diff --git a/Cell_behavior_initial_steps/Uni_cell.py b/Cell_behavior_initial_steps/Uni_cell.py
new file mode 100644
index 0000000000000000000000000000000000000000..9abe05633008e8e3edbd0d4e3b9addd9897cae4f
--- /dev/null
+++ b/Cell_behavior_initial_steps/Uni_cell.py
@@ -0,0 +1,71 @@
+#Single cell migration giving a trace of the path it takes
+
+import numpy as np
+import pickle 
+import random 
+import matplotlib.pyplot as ptl
+import copy
+from matplotlib import pyplot as plt
+import random
+from scipy import ndimage
+from bio2mslib.inout.inout import WriteData as WD
+import os
+
+#Empty matrix size declaration
+lengthx = 12
+lengthy = 12
+G= np.zeros((lengthx,lengthy))
+ST = copy.deepcopy(G)
+
+
+#Loop to add the \ surface 
+for i in range (0,12):
+    for j in range (0,12):
+        if (i == j):
+            ST[i,j]=0.5
+
+#Pickle of the obtained matrix
+with open('Cell_grid.pkl', 'wb') as csv_file:
+    pickle.dump(ST,csv_file)
+
+with open('Cell_grid.pkl', 'rb') as csv_file:
+    data_saved = pickle.load(csv_file)
+Z = copy.deepcopy(ST)
+
+im2 = plt.imshow(Z, cmap="copper_r")
+plt.show()
+
+#incertion of a single cell to track its movement based on the simpspn model
+uni_cell = Z[(5,4)]
+Z[(5,4)] = 1
+iter = 1
+itermax = 3
+im2 = plt.imshow(Z, cmap="copper_r")
+plt.show()
+while iter<= itermax:
+    for i in range(0,12):
+        for j in range(0,12):
+    #         if Zcopy[im,jm]>= 1:
+    #             Zcopyinitial = copy.deepcopy(Zcopy[im,jm])
+
+            h = random.randint(-1,1) #horizontal value for the movement of the cell
+            v = random.randint(-1,1) #vertival value for the movement of the cell
+            if Z[i,j]==1 and (h != 0 or v!= 0):
+                Z[i,j]= 0.7    
+                Z[h + i, v + j]= 1
+                    
+        
+                    #Print the image to locate the cell each iteration.
+                    #Saving the file of pickle
+                im2 = plt.imshow(Z, cmap="copper_r") 
+                plt.show()
+                with open('Cell_migration_'+str(iter)+'.pkl', 'wb') as csv_file:
+                    pickle.dump(Z,csv_file)
+                iter +=1
+                 
+
+
+
+
+
+