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Daniel Suarez-Barrera on Muck Rack

Daniel Suarez-Barrera

As seen in: PLOS Biology, BioRxiv
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Articles

Efficient and reliable spike sorting from neural recordings with UMAP-based unsupervised nonlinear dimensionality reduction

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By Daniel Suarez-Barrera, Lucas Bayonés, Norberto Encinas-Rodríguez
| PLOS Biology Verified
Loading metrics Open Access Peer-reviewed Methods and Resources Methods and Resources report novel methods, substantial improvements to current methodologies, or informational datasets. See Journal Information » ? This is an uncorrected proof. Citation: Suárez-Barrera D, Bayones L, Encinas-Rodríguez N, Parra S, Monroy V, Pujalte S, et al. (2025) Efficient and reliable spike sorting from neural recordings with UMAP-based unsupervised nonlinear dimensionality reduction. PLoS Biol 23(11): e3003527.
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Relevance of Nonlinear Dimensionality Reduction for Efficient and Robust Spike Sorting

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By Lucas Bayonés, Sergio Parra Verified, Daniel Suarez-Barrera, Viktor Monroy
| BioRxiv
Abstract Spike sorting is one of the cornerstones of extracellular electrophysiology. By leveraging advanced signal processing and data analysis techniques, spike sorting makes it possible to detect, isolate, and map single neuron spiking activity from both in vivo and in vitro extracellular electrophysiological recordings. A crucial step of any spike sorting pipeline is to reduce the dimensionality of the recorded spike waveform data.
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