Joshua W. Brown

Joshua W. Brown studies how the brain makes decisions, plans actions, and learns to reach goals, combining computational models with neuroscience data. His work spans theories of how brain regions like the prefrontal cortex and anterior cingulate cortex handle risky choices and error monitoring, along with brain stimulation techniques for conditions such as ADHD and addiction. He also connects these ideas to machine learning, exploring how principles like memory replay and reinforcement learning relate to both brain activity and artificial neural networks.

Publication activity has been fairly steady over the past decade, averaging about five papers per year with modest year-to-year fluctuation.

Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026