Zebra Finch Vocal Development Through Reinforcement Of The Anterior Forebrain Pathway
Open Access
- Author:
- Fraser, David Jeffrey
- Graduate Program:
- Physics
- Degree:
- Doctor of Philosophy
- Document Type:
- Dissertation
- Date of Defense:
- January 06, 2009
- Committee Members:
- Dezge Jin, Dissertation Advisor/Co-Advisor
Dezhe Jin, Committee Chair/Co-Chair
Michael Wenger, Committee Member
John Collins, Committee Member
Jayanth R Banavar, Committee Member - Keywords:
- songbird learning
Zebra Finch
Anterior Forebrain Pathway
biophysics
neural network
birdsong
HVC
RA
AFP
Area X
Computational neuroscience - Abstract:
- This dissertation explores reinforcement learning in the context of zebra finch song development. We argue that similarities in vocal learning and neurophysiology between humans and songbirds offer compelling evidence that the two develop vocalization under similar constraints. A general constraint of motor learning tasks in animals is the requirement of the neurotransmitter dopamine. In mammals dopamine has been shown to encode reward information that is subsequently used to reinforce motor activity. We use simplified binary neurons and synaptic plasticity rules to model activity in critical nuclei that are involved in zebra finch song learning. The model generates exploration in the anterior forebrain pathway (AFP) to guide the song trajectory to a stored tutor song. More specifically, random activity in the lateral magnocellular nucleus of the anterior nidopallium (LMAN) drives random exploration of HVC (proper name) projections to area X. When the model's juvenile song moves towards the memorized tutor template a reward is generated. The reward is represented by activity in the ventral tegmental area (VTA) which globally projects dopamine to area X. The reinforcement of area X activity is permanently mapped onto the premotor projection from HVC to the robust nucleus of the arcopallium (RA). The reward activity is delayed by 100 ms for biological reasons creating a temporal difference problem between activity and its corresponding reward. We resolve this issue using sustained area X activity and a plastic excitatory projection from area X to the VTA. The model is able to guide song development to the tutor song template by using biologically reasonable connectivity and synaptic learning rules.