Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention
Anil Kamat, Rahul Rahul, Lora Cavuoto, Harry Burke, Matthew Hackett,, Jack Norfleet, Steven Schwaitzberg, Suvranu De

TL;DR
This study introduces directed functional connectivity derived from EEG as a novel neural biomarker for tracking motor skill learning and retention, providing deeper insights than traditional performance metrics.
Contribution
It is the first to apply dFC as a biomarker to map neural stages of motor learning and retention, enhancing understanding of neural mechanisms involved.
Findings
dFC effectively tracks stages of motor learning.
dFC remains stable over six weeks, indicating long-term retention.
Control group showed no significant dFC changes, confirming training-specific neural adaptations.
Abstract
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…
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Taxonomy
TopicsEEG and Brain-Computer Interfaces
