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Third-order motifs are sufficient to fully and uniquely characterize spatiotemporal neural network activity
Neuroscientific analyses balance between capturing the brain’s complexity and expressing that complexity in meaningful and understandable ways. Here we present a novel approach that fully characterizes neural network activity and does so by uniquely transforming raw signals into easily interpretable...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9816122/ https://www.ncbi.nlm.nih.gov/pubmed/36604489 http://dx.doi.org/10.1038/s41598-022-27188-6 |