Neuroscience and Neural Engineering

The paper examines how electrical stimulation of cutaneous afferents disrupts spinal processing of proprioceptive inputs and affects neural activity propagation to the somatosensory cortex.

This paper introduces methods for 3D spike localization and motion correction in Neuropixels recordings, improving spike sorting and neural activity tracking.

This study uses computational modeling to explain how pulsatile electrical stimulation affects neural firing rates and shows that these effects can be predicted and corrected.

This paper develops a multimodal neuroprosthetic interface to record, modulate, and classify electrophysiological correlates of cognitive function in rats, showing its potential for personalized therapy.

The paper compares deep networks and linear decoders for recovering visual stimuli from neural activity in mice, finding deep networks perform better.

This paper introduces electrode pooling to increase the number of recording sites on silicon probes by using a single wire for multiple sites, demonstrating its feasibility on Neuropixels 1.0 and simulating its effectiveness.

The paper develops a holographic optogenetic platform to study long-term functional connectivity in human stem-cell-derived neuronal networks.

This paper introduces a triangle-shaped neurofluidic system to study neurite growth kinetics in primary rat hippocampal neurons by applying hydrostatic pressure.

The paper evaluates spike detection methods in intracranial recordings, showing inconsistencies due to varying pipelines and suggesting consensus-based event acceptance to improve reliability.

This study investigates how microchannel patterning strategies affect neuronal connectivity in microfluidic devices, showing they can modulate the direction and number of neurites between neuronal populations.

The paper introduces a new silicon-based micro-fabrication technology for creating high-density neural micro-probe arrays with thousands of electrodes, achieving a record density of 400 electrodes/mm2 in rat brain recordings.

ION-Decoding is a single-channel, interactive, offline spike sorting algorithm that outperforms Wave_Clus in hit count but has higher false-positive errors.

This paper introduces an implant-free, tether-free optical neuromodulation technique using NIR-II light to stimulate deep brain regions in mice through the scalp.

This paper introduces an algorithm to optimize electrode selection in neural recordings, improving neuron isolation quality and yield compared to existing methods.

This paper describes the design of wireless microchips for neural sensing and stimulation, demonstrating their networking capabilities in a rat model.

The paper introduces a system for combining electrophysiology data across multiple sessions in marmosets to enable long-term neural recordings and analysis.

This paper introduces an integrated fibertrode that enables simultaneous optogenetic control and electrical recording of neural activity in small brain volumes with reduced photoelectric artifacts.

The paper introduces the Argo System, a high-density neural recording system with 65,536 channels, validated in rats and sheep for cortical recordings.

This paper introduces a chronic photocapacitor implant that uses deep red light for noninvasive neurostimulation, demonstrating long-term functionality in rats.

The paper designs an implantable electrical connector to reconnect injured neurons using electromagnetic modeling and biocompatible materials.

HSST optimizes spike sorting parameters using neurophysiological metrics, improving sorting accuracy and robustness across varying conditions.

This paper introduces a method to precisely localize deep brain implants in mice using micro-CT and MRI, enabling real-time assessment of implantation success.

This paper introduces a high-density CMOS scanning probe for neural recording, demonstrating its ability to capture neural activity across multiple brain regions with improved resolution compared to lower density devices.

YASS sorts spikes from multi-electrode arrays with > 500 electrodes using neural network detection and denoising, parallelized nonparametric Bayesian clustering, and matching-pursuit deconvolution, outperforming manual sorting on primate retina recordings.

This paper describes a wireless neural interface for long-term home monitoring of neural activity in Parkinson's disease patients, enabling adaptive stimulation and behavioral state decoding.

Tracking_Graph improves neuron tracking in long-term extracellular recordings by handling noise spikes and sorting errors through blockwise analysis and classification.

This paper introduces a high-density CMOS neural probe with multiple shanks for simultaneous recording of neural activity across 2D brain regions.

The paper describes a method to record from the same neuron using patch-clamp and CMOS probes, presents a dataset, and discusses collaborative analysis through an open repository.

Stimjim is an open-source, low-cost electrical stimulation device that provides precise microsecond control for in vitro and in vivo experiments.

This paper introduces a Bayesian model using variational autoencoder for localizing spike sources in extracellular recordings, showing improved accuracy over heuristic methods.