diff --git a/strax/dtypes.py b/strax/dtypes.py
index 9f326981..b18bfa57 100644
--- a/strax/dtypes.py
+++ b/strax/dtypes.py
@@ -164,9 +164,9 @@ def peak_dtype(
     n_channels=100,
     n_sum_wv_samples=200,
     n_widths=11,
-    store_data_top=True,
     hits_timing=True,
-    save_waveform_start=True,
+    store_data_top=True,
+    store_data_start=True,
 ):
     """Data type for peaks - ranges across all channels in a detector
     Remember to set channel to -1 (todo: make enum)
@@ -212,7 +212,7 @@ def peak_dtype(
         )
         dtype.insert(9, top_field)
 
-    if save_waveform_start:
+    if store_data_start:
         start_field = (
             (
                 "Waveform data in PE/sample (not PE/ns!), first 200 not downsampled samples",
diff --git a/strax/processing/peak_splitting.py b/strax/processing/peak_splitting.py
index a1d8aa51..9f6338f5 100644
--- a/strax/processing/peak_splitting.py
+++ b/strax/processing/peak_splitting.py
@@ -147,8 +147,8 @@ def __call__(
                     records,
                     rlinks,
                     to_pe,
-                    n_top_channels,
-                    store_data_start,
+                    n_top_channels=n_top_channels,
+                    store_data_start=store_data_start,
                 )
                 strax.compute_widths(new_peaks)
             elif data_type == "hitlets":
diff --git a/tests/test_peak_processing.py b/tests/test_peak_processing.py
index a0fde4b4..2040f593 100644
--- a/tests/test_peak_processing.py
+++ b/tests/test_peak_processing.py
@@ -88,7 +88,7 @@ def test_sum_waveform(records):
         min_channels=1,
         max_duration=10_000_000,
     )
-    strax.sum_waveform(peaks, hits, records, rlinks, np.ones(n_ch), n_top_channels)
+    strax.sum_waveform(peaks, hits, records, rlinks, np.ones(n_ch), n_top_channels=n_top_channels)
 
     for p in peaks:
         # Area measures must be consistent
@@ -117,7 +117,7 @@ def test_sum_waveform(records):
             records,
             rlinks,
             np.ones(n_ch),
-            n_top_channels,
+            n_top_channels=n_top_channels,
             select_peaks_indices=np.array([0]),
         )