Abstract Neural bursts—brief episodes of heightened oscillatory activity—are increasingly studied as fundamental building blocks of brain function, with relevance to perception, cognition, and disease. As such, detecting and characterizing these bursts in electrophysiological recordings has driven rapid methodological innovation in neuroscience research. However, the growing number of analysis techniques can be overwhelming, making it difficult for researchers to select the most appropriate method for their specific goals. In this review, we provide a structured and practical guide for neuroscientists to measure and interpret neural burst data. We offer an overview of current detection methods, accompanied by a suite of tutorials, including code notebooks and data, to enable concrete implementation and critical evaluation. We then conclude with actionable recommendations to help researchers select the best burst detection strategy in diverse research contexts. This guide is intended for newcomers to the field as well as more experienced neuroscientists seeking to expand their methodological toolkit.
Power et al. (Thu,) studied this question.