Building population models for large-scale neural recordings: opportunities and pitfalls

TL;DR

This paper reviews recent advances in statistical models for analyzing large-scale neural recordings, discussing their strengths, limitations, and the biological insights they enable.

Contribution

It provides a comprehensive overview of current modeling approaches, highlighting opportunities and pitfalls in analyzing large neural populations.

Findings

Comparison of different modeling approaches

Identification of key strengths and limitations

Discussion of biological insights gained

Abstract

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.