diff --git a/src/Modules/Neuron/layout.py b/src/Modules/Neuron/layout.py
index 1b882797ae3052b48b3b43730c5de365632c4f49..747874158c968582ddaa89f99a63a8da39a201a1 100755
--- a/src/Modules/Neuron/layout.py
+++ b/src/Modules/Neuron/layout.py
@@ -23,7 +23,6 @@ class layout(layoutOp):
     xAxisPotentialGraph = dict()
     yAxisSpikeNbrGraph = dict()
     yAxisPotentialGraph = dict()
-    SpikePerNeuron = None
 
     def clearData(self, indexes):
         """ Clear the data when moved forward or backward for more than one step
@@ -59,7 +58,6 @@ class layout(layoutOp):
             self.clearData([])
             if self.g.config.DEBUG:
                 print("neuron-vis")
-            self.SpikePerNeuron = self.getSpikePerNeuron(self.g)
             layer = dbc.Card(
                 dbc.CardBody(
                     [
@@ -115,7 +113,7 @@ class layout(layoutOp):
                 'title': 'No Labels detected'}}
         else:
 
-            data = self.SpikePerNeuron
+            data = self.getSpikePerNeuron(self.g)
 
             total = 0
 
@@ -124,11 +122,9 @@ class layout(layoutOp):
 
             xx = [N["i"]["N"] for N in data]
             yy = [(count["count"]/total) for count in data]
-            zz = [int(c["Label"]) for i, c in product(data, g.finalLabels) if (
-                int(c["N"]) == int(i["i"]["N"]) and c["L"] == i["i"]["L"])]
+            zz = [int(c["Label"]) for i, c in product(data, g.finalLabels) if (int(c["N"]) == int(i["i"]["N"]) and c["L"] == i["i"]["L"])]
 
             labels = list(dict.fromkeys(zz))
-
             items = [[[item[0], item[1], item[2]]
                       for item in zip(xx, yy, zz) if item[2] == x] for x in labels]
 
@@ -181,12 +177,11 @@ class layout(layoutOp):
             return {'data': [],
                     'layout': {'margin': {'l': 0, 'r': 0, 't': 30, 'b': 0}}}
         else:
-            data = self.SpikePerNeuron
-            data = [d for d, l in product(data, g.finalLabels) if (
-                int(l["N"]) == d['i']['N'] and int(l["Label"]) == filteredClass["z"])]
+            data = self.getSpikePerNeuron(self.g)
+            data = [d for d, l in product(data, g.finalLabels) 
+                    if (l["N"] == d['i']['N'] and l["Label"] == filteredClass["z"])]
             xx = [N["i"]["N"] for N in data]
             yy = [count["count"] for count in data]
-
             graph = {'data': [go.Bar(
                 x=[x for x in range(len(xx))],
                 y=yy,