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About sim/ch8/hip #13
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There is some more discussion at: https://github.com/emer/leabra/tree/master/examples/hip_bench -- and we are currently writing up a paper about this. Our latest version of the hippocampus is strongly error driven, although always using the "hebbian regularizer" as we use in general to good effect in the Leabra framework more generally. And using hip_bench it is easy to explore these different parameters for yourself so you can see for yourself what works best :) |
Thank you, It's helpful. |
indeed -- lots of work by Menno Witter and others, e.g.,: http://onlinelibrary.wiley.com/doi/abs/10.1111/ejn.14511 |
I have some questions about hippocampus model in the sim/ch8/hip.
The projections Ecin_to_Ca3, Ca3_to_Ca3, use the Dwt function in the Ecca1.go, and projections Ecin_to_DG uses the Dwt function in the chlprjn.go. Both Dwt function combine the Error driven and self-organizing learning rule. This is quite different with the paper you wrote at 2013 (Theta coordinated error-driven learning in the hippocampus)(deltaCHL = 0). I would like to know the reason you change your model structure.
After I traced your code in /emer/leabra/hip, I knew the different between Ecca1.go (err-driven + bcm) and chl.go(err + CPCA). Could you provide some examples about which situation the model should uses chl.go or ecca1.go?
jui shiang
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