revert to previous plasticity parameters

_literate/learning.jl

@@ -40,14 +40,14 @@ model_name = :g
 @named ASC1 = NextGenerationEIBlox(; namespace=model_name, Cₑ=2*26,Cᵢ=1*26, alpha_invₑₑ=10.0/26, alpha_invₑᵢ=0.8/26, alpha_invᵢₑ=10.0/26, alpha_invᵢᵢ=0.8/26, kₑᵢ=0.6*26, kᵢₑ=0.6*26) 
 
 ## learning rule
-hebbian_cort = HebbianPlasticity(K=5e-3, W_lim=20, t_pre=trial_dur, t_post=trial_dur) 
+hebbian_cort = HebbianPlasticity(K=5e-5, W_lim=7, t_pre=trial_dur, t_post=trial_dur) 
 
 g = MetaDiGraph()
 
 add_edge!(g, stim => VAC, weight=14) 
 add_edge!(g, ASC1 => VAC, weight=44)
 add_edge!(g, ASC1 => AC, weight=44)
-add_edge!(g, VAC => AC, weight=3, density=0.2, learning_rule = hebbian_cort) ## pass learning rule as a keyword argument
+add_edge!(g, VAC => AC, weight=3, density=0.1, learning_rule = hebbian_cort) ## pass learning rule as a keyword argument
 
 agent = Agent(g; name=model_name); 
 env = ClassificationEnvironment(stim, N_trials; name=:env, namespace=model_name);