Neuroscientists want to understand how individual neurons encode information that allows us to distinguish objects, like telling a leaf apart from a rock. But they have struggled to build computational models that are simple enough to allow them to understand what individual neurons are doing.

To address this challenge, researchers in the Stringer and Pachitariu labs at Janelia set out to create a simpler model to explain what’s going on in the primary visual cortex —the first stop in the brain for visual data. Their paper is published in the journal Nature Communications.

“We are trying to build a model that can predict the visual responses of each individual neuron,” says Fengtong Du, a graduate student in the Stringer Lab who led the new research.