Dynamic re-weighting of multisensory cues
Summary
The Bayesian Maximum Likelihood model provides a good description of how sensory information is combined. This project will use a new continuous-measurement technique to measure sensory integration in a dynamic context to study the dynamics of sensory integration.
Supervisor(s)
Research Location
Program Type
Masters/PHD
Synopsis
The Bayesian Maximum Likelihood model provides a good description of how sensory information is combined. This project will use a new continuous-measurement technique to measure sensory integration in a dynamic context to study the dynamics of sensory integration.
Want to find out more?
Contact us to find out what’s involved in applying for a PhD. Domestic students and International students
Contact Research Expert to find out more about participating in this opportunity.
Browse for other opportunities within the School of Psychology .
Keywords
Cross-modal, multisensory, sensory integration Bayesian integration, cue combination, weighted combination
Opportunity ID
The opportunity ID for this research opportunity is: 2852
Other opportunities with Professor David Alais