Probabilistic brains: knowns and unknowns.
Journal Article (Journal Article;Review)
There is strong behavioral and physiological evidence that the brain both represents probability distributions and performs probabilistic inference. Computational neuroscientists have started to shed light on how these probabilistic representations and computations might be implemented in neural circuits. One particularly appealing aspect of these theories is their generality: they can be used to model a wide range of tasks, from sensory processing to high-level cognition. To date, however, these theories have only been applied to very simple tasks. Here we discuss the challenges that will emerge as researchers start focusing their efforts on real-life computations, with a focus on probabilistic learning, structural learning and approximate inference.
Full Text
Duke Authors
Cited Authors
- Pouget, A; Beck, JM; Ma, WJ; Latham, PE
Published Date
- September 2013
Published In
Volume / Issue
- 16 / 9
Start / End Page
- 1170 - 1178
PubMed ID
- 23955561
Pubmed Central ID
- PMC4487650
Electronic International Standard Serial Number (EISSN)
- 1546-1726
Digital Object Identifier (DOI)
- 10.1038/nn.3495
Language
- eng
Conference Location
- United States