Animals learn to recognize the relationships between sensory and spatial information, in order to adapt their behavior accordingly. For example, rodents learn to associate olfactory and spatial cues to successfully explore the environment. Recently, our lab has shown that through associative learning between odorants, spatial contexts and rewards, neuronal encoding at the primary piriform olfactory cortex (PCx) of the mouse undergoes dramatic changes.

We implemented a virtual reality setup, where mice were trained to recognize specific pairings between odors and spatial environments. We recorded the spiking activity of groups of neurons from the PCx, during the first session of training, and when animals became experts in the task. Combining Generalized Linear Models (GLMs) with deep neural networks for neuronal encoding and decoding, we found that, while PCx neurons from the first session primarily represent odors, after learning they become mixed-selective, also encoding the location of the animal in the virtual environment, together with other behavioral, contextual and cognitive variables. The modulation of PCx activity by these non- olfactory signals was dynamic, improving odour discrimination during task engagement and in rewarded contexts. These results indicate that complex and multiplexed information is already present at the earliest stages of the sensory cortex, enhancing sensory processing while encoding the behavioural relevance of stimuli.