Due to differential sensitivities of sensor and source space analyses it is sometimes the case that a particular effect is significant in one but
not the other. When an effect is significant at the sensor level with all the proper corrections for multiple comparisons and the hypothesis is about the existence of an effect rather than about a specific area
being involved, it could be acceptable to only report the peaks of a statistical map at the source level without requiring correction for multiple comparisons over the whole brain. When an effect is significant at
the source level corrected for multiple comparisons and the choice of time and frequency windows for the source analysis can be motivated a-priori, a sensor-level test is not necessary. What should be avoided
is doing a sensor-level test without proper MCP correction and using it to motivate a source-level test that achieves significance. This would constitute double-dipping (Kriegeskorte et al., 2009) similar to using peaks in the data to constrain a sensor-level test.