Name
Abstract | ||
|---|---|---|
Perceptual Bistability refers to the phenomenon of spontaneously switching be- tween two or more interpretations of an image under continuous viewing. Al- though switching behavior is increasingly well characterized, the origins remain elusive. We propose that perceptual switching naturally arises from the brain's search for best interpretations while performing Bayesian inference. In particular, we propose that the brain explores a posterior distribution over image interpreta- tionsat a rapid time scale via a sampling-likeprocessandupdatesits interpretation when a sampled interpretation is better than the discounted value of its current in- terpretation. We formalize the theory, explicitlyderive switching rate distributions and discuss qualitative properties of the theory including the effect of changes in the posterior distribution on switching rates. Finally, predictions of the theory are shown to be consistent with measured changes in human switching dynamics to Necker cube stimuli induced by context. |
Year | Venue | Keywords |
|---|---|---|
2006 | NIPS | posterior distribution,bayesian inference |
Field | DocType | Citations |
Necker cube,Bistability,Bayesian inference,Computer science,Posterior probability,Artificial intelligence,Phenomenon,Perception,Machine learning | Conference | 2 |
PageRank | References | Authors |
0.61 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul R. Schrater | 1 | 141 | 22.71 |
| Rashmi Sundareswara | 2 | 31 | 5.11 |