Abstract
We used Magnetoencephalography (MEG) in combination with Representational Similarity Analysis to probe neural activity associated with distinct, item-specific lexico-semantic predictions during language comprehension. MEG activity was measured as participants read highly constraining sentences in which the final words could be predicted. Before the onset of the predicted words, both the spatial and temporal patterns of brain activity were more similar when the same words were predicted than when different words were predicted. The temporal patterns localized to the left inferior and medial temporal lobe. These findings provide evidence that unique spatial and temporal patterns of neural activity are associated with item-specific lexico-semantic predictions. We suggest that the unique spatial patterns reflected the prediction of spatially distributed semantic features associated with the predicted word, and that the left inferior/medial temporal lobe played a role in temporally 'binding' these features, giving rise to unique lexico-semantic predictions.
Highlights
After reading or hearing the sentence context, ‘In the crib there is a sleeping . . .’, we are able to predict the word, ‘baby’
The sentences were constructed in pairs (120 pairs) that strongly predicted the same sentence-final word (SFW), during presentation, members of the same pair were separated by at least 30 other sentences
Based on a spatial correlation measure, we were able to provide evidence that the prediction of specific individual words produced unique spatial patterns of brain activity. This activity was evident between 120 and 515 ms following the word prior to the predicted sentence-final word (SFW-1). Within this time window, using a temporal correlation measure, we show that the prediction of specific individual words produced distinct temporal patterns of neural activity, which localized to the left inferior temporal region and neighboring areas
Summary
After reading or hearing the sentence context, ‘In the crib there is a sleeping . . .’, we are able to predict the word, ‘baby’. After reading or hearing the sentence context, ‘In the crib there is a sleeping . . .’, we are able to predict the word, ‘baby’. Probabilistic prediction at multiple levels of representation allows us to rapidly understand what we read or hear by giving processing a head start (see Kuperberg and Jaeger, 2016a, for a review). The strength of prediction, and the precise level of representation at which it occurs, is likely to depend on many factors (see Kuperberg and Jaeger, 2016a, section 3.4). There is clear neural evidence that, at least in highly constraining sentence contexts, we are able to predict the semantic features of upcoming words
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