RSE-box: An analysis and modelling package to study response times to multiple signals

The impact of acute asymmetric hearing loss on multisensory integration

Humans have the remarkable ability to integrate information from different senses, which greatly facilitates the detection, localization and identification of events in the environment. About 466 million people worldwide suffer from hearing loss. Yet, the impact of hearing loss on how the senses work together is rarely investigated. Here, we investigate how a common sensory impairment, asymmetric conductive hearing loss (AHL), alters the way our senses interact by examining human orienting behaviour with normal hearing (NH) and acute AHL. This type of hearing loss disrupts auditory localization. We hypothesized that this creates a conflict between auditory and visual spatial estimates and alters how auditory and visual inputs are integrated to facilitate multisensory spatial perception. We analysed the spatial and temporal properties of saccades to auditory, visual and audiovisual stimuli before and after plugging the right ear of participants. Both spatial and temporal aspects of multisensory integration were affected by AHL. Compared with NH, AHL caused participants to make slow, inaccurate and unprecise saccades towards auditory targets. Surprisingly, increased weight on visual input resulted in accurate audiovisual localization with AHL. This came at a cost: saccade latencies for audiovisual targets increased significantly. The larger the auditory localization errors, the less participants were able to benefit from audiovisual integration in terms of saccade latency. Our results indicate that observers immediately change sensory weights to effectively deal with acute AHL and preserve audiovisual accuracy in a way that cannot be fully explained by statistical models of optimal cue integration.

Semantic congruency modulates the speed-up of multisensory responses

Responses to multisensory signals are often faster compared to their unisensory components. This speed-up is typically attributed to target redundancy in that a correct response can be triggered by one or the other signal. In addition, semantic congruency of signals can also modulate multisensory responses; however, the contribution of semantic content is difficult to isolate as its manipulation commonly changes signal redundancy as well. To disentangle the effects of redundancy and semantic congruency, we manipulated semantic content but kept redundancy constant. We presented semantically congruent/incongruent animal pictures and sounds and asked participants to respond with the same response to two target animals (cats and dogs). We find that the speed-up of multisensory responses is larger for congruent (e.g., barking dogs) than incongruent combinations (e.g., barking cats). We then used a computational modelling approach to analyse audio-visual processing interferences that may underlie the effect. Our data is best described by a model that explains the semantic congruency modulation with a parameter that was previously linked to trial sequence effects, which in our experiment occur from the repetition/switching of both sensory modality and animal category. Yet, a systematic analysis of such trial sequence effects shows that the reported congruency effect is an independent phenomenon. Consequently, we discuss potential contributors to the semantic modulation of multisensory responses.

Modal-based attention modulates the redundant-signals effect: Role of unimodal target probability

Multisensory integration includes two behavioral manifestations: the modality dominance effect and the redundant-signals effect (RSE). RSE is a multisensory improvement effect in which individuals respond more quickly and accurately to bimodal audiovisual (AV) targets than to unimodal auditory (A) or visual (V) targets. Previous studies have confirmed that RSE is the product of modality interactions between different modalities. The goal of this study was to systematically investigate the effects of the modality dominance manipulated by modal-based attention and unimodal target probability on RSE. The results showed that when paying attention to both the A and V modalities (Exp. 1), RSE was not significantly different between unimodal target probabilities. When selectively paying attention to the A modality (Exp. 2A), RSE was also not significantly different between unimodal target probabilities. However, when selectively paying attention to the V modality (Exp. 2B), the magnitude of RSE showed a significant decreasing trend with the increasing probability of V targets. Our study is the first to reveal that the unimodal target probability significantly modulates RSE in visual selective attention, and this modulatory effect of the unimodal target probability on RSE is opposite to the modulatory effect on the modality dominance effect.

Robust perceptual-load-dependent audiovisual integration in adult ADHD

We perceive our daily-life surrounded by different senses (e.g., visual, and auditory). For a coherent percept, our brain binds those multiple streams of sensory stimulations, i.e., multisensory integration (MI). Dependent on stimulus complexity, early MI is triggered by bottom-up or late via top-down attentional deployment. Adult attention-deficit/hyperactivity disorder (ADHD) is associated with successful bottom-up MI and deficient top-down MI. In the current study, we investigated the robustness of the bottom-up MI by adding additional task demand varying the perceptual load. We hypothesized diminished bottom-up MI for high perceptual load for patients with ADHD. 18 adult patients with ADHD and 18 age- and gender-matched healthy controls participated in this study. In the visual search paradigm, a target letter was surrounded by uniform distractors (low load) or by different letters (high load). Additionally, either unimodal (visual flash, auditory beep) or multimodal (audiovisual) flanked the visual search. Linear-mixed modeling was used to investigate the influence of load on reaction times. Further, the race model inequality was calculated. Patients with ADHD showed a similar degree of MI performance like healthy controls, irrespective of perceptual load manipulation. ADHD patients violated the race model for the low load but not for the high-load condition. There seems to be robust bottom-up MI independent of perceptual load in ADHD patients. However, the sensory accumulation might be altered when attentional demands are high.

The relationship between multisensory associative learning and multisensory integration

Integrating sensory information from multiple modalities leads to more precise and efficient perception and behaviour. The process of determining which sensory information should be perceptually bound is reliant on both low-level stimulus features, as well as multisensory associations learned throughout development based on the statistics of our environment. Here, we explored the relationship between multisensory associative learning and multisensory integration using encephalography (EEG) and behavioural measures. Sixty-one participants completed a three-phase study. First, participants were exposed to novel audiovisual shape-tone pairings with frequent and infrequent stimulus pairings and complete a target detection task. EEG recordings of the mismatch negativity (MMN) and P3 were calculated as neural indices of multisensory associative learning. Next, the same learned stimulus pairs were presented in audiovisual as well as unisensory auditory and visual modalities while both early (<120 ms) and late neural indices of multisensory integration were recorded. Finally, participants completed an analogous behavioural speeded-response task, with behavioural indices of multisensory gain calculated using the Race Model. Significant relationships were found in fronto-central and occipital areas between neural measures of associative learning and both early and late indices of multisensory integration in frontal and centro-parietal areas, respectively. Participants who showed stronger indices of associative learning also exhibited stronger indices of multisensory integration of the stimuli they learned to associate. Furthermore, a significant relationship was found between neural index of early multisensory integration and behavioural indices of multisensory gain. These results provide insight into the neural underpinnings of how higher-order processes such as associative learning guide multisensory integration.

Resolution of impaired multisensory processing in autism and the cost of switching sensory modality

Children with autism spectrum disorders (ASD) exhibit alterations in multisensory processing, which may contribute to the prevalence of social and communicative deficits in this population. Resolution of multisensory deficits has been observed in teenagers with ASD for complex, social speech stimuli; however, whether this resolution extends to more basic multisensory processing deficits remains unclear. Here, in a cohort of 364 participants we show using simple, non-social audiovisual stimuli that deficits in multisensory processing observed in high-functioning children and teenagers with ASD are not evident in adults with the disorder. Computational modelling indicated that multisensory processing transitions from a default state of competition to one of facilitation, and that this transition is delayed in ASD. Further analysis revealed group differences in how sensory channels are weighted, and how this is impacted by preceding cross-sensory inputs. Our findings indicate that there is a complex and dynamic interplay among the sensory systems that differs considerably in individuals with ASD.

Crosse et al. study a cohort of 364 participants with autism spectrum disorders (ASD) and matched controls, and show that deficits in multisensory processing observed in high-functioning children and teenagers with ASD are not evident in adults with the disorder. Using computational modelling they go on to demonstrate that there is a delayed transition of multisensory processing from a default state of competition to one of facilitation in ASD, as well as differences in sensory weighting and the ability to switch between sensory modalities, which sheds light on the interplay among sensory systems that differ in ASD individuals.

No selective integration required: A race model explains responses to audiovisual motion-in-depth

Looming motion is an ecologically salient signal that often signifies danger. In both audition and vision, humans show behavioral biases in response to perceiving looming motion, which is suggested to indicate an adaptation for survival. However, it is an open question whether such biases occur also in the combined processing of multisensory signals. Towards this aim, Cappe, Thut, Romei, and Murraya (2009) found that responses to audiovisual signals were faster for congruent looming motion compared to receding motion or incongruent combinations. They considered this as evidence for selective integration of multisensory looming signals. To test this proposal, here, we successfully replicate the behavioral results by Cappe et al. (2009). We then show that the redundant signals effect (RSE - a speedup of multisensory compared to unisensory responses) is not distinct for congruent looming motion. Instead, as predicted by a simple probability summation rule, the RSE is primarily modulated by the looming bias in audition, which suggests that multisensory processing inherits a unisensory effect. Finally, we compare a large set of so-called race models that implement probability summation, but that allow for interference between auditory and visual processing. The best-fitting model, selected by the Akaike Information Criterion (AIC), virtually perfectly explained the RSE across conditions with interference parameters that were either constant or varied only with auditory motion. In the absence of effects jointly caused by auditory and visual motion, we conclude that selective integration is not required to explain the behavioral benefits that occur with audiovisual looming motion.

Multisensory integration attenuates visually induced oculomotor inhibition of return

Inhibition of return (IOR) is a mechanism of the attention system involving bias toward novel stimuli and delayed generation of responses to targets at previously attended locations. According to the two-component theory, IOR consists of a perceptual component and an oculomotor component (oculomotor IOR [O-IOR]) depending on whether the eye movement system is activated. Previous studies have shown that multisensory integration weakens IOR when paying attention to both visual and auditory modalities. However, it remains unclear whether the O-IOR effect attenuated by multisensory integration also occurs when the oculomotor system is activated. Here, using two eye movement experiments, we investigated the effect of multisensory integration on O-IOR using the exogenous spatial cueing paradigm. In Experiment 1, we found a greater visual O-IOR effect compared with audiovisual and auditory O-IOR in divided modality attention. The relative multisensory response enhancement (rMRE) and violations of Miller's bound showed a greater magnitude of multisensory integration in the cued location compared with the uncued location. In Experiment 2, the magnitude of the audiovisual O-IOR effect was significantly less than that of the visual O-IOR in single visual modality selective attention. Implications for the effect of multisensory integration on O-IOR were discussed under conditions of oculomotor system activation, shedding new light on the two-component theory of IOR.

Top-down task-specific determinants of multisensory motor reaction time enhancements and sensory switch costs

This study was designed to investigate the complex interplay between multisensory processing, top–down processes related to the task relevance of sensory signals, and sensory switching. Thirty-five adults completed either a speeded detection or a discrimination task using the same auditory and visual stimuli and experimental setup. The stimuli consisted of unisensory and multisensory presentations of the letters ‘b’ and ‘d’. The multisensory stimuli were either congruent (e.g., the grapheme ‘b’ with the phoneme /b/) or incongruent (e.g., the grapheme ‘b’ with the phoneme /d/). In the detection task, the participants had to respond to all of the stimuli as rapidly as possible while, in the discrimination task, they only responded on those trials where one prespecified letter (either ‘b’ or ‘d’) was present. Incongruent multisensory stimuli resulted in faster responses as compared to unisensory stimuli in the detection task. In the discrimination task, only the dual-target congruent stimuli resulted in faster RTs, while the incongruent multisensory stimuli led to slower RTs than to unisensory stimuli; RTs were the slowest when the visual (rather than the auditory) signal was irrelevant, thus suggesting visual dominance. Switch costs were also observed when switching between unisensory target stimuli, while dual-target multisensory stimuli were less likely to be affected by sensory switching. Taken together, these findings suggest that multisensory motor enhancements and sensory switch costs are influenced by top–down modulations determined by task instructions, which can override the influence of prior learnt associations.

The additive nature of the human multisensory evoked pupil response

Pupillometry has received increased interest for its usefulness in measuring various sensory processes as an alternative to behavioural assessments. This is also apparent for multisensory investigations. Studies of the multisensory pupil response, however, have produced conflicting results. Some studies observed super-additive multisensory pupil responses, indicative of multisensory integration (MSI). Others observed additive multisensory pupil responses even though reaction time (RT) measures were indicative of MSI. Therefore, in the present study, we investigated the nature of the multisensory pupil response by combining methodological approaches of previous studies while using supra-threshold stimuli only. In two experiments we presented auditory and visual stimuli to observers that evoked a(n) (onset) response (be it constriction or dilation) in a simple detection task and a change detection task. In both experiments, the RT data indicated MSI as shown by race model inequality violation. Still, the multisensory pupil response in both experiments could best be explained by linear summation of the unisensory pupil responses. We conclude that the multisensory pupil response for supra-threshold stimuli is additive in nature and cannot be used as a measure of MSI, as only a departure from additivity can unequivocally demonstrate an interaction between the senses.