Conceptual Associations Generate Sensory Predictions

Abstract

A crucial ability of the human brain is to learn and exploit probabilistic associations between stimuli to facilitate perception and behavior by predicting future events. Although studies have shown how perceptual relationships are used to predict sensory inputs, relational knowledge is often between concepts rather than percepts (e.g., we learned to associate cats with dogs, rather than specific images of cats and dogs). Here, we asked if and how sensory responses to visual input may be modulated by predictions derived from conceptual associations. To this end we exposed participants of both sexes to arbitrary word–word pairs (e.g., car–dog) repeatedly, creating an expectation of the second word, conditional on the occurrence of the first. In a subsequent session, we exposed participants to novel word–picture pairs, while measuring fMRI BOLD responses. All word–picture pairs were equally likely, but half of the pairs conformed to the previously formed conceptual (word–word) associations, whereas the other half violated this association. Results showed suppressed sensory responses throughout the ventral visual stream, including early visual cortex, to pictures that corresponded to the previously expected words compared with unexpected words. This suggests that the learned conceptual associations were used to generate sensory predictions that modulated processing of the picture stimuli. Moreover, these modulations were tuning specific, selectively suppressing neural populations tuned toward the expected input. Combined, our results suggest that recently acquired conceptual priors are generalized across domains and used by the sensory brain to generate category-specific predictions, facilitating processing of expected visual input.