Decoding Graded Grip-Force Intensity from fMRI Data Reveals a Transformation from Abstract to Effector- and Movement-Specific Codes prior to Execution

Abstract

Motor planning entails a progressive transformation of neural representations--from abstract motor goals, which represent intended action-outcomes independent of any particular effector (i.e., the body part executing the action), to effector-specific movement plans. Functional MRI (fMRI) studies have shown that parametric variations in parietal activity patterns reflect the encoding of intended force intensities in effector-specific regions, even before detailed movement parameters are specified. However, how these intended force intensities are initially represented in an abstract, effector-independent format and subsequently transformed into effector- and movement-specific plans remains unclear. To address this, human participants performed a delayed grip-force task during fMRI. They first prepared two of four possible force intensities, then received a cue indicating which hand should apply which force, and finally executed both grips simultaneously. Using time-resolved support vector regression (SVR) combined with a searchlight approach, we identified brain regions that parametrically code grip-force intensities across two 6-second delay periods. During the first delay, above-chance decoding was observed in the precuneus (PCu), whereas during the second delay it emerged in effector-specific regions, including the contralateral intraparietal sulcus (pIPS/aIPS), primary somatosensory cortex (S1), dorsal premotor cortex (PMd), and supplementary motor area (SMA). Cross-decoding confirmed effector-independent coding in the PCu, while cross-temporal generalization revealed stable representations in the contralateral IPS and PMd from the second delay through execution. Together, these findings indicate a progressive transformation from abstract representations of intended force intensity in the PCu to effector- and movement-specific plans in the IPS and PMd.