Impact of multiunit merging on neural information encoding.

<p>Multiunit merging, a common artifact in spike sorting, combines spikes from multiple neurons into a single “putative neuron.” This inflates firing rates—particularly masking low firing rate neurons—and obscures their distinct information-encoding properties. <b>(A)</b> Schematic...

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書誌詳細
第一著者:	Daniel Suárez-Barrera (22676654) (author)
その他の著者:	Lucas Bayones (22676657) (author), Norberto Encinas-Rodríguez (22676660) (author), Sergio Parra (22676663) (author), Viktor Monroy (22676666) (author), Sebastián Pujalte (22676669) (author), Bernardo Andrade-Ortega (22676672) (author), Héctor Díaz (22676675) (author), Manuel Alvarez (3468647) (author), Antonio Zainos (22676678) (author), Alessio Franci (143351) (author), Román Rossi-Pool (22676681) (author)
出版事項:	2025
主題:	Cell Biology Molecular Biology Neuroscience Physiology Biotechnology Developmental Biology Science Policy Space Science Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified spike sorting pipelines spike sorting pipeline seldom spiking neurons recorded putative neurons correctly sorted neurons clustering algorithms responsible spike sorting makes reliable spike sorting umap drastically increases data analysis techniques drastically improve processed data experimental data universal practice precise explorations neural recordings neural code mathematically grounded fundamentally motivated extracellular electrophysiology enables deeper crucial step computational cost ad hoc
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Impact of multiunit merging on neural information encoding.

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