Biology subjects

Khadka, N.

Publications and source records attributed to Khadka, N..

13 recordsLinked to original sources

bioRxiv2026

Model-based assessment of race, sex, and electrode montage in ECT

Objective: This computational modeling study quantified the influence of sex and race-related cranial anatomy on predicted brain-wide current flow during electroconvulsive therapy (ECT) across conventional (bifrontal (BF), bitemporal/bilateral (BL), right unilateral (RUL)) and experimental (focal electrically administered seizure therapy (FEAST) and frontomedial (FM)) electrode montages. The objective was to determine whether race-associated variability meaningfully contributes to differences in ECT stimulation metrics across montages. Methods: Finite element head models of Chinese, Black, and Caucasian subjects were developed using high-resolution magnetic resonance imaging and analyzed using the Realistic vOlumetric- Approach-based Stimulator for Transcranial electric stimulation (ROAST) pipeline (N = 150 total; n = 50 per cohort, comprising 25 M and 25 F, age range: 20-30 years). Five ECT montages were simulated under a constant-current condition (900mA). Stimulation strength (Ebrain/Eth) was quantified as 90th percentile of brain-wide E-field magnitude (Ebrain) relative to neuronal activation threshold (Eth = 0.25 V/cm) quantified stimulation strength. Overall focality was evaluated as a percentage of brain volume stimulated above the neural activation threshold (Ebrain [≥] Eth), while laterality was quantified as the median right-to-left hemispheric E-field magnitude ratio. The effects of race, sex, and montage on stimulation strength, focality, and hemispheric laterality were statistically analyzed. Results: Substantial race- and sex-related differences observed in cranial anatomy resulted in systematic variation in predicted ECT-induced E-field intensity. Brain-wide E-field magnitude varied by both race and montage, with the largest fields generally observed in Caucasian head models and during BL stimulation. Montage exerted the strongest effect on stimulation strength (Ebrain/Eth) with BL and FEAST producing the highest stimulation strengths, followed by RUL and FM, while BF produced the lowest. Caucasian subjects generally predicted higher stimulation strengths than Black and Chinese subjects, whereas females predicted modestly higher stimulation strengths than males. Laterality was primarily determined by montage, with FEAST producing the greatest hemispheric asymmetry, followed by RUL. Chinese subjects demonstrated higher laterality ratios than both Black and Caucasian subjects. BL, RUL, and FEAST stimulated substantially larger brain volumes above neural activation threshold (less focal stimulation) than BF. Lower focality was observed in Caucasian subjects relative to Black and Chinese subjects, and in females relative to males. Conclusions: Electrode montage was the primary determinant of predicted ECT stimulation strength, focality, and laterality. Race-related anatomical differences and, to a lesser extent, sex-related differences systematically altered stimulation patterns, supporting consideration of individualized anatomy in ECT dosing and treatment optimization.

neuroscience↗

bioRxiv2026

Neuronavigation-free and MRI-free Localization of Deep Brain Targets

Emerging non-invasive brain stimulation modalities, including transcranial focused ultrasound and transcranial interferential stimulation, offer the promise of safely and non-invasively modulating deep brain structures. Accurate targeting of these regions typically involves subject-specific MRI, limiting widespread deployment. Here, we introduce an MRI-free, neuronavigation-free method for localizing deep brain targets using only three simple scalp measurements. These measures define an affine transformation that maps the MNI152 standard head model to an individuals head geometry. We evaluated our approach on 50 healthy adults, comparing our model{square}predicted coordinates against ground-truth coordinates obtained via MRI-based nonlinear normalization. Across ten deep brain targets, our method achieved a mean localization error of 3.82 mm demonstrating a more accessible and cost-efficient alternative than MRI- or neuronavigation-based approaches.

neuroscience↗

bioRxiv2026

Morphological bias of the MNI152 brain

The MNI152 template is widely treated as a representative average brain in neuroimaging, computational modeling, and neuromodulation research, yet its fidelity to true population morphology has not been systematically evaluated. In this study, we compared the MNI152 template to 430 individual MRI scans from a publicly available dataset spanning Asian, Black, and White participants. We additionally generated an alternative template using ANTsPy to assess whether a modern diffeomorphic approach yields a more anatomically representative average. We conducted affine registrations and deformation-based morphometry to detect and quantify gross morphological differences as well as local voxel-level deformations. Across all racial groups, the MNI152 template required consistent global contraction, and its Jacobian fields revealed spatially heterogeneous deformations, indicating systematic mismatches in both size and shape. In contrast, the ANTsPy template showed mean scaling and deformation values near 1.0, reflecting closer correspondence to real human anatomy. These findings demonstrate that the MNI152 template does not accurately represent the morphology of the studied population and that linear registration alone cannot correct its inherent biases. Reliance on MNI152 may therefore introduce unintended distortions in applications requiring anatomically realistic head models. More robust, unbiased template-generation pipelines, and potentially demographic-specific templates, may be necessary for improved accuracy.

neuroscience↗

bioRxiv2026

Assessing suitability of ultra-low-field MRI for TES electric field models

ObjectiveRecent ultra-low-field (ULF) MRI systems provide an option for more accessible and cost-effective imaging to widely used higher field (HF, usually 3T) systems. However, it remains uncertain whether ULF scans can be used for reliable TES current-flow modeling as opposed to using 3T MRI. MethodsWe used raw anatomical scans of 23 healthy adults from 64 mT and 3T systems. We enhanced the 64 mT scans using SynthSR. Using our established current-flow modeling pipeline we determined the electric fields (EF) for the ULF and 3T scans induced by the classic M1-SO electrode montage. We quantified the differences in EF at three regions of interest (ROI): left motor cortex (LMC), anterior commissure (AC), and left hippocampus (LHC). ResultsAt the cortical ROI (LMC), the individual mean EF based on a 3T scan was found to be 27% higher than the corresponding ULF scan. The average mean relative error was found to be 40%. At AC, the individual mean EF based on a 3T scan continued to be elevated by about 13% in magnitude with respect to the corresponding ULF scan with a mean error range of 31-34%. At LHC, comparison of the induced individual mean EF magnitudes indicated no clear bias between 3T-based and ULF-based models. The average mean relative error at this level dropped to [~]20%. DiscussionThe substantial decrease in cortical EF when using an ULF scan is predominantly explained by the overestimation of cerebrospinal fluid (CSF) noted by prior morphological comparison studies. Scaling up EF magnitude to match predicted cortical values to a 3T scan may be considered depending on the modeling question being addressed. While preliminary, our results suggest an "equalizing" effect between ULF and 3T predictions with increasing depth within the brain.

bioengineering↗

bioRxiv2025

High-Capacity transcranial Direct Current Stimulation (HC-tDCS)

BackgroundEnhancing tDCS technology can support the delivery of higher current intensities, enabling broader dose-response studies in human trials. MethodsHigh-Capacity tDCS (HC-tDCS) integrates novel electrodes and adaptive current/voltage controlled electronics. Multi-layer HC electrodes include polarity-specific redox layers and designed hydrogel interfaces, shaped for a bifrontotemporal montage. The stimulator design includes adaptive ramps with hybrid voltage-current control and low (7.5 V) compliance voltage. Scanning electron microscopy (SEM) and electrical impedance spectroscopy (EIS) were used to characterize electrode properties. Tolerability of HD-tDCS was tested for target currents 1-6 mA (in 1 mA increments) for 30 min on 5 healthy subjects, and compared with conventional tDCS using 2 mA F3-F4 sponge-electrodes. MRI-derived computational models predicted cortical electric fields. Tolerability was assessed according to the 100 mm visual analogue scale for pain (VASP-100), skin erythema assessment, thermal imaging, and adverse event questionnaires. ResultsThe electrode design including high-roughness polarity-specific capacity, electrochemically supports high-charge direct current stimulation. In all subjects, HC-tDCS was well tolerated at all tested doses (1-6 mA) with minor transient adverse events and average VASP-100 less than 15. VASP-100 during sponge-electrode tDCS at 2 mA was comparable to 5 and 6 mA HC-tDCS. HC-tDCS operates at significantly lower voltage than sponge-tDCS, impacting tolerability and efficiency. Modeling predicts peak frontal electric fields of 0.65-1.08 V/m for 2 mA HC-tDCS and 1.95-3.25 V/m for 6 mA HC-tDCS, compared to 0.49-0.95 V/m for 2 mA sponge-tDCS. ConclusionsHC-tDCS allows increased cortical stimulation; at 6 mA achieving double the 1 V/m electric field threshold in all subjects. Enabled by pre-stimulation procedures, specialized electrodes, and adaptive low-voltage stimulators, HC-tDCS is well tolerated at intensities up to at least 6 mA.

bioengineering↗

bioRxiv2024

Frequency-dependent and capacitive tissue electrical properties in spinal cord stimulation models

BackgroundModels of spinal cord stimulation (SCS) simulate the electric fields (E-fields) generated in targeted tissues, which in turn can predict physiological and then behavioral outcomes. Notwithstanding increasing sophistication and use in optimizing therapy, SCS models typically calculate E-fields using the quasi-static approximation (QSA). QSA, as implemented in neuromodulation models, neglects the frequency dispersion of tissue conductivity, as well as propagation, capacitive, and inductive effects on the E-field. The reliability of QSA specifically for SCS has not been considered in detail, especially for higher-frequency SCS. MethodsWe implemented a frequency-dependent finite element method (FEM) and solved a high- resolution RADO-SCS model with voltage-controlled (VC) and current-controlled (CC) stimulation to assess the impact of frequency-dependent conductivity (dispersion) and permittivity of spinal tissues on E-fields generated at three different spinal column locations (epidural space, spinal cord, and root) for frequencies spanning from 1 Hz to 10 MHz. Results were compared with predictions of QSA method, with varied conductivity values of purely resistive tissues. We further assessed the impact of frequency-dependent and capacitive tissue properties on spinal heating and distortion of the E-field waveform. ResultsTissue-specific electric properties around the energized leads and mode of stimulation-control impacted the magnitude of E-fields. In the spinal cord, the VC-SCS E-field generated with the frequency-dependent and capacitive properties was comparable to the QSA with 2X epidural fat conductivity, whereas the CC-SCS generated E-field was minimally impacted by frequency- dependent and capacitive properties up to 10 kHz. Spinal cord heating predicted by frequency- dependent and capacitive tissue properties was comparable to the QSA conditions with VC-SCS, whereas with CC-SCS, there was no impact of the frequency-dependent and capacitive tissue properties in spinal cord heating. E-field waveform distortion in the spinal cord, with CC-SCS at 1 kHz-specific electrical properties, was significant when fat capacitance (permittivity) was increased by 10X, whereas with VC-SCS, there was no effect of tissue capacitance. ConclusionRegardless of the mode of SCS, QSA was still valid in predicting SCS-induced E-field and heating at the spinal tissues- across and {beta} dispersion region of spinal tissues dielectric spectrum for VC-SCS and up to 10 kHz for CC-SCS.

bioengineering↗

bioRxiv2023

Transcranial electric stimulation modulates firing rate at clinically relevant intensities

Notwithstanding advances with low-intensity transcranial electrical stimulation (TES), there remain questions about the efficacy of clinically realistic electric fields on neuronal function. We used Neuropixels 2.0 probe with 384 channels in an in-vivo rat model of TES to detect effects of weak fields on neuronal firing rate. High-density field mapping and computational models verified field intensity (1 V/m in hippocampus per 50 {micro}A of applied skull currents). We demonstrate that electric fields below 0.5 V/m acutely modulate firing rate in 5% of neurons recorded in the hippocampus. At these intensities, average firing rate effects increased monotonically with electric field intensity at a rate of 7 % per V/m. For the majority of excitatory neurons, firing increased for cathodal stimulation and diminished for anodal stimulation. While more diverse, the response of inhibitory neurons followed a similar pattern on average, likely as a result of excitatory drive. Our results indicate that responses to TES at clinically relevant intensities are driven by a fraction of high-responder excitatory neurons, with polarity-specific effects. We conclude that transcranial electric stimulation is an effective neuromodulator at clinically realistic intensities.

neuroscience↗

bioRxiv2022

Computational modeling of posteroanterior lumbar traction by an automated massage bed: predicting intervertebral disc stresses and deformation

Spinal traction is a physical intervention that provides constant or intermittent stretching axial force to the lumbar vertebrae to gradually distract spinal tissues into better alignment, reduce intervertebral disc (IVD) pressure, and manage lower back pain (LBP). However, such axial traction may change the normal lordotic curvature, and result in unwanted side effects and/or inefficient reduction of the IVD pressure. An alternative to axial traction has been recently tested, consisting of posteroanterior (PA) traction in supine posture, which was recently shown effective to increase the intervertebral space and lordotic angle using MRI. PA traction aims to maintain the lumbar lordosis curvature throughout the spinal traction therapy while reducing the intradiscal pressure. In this study, we developed finite element simulations of mechanical therapy produced by a commercial thermo-mechanical massage bed capable of spinal PA traction. The stress relief produced on the lumbar discs by the posteroanterior traction system was investigated on human subject models with different BMI (normal, overweight, moderate obese and extreme obese BMI cases). We predict typical traction levels lead to significant distraction stresses in the lumbar discs, thus producing a stress relief by reducing the compression stresses normally experienced by these tissues. Also, the stress relief experienced by the lumbar discs was effective in all BMI models, and it was found maximal in the normal BMI model. These results are consistent with prior observations of therapeutic benefits derived from spinal AP traction.

bioengineering↗

bioRxiv2022

Computational modeling of deep tissue heating by an automatic thermal massage bed: predicting the effects on circulation

Automatic thermal and mechanical massage beds support selfmanaged treatment, including reduction of pain and stress, enhanced circulation, and improved mobility. As the devices become more sophisticated (increasing the degrees of freedom), it is essential to identify the settings that best target the desired tissue. To that end, we developed an MRI-derived model of the lower back and simulated the physiological effects of a commercial thermal-mechanical massage bed. Here we specifically estimated the tissue temperature and increased circulation under steady-state conditions for typical thermal actuator settings (i.e., 45-65{degrees}C). Energy transfer across nine tissues was simulated with finite element modeling (FEM) and the resulting heating was coupled to blood flow with an empirically-guided model of temperature-dependent circulation. Our findings indicate that thermal massage increases tissue temperature by 3-8{degrees}C and 1-3{degrees}C at depths of 2 and 3 cm, respectively. Importantly, due to the rapid (non-linear) increase of circulation with local temperature, this is expected to increase blood flow four-fold (4x) at depths occupied by deep tissue and muscle. These predictions are consistent with prior clinical observations of therapeutic benefits derived from spinal thermal massage.

bioengineering↗

bioRxiv2020

Adaptive current-flow models of ECT: Explaining individual static impedance, dynamic impedance, and brain current delivery

BackgroundImprovements in electroconvulsive therapy (ECT) outcomes have followed refinement in device electrical output and electrode montage. The physical properties of the ECT stimulus, together with those of the patients head, determine the impedances measured by the device and govern current delivery to the brain and ECT outcomes. ObjectiveHowever, the precise relations among physical properties of the stimulus, patient head anatomy, and patient-specific impedance to the passage of current are long-standing questions in ECT research and practice. MethodsWe developed anatomical MRI-derived models of transcranial electrical stimulation (tES) that included changes in tissue conductivity due to local electrical current flow. These "adaptive" models simulate ECT both during therapeutic stimulation using high (~1 A) current and when dynamic impedance is measured, as well as prior to stimulation when low (~1 mA) current is used to measure static impedance. We modeled two scalp layers: a superficial scalp layer with adaptive conductivity that increases with electric field up to a subject specific maximum [Formula], and a deep scalp layer with a subject-specific fixed conductivity ({sigma}DS). ResultsWe demonstrate that variation in these scalp parameters explain clinical data on subject-specific static impedance and dynamic impedance, their imperfect correlation across subjects, their relationships to seizure threshold, and the role of head anatomy. Adaptive tES models demonstrate that current flow changes local tissue conductivity which in turn shapes current delivery to the brain in a manner not accounted for in fixed tissue conductivity models. ConclusionsOur predictions that variation in individual skin properties, rather than other aspects of anatomy, largely govern the relationship between static impedance, dynamic impedance, and current delivery to the brain, are themselves subject to assumptions about tissue properties. Broadly, our novel pipeline for tES models is important in ongoing efforts to optimize devices, personalize interventions, and explain clinical findings.

bioengineering↗

bioRxiv2020

Neurovascular-modulation

Neurovascular-modulation is based on two principles that derive directly from brain vascular ultra-structure, namely an exceptionally dense capillary bed (BBB length density: 972 mm/mm3) and a blood-brain-barrier (BBB) resistivity ({rho} ~ 1x105 {Omega}.m) much higher than brain parenchyma/interstitial space ({rho} ~ 4 {Omega}.m) or blood ({rho} ~ 1 {Omega}.m). Principle 1: Electrical current crosses between the brain parenchyma (interstitial space) and vasculature, producing BBB electric fields (EBBB) that are > 400x of the average parenchyma electric field ([E]BRAIN), which in turn modulates transport across the BBB. Specifically, for a BBB space constant ({lambda}BBB) and wall thickness (dth-BBB): analytical solution for maximum BBB electric field (EABBB) is given as: ([E]BRAIN x {lambda}BBB) / dth-BBB. Direct vascular stimulation suggests novel therapeutic strategies such as boosting metabolic capacity or interstitial fluid clearance. Boosting metabolic capacity impacts all forms of neuromodulation, including those applying intensive stimulation or driving neuroplasticity. Boosting interstitial fluid clearance has broad implications as a treatment for neurodegenerative disease including Alzheimers disease. Principle 2: Electrical current in the brain parenchyma is distorted around brain vasculature, amplifying neuronal polarization. Specifically, vascular ultra-structure produces ~50% modulation of the average parenchyma electric field ([E]BRAIN) over the ~40 m inter-capillary distance. The divergence of EBRAIN (activating function) is thus ~100 kV/m2 per unit average parenchyma electric field ([E]BRAIN). This impacts all forms of neuromodulation, including Deep Brain Stimulation (DBS), Spinal Cord Stimulation (SCS), Transcranial Magnetic Stimulation (TMS), Electroconvulsive Therapy (ECT), and transcranial electrical stimulation (tES) techniques such a transcranial Direct Current Stimulation (tDCS). Specifically, whereas spatial profile of EBRAIN along neurons is traditionally assumed to depend on macroscopic anatomy, it instead depends on local vascular ultra-structure.

neuroscience↗

bioRxiv2019

Realistic Anatomically Detailed Open-Source Spinal Cord Stimulation (RADO-SCS) Model

ObjectiveComputational current flow models of spinal cord stimulation (SCS) are widely used in device development, clinical trial design, and patient programming. Proprietary models of varied sophistication have been developed. An open-source model with state-of-the-art precision would serve as a standard for SCS simulation. ApproachWe developed a sophisticated SCS modeling platform, named Realistic Anatomically Detailed Open-Source Spinal Cord Stimulation (RADO-SCS) model. This platform consists of realistic and detailed spinal cord and ancillary tissues anatomy derived based on prior imaging and cadaveric studies. Represented tissues within the T9-T11 spine levels include vertebrae, intravertebral discs, epidural space, dura, CSF, white-matter, gray-matter, dorsal and ventral roots and rootlets, dorsal root ganglion, sympathetic chain, thoracic aorta, epidural space vasculature, white-matter vasculature, and thorax. As an exemplary, a bipolar SCS montage was simulated to illustrate the model workflow from the electric field calculated from a finite element model (FEM) to activation thresholds predicted for individual axons populating the spinal cord. Main ResultsCompared to prior models, RADO-SCS meets or exceeds detail for every tissue compartment. The resulting electric fields in white and gray-matter, and axon model activation thresholds are broadly consistent with prior stimulations. SignificanceThe RADO-SCS can be used to simulate any SCS approach with both unprecedented resolution (precision) and transparency (reproducibility). Freely available online, the RADO-SCS will be updated continuously with version control.

neuroscience↗

bioRxiv2019

Computational Finite Element Method (FEM) forward modeling workflow for transcranial Direct Current Stimulation (tDCS) current flow on MRI-derived head: Simpleware and COMSOL Multiphysics tutorial

Transcranial Direct Current Stimulation (tDCS) dose designs are often based on computational Finite Element Method (FEM) forward modeling studies. These FEM models educate researchers about the resulting current flow (intensity and pattern) and so the resulting neurophysiological and behavioral changes based on tDCS dose (mA), resistivity of head tissues (e.g. skin, skull, CSF, brain), and head anatomy. Moreover, model support optimization of montage to target specific brain regions. Computational models are thus an ancillary tool used to inform the design, set-up and programming of tDCS devices, and investigate the role of parameters such as electrode assembly, current directionality, and polarity of tDCS in optimizing therapeutic interventions. Computational FEM modeling pipeline of tDCS initiates with segmentation of an exemplary magnetic resonance imaging (MRI) scan of a template head into multiple tissue compartments to develop a higher resolution (< 1 mm) MRI derived FEM model using Simpleware ScanIP. Next, electrode assembly (anode and cathode of variant dimension) is positioned over the brain target and meshed at different mesh densities. Finally, a volumetric mesh of the head with electrodes is imported in COMSOL and a quasistatic approximation (stead-state solution method) is implemented with boundary conditions such as inward normal current density (anode), ground (cathode), and electrically insulating remaining boundaries. A successfully solved FEM model is used to visualize the model prediction via different plots (streamlines, volume plot, arrow plot).

neuroscience↗