ABSTRACT
This chapter examines from a theoretical standpoint, the optimal means for intersensory integration in the face of random measurement error. It compares it to what we know about the intersensory integration in humans. It then shows how combining information across senses can improve estimation of object properties. There are identifiable benefits and problems associated with intersensory integration. It suggests a mechanism for such dynamic weight adjustment. The chapter examines the phenomenon of visual dominance by looking at work on visual-haptic integration in size and shape perception and visual-proprioceptive integration in the perception of hand and arm position. In intersensory tasks, the integrator describes always uses information from both sensory systems, so the combined percept always reflects both sources of information. The purpose of presenting the neural scheme is to show that optimal integration could in principle be accomplished with a simple, plausible neural circuit.
