diff --git a/examples/plot_rat_hippocampus_foraging.py b/examples/plot_rat_hippocampus_foraging.py
index 432c2f7..b718431 100644
--- a/examples/plot_rat_hippocampus_foraging.py
+++ b/examples/plot_rat_hippocampus_foraging.py
@@ -1,9 +1,9 @@
 #!/usr/bin/env python
 """
-Decode location from CA1 activity
+Dataset: CA1 activity during foraging
 ==============================
 
-This is an example of how to decode location in a free field from CA1 activity
+This is an example of how to access data recorded from CA1 during open field foraging
 
 """
 
@@ -15,37 +15,20 @@
 # Let's plot the path in the free field
 
 import matplotlib.pyplot as plt
-plt.plot(dataset.location['x'], dataset.location['y'], alpha=0.5)
+plt.plot(dataset.location['x'], dataset.location['y'])
 plt.axis('equal')
 plt.show()
 
 #########################################
-# Create a feature vector for each time point in the location data
+# Create a feature vector, binning spikes for each time point
 
 from neuroglia.spike import Binner
 
 binner = Binner(sample_times=dataset.location['time'])
 response = binner.fit_transform(dataset.spikes)
-print(response.head())
 
 #########################################
-# create feature
+# Plot CA1 activity
 
-
-from sklearn.linear_model import LinearRegression
-lm = LinearRegression()
-
-split = int(len(response)/2)
-
-X_train = response.values[:split]
-y_train = dataset.location['x'].values[:split]
-
-lm.fit(X_train,y_train)
-
-
-X_test = response.values[split:]
-y_test = dataset.location['x'].values[split:-1]
-y_pred = lm.predict(X_test)
-plt.plot(y_test[:100])
-plt.plot(y_pred[:100])
+response.plot()
 plt.show()