Speech Categorization Is Better Described By Induced Rather Than Evoked Neural Activity

Categorical perception (CP) describes how the human brain categorizes speech despite inherent acoustic variability. We examined neural correlates of CP in both evoked and induced electroencephalogram (EEG) activity to evaluate which mode best describes the process of speech categorization. Listeners labeled sounds from a vowel gradient while we recorded their EEGs. Using a source reconstructed EEG, we used band-specific evoked and induced neural activity to build parameter optimized support vector machine models to assess how well listeners' speech categorization could be decoded via whole-brain and hemisphere-specific responses. We found whole-brain evoked beta-band activity decoded prototypical from ambiguous speech sounds with similar to 70% accuracy. However, induced gamma-band oscillations showed better decoding of speech categories with similar to 95% accuracy compared to evoked beta-band activity (similar to 70% accuracy). Induced high frequency (gamma-band) oscillations dominated CP decoding in the left hemisphere, whereas lower frequencies (theta-band) dominated the decoding in the right hemisphere. Moreover, feature selection identified 14 brain regions carrying induced activity and 22 regions of evoked activity that were most salient in describing category-level speech representations. Among the areas and neural regimes explored, induced gamma-band modulations were most strongly associated with listeners' behavioral CP. The data suggest that the category-level organization of speech is dominated by relatively high frequency induced brain rhythms.