https://doi.org/10.1140/epjb/s10051-025-01074-2
Research - Statistical and Nonlinear Physics
Canine preictal topology: ordinal complexity and neural mapping
1
Instituto de Física de La Plata (IFLP), Universidad Nacional de La Plata, CONICET CCT-La Plata, Diagonal 113 entre 63 y 64 (1900), La Plata, Argentina
2
Instituto de Investigaciones Físicas De Mar del Plata (IFIMAR), CONICET-UNMdP, Mar del Plata (7602), Buenos Aires, Argentina
a
f.montani@fisica.unlp.edu.ar
Received:
23
July
2025
Accepted:
16
October
2025
Published online:
31
October
2025
This research explores the identification of preictal biomarkers in canine epilepsy by employing a multiscale analysis of intracranial EEG data. The approach integrates entropy and complexity quantification using the Bandt–Pompe method 
plane) with topological feature extraction via Self-Organizing Maps (SOMs) and Uniform Manifold Approximation and Projection (UMAP). Although the entropy-complexity framework captured subject-specific neural characteristics, it did not succeed in distinguishing between preictal and interictal states. In contrast, the SOM-UMAP pipeline revealed clear preictal markers, attributed to the reconfiguration of the mesoscale network using optimal parameters 
The main contributions of this study include the topological differentiation of brain states beyond the reach of traditional methods, the discovery of individualized epileptogenic patterns in UMAP embeddings, and the development of a validated methodology suitable for implantable device applications. By combining ordinal pattern analysis with topological preservation techniques, this work advances both the theoretical understanding of seizure mechanisms and the practical implementation of personalized seizure prediction tools, outperforming conventional univariate strategies to detect latent preictal signatures.
Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
© The Author(s), under exclusive licence to EDP Sciences, SIF and Springer-Verlag GmbH Germany, part of Springer Nature 2025
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
