Chronic pain affects over 20% of the adult population in the United States, posing a substantial personal as well as economic burden and contributing to the ongoing opioid crisis. Effective, non-addictive chronic pain treatments are urgently needed. ...
Advanced large-scale neural interfaces call for efficient algorithms to automatically process and optimally exploit the richness of their heavy continuous flow of data. In this context, we introduce here a very frugal generic single-layer Spiking Neu...
Spike sorting, which involves detecting and attributing spikes to their putative neurons from extracellular recordings, is a common process in electrophysiology and brain-computer interface systems. Recent advances in large-scale neural recording tec...
Statistical models are powerful tools for describing biological phenomena such as neuronal spiking activity. Although these models have been widely used to study spontaneous and stimulated neuronal activity, they have not yet been applied to analyze ...
The Journal of neuroscience : the official journal of the Society for Neuroscience
Oct 8, 2025
In temporal lobe epilepsy, interictal spikes (IS)-hyper-synchronous bursts of network activity-occur at high rates in between seizures. We sought to understand the influence of IS on working memory by recording hippocampal local field potentials from...
In neural information processing, the nervous system transmits neuronal activity between layers of neural circuits, occasionally passing through small layers composed only of sparse neurons. Hippocampal hilar mossy cells (MCs) constitute such a typic...
Current machine learning systems consume vastly more energy than biological brains. Neuromorphic systems aim to overcome this difference by mimicking the brain's information coding via discrete voltage spikes. However, it remains unclear how both art...
In this work, a supervised learning rule based on Temporal Single Spike Coding for Effective Transfer Learning (TS4TL) is presented, an efficient approach for training multilayer fully connected Spiking Neural Networks (SNNs) as classifier blocks wit...
The brain exhibits rich dynamical properties that underpin its remarkable temporal processing capabilities. However, spiking neural networks (SNNs) inspired by the brain have not yet matched their biological counterparts in temporal processing and re...
. The compound muscle action potential (CMAP) scan contains a muscle's detailed stimulus-activation information and thereby can be used for motor unit number estimation (MUNE). Due to the challenges in accurately obtaining the motor unit numbers from...
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