Building population models for large-scale neural recordings: opportunities and pitfalls
This review is significant for neuroscientists and computational neuroscientists working with large-scale neural recordings, providing a comprehensive overview of current analytical methods.
This paper reviews recent statistical models developed for analyzing large-scale neural population activity, driven by advancements in recording technologies. It compares different approaches, highlighting their strengths and limitations, and discusses the biological insights they offer.
Modern recording technologies now enable simultaneous recording from large numbers of neurons. This has driven the development of new statistical models for analyzing and interpreting neural population activity. Here we provide a broad overview of recent developments in this area. We compare and contrast different approaches, highlight strengths and limitations, and discuss biological and mechanistic insights that these methods provide.