diff --git a/Scintillator/ScintDigiAlgs/python/ScintDigiAlgsConfig.py b/Scintillator/ScintDigiAlgs/python/ScintDigiAlgsConfig.py
index ddf3074618aff121e704b2214309a14952436837..031fdd92eca1f89b2148cfcb170c6f0714d56611 100644
--- a/Scintillator/ScintDigiAlgs/python/ScintDigiAlgsConfig.py
+++ b/Scintillator/ScintDigiAlgs/python/ScintDigiAlgsConfig.py
@@ -11,12 +11,15 @@ from WaveformConditionsTools.WaveformCableMappingConfig import WaveformCableMapp
 # Crystalball function Parameters estimated from Deion's slides uploaded at
 # https://indico.cern.ch/event/1099652/contributions/4626975/attachments/2352595/4013927/Faser-Physics-run3933-plots.pdf  (20/01/2022)
 # Parameters are per scintillator source, but not per channel.
+# Updated aamplitudes (norm) to match testbeam response
+# Make everything except VetoNu look like the preshower
 dict_CB_param = {}
-dict_CB_param["Trigger"]=dict(CB_alpha=-0.38, CB_n=25, CB_mean=815, CB_sigma=7.7, CB_norm = 500 )
-dict_CB_param["Timing"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=846, CB_sigma=5.3, CB_norm = 500) # copy from Preshower; Timing was not in TestBeam
-dict_CB_param["Veto"]=dict(CB_alpha=-0.38, CB_n=25, CB_mean=815, CB_sigma=7.7, CB_norm = 1000) # copy from Trigger; Veto was not in TestBeam, but in sim "Veto" is the TestBeam Trigger component
-dict_CB_param["VetoNu"]=dict(CB_alpha=-0.38, CB_n=25, CB_mean=815, CB_sigma=7.7, CB_norm = 1000) # copy from Trigger; Veto was not in TestBeam, but in sim "Veto" is the TestBeam Trigger component
-dict_CB_param["Preshower"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=846, CB_sigma=5.3, CB_norm = 500)
+dict_CB_param["VetoNu"]=dict(CB_alpha=-0.38, CB_n=25, CB_mean=815, CB_sigma=7.7, CB_norm = 13300) 
+
+dict_CB_param["Preshower"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=846, CB_sigma=5.3, CB_norm = 330)
+dict_CB_param["Trigger"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=815, CB_sigma=5.3, CB_norm = 330 )
+dict_CB_param["Timing"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=815, CB_sigma=5.3, CB_norm = 330)
+dict_CB_param["Veto"]=dict(CB_alpha=-0.32, CB_n=65, CB_mean=815, CB_sigma=5.3, CB_norm = 330) 
 
 dict_baseline_params = {
     "Trigger"   : {"mean" : 15000, "rms" : 3},