Metamers and Mixtures: Testing Bayesian models using neural data
Ralf Haefner, Sabyasachi Shivkumar, Gabor Lengyel · COSYNE 2025
Bayesian models have been successful in explaining sensorimotor behavior in humans and animals, yet it remains unclear whether they can also explain neural activity. Testing them using neural data is complicated by the fact that linking them to neural activity requires two key moving parts: (1) a hypothesis about which latent variable is represented by a neuron, or neural population (``generative model'') and (2) a hypothesis about how beliefs about a latent variable (``posterior'') are represented by neural responses. Here, we present two new methods that in conjunction allow us to, first, fa
ePoster · Neuroscience