The sociomotor framework outlines a possible role of social action effects on human action control, suggesting that anticipated partner reactions are a major cue to represent, select, and initiate own body movements. Here, we review studies that elucidate the actual content of social action representations and that explore factors that can distinguish action control processes involving social and inanimate action effects. Specifically, we address two hypotheses on how the social context can influence effect-based action control: first, by providing unique social features such as body-related, anatomical codes, and second, by orienting attention towards any relevant feature dimensions of the action effects. The reviewed empirical work presents a surprisingly mixed picture: while there is indirect evidence for both accounts, previous studies that directly addressed the anatomical account showed no signs of the involvement of genuinely social features in sociomotor action control. Furthermore, several studies show evidence against the differentiation of social and non-social action effect processing, portraying sociomotor action representations as remarkably non-social. A focus on enhancing the social experience in future studies should, therefore, complement the current database to establish whether such settings give rise to the hypothesized influence of social context.
The neural representation of a repeated stimulus is the standard against which a deviant stimulus is measured in the brain, giving rise to the well-known mismatch response. It has been suggested that individuals with dyslexia have poor implicit memory for recently repeated stimuli, such as the train of standards in an oddball paradigm. Here, we examined how the neural representation of a standard emerges over repetitions, asking whether there is less sensitivity to repetition and/or less accrual of “standardness” over successive repetitions in dyslexia. We recorded magnetoencephalography (MEG) as adults with and without dyslexia were passively exposed to speech syllables in a roving-oddball design. We performed time-resolved multivariate decoding of the MEG sensor data to identify the neural signature of standard vs. deviant trials, independent of stimulus differences. This “multivariate mismatch” was equally robust and had a similar time course in the two groups. In both groups, standards generated by as few as two repetitions were distinct from deviants, indicating normal sensitivity to repetition in dyslexia. However, only in the control group did standards become increasingly different from deviants with repetition. These results suggest that many of the mechanisms that give rise to neural adaptation as well as mismatch responses are intact in dyslexia, with the possible exception of a putatively predictive mechanism that successively integrates recent sensory information into feedforward processing.