Neuroscience and Neural Engineering

The paper introduces a computational framework for noninvasive neurostimulation using spatio-temporal interference, achieving higher spatial precision than existing methods.

This paper introduces high-density multi-fiber photometry arrays for studying brain circuit dynamics in behaving animals, demonstrating simultaneous recordings and optogenetic perturbations across multiple brain regions.

This study evaluates multichannel silicon probes for chronic electrophysiological recordings in large animals, finding that probe cross-sectional area and design affect single-unit performance and long-term viability.

This paper introduces See-Shells, transparent polymer skulls that enable long-term optical access to the mouse cortex for simultaneous monitoring and perturbation of neural activity across multiple regions.

This paper evaluates Gaussian mixture models for spike sorting, showing improved performance over existing methods in both simulated and real extracellular recordings.

The paper uses high-density extracellular recordings to classify neurons by brain region and identify dendritic backpropagation through waveform analysis.

The paper develops a computational model to study axonal stimulation in epiretinal visual prostheses and finds that activation thresholds vary with stimulus duration and electrode-retina distance.

This paper assesses how neural probe shape and size affect extracellular potentials and introduces a correction method to account for their influence.

This paper demonstrates the adaptation of Neuropixels probes for chronic recordings in freely moving mice, enabling long-term neural activity tracking and probe reuse.

This study uses a computational model to recommend optimal electrode placement for retinal implants to reduce axonal activation and improve visual perception.

This study investigates how frequency-dependent electrical stimulation affects calcium activity in cortical neurons, revealing spatiotemporal response patterns that depend on charge density and frequency.

This paper introduces a high-density, long-term electrophysiological recording system for freely behaving rats, enabling multi-region neural activity monitoring over extended periods.

This paper presents a computational framework to simulate visual perception with a retinal prosthesis and assesses how learning might improve inferred visual perception.

The paper evaluates local return stimulation to improve selective activation of retinal ganglion cells at cellular resolution in isolated primate retina.

The paper introduces a mesoscale electrode array for epicortical recordings that selectively captures synchronized spiking activity, improving signal quality and reducing noise compared to intracortical recordings.

This study investigates how electrode impedance affects extracellular spike recordings and finds that within standard ranges, impedance does not significantly impact data quality or spike sorting.

This paper develops an ultralight head-mounted camera system for monitoring behavior and electrophysiology in freely moving mice, showing correlations between eye position, whisking, and neural activity.

The paper presents a multiscale simulator for peripheral nerve signaling that integrates biophysical axon models with extracellular space models to predict signal shapes and stimulation thresholds.

The paper uses t-SNE to visualize and cluster extracellular spike data from neural recordings, showing it can identify single units and improve sorting efficiency.

The paper quantifies how blanking during electrical stimulation affects spike train statistics, finding up to 27% spike loss at 130 Hz and 2 ms blanking window.

This paper demonstrates the use of multi-electrode arrays to record action potential propagation in single axons, revealing insights into axonal physiology and excitability changes over time.

MEA Viewer provides a high-performance interactive tool for visualizing electrophysiological data from multi-electrode arrays, enabling direct visualization of action potential propagation.

ERAASR removes electrical stimulation artifacts from multielectrode array recordings, improving the detection of spiking activity in neural data.

This paper introduces fluidic microdrives to implant and actuate ultra-flexible neural electrodes with minimal tissue damage and high precision.

The paper develops a Gaussian Process model to cancel electrical stimulation artifacts and detect neural spikes in multi-electrode recordings, achieving low error rates and real-time compatibility.

This paper describes a method to assemble carbon fiber electrodes on a flexible polyimide substrate for high-density neural recording and stimulation in peripheral nerves.

This paper introduces a spike sorting method using a mixture of drifting t-distributions, showing improved robustness and accuracy for chronic extracellular recordings.

The paper demonstrates real-time decoding of bladder pressure from pelvic nerve activity using spectral analysis and linear filtering techniques.

This paper introduces an efficient spike sorting method for high-density multielectrode arrays, enabling fast and reliable clustering of millions of events.

iELVis localizes and visualizes intracranial electrodes using MRI and neuroimaging tools, providing accurate brain shift correction and interactive 3D/2D visualization with functional overlays.