diff --git a/src/spikeinterface/preprocessing/tests/test_zero_padding.py b/src/spikeinterface/preprocessing/tests/test_zero_padding.py
index 75d64b0088..a2fc890c74 100644
--- a/src/spikeinterface/preprocessing/tests/test_zero_padding.py
+++ b/src/spikeinterface/preprocessing/tests/test_zero_padding.py
@@ -6,7 +6,7 @@
 from spikeinterface.core import generate_recording
 from spikeinterface.core.numpyextractors import NumpyRecording
 
-from spikeinterface.preprocessing import zero_channel_pad
+from spikeinterface.preprocessing import zero_channel_pad, bandpass_filter, common_reference
 from spikeinterface.preprocessing.zero_channel_pad import TracePaddedRecording
 
 if hasattr(pytest, "global_test_folder"):
@@ -39,7 +39,7 @@ def test_zero_padding_channel():
 @pytest.fixture
 def recording():
     num_channels = 4
-    num_samples = 10
+    num_samples = 10000
     rng = np.random.default_rng(seed=0)
     traces = rng.random(size=(num_samples, num_channels))
     traces_list = [traces]
@@ -258,5 +258,77 @@ def test_trace_padded_recording_retrieve_traces_with_partial_padding(recording,
     assert np.allclose(padded_traces_end, expected_zeros)
 
 
+@pytest.mark.parametrize("padding_start, padding_end", [(5000, 5000), (5000, 0), (0, 5000)])
+def test_trace_padded_recording_retrieve_full_recording_with_preprocessing(recording, padding_start, padding_end):
+    num_samples = recording.get_num_samples()
+    num_channels = recording.get_num_channels()
+
+    recording = bandpass_filter(recording, freq_min=300, freq_max=6000)
+
+    padded_recording = TracePaddedRecording(
+        parent_recording=recording,
+        padding_start=padding_start,
+        padding_end=padding_end,
+    )
+
+    # Cycle through the whole recording, using get_traces() to pull chunks of
+    # size `step`. This emulates the processing of writing to a binary file.
+    # Data that lie within the padding region should be fill value only, while
+    # data from original trace should match exactly. Note that the step
+    # size must be chosen to retreieve data that is purely padding or original data
+    step = 1000
+    start_frames = np.arange(padded_recording.get_num_samples(), step=step)
+    end_frames = start_frames + step
+
+    for start_frame, end_frame in zip(start_frames, end_frames):
+        padded_trace = padded_recording.get_traces(start_frame=start_frame, end_frame=end_frame)
+
+        end_padding_region_first_idx = padding_start + num_samples
+
+        if padding_start <= start_frame < end_padding_region_first_idx:
+            original_trace = recording.get_traces(
+                start_frame=start_frame - padding_start, end_frame=end_frame - padding_start
+            )
+            assert np.allclose(padded_trace, original_trace, rtol=0, atol=1e-10)
+        else:
+            assert np.all(padded_trace == padded_recording.fill_value)
+
+
+@pytest.mark.parametrize("padding_start, padding_end", [(5000, 5000), (5000, 0), (0, 5000)])
+def test_trace_padded_recording_retrieve_full_recording_with_preprocessing(recording, padding_start, padding_end):
+    num_samples = recording.get_num_samples()
+    num_channels = recording.get_num_channels()
+
+    recording = bandpass_filter(recording, freq_min=300, freq_max=6000)
+
+    padded_recording = TracePaddedRecording(
+        parent_recording=recording,
+        padding_start=padding_start,
+        padding_end=padding_end,
+    )
+
+    # Cycle through the whole recording, using get_traces() to pull chunks of
+    # size `step`. This emulates the processing of writing to a binary file.
+    # Data that lie within the padding region should be fill value only, while
+    # data from original trace should match exactly. Note that the step
+    # size must be chosen to retreieve data that is purely padding or original data
+    step = 1000
+    start_frames = np.arange(padded_recording.get_num_samples(), step=step)
+    end_frames = start_frames + step
+
+    for start_frame, end_frame in zip(start_frames, end_frames):
+        padded_trace = padded_recording.get_traces(start_frame=start_frame, end_frame=end_frame)
+
+        end_padding_region_first_idx = padding_start + num_samples
+
+        if padding_start <= start_frame < end_padding_region_first_idx:
+            original_trace = recording.get_traces(
+                start_frame=start_frame - padding_start, end_frame=end_frame - padding_start
+            )
+            assert np.allclose(padded_trace, original_trace, rtol=0, atol=1e-10)
+        else:
+            assert np.all(padded_trace == padded_recording.fill_value)
+
+
 if __name__ == "__main__":
     test_zero_padding_channel()