Evaluate Cross-Dataset and Cross-Recording-System Transfer

Evaluate transfer of independently trained neural decoding models between datasets and recording systems to determine whether the models generalize across these changes.

Background

The paper trains models independently for each dataset and neural encoder, covering motor-imagery, SSVEP, and speech-decoding tasks with different recording configurations. Although the experiments demonstrate language-supervised decoding within these settings, they do not establish whether a model trained on one dataset or recording system can be transferred successfully to another. The authors explicitly identify this cross-dataset and cross-system generalization as unevaluated.