N400 Responses to Final Words during Sentence Reading in Individuals with Autism: A MEG Study

Banu Ahtam1, Sven Braeutigam1, and Anthony Bailey2. (1) Child and Adolescent Psychiatry, University of Oxford, Oxford, United Kingdom, (2) Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United Kingdom

Background: Individuals with autism are impaired in spontaneously making use of sentence context to decide on the correct pronunciation of words with several meanings; a finding in line with the weak central coherence theory.

Objectives: To use magnetoencephalography (MEG) to establish the neural basis of abnormalities in sentence context effects in individuals with ASD.

Methods: 14 individuals with ASD and 14 typically developing adults participated in the study. Participants were matched on age, gender, and IQ. All measurements were taken at the Oxford Neurodevelopmental Magnetoencephalography Centre using a Neuromag-306 VectorViewTM system, providing a helmet-shaped array of 102 pairs of gradiometers. Participants read sentences ending either with a homonym (dominant vs. subordinate meanings) or an unambiguous word. The sentences were followed by a probe word that was semantically related or unrelated to the meaning of the sentence. This study has been approved by the local NHS (UK) Ethics Committee. All participants gave written informed consent before the experiment.

Results: At 100ms, the responses to all three types of final words are very similar in both groups and consistent with the primary visual response. The word response at 150ms is weakest in the subordinate homonym condition in the ASD group. At 450ms latency, a stronger parietal activation of N400-like responses in all three conditions is seen in the ASD group compared to the control group.

Conclusions: These results suggest that the initial stages of word processing in ASD exhibit typical patterns. The strong N4 activity in ASD may indicate unusual word processing above that required by task demands and consistent with current models of anomalous semantic networks in ASD.