+ perceptron

HH_functions.py

@@ -0,0 +1,47 @@
+import numpy as np
+
+def alphaM(V):
+    return (2.5-0.1*(V+65)) / (np.exp(2.5-0.1*(V+65)) -1)
+
+def betaM(V):
+    return 4*np.exp(-(V+65)/18)
+
+def alphaH(V):
+    return 0.07*np.exp(-(V+65)/20)
+
+def betaH(V):
+    return 1/(np.exp(3.0-0.1*(V+65))+1)
+
+def alphaN(V):
+    return (0.1-0.01*(V+65)) / (np.exp(1-0.1*(V+65)) -1)
+
+def betaN(V):
+    return 0.125*np.exp(-(V+65)/80)
+
+def HH(I0,T0):
+    dt = 0.01;
+    T  = int(np.ceil(T0/dt))  # [ms]
+    gNa0 = 120   # [mS/cm^2]
+    ENa  = 115;  # [mV]
+    gK0  = 36;   # [mS/cm^2]
+    EK   = -12;  # [mV]
+    gL0  = 0.3;  # [mS/cm^2]
+    EL   = 10.6; # [mV]
+
+    t = np.arange(0,T)*dt
+    V = np.zeros([T,1])
+    m = np.zeros([T,1])
+    h = np.zeros([T,1])
+    n = np.zeros([T,1])
+
+    V[0]=-70.0
+    m[0]=0.05
+    h[0]=0.54
+    n[0]=0.34
+
+    for i in range(0,T-1):
+        V[i+1] = V[i] + dt*(gNa0*m[i]**3*h[i]*(ENa-(V[i]+65)) + gK0*n[i]**4*(EK-(V[i]+65)) + gL0*(EL-(V[i]+65)) + I0);
+        m[i+1] = m[i] + dt*(alphaM(V[i])*(1-m[i]) - betaM(V[i])*m[i]);
+        h[i+1] = h[i] + dt*(alphaH(V[i])*(1-h[i]) - betaH(V[i])*h[i]);
+        n[i+1] = n[i] + dt*(alphaN(V[i])*(1-n[i]) - betaN(V[i])*n[i]);
+    return V,m,h,n,t

IF.ipynb

@@ -5,6 +5,7 @@
    "metadata": {},
    "source": [
     "---\n",
+    "title: \"Integrate and Fire Neuron\"\n",
     "project:\n",
     "  type: website\n",
     "format:\n",