Hannah Morrow

Abstract Adaptive behavior requires integrating multiple sources of information, yet neural and computational mechanisms underlying this process are poorly understood. We introduce a novel Bayesian computational framework elucidating how internally maintained and externally cued information are integrated to guide goal-directed actions. Our model infers trial-by-trial beliefs for inputs and integrates them into a joint probability distribution, where entropy quantifies overall uncertainty.

Brooklyn Decker and I are on a call when she says she can’t find her phone. There’s a beat, then it hits her. “Oh my god,” she says into the device already at her ear. “That was mom brain.” The lapse is entirely forgiven — I have no kids and look for my keys while they’re in my hand more than I care to admit — and she can really bear no blame. Decker’s life has a lot of moving parts.

A spellbinding evangelist preacher. A pioneer of early broadcast marketing. A performer who gave the Broadway treatment to the Bible. A Canadian-American single mother and three-time divorcée. Only in Hollywood would a character like Aimee Semple McPherson have been absolutely real. In 1926, at the peak of her fame, McPherson was reportedly kidnapped.