Optimal multisensory integration leads to optimal time estimation

Our brain compensates sensory uncertainty by combining multisensory information derived from an event, and by integrating the current sensory signal with the prior knowledge about the statistical structure of previous events. There is growing evidence that both strategies are statistically optimal; however, how these two stages of information integration interact and shape an optimal percept remains an open question. In the present study, we investigated the perception of time as an amodal perceptual attribute. The central tendency, a phenomenon of biasing the current percept toward previous stimuli, is used to quantify and model how the prior information affects the current timing behavior. We measured the timing sensitivity and the central tendency for unisensory and multisensory stimuli with sensory uncertainty systematically manipulated by adding noise. Psychophysical results demonstrate that the central tendency increases as the uncertainty increases, and that the multisensory timing improves both the timing sensitivity and the central tendency bias compared to the unisensory timing. Computational models indicate that the optimal multisensory integration precedes the optimal integration of prior information causing the central tendency. Our findings suggest that our brain incorporates the multisensory information and prior knowledge in a statistically optimal manner to realize precise and accurate timing behavior.