Recording from a large neuronal population of neurons is a crucial challenge to unravel how
information is processed by the brain. In this review, we highlight the recent advances made …

The meaning behind neural single unit activity has constantly been a challenge, so it will
persist in the foreseeable future. As one of the most sourced strategies, detecting neural …

Spike sorting is the process of grouping spikes of distinct neurons into their respective
clusters. Most frequently, this grouping is performed by relying on the similarity of features …

Spike sorting is the basis for analyzing spike firing patterns encoded in high-dimensional
information spaces. With the fact that high-density microelectrode arrays record multiple …

Spike sorting–the process of separating spikes from different neurons–is often the first and
most critical step in the neural data analysis pipeline. Spike-sorting techniques isolate a …

This paper presents a spike sorting processor based on an accurate spike clustering
algorithm. The proposed spike sorting algorithm employs an L2-normalized convolutional …

Spike sorting is a fundamental step in extracting single-unit activity from neural ensemble
recordings, which play an important role in basic neuroscience and neurotechnologies. A …

Simultaneously recording network activity and ultrastructural changes of the synapse is
essential for advancing understanding of the basis of neuronal functions. However, the rapid …

Spike sorting is a technique used to detect signals generated by the neurons of the brain
and to classify which spike belongs to which neurons. Spike sorting is one of the most …

Objective. Deep learning is increasingly permeating neuroscience, leading to a rise in signal-
processing applications for extracellular recordings. These signals capture the activity of …