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JournalISSN: 2213-4794

Multisensory Research 

Brill
About: Multisensory Research is an academic journal published by Brill. The journal publishes majorly in the area(s): Multisensory integration & Perception. It has an ISSN identifier of 2213-4794. Over the lifetime, 410 publications have been published receiving 4681 citations.

Papers published on a yearly basis

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Journal ArticleDOI
TL;DR: The goal of this review is to show the importance of interaction between sensory systems during the early period of life in order to correct perceptual development to occur.
Abstract: During the first years of life, sensory modalities communicate with each other. This process is fundamental for the development of unisensory and multisensory skills. The absence of one sensory input impacts on the development of other modalities. Since 2008 we have studied these aspects and developed our cross-sensory calibration theory. This theory emerged from the observation that children start to integrate multisensory information (such as vision and touch) only after 8–10 years of age. Before this age the more accurate sense teaches (calibrates) the others; when one calibrating modality is missing, the other modalities result impaired. Children with visual disability have problems in understanding the haptic or auditory perception of space and children with motor disabilities have problems in understanding the visual dimension of objects. This review presents our recent studies on multisensory integration and cross-sensory calibration in children and adults with and without sensory and motor disabilities. The goal of this review is to show the importance of interaction between sensory systems during the early period of life in order to correct perceptual development to occur.

97 citations

Journal ArticleDOI
TL;DR: The latest evidence concerning the various ways in which what the authors hear can influence what they taste leads to the growing realization that the crossmodal influences of music and noise on food perception and consumer behaviour may have some important if, as yet, unrecognized implications for public health.
Abstract: Food product-extrinsic sounds (i.e., those auditory stimuli that are not linked directly to a food or beverage product, or its packaging) have been shown to exert a significant influence over various aspects of food perception and consumer behaviour, often operating outside of conscious awareness. In this review, we summarise the latest evidence concerning the various ways in which what we hear can influence what we taste. According to one line of empirical research, background noise interferes with tasting, due to attentional distraction. A separate body of marketing-relevant research demonstrates that music can be used to bias consumers' food perception, judgments, and purchasing/consumption behaviour in various ways. Some of these effects appear to be driven by the arousal elicited by loud music as well as the entrainment of people's behaviour to the musical beat. However, semantic priming effects linked to the type and style of music are also relevant. Another route by which music influences food perception comes from the observation that our liking/preference for the music that we happen to be listening to carries over to influence our hedonic judgments of what we are tasting. A final route by which hearing influences tasting relates to the emerging field of 'sonic seasoning'. A developing body of research now demonstrates that people often rate tasting experiences differently when listening to soundtracks that have been designed to be (or are chosen because they are) congruent with specific flavour experiences (e.g., when compared to when listening to other soundtracks, or else when tasting in silence). Taken together, such results lead to the growing realization that the crossmodal influences of music and noise on food perception and consumer behaviour may have some important if, as yet, unrecognized implications for public health.

91 citations

Journal ArticleDOI
TL;DR: It is concluded that although the haptic sense seems to be crucial for material perception, the information it can gather alone might not be quite fine-grained and rich enough for perfect material recognition.
Abstract: Research on material perception has received an increasing amount of attention recently. Clearly, both the visual and the haptic sense play important roles in the perception of materials, yet it is still unclear how both senses compare in material perception tasks. Here, we set out to investigate the degree of correspondence between the visual and the haptic representations of different materials. We asked participants to both categorize and rate 84 different materials for several material properties. In the haptic case, participants were blindfolded and asked to assess the materials based on haptic exploration. In the visual condition, participants assessed the stimuli based on their visual impressions only. While categorization performance was less consistent in the haptic condition than in the visual one, ratings correlated highly between the visual and the haptic modality. PCA revealed that all material samples were similarly organized within the perceptual space in both modalities. Moreover, in both senses the first two principal components were dominated by hardness and roughness. These are two material features that are fundamental for the haptic sense. We conclude that although the haptic sense seems to be crucial for material perception, the information it can gather alone might not be quite fine-grained and rich enough for perfect material recognition.

90 citations

Journal ArticleDOI
Cesare Parise1
TL;DR: Questions about their definition, origins, their plasticity, and their underlying computational mechanisms are reviewed in the light of current research on sensory cue integration, where crossmodal correspondences can be conceptualized in terms of natural mappings across different sensory cues that are present in the environment and learnt by the sensory systems.
Abstract: Crossmodal correspondences refer to the systematic associations often found across seemingly unrelated sensory features from different sensory modalities. Such phenomena constitute a universal trait of multisensory perception even in non-human species, and seem to result, at least in part, from the adaptation of sensory systems to natural scene statistics. Despite recent developments in the study of crossmodal correspondences, there are still a number of standing questions about their definition, their origins, their plasticity, and their underlying computational mechanisms. In this paper, I will review such questions in the light of current research on sensory cue integration, where crossmodal correspondences can be conceptualized in terms of natural mappings across different sensory cues that are present in the environment and learnt by the sensory systems. Finally, I will provide some practical guidelines for the design of experiments that might shed new light on crossmodal correspondences.

85 citations

Journal ArticleDOI
TL;DR: This tutorial explains in an accessible manner how to design optimal cue Integration experiments and how to analyse the results from these experiments to test whether humans follow the predictions of the optimal cue integration model.
Abstract: Humans combine redundant multisensory estimates into a coherent multimodal percept. Experiments in cue integration have shown for many modality pairs and perceptual tasks that multisensory information is fused in a statistically optimal manner: observers take the unimodal sensory reliability into consideration when performing perceptual judgments. They combine the senses according to the rules of Maximum Likelihood Estimation to maximize overall perceptual precision. This tutorial explains in an accessible manner how to design optimal cue integration experiments and how to analyse the results from these experiments to test whether humans follow the predictions of the optimal cue integration model. The tutorial is meant for novices in multisensory integration and requires very little training in formal models and psychophysical methods. For each step in the experimental design and analysis, rules of thumb and practical examples are provided. We also publish Matlab code for an example experiment on cue integration and a Matlab toolbox for data analysis that accompanies the tutorial online. This way, readers can learn about the techniques by trying them out themselves. We hope to provide readers with the tools necessary to design their own experiments on optimal cue integration and enable them to take part in explaining when, why and how humans combine multisensory information optimally.

78 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202315
202227
202121
202057
201935
201841