diff --git a/Editor/Cluster_Drawer.cs b/Editor/Cluster_Drawer.cs
index d1e3778..acc8eb3 100644
--- a/Editor/Cluster_Drawer.cs
+++ b/Editor/Cluster_Drawer.cs
@@ -150,20 +150,20 @@ namespace NanoBrain.Unity {
             else if (selectedTarget is GameObject g)
                 gameObject = g;
 
-            // Handles.color = Color.yellow;
-            // if (Cluster_Drawer.currentClusterView.selectedSynapseNeuron != null) {
-            //     foreach (Cluster sibling in Cluster_Drawer.currentClusterView.selectedSynapseNeuron.parent.instances) {
-            //         Neuron siblingNeuron = sibling.GetNeuron(Cluster_Drawer.currentClusterView.selectedSynapseNeuron.name);
-            //         Vector3 worldVector = gameObject.transform.TransformVector(siblingNeuron.outputValue);
-            //         Handles.DrawLine(gameObject.transform.position, gameObject.transform.position + worldVector);
-            //     }
-            // }
-            // else {
-            //     if (Cluster_Drawer.currentClusterView.currentNucleus is Neuron currentNeuron) {
-            //         Vector3 worldVector = gameObject.transform.TransformVector(currentNeuron.outputValue);
-            //         Handles.DrawLine(gameObject.transform.position, gameObject.transform.position + worldVector);
-            //     }
-            // }
+            Handles.color = Color.yellow;
+            if (Cluster_Drawer.currentClusterView.selectedSynapseNeuron != null) {
+                foreach (Cluster sibling in Cluster_Drawer.currentClusterView.selectedSynapseNeuron.parent.instances) {
+                    Neuron siblingNeuron = sibling.GetNeuron(Cluster_Drawer.currentClusterView.selectedSynapseNeuron.name);
+                    Vector3 worldVector = gameObject.transform.TransformVector(siblingNeuron.outputValue);
+                    Handles.DrawLine(gameObject.transform.position, gameObject.transform.position + worldVector);
+                }
+            }
+            else {
+                if (Cluster_Drawer.currentClusterView.currentNucleus is Neuron currentNeuron) {
+                    Vector3 worldVector = gameObject.transform.TransformVector(currentNeuron.outputValue);
+                    Handles.DrawLine(gameObject.transform.position, gameObject.transform.position + worldVector);
+                }
+            }
         }
 
     }
diff --git a/Runtime/Scripts/Core/Neuron.cs b/Runtime/Scripts/Core/Neuron.cs
index c8a74e3..58e1946 100644
--- a/Runtime/Scripts/Core/Neuron.cs
+++ b/Runtime/Scripts/Core/Neuron.cs
@@ -355,14 +355,15 @@ namespace NanoBrain
             {
                 Debug.Break();
             }
-            var combination = Combinator(this.bias, this.synapses);
-            this.outputValue = Activator(combination);
+            this.combinationValue = Combinator(this.bias, this.synapses);
+            this.outputValue = Activator(this.combinationValue);
             this.lastUpdate = Time.time;
         }
 
         #region Combinator
 
 #if UNITY_MATHEMATICS
+        public float3 combinationValue;
 
         /// <summary>
         /// The combinator which combines the bias with the values from all synapses
@@ -418,6 +419,7 @@ namespace NanoBrain
         }
 
 #else
+        public Vector3 combinationValue;
 
         /// <summary>
         /// The combinator which combines the bias with the values from all synapses
@@ -716,9 +718,23 @@ namespace NanoBrain
             // loss is a derivative of error
             // Backpropagation = loss * d(combinator)
 
-            // Assuming linear activation function.
-            // Derivative of this (f'()) would be 1.
-            Vector3 delta2 = loss * 1;
+            Vector3 delta2;
+            switch (activator)
+            {
+                case ActivationType.Linear:
+                    // Derivative of this (f'()) would be 1.
+                    delta2 = loss * 1;
+                    break;
+                case ActivationType.Power:
+                    delta2 = loss * (2 * this.combinationValue);
+                    break;
+                case ActivationType.Reciprocal:
+                    delta2 = loss * (-1 / (this.combinationValue * this.combinationValue));
+                    break;
+                default:
+                    delta2 = loss;
+                    break;
+            }
 
             Vector3 scaledOutput = Vector3.Scale(delta2, synapse.neuron.outputValue);
             float deltaWeight = Mathf.Abs(scaledOutput.x) + Mathf.Abs(scaledOutput.y) + Mathf.Abs(scaledOutput.z);