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Prior experience modulates top-down predictive processing in the ventral visual areas

Repetition suppression(RS)refers to that the reduction of neural activities for repeated presentations of a given stimulus compared to its first presentation. Summerfield et al(2008) found the magnitude of RS is affected by the repetition probability of stimuli, called as P(rep) effect. Based on the predictive coding theory, prior experience about the sensory inputs is necessary to optimally achieve cognitive processes. But it remains unclear how prior experience modulates predictive processes. To address this issue, in Study I, we estimated the P(rep) effects for Chinese characters and German words in native Chinese and German participants to test whether prior experience affects the P(rep) effect of lexical stimuli. The results showed that the P(rep) effect is only manifest for words of a language with which participants had prior experience. Study II performed fMRI measurements before and after a 10-day perceptual learning (PL) training for cars to test the modulation of short-term experience on the P(rep) effect. The results replicated the P(rep) effect for faces and cars. More interestingly, the P(rep) effect can be temporarily abolished by the short-term PL experience. The third study investigated how prior experience modulates sensory inputs. Study 3a adopted a classic stimulus repetition paradigm to measure RS for faces, together with either concurrent short-term memory (STM) load or a control condition. The results showed that RS is significantly attenuated when visual STM is loaded. Study 3b manipulates attention by a face inversion detection task. The results showed that the RS effect appears in the STM condition when participants attend to faces. The main conclusions: i) predictive processes, as measured by the P(rep) effect, require extensive prior experiences with stimuli, but ii) these can also be modulated by short-term learning experience. Further, iii) STM and attention are two modulators of prior experiences on predictive processes.

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