Biology subjects

Nejedly, P.

Publications and source records attributed to Nejedly, P..

3 recordsLinked to original sources

bioRxiv2026

In silico framework for benchmarking optogenetic hearing restoration

Cochlear implants (CI) partially restore hearing in profoundly hearing impaired or deaf people by electrically stimulating the auditory nerve. A bottleneck of electrical CIs is the broad spread of electrical current from each electrode that limits the transfer of spectral information, which might be overcome by future spatially confined optogenetic stimulation. Here we established an in silico framework, FraSCO, to model sound encoding in the human cochlea by an optogenetic CI (oCI) for testing the potential of optogenetic hearing restoration. The biophysical modeling framework combined an optical raytracing model implementing a human cochlea implanted with a waveguide-based oCI with a single compartment model of optogenetically modified spiral ganglion neurons (SGNs). The input was an optogenetic sound coding strategy and the quality of the neural representation was evaluated based on comparison of neurograms evoked by optogenetic and electrical stimulation to the spectrogram of the sound applied. The model aimed for technologically feasible properties of the oCIs with 64 stimulation channels. The biophysical modeling framework successfully captured essential physiological features of optogenetic SGN stimulation with a minimal set of ion channel types expressed in the SGN soma. Working with a sample of 1000 SGNs distributed along the tonotopic axis to represent sound encoding, we found that improved spectral selectivity more than compensates for lower temporal fidelity of current implementations of optogenetic stimulation. The established computational framework enables in silico investigation and benchmarking of sound encoding in the cochlea by future oCI and state-of-the-art eCI. The results indicate that optogenetic sound encoding has potential to improve speech understanding in noisy environments for CI users.

neuroscience↗

bioRxiv2021

Independent dynamics of slow, intermediate, and fast intracranial EEG spectral activities during human memory formation

A wide spectrum of brain rhythms are engaged throughout the human cortex in cognitive functions. How the rhythms of various low and high frequencies are spatiotemporally coordinated across the human brain during memory processing is inconclusive. They can either be coordinated together across a wide range of the frequency spectrum or induced in specific bands. We used a large dataset of human intracranial electroencephalography (iEEG) to parse the spatiotemporal dynamics of spectral activities induced during formation of verbal memories. Encoding of words for subsequent free recall activated slow theta, intermediate alpha and beta, and fast gamma frequency power in discrete cortical sites. A majority of the electrode sites recorded activity in only one of these frequencies, except for the visual cortex where spectral power was induced across multiple bands. Each frequency band showed characteristic dynamics of the induced power specific to cortical area and hemisphere. The power of the low, intermediate, and fast activities propagated in distinct spatiotemporal patterns across the visual, temporal and prefrontal cortical areas as the words were presented for encoding. Our results suggest anatomically and temporally distributed spectral activities in the formation of human memory.

neuroscience↗

bioRxiv2021

Distributed Brain Co-Processor for Neurophysiologic Tracking and Adaptive Stimulation: Application to Drug Resistant Epilepsy

Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioral inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behavior and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a hand-held device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes, and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from 9 humans and 8 canines with epilepsy, and then implemented prospectively in out-of-sample testing in 2 pet canines and 4 humans with drug resistant epilepsy living in their natural environments.

bioengineering↗