Why We Master It at a Glance but Fail in Practice: A Unified Mechanism of Signal Source and Filtering Level Asymmetry in Motor Skill Acquisition

Author Information Author: Baichen Yi Corresponding Author: Baichen Yi, E-mail: ybcbenxin@163.com Affiliation: Independent Researcher, Xi'an, Shaanxi Province, 710000, P.R. China ORCID: 0009-0008-6242-7743 Version: V1.0 Funding: None Conflict of Interest: All authors declare no conflicts of interest related to this work. Preprint Statement This paper is an unpeer-reviewed preprint and does not represent the final published academic conclusion. All mechanistic interpretations and cross-scenario applications presented herein are heuristic analogies and testable hypotheses, not confirmed scientific conclusions. Copyright License This preprint is licensed under the CC BY-NC-ND 4.0 International License. It is open for sharing and redistribution worldwide on the premise of proper attribution, non-commercial use, and no modified derivation of the original text. Special Authorization Statement: The author expressly authorizes any individual or institution to translate the full or partial content of this paper into other languages. Translated versions shall retain the core logic of the original text and indicate the original source and author information. The full license text is available at: https://creativecommons.org/licenses/by-nc-nd/4.0/ Positioning of the Series Paper This paper is an application of the MFY theoretical series in the field of motor skill science. The variable system (M, F, Y) adopted in this paper is derived from the formal definitions of the MFY framework. The four hypotheses proposed in this paper can be tested independently of this system. Readers may skip the theoretical derivation section (§2) and proceed directly to the hypothesis testing design section (§3). Abstract Abundant empirical evidence has been accumulated for three pathways of motor skill acquisition: physical training, virtual reality (VR) simulation training, and mental imagery training. However, a unified causal mechanistic explanation remains absent: why is imagery training nearly ineffective for novices with zero prior experience? Why is the transfer effect of VR training to real environments highly inconsistent? Why do the weights of the seven PETTLEP factors vary systematically with experience level? This paper proposes the F₁ Source Continuum Model, which covers the three scenarios through a single causal chain. The essence of differences among the three training modalities lies in the system filtering protection level determined by signal sources: physical training has the highest filtering level, with slow penetration but high deposition accuracy; imagery training has the lowest filtering level, with fast penetration but calibration accuracy constrained by prior experience; VR training sits in between, where visual-auditory signals pass through external high-threshold channels while proprioceptive and tactile signals travel through internal low-threshold channels, presenting channel differentiation. The gain of all training modalities is constrained by the same antecedent variable: the density of multi-channel perceptual templates formed and deposited through physical training. Without templates, calibration lacks a reference benchmark. The model identifies two types of structural risks that have not been systematically discussed previously. For VR training: under low template density conditions, erroneous movement signals are rapidly deposited through low-threshold channels, while correction instructions penetrate slowly through high-threshold channels, leading to preferential consolidation of error patterns. For imagery training: the inflation effect of expected ability is independent of actual ability improvement, generating a systematic expectation-ability gap. This gap reaches its maximum in the lowest experience bracket, meaning the group with the worst training effect is precisely the group with the largest blind spot in safety risk. Two practical principles are derived accordingly: in safety-sensitive fields, physical training should be adopted as a prerequisite to establish basic templates before simulation training is introduced; learners who have only received simulation training should undergo objective ability tests to calibrate the expectation gap before entering real practice. This paper puts forward four independently testable hypotheses, none of which rely on the theoretical premises of the MFY framework, providing a unified causal analysis framework for motor skill science, VR engineering, rehabilitation medicine, and sports safety.