Nowadays, it is possible to record the activity of hundreds of cells at the same time in behaving animals. However, these data are often treated and analyzed as if they consisted of many independently recorded neurons. How can neuronal populations be uniquely used to learn about cognition? We describe recent work that shows that populations of simultaneously recorded neurons are fundamental to understand the basis of decision-making, including processes such as ongoing deliberations and decision confidence, which generally fall outside the reach of single-cell analysis. Thus, neuronal population data allow addressing novel questions, but they also come with so far unsolved challenges.

Acknowledgements: This work has been supported by the Spanish PSI2013-44811-P and SlowDyn FLAGERA-PCIN-2015-162-C02-02 grants from MINECO to R. M. B., and IJCI-2014-21937 grant from MINECO to G. M.