Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information.
<p><b>(A)</b> Cumulative average firing rate distributions for UMAP-based and principal component analysis (PCA)-based spike sorting reveal that UMAP identifies more low-firing neurons, reflecting greater sensitivity to sparse firing. <b>(B)</b> Anatomical maps illustra...
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| _version_ | 1849927641752141824 |
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| author | Daniel Suárez-Barrera (22676654) |
| author2 | Lucas Bayones (22676657) Norberto Encinas-Rodríguez (22676660) Sergio Parra (22676663) Viktor Monroy (22676666) Sebastián Pujalte (22676669) Bernardo Andrade-Ortega (22676672) Héctor Díaz (22676675) Manuel Alvarez (3468647) Antonio Zainos (22676678) Alessio Franci (143351) Román Rossi-Pool (22676681) |
| author2_role | author author author author author author author author author author author |
| author_facet | Daniel Suárez-Barrera (22676654) Lucas Bayones (22676657) Norberto Encinas-Rodríguez (22676660) Sergio Parra (22676663) Viktor Monroy (22676666) Sebastián Pujalte (22676669) Bernardo Andrade-Ortega (22676672) Héctor Díaz (22676675) Manuel Alvarez (3468647) Antonio Zainos (22676678) Alessio Franci (143351) Román Rossi-Pool (22676681) |
| author_role | author |
| dc.creator.none.fl_str_mv | Daniel Suárez-Barrera (22676654) Lucas Bayones (22676657) Norberto Encinas-Rodríguez (22676660) Sergio Parra (22676663) Viktor Monroy (22676666) Sebastián Pujalte (22676669) Bernardo Andrade-Ortega (22676672) Héctor Díaz (22676675) Manuel Alvarez (3468647) Antonio Zainos (22676678) Alessio Franci (143351) Román Rossi-Pool (22676681) |
| dc.date.none.fl_str_mv | 2025-11-24T18:33:35Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pbio.3003527.g004 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Uniform_Manifold_Approximation_and_Projection_UMAP_-based_sorting_enhances_detection_of_low-firing_rate_neurons_and_boosts_mutual_information_/30697586 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | 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 |
| dc.title.none.fl_str_mv | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p><b>(A)</b> Cumulative average firing rate distributions for UMAP-based and principal component analysis (PCA)-based spike sorting reveal that UMAP identifies more low-firing neurons, reflecting greater sensitivity to sparse firing. <b>(B)</b> Anatomical maps illustrate three cortical regions: ventral premotor cortex (VPC, green), secondary somatosensory cortex (S2, red), and dorsal prefrontal cortex (DPC, blue). Dotted lines in the lightly shaded oval above S2 indicate recording sites in deeper cortical layers—areas involved in higher-level processing and decision-making. <b>(C–E)</b> Comparisons of PCA and UMAP sorting across these regions. Left: UMAP consistently recovers a larger number of low-firing neurons based on cumulative firing rate distributions: 134 (UMAP) and 60 (PCA) neurons were identified in S2; 228 (UMAP) and 145 (PCA) in VPC; 129 (UMAP) and 96 (PCA) in DPC. Center: It also yields higher overall neuron counts from the same sessions: average number of neuron pairs in S2 from about 4 to almost 10; VPC from about 5 to almost 9; DPC from about 6 to almost 8. Right: UMAP reveals greater mutual information (MI) compared to PCA, indicating stronger information decoding across all brain regions. In summary, UMAP effectively increases neuron recovery, captures low-firing activity, and enhances the information gained from cognitive task data. The neuronal activity recorded during the foreperiod of the cognitive tasks, used for the cumulative distributions, is available at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref044" target="_blank">44</a>]; the single neurons from different sessions used for the mutual information calculations can be found at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref043" target="_blank">43</a>]; and the corresponding analysis code is available at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref049" target="_blank">49</a>].</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_8dbe3b5e70aedc164e8832c44836ea32 |
| identifier_str_mv | 10.1371/journal.pbio.3003527.g004 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30697586 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information.Daniel Suárez-Barrera (22676654)Lucas Bayones (22676657)Norberto Encinas-Rodríguez (22676660)Sergio Parra (22676663)Viktor Monroy (22676666)Sebastián Pujalte (22676669)Bernardo Andrade-Ortega (22676672)Héctor Díaz (22676675)Manuel Alvarez (3468647)Antonio Zainos (22676678)Alessio Franci (143351)Román Rossi-Pool (22676681)Cell BiologyMolecular BiologyNeurosciencePhysiologyBiotechnologyDevelopmental BiologyScience PolicySpace ScienceBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedspike sorting pipelinesspike sorting pipelineseldom spiking neuronsrecorded putative neuronscorrectly sorted neuronsclustering algorithms responsiblespike sorting makesreliable spike sortingumap drastically increasesdata analysis techniquesdrastically improveprocessed dataexperimental datauniversal practiceprecise explorationsneural recordingsneural codemathematically groundedfundamentally motivatedextracellular electrophysiologyenables deepercrucial stepcomputational costad hoc<p><b>(A)</b> Cumulative average firing rate distributions for UMAP-based and principal component analysis (PCA)-based spike sorting reveal that UMAP identifies more low-firing neurons, reflecting greater sensitivity to sparse firing. <b>(B)</b> Anatomical maps illustrate three cortical regions: ventral premotor cortex (VPC, green), secondary somatosensory cortex (S2, red), and dorsal prefrontal cortex (DPC, blue). Dotted lines in the lightly shaded oval above S2 indicate recording sites in deeper cortical layers—areas involved in higher-level processing and decision-making. <b>(C–E)</b> Comparisons of PCA and UMAP sorting across these regions. Left: UMAP consistently recovers a larger number of low-firing neurons based on cumulative firing rate distributions: 134 (UMAP) and 60 (PCA) neurons were identified in S2; 228 (UMAP) and 145 (PCA) in VPC; 129 (UMAP) and 96 (PCA) in DPC. Center: It also yields higher overall neuron counts from the same sessions: average number of neuron pairs in S2 from about 4 to almost 10; VPC from about 5 to almost 9; DPC from about 6 to almost 8. Right: UMAP reveals greater mutual information (MI) compared to PCA, indicating stronger information decoding across all brain regions. In summary, UMAP effectively increases neuron recovery, captures low-firing activity, and enhances the information gained from cognitive task data. The neuronal activity recorded during the foreperiod of the cognitive tasks, used for the cumulative distributions, is available at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref044" target="_blank">44</a>]; the single neurons from different sessions used for the mutual information calculations can be found at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref043" target="_blank">43</a>]; and the corresponding analysis code is available at [<a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.3003527#pbio.3003527.ref049" target="_blank">49</a>].</p>2025-11-24T18:33:35ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pbio.3003527.g004https://figshare.com/articles/figure/Uniform_Manifold_Approximation_and_Projection_UMAP_-based_sorting_enhances_detection_of_low-firing_rate_neurons_and_boosts_mutual_information_/30697586CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/306975862025-11-24T18:33:35Z |
| spellingShingle | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. Daniel Suárez-Barrera (22676654) 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 |
| status_str | publishedVersion |
| title | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| title_full | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| title_fullStr | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| title_full_unstemmed | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| title_short | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| title_sort | Uniform Manifold Approximation and Projection (UMAP)-based sorting enhances detection of low-firing rate neurons and boosts mutual information. |
| topic | 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 |