doc string changes

mne/decoding/search_light.py

@@ -345,7 +345,7 @@ def _sl_score(estimators, scoring, X, y):
     X : array, shape (n_samples, nd_features, n_estimators)
         The target data. The feature dimension can be multidimensional e.g.
         X.shape = (n_samples, n_features_1, n_features_2, n_estimators)
-    scoring : callable or None
+    scoring : callable, string or None
         If scoring is None (default), the predictions are internally
         generated by estimator.score(). Else, we must first get the
         predictions to pass them to ad-hoc scorer.
@@ -399,7 +399,7 @@ class GeneralizationLight(SearchLight):
     ----------
     base_estimator : object
         The base estimator to iteratively fit on a subset of the dataset.
-    scoring : callable, string, defaults to None
+    scoring : callable | string | None
         Score function (or loss function) with signature
         score_func(y, y_pred, **kwargs).
     n_jobs : int, optional (default=1)