Coin-Flipping in the Brain - Probabilistic Computation and Learning in the Assembly Model

Explore a lecture on probabilistic computation and learning in the brain's assembly model. Delve into the role of uncertainty in intelligence and how the brain's inherent noise may be utilized for sampling from environmental models to generate predictions. Examine the emergence of statistical learning in a biologically plausible computational brain model based on stylized neurons, synapses, plasticity, and inhibition. Discover how assemblies—groups of neurons representing cognitive primitives—can record statistics and harness ambient noise for probabilistic decision-making. Learn about the theoretical and simulated evidence supporting the learning of statistical models like Markov chains through stimulus presentation. Gain insights into the foundations of biologically plausible probabilistic computation and the potential significance of noise in cognitive mechanisms.