Instead of integrating expectations, neural populations enhance the likelihood of expected stimuli—sharpening perception rather than shifting it.
This means sensory systems maintain a veridical, faithful, representation of the world. (7/n)

Sensory populations reflect the Bayesian likelihood. And expectation modulates sensory activity. But here’s the twist: sensory neurons don’t integrate the likelihood and prior expectation. (6/n)

Behaviorally, birds integrate expectations and sensory input probabilistically, following a Bayesian strategy. This aligns with classic models of categorical perception. 5/n

To investigate this, we trained European starlings to classify ambiguous song syllables generated from a variational autoencoder. We manipulated expectation by changing the probabilities of syllables within song sequences. 4/n

We show that while decision-making systems integrate expectations probabilistically, sensory systems do something surprising: Rather than biasing perception, expectation sharpens it, enhancing sensory precision. 3/n

On one hand, we use expectations to pull experience into expected perceptual categories, stabilizing perception but *reducing acuity*. On the other hand our expectations allow us to focus our attention on relevant signals, *improving acuity*. 2/n