{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,16]],"date-time":"2026-02-16T17:06:15Z","timestamp":1771261575575,"version":"3.50.1"},"reference-count":55,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T00:00:00Z","timestamp":1687996800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61673353"],"award-info":[{"award-number":["61673353"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Objective: Phase transfer entropy (TE\u03b8) methods perform well in animal sensory\u2013spatial associative learning. However, their advantages and disadvantages remain unclear, constraining their usage. Method: This paper proposes the performance baseline of the TE\u03b8 methods. Specifically, four TE\u03b8 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 TE\u03b8 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\u2013spatial associative learning. Results: (1) This paper obtains a performance baseline table that contains the most suitable method for different scenarios. (2) The TE\u03b8 method identifies an information flow preferentially from Hp to NCL of pigeons at the \u03b8 band (4\u201312 Hz) in visual\u2013spatial associative learning. Significance: These outcomes provide a reference for the TE\u03b8 methods in detecting the interactions between brain areas.<\/jats:p>","DOI":"10.3390\/e25070994","type":"journal-article","created":{"date-parts":[[2023,6,29]],"date-time":"2023-06-29T01:53:57Z","timestamp":1688003637000},"page":"994","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Performance Baseline of Phase Transfer Entropy Methods for Detecting Animal Brain Area Interactions"],"prefix":"10.3390","volume":"25","author":[{"given":"Jun-Yao","family":"Zhu","sequence":"first","affiliation":[{"name":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China"},{"name":"Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2788-0314","authenticated-orcid":false,"given":"Meng-Meng","family":"Li","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China"},{"name":"Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China"}]},{"given":"Zhi-Heng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China"},{"name":"Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7379-1988","authenticated-orcid":false,"given":"Gang","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China"},{"name":"Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China"}]},{"given":"Hong","family":"Wan","sequence":"additional","affiliation":[{"name":"School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China"},{"name":"Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology, Zhengzhou 450001, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"842","DOI":"10.1002\/hipo.20321","article-title":"Integrating associative learning signals across the brain","volume":"17","author":"Suzuki","year":"2010","journal-title":"Hippocampus"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"503","DOI":"10.1002\/hipo.23311","article-title":"Hippocampal beta oscillations predict mouse object-location associative memory performance","volume":"31","author":"Iwasaki","year":"2021","journal-title":"Hippocampus"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2419","DOI":"10.1016\/j.celrep.2017.10.123","article-title":"Gamma Oscillations in Rat Hippocampal Subregions Dentate Gyrus, CA3, CA1, and Subiculum Underlie Associative Memory Encoding","volume":"21","author":"Trimper","year":"2017","journal-title":"Cell Rep."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"3281","DOI":"10.1111\/j.1460-9568.2005.04477.x","article-title":"The role of prefrontal cortex in object-in-place learning in monkeys","volume":"22","author":"Browning","year":"2005","journal-title":"Eur. 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