N400-like magnetoencephalography responses modulated by semantic context, word frequency, and lexical class in sentences

Words have been found to elicit a negative potential at the scalp peaking at similar to400 ms that is strongly modulated by semantic context. The current study used whole-head magnetoencephalography (MEG) as male subjects read sentences ending with semantically congruous or incongruous words. Compared with congruous words, sentence-terminal incongruous words consistently evoked a large magnetic field over the left hemisphere, peaking at similar to450 ms. Source modeling at this latency with conventional equivalent current dipoles (ECDs) placed the N400m generator in or near the left superior temporal sulcus. A distributed solution constrained to the cortical surface suggested a sequence of differential activation, beginning in Wernicke's area at similar to250 ms, spreading to anterior temporal sites at similar to270 ms, to Broca's area by similar to300 ms, to dorsolateral prefrontal cortices by similar to320 ms, and to anterior orbital and frontopolar cortices by similar to370 ms. Differential activity was exclusively left-sided until >370 ms, and then involved right anterior temporal and orbital cortices. At the peak of the N400m, activation in the left hemisphere was estimated to be widespread in the anterior temporal, perisylvian, orbital, frontopolar, and dorsolateral prefrontal cortices. In the right hemisphere, the orbital, as well as, weakly, the right anterior temporal cortices were activated. Similar but weaker field patterns were evoked by intermediate words in the sentences, especially to low-frequency words occurring in early sentence positions where there is little preceding context. The locations of the N400m sources identified with the distributed solution correspond well with those previously demonstrated with direct intracranial recordings, and suggested by functional magnetic resonance imaging (fMRI). These results help identify a distributed cortical network that supports online semantic processing. (C) 2002 Elsevier Science (USA).