You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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
The text was updated successfully, but these errors were encountered:
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.
EC and CA1 use pool (4D) structure in your model. Could you provide some biologial evidence(paper) about this assumption?
thanks a lot
Jui Shiang
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
The text was updated successfully, but these errors were encountered: