Abstract
In order to understand the world around us, we combine information across the different senses. This multisensory integration is highly dependent on the temporal relationship between unisensory events and our brain’s ability to discern small timing differences between stimuli (crossmodal temporal acuity). Our previous research found that increasing both visual and auditory perceptual load led to sharp declines in participants’ crossmodal temporal acuity. Previous research in other labs has demonstrated that the brain integrates multisensory information in a Bayes’ optimal way and that the integration of temporally disparate audiovisual stimuli can be modeled using Bayesian causal inference modeling. The present study investigates the influence of visual and auditory perceptual load on the integration of simple stimuli using Bayesian modeling. Participants completed a simultaneity judgment (SJ) task during which they determined whether temporally offset flash-beep stimuli occurred (a)synchronously. In addition, participants completed the SJ task alone (distractor free; DF), in the presence of task-irrelevant visual or auditory distractors (no load; NL), and while completing a concurrent visual or auditory distractor task (high load; HL). Data was modeled using the causal inference model derived in Magnotti et al. 2013, which is based on Bayesian statistics. Our preliminary data show an increase in the temporal binding window for both visual and auditory NL and HL as compared to DF conditions, indicating that the presence of extraneous stimuli enlarge the temporal binding window. Sensory noise increased in the visual and auditory HL conditions as compared to the DF and NL. Similarly, the prior likelihood to assume synchronicity (prior) decreased only when participants attended to the distractors (HL). These preliminary findings indicate that attention alters both low-level (sensory noise) and high-level (priors) processing of simple multisensory stimuli and that our previously observed effects of attention multisensory temporal processing are generalizable