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Article

NeAT: a Nonlinear Analysis Toolbox for Neuroimaging.

Neuroinformatics - 1 Oct 2020

Casamitjana Adrià, Vilaplana Verónica, Puch Santi, Aduriz Asier, López Carlos, Operto Grégory, Cacciaglia Raffaele, Falcón Carles, Molinuevo José Luis, Gispert Juan Domingo

Abstract excerpt

NeAT is a modular, flexible and user-friendly neuroimaging analysis toolbox for modeling linear and nonlinear effects overcoming the limitations of the standard neuroimaging methods which are solely based on linear models. NeAT provides a wide range of statistical and machine learning non-linear methods for model estimation, several metrics based on curve fitting and complexity for model inference and a graphical...

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Identifiers

PMID: 32212063
DOI: 10.1007/s12021-020-09456-w
PMCID: PMC7498484

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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