CUSP: Complex spike sorting from multi-electrode array recordings with U-net sequence-to-sequence prediction

CUSP provides a scalable, robust framework for analyzing burst-like or dynamically complex spike patterns. Its generalizability makes it valuable for large-scale cerebellar datasets and other neural systems, such as hippocampal pyramidal cells, where complex bursts are critical for computation. By combining expert-level accuracy with automation, CUSP offers a broadly applicable solution for studying information coding across circuits.

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Publication Details

Journal
Journal of Neuroscience Methods
Published
2025-11-20
DOI
https://doi.org/10.1016/j.jneumeth.2025.110631
Primary Topic
Neural dynamics and brain function
Type
article
Field-Weighted Citation Impact
0.00
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article

CUSP: Complex spike sorting from multi-electrode array recordings with U-net sequence-to-sequence prediction

Kathleen E. Cullen, Robyn L. Mildren, Adam S. Charles, Chenhao Bao
Journal of Neuroscience Methods
Neural dynamics and brain function
article

CUSP: Complex spike sorting from multi-electrode array recordings with U-net sequence-to-sequence prediction

Kathleen E. Cullen, Robyn L. Mildren, Adam S. Charles, Chenhao Bao
article en

Abstract

CUSP provides a scalable, robust framework for analyzing burst-like or dynamically complex spike patterns. Its generalizability makes it valuable for large-scale cerebellar datasets and other neural systems, such as hippocampal pyramidal cells, where complex bursts are critical for computation. By combining expert-level accuracy with automation, CUSP offers a broadly applicable solution for studying information coding across circuits.

Journal of Neuroscience MethodsVol. 426
Johns Hopkins University (US), Johns Hopkins Medicine (US)
Openalex Percentile: Top 65%
Neural dynamics and brain function
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