Swap JansenRit implementation to flag

Instead of separate `JansenRit()` and `JansenRitDelayed` constructors, create a single constructor with flag `delayed=false` default.

examples/jansen_rit_liu_et_al.jl

@@ -62,14 +62,14 @@ sol_dde_no_delays = solve(prob, alg, saveat=1)
 # Example of delayed connections
 
 # First, recreate the graph to remove previous connections
-@named Str = JansenRitDelayed(τ=0.0022*τ_factor, H=20, λ=300, r=0.3)
-@named GPE = JansenRitDelayed(τ=0.04*τ_factor, cortical=false) # all default subcortical except τ
-@named STN = JansenRitDelayed(τ=0.01*τ_factor, H=20, λ=500, r=0.1)
-@named GPI = JansenRitDelayed(cortical=false) # default parameters subcortical Jansen Rit blox
-@named Th  = JansenRitDelayed(τ=0.002*τ_factor, H=10, λ=20, r=5)
-@named EI  = JansenRitDelayed(τ=0.01*τ_factor, H=20, λ=5, r=5)
-@named PY  = JansenRitDelayed(cortical=true) # default parameters cortical Jansen Rit blox
-@named II  = JansenRitDelayed(τ=2.0*τ_factor, H=60, λ=5, r=5)
+@named Str = JansenRit(τ=0.0022*τ_factor, H=20, λ=300, r=0.3, delayed=true)
+@named GPE = JansenRit(τ=0.04*τ_factor, cortical=false, delayed=true) # all default subcortical except τ
+@named STN = JansenRit(τ=0.01*τ_factor, H=20, λ=500, r=0.1, delayed=true)
+@named GPI = JansenRit(cortical=false, delayed=true) # default parameters subcortical Jansen Rit blox
+@named Th  = JansenRit(τ=0.002*τ_factor, H=10, λ=20, r=5, delayed=true)
+@named EI  = JansenRit(τ=0.01*τ_factor, H=20, λ=5, r=5, delayed=true)
+@named PY  = JansenRit(cortical=true, delayed=true) # default parameters cortical Jansen Rit blox
+@named II  = JansenRit(τ=2.0*τ_factor, H=60, λ=5, r=5, delayed=true)
 blox = [Str, GPE, STN, GPI, Th, EI, PY, II]
 g = MetaDiGraph()
 add_blox!.(Ref(g), blox)

src/Neuroblox.jl

@@ -185,7 +185,7 @@ export JansenRitSPM12, next_generation, qif_neuron, if_neuron, hh_neuron_excitat
     hh_neuron_inhibitory, synaptic_network, van_der_pol
 export IFNeuronBlox, LIFNeuronBlox, QIFNeuronBlox, HHNeuronExciBlox, HHNeuronInhibBlox,
     CanonicalMicroCircuitBlox, WinnerTakeAllBlox, CorticalBlox, SuperCortical
-export LinearNeuralMass, HarmonicOscillator, JansenRit, JansenRitDelayed, WilsonCowan, LarterBreakspear, NextGenerationBlox, NextGenerationResolvedBlox, NextGenerationEIBlox
+export LinearNeuralMass, HarmonicOscillator, JansenRit, WilsonCowan, LarterBreakspear, NextGenerationBlox, NextGenerationResolvedBlox, NextGenerationEIBlox
 export Matrisome, Striosome, Striatum, GPi, GPe, Thalamus, STN, TAN, SNc
 export HebbianPlasticity, HebbianModulationPlasticity
 export Agent, ClassificationEnvironment, GreedyPolicy, reset!

src/blox/neural_mass.jl

@@ -179,37 +179,6 @@ Citations:
 1. Liu C, Zhou C, Wang J, Fietkiewicz C, Loparo KA. The role of coupling connections in a model of the cortico-basal ganglia-thalamocortical neural loop for the generation of beta oscillations. Neural Netw. 2020 Mar;123:381-392. doi: 10.1016/j.neunet.2019.12.021.
 
 """
-struct JansenRitDelayed <: NeuralMassBlox
-    params
-    output
-    jcn
-    odesystem
-    namespace
-    function JansenRitDelayed(;name,
-                        namespace=nothing,
-                        τ=nothing, 
-                        H=nothing, 
-                        λ=nothing, 
-                        r=nothing, 
-                        cortical=true)
-
-        τ = isnothing(τ) ? (cortical ? 1 : 14) : τ
-        H = isnothing(H) ? 20.0 : H # H doesn't have different parameters for cortical and subcortical
-        λ = isnothing(λ) ? (cortical ? 5.0 : 400.0) : λ
-        r = isnothing(r) ? (cortical ? 0.15 : 0.1) : r
-
-        # p = progress_scope(τ, H, λ, r)
-        p = paramscoping(τ=τ, H=H, λ=λ, r=r)
-        τ, H, λ, r = p
-        sts = @variables x(..)=1.0 [output=true] y(t)=1.0 jcn(t)=0.0 [input=true] 
-        eqs = [D(x(t)) ~ y - ((2/τ)*x(t)),
-               D(y) ~ -x(t)/(τ*τ) + (H/τ)*((2*λ)/(1 + exp(-r*(jcn))) - λ)]
-        sys = System(eqs, name=name)
-        #can't use outputs because x(t) is Num by then
-        #wrote inputs similarly to keep consistent
-        new(p, sts[1], sts[3], sys, namespace)
-    end
-end
 
 """
     JansenRit(name, namespace, τ, H, λ, r, cortical)
@@ -249,7 +218,8 @@ struct JansenRit <: NeuralMassBlox
                         H=nothing, 
                         λ=nothing, 
                         r=nothing, 
-                        cortical=true)
+                        cortical=true, 
+                        delayed=false)
 
         τ = isnothing(τ) ? (cortical ? 1 : 14) : τ
         H = isnothing(H) ? 20.0 : H # H doesn't have different parameters for cortical and subcortical
@@ -259,13 +229,23 @@ struct JansenRit <: NeuralMassBlox
         # p = progress_scope(τ, H, λ, r)
         p = paramscoping(τ=τ, H=H, λ=λ, r=r)
         τ, H, λ, r = p
-        sts = @variables x(t)=1.0 [output=true] y(t)=1.0 jcn(t)=0.0 [input=true] 
-        eqs = [D(x) ~ y - ((2/τ)*x),
-               D(y) ~ -x/(τ*τ) + (H/τ)*((2*λ)/(1 + exp(-r*(jcn))) - λ)]
-        sys = System(eqs, name=name)
-        #can't use outputs because x(t) is Num by then
-        #wrote inputs similarly to keep consistent
-        new(p, sts[1], sts[3], sys, namespace)
+        if !delayed
+            sts = @variables x(t)=1.0 [output=true] y(t)=1.0 jcn(t)=0.0 [input=true] 
+            eqs = [D(x) ~ y - ((2/τ)*x),
+                   D(y) ~ -x/(τ*τ) + (H/τ)*((2*λ)/(1 + exp(-r*(jcn))) - λ)]
+            sys = System(eqs, name=name)
+            #can't use outputs because x(t) is Num by then
+            #wrote inputs similarly to keep consistent
+            return new(p, sts[1], sts[3], sys, namespace)
+        else
+            sts = @variables x(..)=1.0 [output=true] y(t)=1.0 jcn(t)=0.0 [input=true] 
+            eqs = [D(x(t)) ~ y - ((2/τ)*x(t)),
+                   D(y) ~ -x(t)/(τ*τ) + (H/τ)*((2*λ)/(1 + exp(-r*(jcn))) - λ)]
+            sys = System(eqs, name=name)
+            #can't use outputs because x(t) is Num by then
+            #wrote inputs similarly to keep consistent
+            return new(p, sts[1], sts[3], sys, namespace)
+        end
     end
 end