Data from: Electrophysiological correlates of semantic dissimilarity reflect the comprehension of natural, narrative speech

People routinely hear and understand speech at rates of 120–200 words per
minute [1, 2]. Thus, speech comprehension must involve rapid, online
neural mechanisms that process words’ meanings in an approximately
time-locked fashion. However, in the context of continuous speech,
electrophysiological evidence for such time-locked processing has been
lacking. Whilst valuable insights into the semantic processing of speech
have been provided by the “N400 component” of the event-related potential
[3-6], this literature has been dominated by paradigms using incongruous
words within specially constructed sentences, and may not accurately
reflect natural, narrative speech comprehension. Building on the discovery
that cortical activity “tracks” the dynamics of running speech [7-9], and
psycholinguistic work both demonstrating [10-12] and modeling [13-15] how
context rapidly impacts on word processing, we describe a new approach for
deriving an electrophysiological correlate of natural speech
comprehension. We used a computational model [16] to quantify the meaning
carried by each word based on how semantically dissimilar it was to its
preceding context and then regressed this quantity against
electroencephalographic (EEG) data recorded from subjects as they listened
to narrative speech. This produced a prominent negativity at a time-lag of
200–600 ms on centro-parietal EEG channels, characteristics common to the
N400. Applying this approach to EEG datasets involving time-reversed
speech, cocktail party attention and audiovisual speech-in-noise
demonstrated that this response was very sensitive to whether or not
subjects understood the speech they heard. These findings demonstrate
that, when successfully comprehending natural speech, the human brain
responds to the contextual semantic content of each word in a relatively
time-locked fashion.