A framework to identify structured behavioral patterns within rodent spatial trajectories
| dc.citation.articleNumber | 468 | en_US |
| dc.citation.journalTitle | Scientific Reports | en_US |
| dc.citation.volumeNumber | 11 | en_US |
| dc.contributor.author | Donnarumma, Francesco | en_US |
| dc.contributor.author | Prevete, Roberto | en_US |
| dc.contributor.author | Maisto, Domenico | en_US |
| dc.contributor.author | Fuscone, Simone | en_US |
| dc.contributor.author | Irvine, Emily M. | en_US |
| dc.contributor.author | van der Meer, Matthijs A.A. | en_US |
| dc.contributor.author | Kemere, Caleb | en_US |
| dc.contributor.author | Pezzulo, Giovanni | en_US |
| dc.date.accessioned | 2021-02-24T19:16:05Z | en_US |
| dc.date.available | 2021-02-24T19:16:05Z | en_US |
| dc.date.issued | 2021 | en_US |
| dc.description.abstract | Animal behavior is highly structured. Yet, structured behavioral patterns—or “statistical ethograms”—are not immediately apparent from the full spatiotemporal data that behavioral scientists usually collect. Here, we introduce a framework to quantitatively characterize rodent behavior during spatial (e.g., maze) navigation, in terms of movement building blocks or motor primitives. The hypothesis that we pursue is that rodent behavior is characterized by a small number of motor primitives, which are combined over time to produce open-ended movements. We assume motor primitives to be organized in terms of two sparsity principles: each movement is controlled using a limited subset of motor primitives (sparse superposition) and each primitive is active only for time-limited, time-contiguous portions of movements (sparse activity). We formalize this hypothesis using a sparse dictionary learning method, which we use to extract motor primitives from rodent position and velocity data collected during spatial navigation, and successively to reconstruct past trajectories and predict novel ones. Three main results validate our approach. First, rodent behavioral trajectories are robustly reconstructed from incomplete data, performing better than approaches based on standard dimensionality reduction methods, such as principal component analysis, or single sparsity. Second, the motor primitives extracted during one experimental session generalize and afford the accurate reconstruction of rodent behavior across successive experimental sessions in the same or in modified mazes. Third, in our approach the number of motor primitives associated with each maze correlates with independent measures of maze complexity, hence showing that our formalism is sensitive to essential aspects of task structure. The framework introduced here can be used by behavioral scientists and neuroscientists as an aid for behavioral and neural data analysis. Indeed, the extracted motor primitives enable the quantitative characterization of the complexity and similarity between different mazes and behavioral patterns across multiple trials (i.e., habit formation). We provide example uses of this computational framework, showing how it can be used to identify behavioural effects of maze complexity, analyze stereotyped behavior, classify behavioral choices and predict place and grid cell displacement in novel environments. | en_US |
| dc.identifier.citation | Donnarumma, Francesco, Prevete, Roberto, Maisto, Domenico, et al.. "A framework to identify structured behavioral patterns within rodent spatial trajectories." <i>Scientific Reports,</i> 11, (2021) Springer Nature: https://doi.org/10.1038/s41598-020-79744-7. | en_US |
| dc.identifier.digital | s41598-020-79744-7 | en_US |
| dc.identifier.doi | https://doi.org/10.1038/s41598-020-79744-7 | en_US |
| dc.identifier.uri | https://hdl.handle.net/1911/110103 | en_US |
| dc.language.iso | eng | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.rights | This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.title | A framework to identify structured behavioral patterns within rodent spatial trajectories | en_US |
| dc.type | Journal article | en_US |
| dc.type.dcmi | Text | en_US |
| dc.type.publication | publisher version | en_US |
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