Neuroscience and Neural Engineering

This paper introduces a method to dynamically alter electrode size in vivo to study the impact of electrode size on intracranial EEG features across different brain regions.

This paper introduces a minimally invasive brain-computer interface platform using thin-film electrodes and demonstrates its feasibility for high-density neural recording and stimulation in preclinical and clinical settings.

The paper presents a method to create topologically controlled circuits of human iPSC-derived neurons for long-term electrophysiology recordings.

This paper introduces a 3D neuro-microphysiological system with microelectrodes for high-throughput electrical recording and analysis of human neurons.

This paper introduces flexible graphene micro-transistor depth neural probes for recording infraslow and high-frequency neuronal activity in rodents, demonstrating their utility in epilepsy research.

This paper uses computational modeling to resolve conflicting findings on how intracortical microstimulation (ICMS) intensity affects neural activation, showing increased activation density without increased volume.

The paper introduces a tool for simultaneous optical recording and optogenetic stimulation in two cortical layers of mice.

This study demonstrates that carbon fiber electrodes can record intracellular activity and stimulate neurons in intact nervous systems, offering a stable and scalable alternative to traditional methods.

This paper introduces a biohybrid OB-CMOS platform to study spatiotemporal dynamics in olfactory bulb circuits using high-density electrode recordings.

The paper examines ultrastructural interfaces between neuroimplants and brain parenchyma, revealing regenerative processes and microglia-mediated barriers affecting electrophysiological function.

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 evaluates existing spike sorters and introduces a new method called full binary pursuit (FBP) that addresses multiple sorting challenges in neural recordings.

This paper develops a new neural probe with a silicon backbone and thin polyimide wings for long-term stable in vivo recordings in mice.

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

This study characterizes the transcriptional response of glial cells to chronic implantation of flexible microprobes over 18 weeks, showing initial activation and eventual partial normalization.

This study decodes large-scale cortical activity from local surface potentials using a recurrent neural network, showing that surface potentials contain rich information about neural activity across multiple regions.

The paper develops a workflow to accurately localize electrodes in Neuropixels probes across multiple brains using imaging and electrophysiological data.

This paper introduces a multifunctional optrode for optogenetics, enabling simultaneous drug delivery, optical stimulation, and electrophysiological recording in freely moving rats.

The paper introduces Piphys, an open-source platform for neural recording that enables remote control and scalability through cloud-based software and low-cost hardware.

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 new fabrication methods for multifunctional neural interfaces that integrate electrical, optical, and microfluidic functions, demonstrating their long-term viability in mice.

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 benchmarks MEA recordings from healthy hiPSC-derived neuronal networks to establish standards for experimental design and analysis, showing MEAs are robust for disease-phenotyping and drug discovery.

This study investigates how microstimulation frequency affects perceptual responses in human somatosensory cortex, finding spatially organized effects on perceptual intensity and quality.

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 an adaptive spike sorting algorithm that improves detection, alignment, and clustering of spikes by using a mixture of skew-t distributions, showing better precision and recall across datasets.

This paper develops a method for chronic wireless neural recordings in marmosets across multiple behaviors and brain states, validated through sensorimotor cortex activity tracking.

The paper models the effects of recording instruments on axonal voltage measurements and shows how instrumentation distorts signals, offering a method to predict native waveforms from distorted recordings.

This paper demonstrates an optical brain-computer interface (oBCI) using dendritic calcium signals from rhesus macaques during motor tasks, achieving stable decoding of movement direction.

This study demonstrates the use of magnetoelectric nanoparticles for non-invasive, targeted brain stimulation in mice, showing reliable neuronal activation and minimal immune response.