Terry Stewart
Simple learning rule: $\Delta d_i = \kappa (y_d - y)a_i$
How do we make it realistic?
Decoders don't exist in the brain
$\omega_{ij} = \alpha_j d_i \cdot e_j$
$\Delta \omega_{ij} = \alpha_j \kappa (y_d - y)a_i \cdot e_j$
let's write $(y_d - y)$ as $E$
$\Delta \omega_{ij} = \alpha_j \kappa a_i E \cdot e_j$
$\Delta \omega_{ij} = \kappa a_i (\alpha_j E \cdot e_j)$
This is the "Prescribed Error Sensitivity" PES rule (MacNeil & Eliasmith, 2011)
Nengo Examples:
Is this realistic?
Hebbian learning
BCM rule (Bienenstock, Cooper, & Munro, 1982)
just do them both
and have a parameter $S$ to adjust how much of each
$\Delta \omega_{ij} = \kappa \alpha_j a_j (S e_j \cdot E + (1-S) a_j (a_j-\theta))$
http://mindmodeling.org/cogsci2013/papers/0058/paper0058.pdf
Works as well (or better) than PES
Biological evidence?