Analysis of Representations of 3-Dimensional Objects in the Cell Populations in the Temporal Association Area Using Machine Learning

Autor: Yousuke Yamada, Yoshihiro Uto, Lulin Dai, Jun-ya Okamura, Gang Wang, Yusuke Yamamoto
Rok vydání: 2021
Předmět:
Zdroj: IFMBE Proceedings ISBN: 9783030661687
DOI: 10.1007/978-3-030-66169-4_23
Popis: Three-dimensional objects can be recognized regardless of the viewing angles. It was reported that the cells in the temporal association area responded tolerantly in a certain viewing angle range to the objects experienced in discrimination at the same viewing angles. In the present study, machine learning was applied to the population response vectors in the temporal association area. A classifier was trained to create a hyperplane that separated an object from similar object at the same viewing angles and then tested by the population response vectors to the object images at a different viewing angle. The discrimination performance evaluated from true positives, false positives, and d’ values was higher in the objects experienced in discrimination at the same viewing angles than those without discrimination experience in the whole 100–600 ms time window. For the objects experienced in discrimination at the same viewing angles, the d’ values were low in the early phase of the responses of 100–220 ms time window, but became higher in the late phase of 220–600 ms time window. The d’ values for the objects experienced by learning association of different views of the objects were high in the early and late phases of the responses. The results demonstrate computational models for object representation created by using cellular responses in the temporal association area, and differences of the representation of the viewing angle tolerance in different time windows.
Databáze: OpenAIRE