Editorial: Methods in brain-computer interfaces: 2023

Brain-computer interfaces (BCIs) represent a rapidly evolving field within human neuroscience, enabling direct link between the brain and external devices. BCI research is aiming at transitioning from experimental constructs to accurate and generalized tools with transformative implications in clinical, commercial, and assistive domains. Despite significant advancements in the field, such as the design and application of artificial intelligence methods (e.g., convolutional neural networks) for improving neural decoding, several challenges persist. A primary concern involves neural decoding, which is affected by intra- and inter-subject variability as well as the limited availability of labeled data. In addition, improving user experience and ensuring system robustness in complex, real-world scenarios are critical challenges that should be addressed to advance practical BCI applications. The objective of this Research Topic Methods in brain-computer interfaces: 2023 is not only to highlight technological advances in BCI, but also to critically assess and share methodological insights that can inform future research design, improve reproducibility, and facilitate practical deployment. This editorial introduces and discusses the key methodologies developed in 2023, emphasizing the methodological advances and their implications for clinical and cognitive applications.