The time-course of phonological encoding: insights from time-resolved MVPA.

To produce a word, speakers need to decide which concept to express, select an appropriate item from the mental lexicon and spell out its phonological form. The temporal dynamics of these processes remain a subject of debate. We investigated the time course of lexical access in picture naming with electroencephalography (EEG). Thirty participants (23 female) named pictures using simple nouns. The pictures varied in conceptual category (animate or inanimate), stress pattern (first or second syllable), and the structure of the first syllable (open or closed). Using time-resolved multivariate pattern analysis (MVPA), we decoded the time course in which each dimension was available during speech preparation. The results demonstrated above-chance decoding of animacy within 100 ms after picture onset, confirming early access to conceptual information. This was followed by stress pattern and syllable structure, at around 150 and 250 ms after picture onset, respectively. These results suggest that a word's stress pattern can be retrieved before syllable structure information becomes available. An exploratory analysis demonstrated the availability of the word-initial phoneme within 100 ms after picture onset. This result hints at the possibility that during picture naming conceptual, phonological and phonetic information may be accessed rapidly and in parallel. Producing spoken words is an effortless yet complex process. The mechanisms through which we retrieve and assemble the sound structure of words remain largely unknown. So far, speech production theories have mostly relied on behavioural experiments. We investigated the time course of phonological encoding during spoken word production using EEG. Results show that after rapid processing of word meaning, speakers access a word's stress pattern, followed by the composition of individual syllables. We show that subtle linguistic characteristics can be predicted before a speaker produces a word. Importantly, this study demonstrates successful application of MVPA on pre-articulation data from the widely-available method EEG, offering an accessible approach to address novel questions in speech production research.