4 Using vector-based models of semantic representation to account for the systematic variances in neural activity Computational linguists have demonstrated that a word's meaning is captured to some extent by the distribution of words and phrases with which it commonly co-occurs (Church and Hanks, 1990).
 encoded the meaning of a word as a vector of intermediate semantic features computed from the co-occurrences with stimulus words within the Google trillion-token text corpus that captures the typical use of words in English text.