Biology subjects

Somogyvari, Z.

Publications and source records attributed to Somogyvari, Z..

6 recordsLinked to original sources

bioRxiv2026

Low-intensity ultrasound drives offline neuromodulation through passive membrane mechanisms in synaptically isolated hippocampal neurons

Low-intensity ultrasound alters neuronal excitability long after exposure ends, but the basis of this offline effect is unclear and most proposed mechanisms require synaptic receptors. We recorded from cultured mouse hippocampal neurons in whole-cell current clamp, before and 20 min after 1 min of 850 kHz continuous-wave ultrasound at 0.5 W/cm2 or sham, with synaptic transmission blocked throughout, each neuron re-patched. Sonicated neurons remained intact and firing, yet depolarized, with smaller action potentials and more noise. A passive-membrane fit showed reduced capacitance and a depolarized leak reversal potential in every sonicated cell, with a shortened time constant and no detectable change in input conductance, while sham cells showed no significant change. Changes in the time constant and reversal potential, both independent of membrane area, indicate a modification of the membrane itself rather than a loss of area. Brief ultrasound therefore leaves a lasting, receptor-independent imprint on passive membrane properties.

neuroscience↗

bioRxiv2026

Phase-dependent closed-loop intersectional short-pulse stimulation reduces seizure duration: From computational modeling to clinical application

Drug-resistant epilepsy affects one-third of patients with persistent seizures despite optimal therapy. Intersectional short-pulse (ISP) stimulation is a novel transcranial electrical stimulation technique designed to deliver temporally precise, spatially targeted modulation of pathological brain activity. Here, we combined computational modeling with measurements in a rat epilepsy model and in patients with epilepsy to map the relationship between stimulation phase and seizure attenuation. In silico simulations of epileptiform networks showed that ISP stimulation significantly shortened seizure duration, with efficacy strongly depending on the phase of delivery. Phase-targeted stimulation during the rising phase and around the peaks (~45-90{degrees}) of the seizure oscillations led to the greatest reduction in seizure length. In rodents, ISP decreased seizure duration by 42.4% and shortened generalized seizure segments by 58.3%. In humans, stimulation reduced seizure length by 60.9% compared to control seizures. Phase dependence was evident across models and species, with a prominent efficacy window in the rising-to-peak portion of the ictal oscillation and model-specific secondary windows. These findings show that phase-targeted ISP can substantially shorten seizures and support phase-resolved stimulation as a precision-neuromodulation approach for epilepsy.

neuroscience↗

bioRxiv2026

From Scalp to Source: Precise Phase Retrieval of Intracerebral Epileptic Sources Based on Surface EEG

Accurate phase tracking of deep-brain activity is critical for effective closed-loop and phase-locked neuromodulation therapies. However, direct access to deep neural phase through intracranial recordings remains clinically restrictive due to the invasiveness. Here we validate and clinically benchmark the Gabor-Nelson (GN) dipole estimation method for reconstructing deep-brain oscillatory phase from non-invasive scalp EEG. GN is a geometry-based, imaging-independent approach that offers computationally efficient dipole reconstruction and has rarely been applied to source-level phase estimation in human neuroscience. We compared GN with an established MRI-informed Inverse Solution (IS) method using a three-stage reconstruction pipeline consisting of dipole modeling, dimensionality reduction, and frequency-dependent phase-delay correction. Validation is performed using (i) cadaveric recordings, where known ground-truth seizure waveforms were replayed through implanted deep electrodes, and (ii) simultaneous scalp EEG and SEEG recordings in human patients, where pseudo-ground truth was approximated via the intracranial contacts. GN achieved phase accuracy and signal fidelity comparable to IS across both datasets despite requiring no anatomical imaging. In cadaver recordings, phase-corrected reconstruction correlations exceeded r > 0.91 and {Delta}{Phi} < 9{degrees} in mean phase error. In patient SEEG data, GN reached up to r {approx} 0.80 with phase offsets suitable for neuromodulatory timing. GN offers a viable, low-barrier, imaging-independent alternative to traditional inverse modeling for non-invasive seizure phase tracking. This framework opens pathways for scalable, phase-locked and closed-loop stimulation therapies in epilepsy and potentially other network-based brain disorders.

neuroscience↗

bioRxiv2025

Optimal inter-electrode distances for maximizing single unit yield per electrode in neural recordings

State-of-the-art high-density multielectrode arrays enable the recording of simultaneous spiking activity from hundreds of neurons. Although significant efforts have been dedicated to enhancing neural recording devices and developing more efficient sorting algorithms, there has been relatively less focus on the allocation of microelectrodes--a factor that undeniably affects spike sorting effectiveness and ultimately the total number of detected neurons. Here, we systematically examined the relationship between optimal electrode spacing and spike sorting efficiency by creating virtual sparser layouts from high-density recordings through spatial downsampling. We assessed spike sorting performance by comparing the quantity of well-isolated single units per electrode in sparse configurations across various brain regions (neocortex and thalamus) and species (rat, mouse, and human). Enabling the theoretical estimation of optimal electrode arrangements, we complement experimental results with a geometrical modeling framework. Contrary to the general assumption that higher electrode density inherently leads to more efficient sorting, both our theoretical and experimental results reveal a clear optimum for electrode spacing specific to species and regions. We demonstrate that carefully choosing optimal electrode distances could yield a total of 1.7 to 3 times increase in spike sorting efficiency. These findings emphasize the necessity of species- and region-specific microelectrode design optimization.

neuroscience↗

bioRxiv2025

Non-vectorial Integration of Intersectional Short-Pulse Stimulation Enables Enhanced Deep Brain Modulation and Effective Seizure Control

Transcranial electrical stimulation (TES) holds promise to treat neurological disorders, but its efficacy is limited by poor spatial focality and depth of penetration. Here, we examined the potential utility of Intersectional Short-Pulse (ISP) stimulation of deeper brain penetration. Using computational modeling and in vivo patch-clamp recordings in rats, we demonstrate that neurons integrate ISP-induced electric fields in a non-vectorial manner. This mechanism allows ISP to overcome some limits of conventional TES, achieving spatially limited stimulation across cortical and subcortical structures. In a rat model of temporal lobe epilepsy, closed-loop ISP stimulation significantly outperformed conventional TES in reducing seizure duration and severity. ISP reduced hippocampal seizure duration by 49% and 41% compared to sham stimulation and conventional TES and significantly reduced motor seizure severity. Our findings demonstrate that ISP stimulation can rapidly terminate hippocampal seizures, offering a potential new approach for non-invasive neuromodulation with applications across diverse neurologic and psychiatric disorders.

neuroscience↗

bioRxiv2017

Revealing The Distribution Of Transmembrane Currents Along The Dendritic Tree Of A Neuron With Known Morphology From Extracellular Recordings

Revealing the membrane current source distribution of neurons is a key step on the way to understanding neural computations, however, the experimental and theoretical tools to achieve sufficient spatiotemporal resolution for the estimation remain to be established. Here we address this problem using extracellularly recorded potentials with arbitrarily distributed electrodes in a neuron of known morphology. We use simulations of models with varying complexity to validate the proposed method and to give recommendations for experimental applications. The method is applied to in vitro data from rat hippocampus.

neuroscience↗