Developmental learning of complex syntactical song in the Bengalese finch: a neural network model.

Full Abstract

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.

Author information

Author/s: Yamashita, Yuichi (Y); Takahasi, Miki (M); Okumura, Tetsu (T); Ikebuchi, Maki (M); Yamada, Hiroko (H); Suzuki, Madoka (M); Okanoya, Kazuo (K); Tani, Jun (J);

Affiliation: Lab. for Behavior and Dynamic Cognition, Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako-shi, Saitama, 3510198, Japan. yamay(-atsign-)brain.riken.jp

Journal and publication information

Publication Type: Journal Article

Journal: Neural networks : the official journal of the International Neural Network Society (Neural Netw), published in United States. (Language: eng)

Reference: 2008-Nov; vol 21 (issue 9) : pp 1224-31

Dates: Created 2008/11/05; Completed 2009/01/09;

PMID: 18460417, status: MEDLINE (last retrieval date: 2/18/2009, IMS Date: )

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