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Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions

Objective: Phase transfer entropy ([Formula: see text]) methods perform well in animal sensory–spatial associative learning. However, their advantages and disadvantages remain unclear, constraining their usage. Method: This paper proposes the performance baseline of the [Formula: see text] methods....

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Detalles Bibliográficos
Autores principales: Zhu, Jun-Yao, Li, Meng-Meng, Zhang, Zhi-Heng, Liu, Gang, Wan, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10378602/
https://www.ncbi.nlm.nih.gov/pubmed/37509941
http://dx.doi.org/10.3390/e25070994
Descripción
Sumario:Objective: Phase transfer entropy ([Formula: see text]) methods perform well in animal sensory–spatial associative learning. However, their advantages and disadvantages remain unclear, constraining their usage. Method: This paper proposes the performance baseline of the [Formula: see text] methods. Specifically, four [Formula: see text] methods are applied to the simulated signals generated by a neural mass model and the actual neural data from ferrets with known interaction properties to investigate the accuracy, stability, and computational complexity of the [Formula: see text] methods in identifying the directional coupling. Then, the most suitable method is selected based on the performance baseline and used on the local field potential recorded from pigeons to detect the interaction between the hippocampus (Hp) and nidopallium caudolaterale (NCL) in visual–spatial associative learning. Results: (1) This paper obtains a performance baseline table that contains the most suitable method for different scenarios. (2) The [Formula: see text] method identifies an information flow preferentially from Hp to NCL of pigeons at the [Formula: see text] band (4–12 Hz) in visual–spatial associative learning. Significance: These outcomes provide a reference for the [Formula: see text] methods in detecting the interactions between brain areas.