diff --git a/src/spikeanalysis/analysis_utils/latency_functions.py b/src/spikeanalysis/analysis_utils/latency_functions.py
index a9dad4e..ccaead8 100644
--- a/src/spikeanalysis/analysis_utils/latency_functions.py
+++ b/src/spikeanalysis/analysis_utils/latency_functions.py
@@ -16,14 +16,14 @@ def latency_core_stats(bsl_fr: float, firing_data: np.array, time_bin_size: floa
             )
             if final_prob <= 10e-6:
                 break
-            elif n_bin * time_bin_size >= 0.200:  # past 200 ms is not really a true latency
+            elif n_bin * time_bin_size >= 0.400:  # past 400 ms is not really a true latency
                 n_bin = np.shape(firing_data)[1] - 2
                 break
 
-    if n_bin == np.shape(firing_data)[1] - 2:  # need to go to second last bin
-        latency[trial] = np.nan
-    else:
-        latency[trial] = (n_bin + 1) * time_bin_size
+        if n_bin == np.shape(firing_data)[1] - 2:  # need to go to second last bin
+            latency[trial] = np.nan
+        else:
+            latency[trial] = (n_bin + 1) * time_bin_size
 
     return latency
 
@@ -37,7 +37,7 @@ def latency_median(firing_counts: np.array, time_bin_size: float):
     latency = np.zeros((np.shape(firing_counts)[0]))
     for trial in range(np.shape(firing_counts)[0]):
         min_spike_time = np.nonzero(firing_counts[trial])[0]
-        if len(min_spike_time) == 0:
+        if len(min_spike_time) == 0 or (np.min(min_spike_time) + 1) * time_bin_size > 0.400:
             latency[trial] = np.nan
         else:
             latency[trial] = (np.min(min_spike_time) + 1) * time_bin_size
diff --git a/test/test_latency_functions.py b/test/test_latency_functions.py
index 030886c..556cbe2 100644
--- a/test/test_latency_functions.py
+++ b/test/test_latency_functions.py
@@ -49,9 +49,13 @@ def test_latency_median():
         ]
     )
     test_array = np.expand_dims(test_array, axis=0)
-    lat = lf.latency_median(test_array, time_bin_size=1)
+    lat = lf.latency_median(test_array, time_bin_size=0.1)
     print(lat)
-    assert lat == [3.0]
+    assert round(lat[0], 2) == 0.30
+
+    # nan test
+    lat = lf.latency_median(test_array, time_bin_size=1)
+    assert np.isnan(lat)
 
 
 def test_latency_nan():