The motor and sensory systems work collaboratively to fulfill cognitive tasks, such as speech. For example, it has been hypothesized that neural signals generated in the motor system can transfer directly to the sensory system along a neural pathway (termed as motor-to-sensory transformation). Previous studies have demonstrated that the motor-to-sensory transformation is crucial for speech production. However, it is still unclear how neural representation dynamically evolves among distinct neural systems and how such representational transformation depends on task demand and the degrees of motor involvement. Using three speech tasks - overt articulation, silent articulation, and imagined articulation, the present fMRI study systematically investigated the representational formats and their dynamics in the motor-to-sensory transformation. Frontal-parietal-temporal neural pathways were observed in all three speech tasks in univariate analyses. The extent of the motor-to-sensory transformation network differed when the degrees of motor engagement varied among tasks. The representational similarity analysis (RSA) revealed that articulatory and acoustic information was represented in motor and auditory regions, respectively, in all three tasks. Moreover, articulatory information was cross-represented in the somatosensory and auditory regions in overt and silent articulation tasks. These results provided evidence for the dynamics and task-dependent transformation between representational formats in the motor-to-sensory transformation.
Keywords: RSA; Speech production; efference copy/corollary discharge; internal forward model; motor-to-sensory transformation; phonetic features; prediction; sensorimotor integration.