The role of priors in bayesian models of perception

Frontiers in Computational Neuroscience

Volumn , Issue MAR, 2013, Pages

  Teufel, Christoph ^a   Subramaniam, Naresh ^a   Fletcher, Paul C ^a  

^a UNIVERSITY OF CAMBRIDGE   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AUTISM; BAYES THEOREM; BAYESIAN OBSERVER MODEL; BRAIN FUNCTION; HUMAN; ILLUSION; INFORMATION PROCESSING; LEARNING; MATHEMATICAL ANALYSIS; NOTE; PERCEPTION; PERCEPTION DISORDER; QUALITY CONTROL; SENSORY DYSFUNCTION; SENSORY MEMORY; SOCIAL INTERACTION; SOMATOSENSORY STIMULATION; SYSTEM ANALYSIS; VISION;

EID: 84875337684     PISSN: 16625188     EISSN: None     Source Type: Journal    
DOI: 10.3389/fncom.2013.00025     Document Type: Note

References (15)

1. Berger, J.O. (1985). Statistical decision theory and Bayesian analysis. New York: Springer.
2. Brock, J. (2012). Alternative Bayesian accounts of autistic perception: comment on Pellicano and Burr. Trends in Cognitive Sciences 16, 573-574.
3. Chernoff, H., and Lincoln, E.M. (1959). Elementary Decision Theory. New York: John Wiley & Sons.
4. Friston, K.J., Lawson, R., and Frith, C.D. (2013). On hyperpriors and hypopriors: comment on Pellicano and Burr. Trends in Cognitive Sciences 17, 1-1.
5. Geisler, W.S., and Kersten, D. (2002). Illusions, perception and Bayes. Nature Neuroscience 5, 508-510.
6. Happé, F.G.E. (1996). Studying weak central coherence at low levels: Children with autism do not succumb to visual illusions. A research note. Journal of Child Psychology and Psychiatry and Allied Disciplines 37, 873-877.
7. Hoy, J.A., Hatton, C., and Hare, D. (2004). Weak central coherence: a cross-domain phenomenon specific to autism? Autism 8, 267-281.
8. Milne, E., and Scope, A. (2008). Are children with autistic spectrum disorders susceptible to contour illusions? British Journal of Developmental Psychology 26, 91-102.
9. Mitchell, P., and Ropar, D. (2004). Visuo-spatial abilities in autism: A review. Infant and Child Development 13, 185-198.
10. Montague, P.R., Dolan, R.J., Friston, K.J., and Dayan, P. (2012). Computational psychiatry. Trends in Cognitive Sciences 16, 72-80.
11. Pellicano, E., and Burr, D. (2012). When the world becomes 'too real': a Bayesian explanation of autistic perception. Trends in Cognitive Sciences 16, 504-510.
12. Simmons, D.R., Robertson, A.E., Mckay, L.S., Toal, E., Mcaleer, P., and Pollick, F.E. (2009). Vision in autism spectrum disorders. Vision Research 49, 2705-2739.
13. Van Boxtel, J.J.A., and Lu, H. (2013). A predictive coding perspective on autism spectrum disorders: a General Comment on Pellicano and Burr (2012). Frontiers in Psychology 4.
14. Weiss, Y., Simoncelli, E.P., and Adelson, E.H. (2002). Motion illusions as optimal percepts. Nature Neuroscience 5, 598-604.
15. Young, G. A., & Smith, R. L. (2005). Essentials of statistical inference. Cambridge, UK: Cambridge University Press.