Convolutional Neural Networks Decode Finger Movements in Motor Sequence Learning from MEG Data

Frontiers in Neuroscience. 2025. Vol. 19. Article 1623380.

Zabolotniy A., Chan R. W., Moiseeva V., Fedele T.

We demonstrated the feasibility of finger movement decoding with a tailored Convolutional Neural Network. The performance of our approach was comparable to complex deep learning architectures, while providing faster and interpretable outcome. This algorithmic strategy holds high potential for the investigation of the mechanisms underlying non-invasive neurophysiological recordings in cognitive neuroscience.

Keywords: MEG, convolutional neural networks, Serial reaction time task, Motor learning, finger movement decoding

Publication based on the results of: Multidisciplinary study of behavior and decision-making in health population and patients using behavioral, economic, neurocognitive, neuroeconomic, neurocomputational and neural network approaches (2025)