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Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions.
- Source :
- Entropy; Jul2023, Vol. 25 Issue 7, p994, 20p
- Publication Year :
- 2023
-
Abstract
- Objective: Phase transfer entropy ( T E θ ) 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 T E θ methods. Specifically, four T E θ 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 T E θ 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 T E θ method identifies an information flow preferentially from Hp to NCL of pigeons at the θ band (4–12 Hz) in visual–spatial associative learning. Significance: These outcomes provide a reference for the T E θ methods in detecting the interactions between brain areas. [ABSTRACT FROM AUTHOR]
- Subjects :
- ASSOCIATIVE learning
ENTROPY
COMPUTATIONAL complexity
PIGEONS
FERRET
Subjects
Details
- Language :
- English
- ISSN :
- 10994300
- Volume :
- 25
- Issue :
- 7
- Database :
- Complementary Index
- Journal :
- Entropy
- Publication Type :
- Academic Journal
- Accession number :
- 168601221
- Full Text :
- https://doi.org/10.3390/e25070994