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Functional MRI (fMRI) studies have shown that parametric variations in parietal activity patterns reflect the encoding of intended force\u2010intensities in effector\u2010specific regions, even before detailed movement parameters are specified. However, how these intended force\u2010intensities are initially represented in an abstract, effector\u2010independent format and subsequently transformed into effector\u2010 and movement\u2010specific plans remains unclear. To address this, human\u2010participants performed a delayed grip\u2010force task during fMRI. They first prepared two of four possible force\u2010intensities, then received a cue indicating which hand should apply which force, and finally executed both grips simultaneously. Using time\u2010resolved support vector regression (SVR) combined with a searchlight approach, we identified brain\u2010regions that parametrically code grip\u2010force intensities across two 6\u2010s delay periods. During the first delay, above\u2010chance decoding was observed in a medial section of the posterior parietal cortex spanning the precuneus and superior parietal lobule (PCu\/SPL), whereas during the second delay it emerged in effector\u2010specific regions, including the contralateral intraparietal sulcus (pIPS\/aIPS), primary somatosensory cortex (S1), dorsal premotor cortex (PMd), and supplementary motor area (SMA). Cross\u2010decoding confirmed effector\u2010independent coding in the PCu\/SPL, while cross\u2010temporal 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\u2010intensity in the PCu\/SPL to effector\u2010 and movement\u2010specific plans in the IPS and PMd.<\/jats:p>","DOI":"10.1002\/hbm.70657","type":"journal-article","created":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T07:02:03Z","timestamp":1792652523000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Decoding Graded Grip\u2010Force Intensity From\n                    <scp>fMRI<\/scp>\n                    Data Reveals a Transformation From Abstract to Effector\u2010 and Movement\u2010Specific Codes Prior to Execution"],"prefix":"10.1002","volume":"47","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-4582-0583","authenticated-orcid":false,"given":"Guido","family":"Caccialupi","sequence":"first","affiliation":[{"name":"Neurocomputation and Neuroimaging Unit (NNU) Freie Universit\u00e4t Berlin  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