to: (i) systematically analyze exposure conditions with passive and active implants, considering local field enhancement, exposure dosimetry, tissue heating and neuromodulation, capacitive lead current injection, low-impedance pathways between electrode contacts, and insulation damage; (ii) identify safety metrics and efficient prediction strategies; (iii) quantify these metrics in relevant exposure cases and (iv) identify worst case conditions. Various aspects including implant design, positioning, scar tissue formation, anisotropy, and frequency were investigated. ResultsAt typical tES frequencies, local enhancement of dosimetric exposure quantities can reach up to one order of magnitude for DBS and SEEG implants (more for elongated passive implants), potentially resulting in unwanted neuromodulation that can confound results but is still 2-3 orders of magnitude lower than active DBS. Under worst-case conditions, capacitive current injection in the lead of active implants can produce local exposures of similar magnitude as the passive field enhancement, while capacitive pathways between contacts are negligible. Above 10 kHz, applied current magnitudes increase, necessitating consideration of tissue heating. Furthermore, capacitive effects become more prominent, leading to current injection that can reach DBS-like levels. Adverse effects from abandoned/damaged leads in direct electrode vicinity cannot be excluded. SignificanceSafety related concerns of tES application in the presence of implants are systematically identified and explored, resulting in specific and quantitative guidance and establishing a basis for safety standards. Furthermore, several methods for reducing risks are suggested.

bioengineering↗

bioRxiv2024

Improved Temporal and Spatial Focality of Non-invasive Deep-brain Stimulation using Multipolar Single-pulse Temporal Interference with Applications in Epilepsy

Temporal Interference (TI) is an emerging method to non-invasively stimulate deep brain structures. This innovative technique is increasingly recognized for its potential applications in the treatment of various neurological disorders, including epilepsy, depression, and Alzheimers disease. However, several drawbacks to the TI method exist that we aim to improve upon. To begin, the applied electric field in the TI target is not much higher than what non-invasive transcranial alternating current stimulation (TACS) provides in the cortex. Additionally, the TI stimulation onset is dependent on the envelope of the amplitude modulated (AM) signal, where for example 1 Hz and 100 Hz envelopes have significantly different rise times to reach maximum envelope amplitude - unlike square biphasic pulses. This limitation in turn prevents classic TI, from applying bursts of pulses. Finally, the electric field intensity of TI cannot be increased or decreased at the target without dramatically altering the spatial profile of the stimulation focus. In the work presented here, we efficiently address all three of these limitations. First, we performed two-photon calcium imaging to show that individual neurons selectively respond to the TI envelope frequency, providing evidence that TI modulates neural activity with temporal specificity. This marks a significant advancement, representing the first empirical demonstration of neuronal activation at the {Delta}f frequency within the context of TI and in an imaging modality. Subsequently, we compared the AM signals of TI with phase-shift keying (PSK) modulated signals to highlight the superior effectiveness of noninvasive pulses in contrast to the traditional TI method, particularly in inducing epileptic activity (after-discharges) in mice. We also added a multipolar configuration to create a significant increase in the electric field at the target without significantly altering the spatial profile and applied Fourier components to replicate classic biphasic bursts of square pulses - all transcranially, without the use of penetrating electrodes. These innovations aim to enhance the precision and efficacy of TI stimulation, to advance its application in neurological research and therapy. Key Points / HighlightsO_LINon-invasive temporal interference stimulation modulates the activity of individual neurons at the envelope frequency. C_LIO_LIA non-invasive multi-pulse TI stimulation paradigm improves both temporal and spatial focality in the deep target neural tissue when compared to traditional continuous wave (amplitude-modulated) TI stimulation. C_LIO_LIPulse TI paradigms can stimulate deep neural targets with reduced amplitude of the topical high-frequency stimulation, decreasing off-target stimulation when compared to continuous wave TI patterns. As a consequence, pulse TI stimulation reduces the risk of undesired side effects such as high-frequency conduction block in off-target tissues or cortical areas. C_LIO_LIBoth temporal and spatial focality of the TI stimulation pattern positively correlate with the efficacy of the stimulation to induce seizures in the mouse hippocampus. C_LI

neuroscience↗

bioRxiv2023

Effects of hippocampal noninvasive theta-burst stimulation on consolidation of associative memory in healthy older adults

Stimulation of deep brain areas can offer benefits against cognitive impairments associated with aging. So far, this was only possible via invasive methods accompanied by risks. Grossman et al. proposed a new noninvasive stimulation technique, transcranial temporal interference electric stimulation (tTIS), which can be steered to target and modulate activity of deep brain structures. Memory capacity depends on subcortical structures such as the hippocampus, hence, modulation of hippocampal activity could benefit declining cognitive functions. The current study investigates whether theta-burst patterned tTIS targeting the hippocampus influences performance of associative memory in older adults. We found that theta-burst patterned tTIS, but not the control stimulation, improved recollection time in a follow-up 24h after the stimulation, suggesting that theta-burst patterned tTIS can influence the efficiency of longer-term encoding. This outcome indicates that tTIS may provide a new noninvasive deep brain stimulation method to modulate senescent memory processes.

neuroscience↗

bioRxiv2023

Controlling focality and intensity of non-invasive deep brain stimulation using multipolar temporal interference in non-human primates and rodents

Temporal interference (TI) is a method of non-invasive brain stimulation using transcutaneous electrodes that allows the targeting and modulation of deeper brain structures, not normally associated with non-invasive simulation, while avoiding unwanted stimulation of shallower cortical structures. The properties of TI have been previously demonstrated, however, the problem of decoupling stimulation focality from stimulation intensity has not been addressed. In this paper, we provide a possible novel solution, multipolar TI (mTI), which allows increased independent control over both the size of the stimulated region and the stimulation intensity. The mTI method uses multiple carrier frequencies to create multiple overlapping amplitude-modulated envelopes, rather than using one envelope as in standard TI. The study presents an explanation of the concept of mTI along with experimental data gathered from Rhesus macaques and mice. We improved the focality at depth in anesthetized mice and monkeys, and using the new focality in awake monkeys, evoked targeted activity at depth in the superior colliculus. The mTI method could be an interesting and potentially useful new tool alongside other forms of non-invasive brain stimulation. Teaser: Multipolar Temporal Interference Stimulation can produce a more focal brain stimulation at depth compared to Temporal Interference.

neuroscience↗

bioRxiv2023

Obstructive Sleep Apnea Improves with Non-invasive Hypoglossal Nerve Stimulation using Temporal Interference

BackgroundPeripheral nerve stimulation is used in both clinical and fundamental research for therapy and exploration. At present, non-invasive peripheral nerve stimulation still lacks the penetration depth to reach deep nerve targets and the stimulation focality to offer selectivity. It is therefore rarely employed as the primary selected nerve stimulation method. We have previously demonstrated that a new stimulation technique, temporal interference stimulation, can overcome depth and focality issues. MethodsHere, we implement a novel form of temporal interference, bilateral temporal interference stimulation, for bilateral hypoglossal nerve stimulation in rodents and humans. Pairs of electrodes are placed alongside both hypoglossal nerves to stimulate them synchronously and thus decrease the stimulation amplitude required to activate hypoglossal-nerve controlled tongue movement. ResultsComparing bilateral temporal interference stimulation with unilateral temporal interference stimulation, we show that it can elicit the same behavioral and electrophysiological responses at a reduced stimulation amplitude. Traditional transcutaneous stimulation evokes no response with equivalent amplitudes of stimulation. ConclusionsDuring first in-man studies, temporal interference stimulation was found to be well-tolerated, and to clinically reduce apnea-hypopnea events in a subgroup of female patients with obstructive sleep apnea. These results suggest a high clinical potential for the use of temporal interference in the treatment of obstructive sleep apnea and other diseases as a safe, effective, and patient-friendly approach. Trial registrationThe protocol was conducted with the agreement of the International Conference on Harmonisation Good Clinical Practice (ICH GCP), applicable United States Code of Federal Regulations (CFR) and followed the approved BRANY IRB File # 22-02-636-1279.

neuroscience↗

bioRxiv2022

Safety Recommendations for Temporal Interference Stimulation in the Brain

Temporal interference stimulation (TIS) is a new form of transcranial electrical stimulation (tES) that has been proposed as a method for targeted, non-invasive stimulation of deep brain structures. While TIS holds promise for a variety of clinical and non-clinical applications, little data is yet available regarding its effects in humans. To inform the design and approval of experiments involving TIS, researchers require quantitative guidance regarding exposure limits and other safety concerns. To this end, we sought to delineate a safe range of exposure parameters (voltages and currents applied via external scalp electrodes) for TIS in humans through comparisons with well-established but related brain stimulation modalities. Specifically, we surveyed the literature for adverse events (AEs) associated with transcranial alternating/direct current stimulation (tACS/tDCS), deep brain stimulation (DBS), and TIS to establish known boundaries for safe operating conditions. Drawing on the biophysical mechanisms associated with the identified AEs, we determined appropriate exposure metrics for each stimulation modality. Using these metrics, we conducted an in silico comparison of various exposure scenarios for tACS, DBS, and TIS using multiphysics simulations in an anatomically detailed head model with realistic current strengths. By matching stimulation scenarios in terms of biophysical impact, we inferred the frequency-dependent TIS stimulation parameters that resulted in exposure magnitudes known to be safe for tACS and DBS. Based on the results of our simulations and existing knowledge regarding tES and DBS safety, we propose frequency-dependent thresholds below which TIS voltages and currents are unlikely to pose a risk to humans. Safety-related data from ongoing and future human studies are required to verify and refine the thresholds proposed here.

neuroscience↗

bioRxiv2022

Non-invasive stimulation of the human striatum disrupts reinforcement learning of motor skills

Reinforcement feedback can improve motor learning, but the underlying brain mechanisms remain underexplored. Especially, the causal contribution of specific patterns of oscillatory activity within the human striatum is unknown. To address this question, we exploited an innovative, non-invasive deep brain stimulation technique called transcranial Temporal Interference Stimulation (tTIS) during reinforcement motor learning with concurrent neuroimaging, in a randomised, sham-controlled, double-blind study. Striatal tTIS applied at 80Hz, but not at 20Hz, abolished the benefits of reinforcement on motor learning. This effect was related to a selective modulation of neural activity within the striatum. Moreover, 80Hz, but not 20Hz tTIS increased the neuromodulatory influence of the striatum on frontal areas involved in reinforcement motor learning. These results show for the first time that tTIS can non-invasively and selectively modulate a striatal mechanism involved in reinforcement learning, opening new horizons for the study of causal relationships between deep brain structures and human behaviour.

neuroscience↗