PT  - JOURNAL ARTICLE
AU  - Tiberiu Teşileanu
AU  - Bence Ölveczky
AU  - Vijay Balasubramanian
TI  - Rules and mechanisms for efficient two-stage learning in neural circuits
AID  - 10.1101/071910
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 071910
4099  - http://biorxiv.org/content/early/2017/03/08/071910.short
4100  - http://biorxiv.org/content/early/2017/03/08/071910.full
AB  - Trial-and-error learning requires evaluating variable actions and reinforcing successful variants. In songbirds, vocal exploration is induced by LMAN, the output of a basal ganglia-circuit that also contributes a corrective bias to the vocal output. This bias is gradually consolidated in RA, a motor cortex analogue downstream of LMAN. We develop a new model of such two-stage learning. Using stochastic gradient descent, we derive how the activity in ‘tutor’ circuits (e.g., LMAN) should match plasticity mechanisms in ‘student’ circuits (e.g., RA) to achieve efficient learning. We further describe a reinforcement learning framework through which the tutor can build its teaching signal. We show that mismatches between the tutor signal and the plasticity mechanism can impair learning. Applied to birdsong, our results predict the temporal structure of the corrective bias from LMAN given a plasticity rule in RA. Our framework can be applied predictively to other paired brain areas showing two-stage learning.