Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention
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arXiv
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| Autores principales: | , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866916623046148096 |
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| author | Kamat, Anil Rahul, Rahul Cavuoto, Lora Burke, Harry Hackett, Matthew Norfleet, Jack Schwaitzberg, Steven De, Suvranu |
| author_facet | Kamat, Anil Rahul, Rahul Cavuoto, Lora Burke, Harry Hackett, Matthew Norfleet, Jack Schwaitzberg, Steven De, Suvranu |
| contents | Motor skill acquisition in fields like surgery, robotics, and sports involves learning complex task sequences through extensive training. Traditional performance metrics, like execution time and error rates, offer limited insight as they fail to capture the neural mechanisms underlying skill learning and retention. This study introduces directed functional connectivity (dFC), derived from electroencephalography (EEG), as a novel brain-based biomarker for assessing motor skill learning and retention. For the first time, dFC is applied as a biomarker to map the stages of the Fitts and Posner motor learning model, offering new insights into the neural mechanisms underlying skill acquisition and retention. Unlike traditional measures, it captures both the strength and direction of neural information flow, providing a comprehensive understanding of neural adaptations across different learning stages. The analysis demonstrates that dFC can effectively identify and track the progression through various stages of the Fitts and Posner model. Furthermore, its stability over a six-week washout period highlights its utility in monitoring long-term retention. No significant changes in dFC were observed in a control group, confirming that the observed neural adaptations were specific to training and not due to external factors. By offering a granular view of the learning process at the group and individual levels, dFC facilitates the development of personalized, targeted training protocols aimed at enhancing outcomes in fields where precision and long-term retention are critical, such as surgical education. These findings underscore the value of dFC as a robust biomarker that complements traditional performance metrics, providing a deeper understanding of motor skill learning and retention. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_14731 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention Kamat, Anil Rahul, Rahul Cavuoto, Lora Burke, Harry Hackett, Matthew Norfleet, Jack Schwaitzberg, Steven De, Suvranu Neurons and Cognition Machine Learning Motor skill acquisition in fields like surgery, robotics, and sports involves learning complex task sequences through extensive training. Traditional performance metrics, like execution time and error rates, offer limited insight as they fail to capture the neural mechanisms underlying skill learning and retention. This study introduces directed functional connectivity (dFC), derived from electroencephalography (EEG), as a novel brain-based biomarker for assessing motor skill learning and retention. For the first time, dFC is applied as a biomarker to map the stages of the Fitts and Posner motor learning model, offering new insights into the neural mechanisms underlying skill acquisition and retention. Unlike traditional measures, it captures both the strength and direction of neural information flow, providing a comprehensive understanding of neural adaptations across different learning stages. The analysis demonstrates that dFC can effectively identify and track the progression through various stages of the Fitts and Posner model. Furthermore, its stability over a six-week washout period highlights its utility in monitoring long-term retention. No significant changes in dFC were observed in a control group, confirming that the observed neural adaptations were specific to training and not due to external factors. By offering a granular view of the learning process at the group and individual levels, dFC facilitates the development of personalized, targeted training protocols aimed at enhancing outcomes in fields where precision and long-term retention are critical, such as surgical education. These findings underscore the value of dFC as a robust biomarker that complements traditional performance metrics, providing a deeper understanding of motor skill learning and retention. |
| title | Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention |
| topic | Neurons and Cognition Machine Learning |
| url | https://arxiv.org/abs/2502.14731 |