Cross-modal training reduced susceptibility to the sound-induced flash illusion and generalized across stimulus onset asynchronies - Psychological Research

The sound-induced flash illusion (SiFI) is a typical auditory-dominated multisensory illusion, and its susceptibility can be modified by perceptual training. However, the effects of different training protocols and their transfer effects on SiFI remain unclear. The present study employed the SiFI paradigm combined with feedback training to examine the effects of different types of training on SiFI performance across multiple stimulus onset asynchronies (SOAs). SOA was manipulated in the pretest and posttest to determine whether training effects would generalize to untrained temporal intervals. Participants were assigned to four groups, including a control group that completed only the pretest and posttest and three training groups that received 5 days of combined training, audiovisual training, or visual-only training respectively. The results showed that perceptual training significantly improved performance on the SiFI task, but the magnitude of improvement differed across training modalities. Audiovisual and combined training were more effective than visual-only training, and these benefits generalized from the trained SOA to untrained SOAs, indicating transfer of the training effect across temporal intervals. These findings suggest that cross-modal training is more effective than unimodal visual training in reducing SiFI susceptibility and provide further evidence for the plasticity of multisensory perceptual processing.

Cross-modal training reduced susceptibility to the sound-induced flash illusion and generalized across stimulus onset asynchronies - Psychological Research

The sound-induced flash illusion (SiFI) is a typical auditory-dominated multisensory illusion, and its susceptibility can be modified by perceptual training. However, the effects of different training protocols and their transfer effects on SiFI remain unclear. The present study employed the SiFI paradigm combined with feedback training to examine the effects of different types of training on SiFI performance across multiple stimulus onset asynchronies (SOAs). SOA was manipulated in the pretest and posttest to determine whether training effects would generalize to untrained temporal intervals. Participants were assigned to four groups, including a control group that completed only the pretest and posttest and three training groups that received 5 days of combined training, audiovisual training, or visual-only training respectively. The results showed that perceptual training significantly improved performance on the SiFI task, but the magnitude of improvement differed across training modalities. Audiovisual and combined training were more effective than visual-only training, and these benefits generalized from the trained SOA to untrained SOAs, indicating transfer of the training effect across temporal intervals. These findings suggest that cross-modal training is more effective than unimodal visual training in reducing SiFI susceptibility and provide further evidence for the plasticity of multisensory perceptual processing.

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1 likes, 0 comments - familywelltraveled on March 6, 2026: "When we stepped out of Omega Mart's supermarket, we stepped into other worlds and galaxies. It was a truly multi-sensory experience that we will never forget. Here's a brief glimpse at some of what you'll see in Omega Mart, which is a Meow Wolf interactive art exhibit in Las Vegas. #omegamart #lasvegas #multisensory #familytravel #meowwolflasvegas".

Crossmodal interaction of flashes and beeps across time and number follows Bayesian causal inference - Psychonomic Bulletin & Review

Multisensory perception requires the brain to dynamically infer causal relationships between sensory inputs across various dimensions, such as temporal and spatial attributes. Traditionally, Bayesian Causal Inference (BCI) models have generally provided a robust framework for understanding sensory processing in unidimensional settings where stimuli across sensory modalities vary along one dimension such as spatial location, or numerosity (Samad et al., PloS one, 10 (2), e0117178, 2015). However, real-world sensory processing involves multidimensional cues, where the alignment of information across multiple dimensions influences whether the brain perceives a unified or segregated source. In an effort to investigate sensory processing in more realistic conditions, this study introduces an expanded BCI model that incorporates multidimensional information, specifically numerosity and temporal discrepancies. Using a modified sound-induced flash illusion (SiFI) paradigm with manipulated audiovisual disparities, we tested the performance of the enhanced BCI model. Results showed that integration probability decreased with increasing temporal discrepancies, and our proposed multidimensional BCI model accurately predicts multisensory perception outcomes under the entire range of stimulus conditions. This multidimensional framework extends the BCI model’s applicability, providing deeper insights into the computational mechanisms underlying multisensory processing and offering a foundation for future quantitative studies on naturalistic sensory processing.

Crossmodal interaction of flashes and beeps across time and number follows Bayesian causal inference - Psychonomic Bulletin & Review

Multisensory perception requires the brain to dynamically infer causal relationships between sensory inputs across various dimensions, such as temporal and spatial attributes. Traditionally, Bayesian Causal Inference (BCI) models have generally provided a robust framework for understanding sensory processing in unidimensional settings where stimuli across sensory modalities vary along one dimension such as spatial location, or numerosity (Samad et al., PloS one, 10 (2), e0117178, 2015). However, real-world sensory processing involves multidimensional cues, where the alignment of information across multiple dimensions influences whether the brain perceives a unified or segregated source. In an effort to investigate sensory processing in more realistic conditions, this study introduces an expanded BCI model that incorporates multidimensional information, specifically numerosity and temporal discrepancies. Using a modified sound-induced flash illusion (SiFI) paradigm with manipulated audiovisual disparities, we tested the performance of the enhanced BCI model. Results showed that integration probability decreased with increasing temporal discrepancies, and our proposed multidimensional BCI model accurately predicts multisensory perception outcomes under the entire range of stimulus conditions. This multidimensional framework extends the BCI model’s applicability, providing deeper insights into the computational mechanisms underlying multisensory processing and offering a foundation for future quantitative studies on naturalistic sensory processing.