diff --git a/neuralpredictors/layers/readouts/multi_readout.py b/neuralpredictors/layers/readouts/multi_readout.py
index 24c7b715..26136965 100644
--- a/neuralpredictors/layers/readouts/multi_readout.py
+++ b/neuralpredictors/layers/readouts/multi_readout.py
@@ -86,37 +86,40 @@ class MultiReadoutSharedParametersBase(MultiReadoutBase):
     For more information on which parameters can be shared, refer for example to the FullGaussian2d readout
     """
 
-    def prepare_readout_kwargs(self, i, data_key, first_data_key, **kwargs):
+    def prepare_readout_kwargs(
+        self,
+        i,
+        data_key,
+        first_data_key,
+        grid_mean_predictor=None,
+        grid_mean_predictor_type=None,
+        share_transform=False,
+        share_grid=False,
+        share_features=False,
+        **kwargs
+    ):
         readout_kwargs = kwargs.copy()
 
-        if "grid_mean_predictor" in readout_kwargs:
-            if readout_kwargs["grid_mean_predictor"] is not None:
-                if readout_kwargs["grid_mean_predictor_type"] == "cortex":
-                    readout_kwargs["source_grid"] = readout_kwargs["source_grids"][data_key]
-                else:
-                    raise KeyError(
-                        "grid mean predictor {} does not exist".format(readout_kwargs["grid_mean_predictor_type"])
-                    )
-                if readout_kwargs["share_transform"]:
-                    readout_kwargs["shared_transform"] = None if i == 0 else self[first_data_key].mu_transform
-
-            elif readout_kwargs["share_grid"]:
-                readout_kwargs["shared_grid"] = {
-                    "match_ids": readout_kwargs["shared_match_ids"][data_key],
-                    "shared_grid": None if i == 0 else self[first_data_key].shared_grid,
-                }
-
-            del readout_kwargs["share_transform"]
-            del readout_kwargs["share_grid"]
-            del readout_kwargs["grid_mean_predictor_type"]
-
-        if "share_features" in readout_kwargs:
-            if readout_kwargs["share_features"]:
-                readout_kwargs["shared_features"] = {
-                    "match_ids": readout_kwargs["shared_match_ids"][data_key],
-                    "shared_features": None if i == 0 else self[first_data_key].shared_features,
-                }
+        if grid_mean_predictor:
+            if grid_mean_predictor_type == "cortex":
+                readout_kwargs["source_grid"] = readout_kwargs["source_grids"][data_key]
+                readout_kwargs["grid_mean_predictor"] = grid_mean_predictor
             else:
-                readout_kwargs["shared_features"] = None
-            del readout_kwargs["share_features"]
+                raise KeyError("grid mean predictor {} does not exist".format(grid_mean_predictor_type))
+            if share_transform:
+                readout_kwargs["shared_transform"] = None if i == 0 else self[first_data_key].mu_transform
+
+        elif share_grid:
+            readout_kwargs["shared_grid"] = {
+                "match_ids": readout_kwargs["shared_match_ids"][data_key],
+                "shared_grid": None if i == 0 else self[first_data_key].shared_grid,
+            }
+
+        if share_features:
+            readout_kwargs["shared_features"] = {
+                "match_ids": readout_kwargs["shared_match_ids"][data_key],
+                "shared_features": None if i == 0 else self[first_data_key].shared_features,
+            }
+        else:
+            readout_kwargs["shared_features"] = None
         return readout_kwargs