diff --git a/Editor/ClusterEditor.cs b/Editor/ClusterEditor.cs
index fe182c8..d5aaf06 100644
--- a/Editor/ClusterEditor.cs
+++ b/Editor/ClusterEditor.cs
@@ -57,7 +57,7 @@ namespace NanoBrain.Unity {
                 versionProp.intValue++;
                 serializedObject.ApplyModifiedProperties();
                 EditorUtility.SetDirty(target);
-                Debug.Log($"{name} Prefab changed, version {versionProp.intValue}");
+                // Debug.Log($"{name} Prefab changed, version {versionProp.intValue}");
             }
 
         }
diff --git a/Runtime/Scripts/Core/Cluster.cs b/Runtime/Scripts/Core/Cluster.cs
index 18332e1..e93b7e4 100644
--- a/Runtime/Scripts/Core/Cluster.cs
+++ b/Runtime/Scripts/Core/Cluster.cs
@@ -157,7 +157,7 @@ namespace NanoBrain {
                             // Could not find the neuron in the cloned cluster
                             continue;
 
-                        clonedSender.AddReceiver(clonedNeuron, prefabSynapse.weight);
+                        clonedSender.AddReceiver(clonedNeuron, prefabSynapse.weight, prefabSynapse.trainable);
                         //Debug.Log($"Add synapse {clonedCluster.name}.{clonedSender.name} -> {clonedNeuron.name} [{clonedSender.receivers.Count}]");
                     }
                     else {
@@ -168,7 +168,7 @@ namespace NanoBrain {
                             continue;
 
                         // Copy the receivers which will also create the synapse
-                        clonedSender.AddReceiver(clonedNeuron, prefabSynapse.weight);
+                        clonedSender.AddReceiver(clonedNeuron, prefabSynapse.weight, prefabSynapse.trainable);
                         // Debug.Log($"Add synapse {clonedSender.name} -> {clonedNeuron.name}");
                     }
                 }
diff --git a/Runtime/Scripts/Core/Neuron.cs b/Runtime/Scripts/Core/Neuron.cs
index b5ebda2..9a9ccef 100644
--- a/Runtime/Scripts/Core/Neuron.cs
+++ b/Runtime/Scripts/Core/Neuron.cs
@@ -63,8 +63,10 @@ namespace NanoBrain {
         /// <param name="weight">The weight applied to the input. Default value = 1</param>
         /// <returns>The created Synapse</returns>
         /// This will add a new input to this nucleus with the given weight.
-        public Synapse AddSynapse(Neuron sendingNucleus, float weight = 1) {
-            Synapse synapse = new(sendingNucleus, weight);
+        public Synapse AddSynapse(Neuron sendingNucleus, float weight = 1, bool trainable = false) {
+            Synapse synapse = new(sendingNucleus, weight) {
+                trainable = trainable
+            };
             this.synapses.Add(synapse);
             return synapse;
         }
@@ -627,11 +629,11 @@ namespace NanoBrain {
         /// </summary>
         /// <param name="receiverToAdd">The receiver to add</param>
         /// <param name="weight">The weight to use for the synapse to his neuron</param>
-        public virtual void AddReceiver(Nucleus receiverToAdd, float weight = 1) {
+        public virtual void AddReceiver(Nucleus receiverToAdd, float weight = 1, bool trainable = false) {
             if (receiverToAdd is not Neuron receiverNeuron)
                 return;
             this._receivers.Add(receiverNeuron);
-            receiverNeuron.AddSynapse(this, weight);
+            receiverNeuron.AddSynapse(this, weight, trainable);
             //Debug.Log($"Add synapse {this.clusterPrefab.name}.{this.name} -> {receiverToAdd.name} --- [{this.receivers.Count}]");
 
         }
@@ -762,25 +764,26 @@ namespace NanoBrain {
             this.bias -= stepSize;
 
             foreach (Synapse synapse in this.synapses) {
-                // derivative for the weight?
-                float3 deltaSynapse = derivative; // dSSR/dActivator
+                synapse.BackPropagation(length(derivative), learningRate);
+                // // derivative for the weight?
+                // float3 deltaSynapse = derivative; // dSSR/dActivator
 
-                // derivative for the activator
-                // dActivator/dCombinator
-                switch (activator) {
-                    case ActivationType.Linear:
-                        //deltaSynapse *= 1;
-                        break;
-                    default:
-                        break;
-                }
+                // // derivative for the activator
+                // // dActivator/dCombinator
+                // switch (activator) {
+                //     case ActivationType.Linear:
+                //         //deltaSynapse *= 1;
+                //         break;
+                //     default:
+                //         break;
+                // }
 
-                // derivative for the previous activation
-                // dCombinator/dWeight
-                deltaSynapse *= synapse.neuron.activation;
+                // // derivative for the previous activation
+                // // dCombinator/dWeight
+                // deltaSynapse *= synapse.neuron.activation;
 
-                float deltaWeight = length(deltaSynapse);
-                synapse.weight += learningRate * deltaWeight;
+                // float deltaWeight = length(deltaSynapse);
+                // synapse.weight += learningRate * deltaWeight;
 
                 BackPropagation2(derivative * synapse.weight, learningRate);
             }
diff --git a/Runtime/Scripts/Core/Synapse.cs b/Runtime/Scripts/Core/Synapse.cs
index 5cca04a..22ee378 100644
--- a/Runtime/Scripts/Core/Synapse.cs
+++ b/Runtime/Scripts/Core/Synapse.cs
@@ -13,6 +13,7 @@ namespace NanoBrain {
         /// The neuron from which input is received
         /// </summary>
         [SerializeReference]
+        [HideInInspector]
         public Neuron neuron;
 
         /// <summary>
@@ -32,7 +33,7 @@ namespace NanoBrain {
             this.weight = weight;
         }
 
-        public virtual void BasicBackPropagation(float error, float learningRate) {
+        public virtual void BackPropagation(float error, float learningRate) {
             float derivative = error;
             switch (neuron.activator) {
                 case Neuron.ActivationType.Linear: