diff --git a/hippocampy/detectors.py b/hippocampy/detectors.py
index e6a5863..585cd44 100644
--- a/hippocampy/detectors.py
+++ b/hippocampy/detectors.py
@@ -139,7 +139,7 @@ def sce(
     ## TO DO
     # check the IV from and to bool it seem wrong
     # incorporate the restrict to quiet period
-    T = np.array(T)
+    T = np.array(T, dtype=bool)
     window_len_samples = int(window_len * fs)
     n_cells, n_samples = T.shape
 
@@ -159,7 +159,9 @@ def sce(
             )
 
     T_sum = bn.move_sum(T, window_len_samples, axis=1)
-    T_sum_shuff = bn.move_sum(T_shuff, window_len_samples, axis=1)  # , min_count=1
+    T_sum_shuff = bn.move_sum(T_shuff, window_len_samples, axis=1)  # , min_count=12
+
+    # we could restrict the previous vectors here
 
     # now we could to a percentile of the shuffling
     avg = bn.nansum(T_sum, axis=0)
diff --git a/hippocampy/utils/gen_utils.py b/hippocampy/utils/gen_utils.py
index b374f2d..ee8d56e 100644
--- a/hippocampy/utils/gen_utils.py
+++ b/hippocampy/utils/gen_utils.py
@@ -47,7 +47,7 @@ def start_stop(B: np.ndarray, axis=-1):
     stops: np.ndarray
         boolean array with True values for stops     
     """
-    B = np.array(B, dtype=bool, ndmin=2)
+    B = np.array(B, ndmin=2)
     start = np.empty_like(B, dtype=bool)
     stop = np.empty_like(B, dtype=bool)
 
diff --git a/hippocampy/wavelet.py b/hippocampy/wavelet.py
index f20bc8c..1c04845 100644
--- a/hippocampy/wavelet.py
+++ b/hippocampy/wavelet.py
@@ -88,7 +88,7 @@ def _calc_sigma(coeffs, scaling, axis):
 def wden(
     data,
     *,
-    wavelet_name="sym5",
+    wavelet_name="sym4",
     level=None,
     noise_est_method="sqtwolog",
     scaling="mln",