Steve Byrnes lays out his 7 guiding principles for understanding how the brain works computationally. He argues the neocortex uses a single general learning algorithm that starts as a blank slate, while the subcortex contains hard-coded instincts and steers the neocortex toward biologically adaptive behaviors.
The neocortex has been hypothesized to be uniformly composed of general-purpose data-processing modules. What does the currently available evidence suggest about this hypothesis? Alex Zhu explores various pieces of evidence, including deep learning neural networks and predictive coding theories of brain function. [tweet]