Smarter algorithms could lead to greater understanding of the brain’s true complexity
The human brain naturally makes its best guess when making a decision, and studying those guesses can be very revealing about the brain’s inner workings. But neuroscientists at Rice University and Baylor College of Medicine said a full understanding of the complexity of the human brain will require new research strategies that better simulate real-world conditions.
Xaq Pitkow and Dora Angelaki, both faculty members in Baylor’s Department of Neuroscience and Rice’s Department of Electrical and Computer Engineering, said the brain’s ability to perform “approximate probabilistic inference” cannot be truly studied with simple tasks that are “ill-suited to expose the inferential computations that make the brain special.”
The human brain naturally makes its best guess when making a decision, and studying those guesses can be very revealing about the brain’s inner workings. But neuroscientists at Rice University and Baylor College of Medicine said a full understanding of the complexity of the human brain will require new research strategies that better simulate real-world conditions.
Xaq Pitkow and Dora Angelaki, both faculty members in Baylor’s Department of Neuroscience and Rice’s Department of Electrical and Computer Engineering, said the brain’s ability to perform “approximate probabilistic inference” cannot be truly studied with simple tasks that are “ill-suited to expose the inferential computations that make the brain special.”
Author: desertedbeach