PT  - JOURNAL ARTICLE
AU  - Claire Chambers
AU  - Taegh Sokhey
AU  - Deborah Gaebler-Spira
AU  - Konrad Kording
TI  - The development of Bayesian integration in sensorimotor estimation
AID  - 10.1101/136267
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 136267
4099  - http://biorxiv.org/content/early/2017/05/10/136267.short
4100  - http://biorxiv.org/content/early/2017/05/10/136267.full
AB  - If the brain is inherently Bayesian, then behavior should show the signatures of Bayesian computation from an early stage in life without the need for learning. Children should integrate probabilistic information from prior and likelihood distributions to reach decisions and should be as statistically efficient as adults. To test this idea, we examined the integration of prior and likelihood information in a simple position estimation task comparing children aged 6-11 years and adults. During development, estimation performance became closer to the statistical optimum. Children use likelihood information as well as adults but are limited in their use of priors. This finding suggests that Bayesian behavior is not inherent but learnt over the course of development.