diff --git a/coursera_compneuro/w2quiz2_code_python3.4/c1p8.pickle b/coursera_compneuro/w2quiz2_code_python3.4/c1p8.pickle
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diff --git a/coursera_compneuro/w2quiz2_code_python3.4/c1p8.pickle b/coursera_compneuro/w2quiz2_code_python3.4/c1p8.pickle
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diff --git a/coursera_compneuro/w2quiz2_code_python3.4/compute_sta.py b/coursera_compneuro/w2quiz2_code_python3.4/compute_sta.py
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+"""
+Created on Wed Apr 22 15:21:11 2015
+
+Code to compute spike-triggered average.
+"""
+
+from __future__ import division
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+def compute_sta(stim, rho, num_timesteps):
+    """Compute the spike-triggered average from a stimulus and spike-train.
+    
+    Args:
+        stim: stimulus time-series
+        rho: spike-train time-series
+        num_timesteps: how many timesteps to use in STA
+        
+    Returns:
+        spike-triggered average for num_timesteps timesteps before spike"""
+    
+    sta = np.zeros((num_timesteps,))
+
+    # This command finds the indices of all of the spikes that occur
+    # after 300 ms into the recording.
+    spike_times = rho[num_timesteps:].nonzero()[0] + num_timesteps
+
+    # Fill in this value. Note that you should not count spikes that occur
+    # before 300 ms into the recording.
+    num_spikes = rho[150:].sum()
+    
+    # Compute the spike-triggered average of the spikes found.
+    # To do this, compute the average of all of the vectors
+    # starting 300 ms (exclusive) before a spike and ending at the time of
+    # the event (inclusive). Each of these vectors defines a list of
+    # samples that is contained within a window of 300 ms before each
+    # spike. The average of these vectors should be completed in an
+    # element-wise manner.
+    # 
+    # Your code goes here.
+
+
+    print('num of spikes for STA:', num_spikes)
+    for sp in range(num_spikes):
+        t = spike_times[sp]
+        w = stim[t-150:t].T
+        sta = sta + w
+    sta = sta / num_spikes
+    return sta
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diff --git a/coursera_compneuro/w2quiz2_code_python3.4/c1p8.pickle b/coursera_compneuro/w2quiz2_code_python3.4/c1p8.pickle
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diff --git a/coursera_compneuro/w2quiz2_code_python3.4/compute_sta.py b/coursera_compneuro/w2quiz2_code_python3.4/compute_sta.py
new file mode 100644
index 0000000..73ef670
--- /dev/null
+++ b/coursera_compneuro/w2quiz2_code_python3.4/compute_sta.py
@@ -0,0 +1,50 @@
+"""
+Created on Wed Apr 22 15:21:11 2015
+
+Code to compute spike-triggered average.
+"""
+
+from __future__ import division
+import numpy as np
+import matplotlib.pyplot as plt
+
+
+def compute_sta(stim, rho, num_timesteps):
+    """Compute the spike-triggered average from a stimulus and spike-train.
+    
+    Args:
+        stim: stimulus time-series
+        rho: spike-train time-series
+        num_timesteps: how many timesteps to use in STA
+        
+    Returns:
+        spike-triggered average for num_timesteps timesteps before spike"""
+    
+    sta = np.zeros((num_timesteps,))
+
+    # This command finds the indices of all of the spikes that occur
+    # after 300 ms into the recording.
+    spike_times = rho[num_timesteps:].nonzero()[0] + num_timesteps
+
+    # Fill in this value. Note that you should not count spikes that occur
+    # before 300 ms into the recording.
+    num_spikes = rho[150:].sum()
+    
+    # Compute the spike-triggered average of the spikes found.
+    # To do this, compute the average of all of the vectors
+    # starting 300 ms (exclusive) before a spike and ending at the time of
+    # the event (inclusive). Each of these vectors defines a list of
+    # samples that is contained within a window of 300 ms before each
+    # spike. The average of these vectors should be completed in an
+    # element-wise manner.
+    # 
+    # Your code goes here.
+
+
+    print('num of spikes for STA:', num_spikes)
+    for sp in range(num_spikes):
+        t = spike_times[sp]
+        w = stim[t-150:t].T
+        sta = sta + w
+    sta = sta / num_spikes
+    return sta
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diff --git a/coursera_compneuro/w2quiz2_code_python3.4/quiz2.py b/coursera_compneuro/w2quiz2_code_python3.4/quiz2.py
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+++ b/coursera_compneuro/w2quiz2_code_python3.4/quiz2.py
@@ -0,0 +1,38 @@
+# %%
+"""
+Created on Wed Apr 22 15:15:16 2015
+
+Quiz 2 code.
+"""
+
+from __future__ import division
+import numpy as np
+import matplotlib.pyplot as plt
+
+import pickle
+
+from compute_sta import compute_sta
+
+
+FILENAME = 'c1p8.pickle'
+
+with open(FILENAME, 'rb') as f:
+    data = pickle.load(f)
+
+stim = data['stim']
+rho = data['rho']
+
+# Fill in these values
+sampling_period = 2 # in ms
+num_timesteps = 150
+
+sta = compute_sta(stim, rho, num_timesteps)
+
+time = (np.arange(-num_timesteps, 0) + 1) * sampling_period
+
+plt.plot(time, sta)
+plt.xlabel('Time (ms)')
+plt.ylabel('Stimulus')
+plt.title('Spike-Triggered Average')
+
+plt.show()
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