Temporal predictive codes for spoken words in auditory cortex.
Bottom Line: Computational simulations show that knowing "formubo" increases lexical competition when hearing "formu…", but reduces segment prediction error.The time course of magnetoencephalographic brain responses in the superior temporal gyrus (STG) is uniquely consistent with a segment prediction account.This prediction error signal explains the efficiency of human word recognition and simulates neural responses in auditory regions.
Affiliation: MRC Cognition and Brain Sciences Unit, Cambridge, UK.Show MeSH
Mentions: Results of the sensor analyses clearly suggest that changes to the neural response to spoken words and pseudowords reflect computations of segment prediction error rather than lexical entropy. Prediction error is assumed to encode the difference between activity in segment prediction units (derived from a distributed lexical-semantic system) and activity in state units (i.e., sensory evidence) derived from acoustic analysis in lower levels (e.g., primary auditory cortex; see Figure 4). Neural responses linked to this prediction error signal should therefore be localized to neural populations in the STG that have previously been argued to represent the segmental content of speech [18–20]. We therefore estimated the cortical sources of the MEG data during the 100–500 ms post-DP period, and searched for regions that matched the response profile across the six trained (day 1 and day 2) conditions that was predicted by our computational simulation (see Figure 1F; Figure S3). We found two clusters of 1,075 and 717 voxels whose spatial extent survived correction for multiple comparisons. These were spread across the left and right STG, supramarginal gyri, and rolandic operculum (Figure 3C). The largest differences in the response profile for prediction error in Figure 1F arises from lexicalized versus nonlexicalized items. We therefore defined a restricted search volume based on an orthogonal contrast of novel and baseline nonwords versus source words in the untrained condition (this lexicality effect showed good spatial correspondence to prior findings in a meta-analysis of relevant PET and functional magnetic resonance imaging studies ; see Figure S2). The peak statistic in both the left (x = −54, y = −12, z = +10, T(160) = 4.7) and right (x = 60, y = −20, z = +12, T(160) = 4.3) STG survived correction for multiple comparisons within this restricted volume (the source energies in left STG peak for each condition, pre- and post-DP, are shown for illustrative purposes in Figure 3D). Thus, source reconstruction further supports the view that MEG signals reflect prediction error at the level of segments, rather than competition at a higher lexical level.
Affiliation: MRC Cognition and Brain Sciences Unit, Cambridge, UK.