A neural network model for generating complex birdsong syntax

Biological Cybernetics

Volumn 97, Issue 5-6, 2007, Pages 441-448

  Katahira, Kentaro ^a,b   Okanoya, Kazuo ^b   Okada, Masato ^a,b  

^a UNIVERSITY OF TOKYO   (Japan)

^b RIKEN BRAIN SCIENCE INSTITUTE   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; LEARNING SYSTEMS; MARKOV PROCESSES; NEURONS; STOCHASTIC MODELS;

FINITE STATE AUTOMATON; NEURAL STRUCTURE;

NEURAL NETWORKS;

LONCHURA STRIATA; LONCHURA STRIATA DOMESTICA; PASSERI;

ANIMAL; ANIMAL BEHAVIOR; ARTICLE; ARTIFICIAL NEURAL NETWORK; CYTOLOGY; FOREBRAIN; LEARNING; NERVE CELL; NERVE CELL NETWORK; NERVE TRACT; PHYSIOLOGY; PROBABILITY; SONGBIRD; VOCALIZATION;

ANIMALS; BEHAVIOR, ANIMAL; LEARNING; MARKOV CHAINS; NERVE NET; NEURAL NETWORKS (COMPUTER); NEURAL PATHWAYS; NEURONS; PROSENCEPHALON; SONGBIRDS; VOCALIZATION, ANIMAL;

EID: 40749109402     PISSN: 03401200     EISSN: 14320770     Source Type: Journal    
DOI: 10.1007/s00422-007-0184-y     Document Type: Article

References (22)

1. Abarbanel HDI, Gibb L, Huerta R, Rabinovich MI and Talathi S (2004). Spike timing and synaptic plasticity in the premotor pathway of birdsong. Biol Cybern 91: 159-167
2. Chatfield C (2004). Analysing sequences of behavioural events. J Theor Biol 29: 427-445
3. Doya K and Sejnowski TJ (1995). A novel reinforcement model of birdsong vocalization learning. Adv Neural Inf Process Syst 7: 101-108
4. Drew PJ and Abbott LF (2003). Model of song selectivity and sequence generation in area HVc of the songbird. J Neurophysiol 89: 2697-2706
5. Fee MS, Kozhevnikov AA and Hahnloser RH (2004). Neural mechanisms of vocal sequence generation in the songbird. Ann N Y Acad Sci 1016: 153-170
6. Dutar P, Vu HM and Perkel DJ (1998). Multiple cell types distinguished by physiological, pharmacological, and anatomic properties in nucleus HVc of the adult zebra finch. J Neurophysiol 80: 1828-1838
7. Hahnloser RH, Kozhevnikov AA and Fee MS (2002). An ultra-sparse code underlies the generation of neural sequences in songbird. Nature 419: 65-70
8. Hosino T and Okanoya K (2000). Lesion of a higher-order song nucleus disrupts phrase level complexity in Bengalese finches. Neuroreport 11: 2091-2095
9. Jin DZ, Ramazanoǧlu FM, Seung HS (2007) Intrinsic bursting enhances the robustness of a neural network model of sequence generation by avian brain area HVC. J Comput Neurosci (in press)
10. Kozhevnikov AA, Fee MS (2007) Singing-related activity of identified HVC neurons in the zebra finch. J Neurophysiol (in press)
11. Katahira K, Kawamura M, Okanoya K and Okada M (2007). Retrieval of branching sequences in an associative memory model with common external input and bias input. J Phys Soc Jpn 76: 044804
12. Li M and Greenside H (2006). Stable propagation of a burst through a one-dimensional homogeneous excitatory chain model of songbird nucleus HVC. Phys Rev E 74: 011918
13. Leonardo A and Fee MS (2005). Ensemble coding of vocal control in birdsong. J Neurosci 25: 652-661
14. Mooney R and Prather J (2005). The HVC microcircuit: the synaptic basis for interactions between song motor and vocal plasticity pathways. J Neurosci 25: 1952-1964
15. Okanoya K (2004a). Bengalese finches: A window to the neurobiology of birdsong syntax. Ann N Y Acad Sci 1016: 724-735
16. Okanoya K (2004b). Proximate and ultimate studies of song complexity in Bengalese finches. Adv Study Behav 34: 297-346
17. Sakata J and Brainard MS (2006). Real-time contributions of auditory feedback to avian vocal motor control. J Neurosci 26: 9619-9628
18. Schmidt MF (2003). Pattern of interhemispheric synchronization in HVc during singing correlates with key transitions in the song pattern. J Neurophysiol 90: 3931-3949
19. Troyer TW and Doupe AJ (2000). An associational model of birdsong sensorimotor learning II. Temporal hierarchies and the learning of song sequence. J Neurophysiol 84: 1224-1239
20. Uno H, Okanoya K (1998) Neural basis for song production in Bengalese finches: effects of partial lesions on the higher vocal center (in Japanese). Tech Report IEICE SP97:137
21. Vu ET, Mazurek ME and Kuo YC (1994). Identification of a forebrain motor programming network for the learned song of zebra finches. J Neurosci 14: 6924-6934
22. Wang XJ (1999). Synaptic basis of cortical persistent activity: the importance of NMDA receptors to working memory. J Neurosci 18: 9587-9603