Neuroscience and Neural Engineering

This paper introduces two Python tools, spikeNburst and nicespike, for analyzing HD-MEA data, improving spike sorting and synchronization analysis.

This study evaluates biodegradable PDLLA optical fibers as neural interfaces in mice, showing degradation and efficient SW-NIR light transmission with potential for optogenetics and therapy.

The paper introduces an adaptable implant for chronic Neuropixels recordings in mice, enabling stable, reusable, and lightweight neural recordings across multiple experimental conditions.

This paper introduces a biodegradable neural interface that monitors nerve injury recovery using machine learning, enabling early detection of neuroma formation and improved therapeutic outcomes.

This paper accelerates multi-electrode array simulations using sparse and low-rank matrix techniques, achieving up to 133x speedup with minimal error.

MEDiCINe improves motion correction in neural electrophysiology recordings, leading to more accurate spike sorting.

SpikeAgent automates spike sorting with a multimodal LLM-based AI agent, achieving curation consistency equal to or exceeding human experts and drastically reducing expertise barriers.

This paper develops an implantable biohybrid nerve model for synaptic deep brain stimulation, demonstrating in vitro and in vivo functionality for over 22 days.

This paper introduces a sapphire-based optrode that combines high-intensity LED optogenetic stimulation with low-noise neural recording, demonstrating its effectiveness in vivo.

The paper tests asymmetric microchannel designs to promote unidirectional connectivity in cultured neuronal circuits and finds that the 'Rams' design achieves ~76% unidirectional connections and ~94% directional spiking activity.

This study develops graphene-based micro-electrodes with tunable porous structures to improve neural recordings by reducing impedance and increasing charge injection capacity.

This paper develops a graphene-based sensor integrated into a microfluidic chip for real-time monitoring of cell growth and viability through impedance spectroscopy.

The paper introduces a cost-effective, customizable open-source device for multipolar brain stimulation experiments, demonstrating its effectiveness through bench-top and in vivo testing.

This paper develops an automatic method to optimize electrode placement for visual prostheses by matching phosphene distributions using retinotopic predictions and individual anatomy data.

This study shows that three-organoid networks exhibit better stimulus decoding after repetitive stimulation compared to smaller networks.

This paper develops flexible microelectrode arrays (MEAs) for recording neuronal activity in 3D cultures, showing improved performance and scalability.

This study evaluates nanoporous platinum microelectrode morphologies for neural cell cultures, finding that uniform nanoporous electrodes balance biocompatibility and electrophysiological performance.

This paper develops a reversible and reusable microfluidic chip for culturing dorsal root ganglion neurons, enabling PNS modeling with improved accessibility and sustainability.

This paper demonstrates in vitro neuronal networks capable of performing Boolean computations like NAND and OR using controlled topology and extracellular stimulation.

This study introduces DC-coupled graphene neural probes to record infra-slow brain dynamics in freely moving rats, linking synchronous states to structured DC potential shifts.

The paper develops a biophysical model to study retinal ganglion cell responses to multi-electrode stimulation and validates it with experimental data from macaque retinas.

The paper introduces a multidimensional neural bidomain model to study ephaptic coupling in myelinated fiber bundles, showing how fiber configurations affect spike propagation.

This paper demonstrates that graphene-polymer nanofibers can be optically stimulated to enhance electrical activity in stem cell-derived cardiomyocytes and brain organoids.

This paper introduces an AI-cyborg system that uses adaptive intelligent modulation to enhance cardiac organoid maturation through real-time feedback.

This study evaluates biomimetic multi-channel microstimulation for restoring high-resolution force feedback in bionic hands through somatosensory cortex stimulation.

RT-Sort detects and sorts action potentials in real time with millisecond latencies using propagation patterns and a convolutional neural network.

The paper evaluates spike sorters using a cortical model, finding that sorting biases reduce stimulus discrimination ability by nearly half.

This study examines how induced P301L tau mutation alters structural and functional connectivity in engineered neural networks over time.

This study evaluates long-term biocompatibility and performance of 3D honeycomb-shaped subretinal implants in rats, showing improved stimulation thresholds compared to flat designs.

This study demonstrates that a cortical biohybrid implant can transmit information to the brain by enabling mice to report optogenetic stimulation of engrafted neurons.