Developmental learning of complex syntactical song in the Bengalese finch: a neural network model.
We developed a neural network model for studying neural mechanisms underlying complex syntactical songs of the Bengalese finch, which result from interactions between sensori-motor nuclei, the nucleus HVC (HVC) and the nucleus interfacialis (NIf). Results of simulations are tested by comparison with the song development of real young birds learning the same songs from their fathers. The model shows that complex syntactical songs can be reproduced from the simple interaction between the deterministic dynamics of a recurrent neural network and random noise. Features of the learning process in the simulations show similar trends to those observed in empirical data on the song development of real birds. These observations suggest that the temporal note sequences of songs take the form of a dynamical process involving recurrent connections in the network of the HVC, as opposed to feedforward activities, the mechanism proposed in the previous model.
Yamashita
Yuichi
Y
Lab. for Behavior and Dynamic Cognition, Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama, 3510198, Japan. yamay@brain.riken.jp
Takahasi
Miki
M
Okumura
Tetsu
T
Ikebuchi
Maki
M
Yamada
Hiroko
H
Suzuki
Madoka
M
Okanoya
Kazuo
K
Tani
Jun
J
D000375:Aging / Q000523:psychology*; D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology; D030141:Feedback, Psychological; D046369:Finches / Q000254:growth & development* / Q000502:physiology*; D007858:Learning / Q000502:physiology*; D016571:Neural Networks, Computer; D014828:Vocalization, Animal / Q000502:physiology*