diff --git a/meggie/actions/evoked_group_average/controller/evoked.py b/meggie/actions/evoked_group_average/controller/evoked.py
index aa964182..60d030ef 100644
--- a/meggie/actions/evoked_group_average/controller/evoked.py
+++ b/meggie/actions/evoked_group_average/controller/evoked.py
@@ -34,6 +34,36 @@ def group_average_evoked(experiment, evoked_name, groups, new_name):
 
     assert_arrays_same(time_arrays)
 
+    # handle channel differences
+    ch_names = []
+    for group_key, group_subjects in groups.items():
+        for subject_name in group_subjects:
+            try:
+                subject = experiment.subjects.get(subject_name)
+                evoked = subject.evoked.get(evoked_name)
+
+                mne_evokeds = evoked.content
+                for mne_evoked in mne_evokeds.values():
+                    ch_idxs = mne.pick_types(mne_evoked.info, meg=True, eeg=True)
+                    ch_names.append(tuple(
+                        [ch_name for ch_idx, ch_name
+                         in enumerate(mne_evoked.info['ch_names'])
+                         if ch_idx in ch_idxs]
+                    ))
+            except Exception as exc:
+                continue
+
+    if len(set(ch_names)) != 1:
+        logging.getLogger('ui_logger').debug(
+            "Evokeds contain different sets of good channels. Identifying common ones..")
+
+        common_ch_names = list(set.intersection(*map(set, ch_names)))
+
+        logging.getLogger('ui_logger').debug(
+            str(len(common_ch_names)) + ' common channels found.')
+    else:
+        common_ch_names = ch_names[0]
+
     grand_evokeds = {}
     for group_key, group_subjects in groups.items():
         for subject in experiment.subjects.values():
@@ -51,7 +81,9 @@ def group_average_evoked(experiment, evoked_name, groups, new_name):
 
                 if grand_key not in grand_evokeds:
                     grand_evokeds[grand_key] = []
-                grand_evokeds[grand_key].append(evoked_item)
+                grand_evokeds[grand_key].append(
+                    evoked_item.copy().pick(common_ch_names)
+                )
 
     grand_averages = {}
     new_keys = []
@@ -63,10 +95,13 @@ def group_average_evoked(experiment, evoked_name, groups, new_name):
             grand_averages[new_key] = mne.grand_average(grand_evoked)
         new_keys.append(new_key)
 
-    subject = experiment.active_subject
+    # to avoid mne complaints, set dev_head_t manually to same for all
+    keys = sorted(grand_averages.keys())
+    for key in keys:
+        grand_averages[key].info['dev_head_t'] = grand_averages[keys[0]].info['dev_head_t']
 
+    subject = experiment.active_subject
     evoked_directory = subject.evoked_directory
-
     params = {'conditions': new_keys,
               'groups': groups}
 
diff --git a/meggie/actions/tfr_plot_tse/controller/tfr.py b/meggie/actions/tfr_plot_tse/controller/tfr.py
index 3e19dec3..907a2aab 100644
--- a/meggie/actions/tfr_plot_tse/controller/tfr.py
+++ b/meggie/actions/tfr_plot_tse/controller/tfr.py
@@ -95,10 +95,14 @@ def individual_plot(ax, info_idx, names_idx):
         ax.legend()
 
         ax.set_xlabel('Time (s)')
-        ax.set_ylabel('Power ({})'.format(get_power_unit(
-            mne.io.pick.channel_type(info, info_idx),
-            False
-        )))
+
+        if blmode and blmode != "mean":
+            ax.set_ylabel('Power')
+        else:
+            ax.set_ylabel('Power ({})'.format(get_power_unit(
+                mne.io.pick.channel_type(info, info_idx),
+                log=False
+            )))
 
         plt.show()
 
@@ -158,8 +162,12 @@ def plot_fun(ax_idx, ax):
             ch_group = ch_groups[ax_idx]
             ax.set_title(ch_group)
             ax.set_xlabel('Time (s)')
-            ax.set_ylabel('Power ({})'.format(get_power_unit(
-                ch_type, False)))
+
+            if blmode and blmode != "mean":
+                ax.set_ylabel('Power')
+            else:
+                ax.set_ylabel('Power ({})'.format(get_power_unit(
+                    ch_type, log=False)))
 
             for color_idx, (key, times, curve) in enumerate(averages[(ch_type, ch_group)]):
                 ax.plot(times, curve, color=colors[color_idx], label=key)