介绍多感觉通道（比如视觉、听觉和触觉）信息加工、感知与运动学习过程中的认知建模原理和实践

英文摘要： 

The brain receives information about the environment from all sensory modalities, including vision, touch, and audition. To efficiently interact with the environment, this information must eventually converge in the brain in order to form a reliable and accurate multimodal percept. This process is often complicated by the existence of environmental disturbances and signal noise, which makes the sensory information derived from the world imprecise, potentially inaccurate and sometimes ambiguous. Many recent studies have shown that human multisensory perception and action is using the available sensory information in a close to optimal way. However, the environment we live in is constantly changing so that in order to behave optimal, humans have to adapt to these changes. In this talk I will review some of our recent findings on multisensory integration and sensorimotor learning and will show how humans make optimal use of the ever changing statistical regularities of the environment for integration and action. Ultimately, the goal is to develop a model for multisensory perception for action based on Bayesian Decision Theory that can capture human integration and adaptation behavior from first principles.