Causal Inference in Audiovisual Perception

Older adults preserve audiovisual integration through enhanced cortical activations, not by recruiting new regions

Effective interactions with the environment rely on the integration of multisensory signals: Our brains must efficiently combine signals that share a common source, and segregate those that do not. Healthy ageing can change or impair this process. This functional magnetic resonance imaging study assessed the neural mechanisms underlying age differences in the integration of auditory and visual spatial cues. Participants were presented with synchronous audiovisual signals at various degrees of spatial disparity and indicated their perceived sound location. Behaviourally, older adults were able to maintain localisation accuracy. At the neural level, they integrated auditory and visual cues into spatial representations along dorsal auditory and visual processing pathways similarly to their younger counterparts but showed greater activations in a widespread system of frontal, temporal, and parietal areas. According to multivariate Bayesian decoding, these areas encoded critical stimulus information beyond that which was encoded in the brain areas commonly activated by both groups. Surprisingly, however, the boost in information provided by these areas with age-related activation increases was comparable across the 2 age groups. This dissociation-between comparable information encoded in brain activation patterns across the 2 age groups, but age-related increases in regional blood-oxygen-level-dependent responses-contradicts the widespread notion that older adults recruit new regions as a compensatory mechanism to encode task-relevant information. Instead, our findings suggest that activation increases in older adults reflect nonspecific or modulatory mechanisms related to less efficient or slower processing, or greater demands on attentional resources.

Multisensory Integration and Causal Inference in Typical and Atypical Populations

Multisensory perception is critical for effective interaction with the environment, but human responses to multisensory stimuli vary across the lifespan and appear changed in some atypical populations. In this review chapter, we consider multisensory integration within a normative Bayesian framework. We begin by outlining the complex computational challenges of multisensory causal inference and reliability-weighted cue integration, and discuss whether healthy young adults behave in accordance with normative Bayesian models. We then compare their behaviour with various other human populations (children, older adults, and those with neurological or neuropsychiatric disorders). In particular, we consider whether the differences seen in these groups are due only to changes in their computational parameters (such as sensory noise or perceptual priors), or whether the fundamental computational principles (such as reliability weighting) underlying multisensory perception may also be altered. We conclude by arguing that future research should aim explicitly to differentiate between these possibilities.

Development and experience-dependence of multisensory spatial processing

Multisensory spatial processes are fundamental for efficient interaction with the world. They include not only the integration of spatial cues across sensory modalities, but also the adjustment or recalibration of spatial representations to changing cue reliabilities, crossmodal correspondences, and causal structures. Yet how multisensory spatial functions emerge during ontogeny is poorly understood. New results suggest that temporal synchrony and enhanced multisensory associative learning capabilities first guide causal inference and initiate early coarse multisensory integration capabilities. These multisensory percepts are crucial for the alignment of spatial maps across sensory systems, and are used to derive more stable biases for adult crossmodal recalibration. The refinement of multisensory spatial integration with increasing age is further promoted by the inclusion of higher-order knowledge.

The role of conflict processing in multisensory perception: behavioural and electroencephalography evidence

To form coherent multisensory perceptual representations, the brain must solve a causal inference problem: to decide if two sensory cues originated from the same event and should be combined, or if they came from different events and should be processed independently. According to current models of multisensory integration, during this process, the integrated (common cause) and segregated (different causes) internal perceptual models are entertained. In the present study, we propose that the causal inference process involves competition between these alternative perceptual models that engages the brain mechanisms of conflict processing. To test this hypothesis, we conducted two experiments, measuring reaction times (RTs) and electroencephalography, using an audiovisual ventriloquist illusion paradigm with varying degrees of intersensory disparities. Consistent with our hypotheses, incongruent trials led to slower RTs and higher fronto-medial theta power, both indicative of conflict. We also predicted that intermediate disparities would yield slower RTs and higher theta power when compared to congruent stimuli and to large disparities, owing to the steeper competition between causal models. Although this prediction was only validated in the RT study, both experiments displayed the anticipated trend. In conclusion, our findings suggest a potential involvement of the conflict mechanisms in multisensory integration of spatial information. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Anterior cingulate glutamate levels associate with functional activation and connectivity during sensory integration in schizophrenia: a multimodal 1H-MRS and fMRI study

BACKGROUND

Glutamatergic dysfunction has been implicated in sensory integration deficits in schizophrenia, yet how glutamatergic function contributes to behavioural impairments and neural activities of sensory integration remains unknown.

METHODS

Fifty schizophrenia patients and 43 healthy controls completed behavioural assessments for sensory integration and underwent magnetic resonance spectroscopy (MRS) for measuring the anterior cingulate cortex (ACC) glutamate levels. The correlation between glutamate levels and behavioural sensory integration deficits was examined in each group. A subsample of 20 pairs of patients and controls further completed an audiovisual sensory integration functional magnetic resonance imaging (fMRI) task. Blood Oxygenation Level Dependent (BOLD) activation and task-dependent functional connectivity (FC) were assessed based on fMRI data. Full factorial analyses were performed to examine the Group-by-Glutamate Level interaction effects on fMRI measurements (group differences in correlation between glutamate levels and fMRI measurements) and the correlation between glutamate levels and fMRI measurements within each group.

RESULTS

We found that schizophrenia patients exhibited impaired sensory integration which was positively correlated with ACC glutamate levels. Multimodal analyses showed significantly Group-by-Glutamate Level interaction effects on BOLD activation as well as task-dependent FC in a 'cortico-subcortical-cortical' network (including medial frontal gyrus, precuneus, ACC, middle cingulate gyrus, thalamus and caudate) with positive correlations in patients and negative in controls.

CONCLUSIONS

Our findings indicate that ACC glutamate influences neural activities in a large-scale network during sensory integration, but the effects have opposite directionality between schizophrenia patients and healthy people. This implicates the crucial role of glutamatergic system in sensory integration processing in schizophrenia.

Changing the Tendency to Integrate the Senses

Integration of sensory signals that emanate from the same source, such as the visual of lip articulations and the sound of the voice of a speaking individual, can improve perception of the source signal (e.g., speech). Because momentary sensory inputs are typically corrupted with internal and external noise, there is almost always a discrepancy between the inputs, facing the perceptual system with the problem of determining whether the two signals were caused by the same source or different sources. Thus, whether or not multisensory stimuli are integrated and the degree to which they are bound is influenced by factors such as the prior expectation of a common source. We refer to this factor as the tendency to bind stimuli, or for short, binding tendency. In theory, the tendency to bind sensory stimuli can be learned by experience through the acquisition of the probabilities of the co-occurrence of the stimuli. It can also be influenced by cognitive knowledge of the environment. The binding tendency varies across individuals and can also vary within an individual over time. Here, we review the studies that have investigated the plasticity of binding tendency. We discuss the protocols that have been reported to produce changes in binding tendency, the candidate learning mechanisms involved in this process, the possible neural correlates of binding tendency, and outstanding questions pertaining to binding tendency and its plasticity. We conclude by proposing directions for future research and argue that understanding mechanisms and recipes for increasing binding tendency can have important clinical and translational applications for populations or individuals with a deficiency in multisensory integration.

Audiovisual adaptation is expressed in spatial and decisional codes

The brain adapts dynamically to the changing sensory statistics of its environment. Recent research has started to delineate the neural circuitries and representations that support this cross-sensory plasticity. Combining psychophysics and model-based representational fMRI and EEG we characterized how the adult human brain adapts to misaligned audiovisual signals. We show that audiovisual adaptation is associated with changes in regional BOLD-responses and fine-scale activity patterns in a widespread network from Heschl’s gyrus to dorsolateral prefrontal cortices. Audiovisual recalibration relies on distinct spatial and decisional codes that are expressed with opposite gradients and time courses across the auditory processing hierarchy. Early activity patterns in auditory cortices encode sounds in a continuous space that flexibly adapts to misaligned visual inputs. Later activity patterns in frontoparietal cortices code decisional uncertainty consistent with these spatial transformations. Our findings suggest that regions within the auditory processing hierarchy multiplex spatial and decisional codes to adapt flexibly to the changing sensory statistics in the environment.

The brain adapts dynamically to the statistics of its environment. Here, the authors use psychophysics and model-based representational fMRI and EEG to show that audiovisual recalibration relies on distinct spatial and decisional codes that are expressed with opposite gradients and time courses across the auditory processing hierarchy.

Multisensory correlation computations in the human brain identified by a time-resolved encoding model

Neural mechanisms that arbitrate between integrating and segregating multisensory information are essential for complex scene analysis and for the resolution of the multisensory correspondence problem. However, these mechanisms and their dynamics remain largely unknown, partly because classical models of multisensory integration are static. Here, we used the Multisensory Correlation Detector, a model that provides a good explanatory power for human behavior while incorporating dynamic computations. Participants judged whether sequences of auditory and visual signals originated from the same source (causal inference) or whether one modality was leading the other (temporal order), while being recorded with magnetoencephalography. First, we confirm that the Multisensory Correlation Detector explains causal inference and temporal order behavioral judgments well. Second, we found strong fits of brain activity to the two outputs of the Multisensory Correlation Detector in temporo-parietal cortices. Finally, we report an asymmetry in the goodness of the fits, which were more reliable during the causal inference task than during the temporal order judgment task. Overall, our results suggest the existence of multisensory correlation detectors in the human brain, which explain why and how causal inference is strongly driven by the temporal correlation of multisensory signals.

Unity Assumption in Audiovisual Emotion Perception

We experience various sensory stimuli every day. How does this integration occur? What are the inherent mechanisms in this integration? The “unity assumption” proposes a perceiver’s belief of unity in individual unisensory information to modulate the degree of multisensory integration. However, this has yet to be verified or quantified in the context of semantic emotion integration. In the present study, we investigate the ability of subjects to judge the intensities and degrees of similarity in faces and voices of two emotions (angry and happy). We found more similar stimulus intensities to be associated with stronger likelihoods of the face and voice being integrated. More interestingly, multisensory integration in emotion perception was observed to follow a Gaussian distribution as a function of the emotion intensity difference between the face and voice—the optimal cut-off at about 2.50 points difference on a 7-point Likert scale. This provides a quantitative estimation of the multisensory integration function in audio-visual semantic emotion perception with regards to stimulus intensity. Moreover, to investigate the variation of multisensory integration across the population, we examined the effects of personality and autistic traits of participants. Here, we found no correlation of autistic traits with unisensory processing in a nonclinical population. Our findings shed light on the current understanding of multisensory integration mechanisms.

Attention controls multisensory perception via two distinct mechanisms at different levels of the cortical hierarchy

To form a percept of the multisensory world, the brain needs to integrate signals from common sources weighted by their reliabilities and segregate those from independent sources. Previously, we have shown that anterior parietal cortices combine sensory signals into representations that take into account the signals' causal structure (i.e., common versus independent sources) and their sensory reliabilities as predicted by Bayesian causal inference. The current study asks to what extent and how attentional mechanisms can actively control how sensory signals are combined for perceptual inference. In a pre- and postcueing paradigm, we presented observers with audiovisual signals at variable spatial disparities. Observers were precued to attend to auditory or visual modalities prior to stimulus presentation and postcued to report their perceived auditory or visual location. Combining psychophysics, functional magnetic resonance imaging (fMRI), and Bayesian modelling, we demonstrate that the brain moulds multisensory inference via two distinct mechanisms. Prestimulus attention to vision enhances the reliability and influence of visual inputs on spatial representations in visual and posterior parietal cortices. Poststimulus report determines how parietal cortices flexibly combine sensory estimates into spatial representations consistent with Bayesian causal inference. Our results show that distinct neural mechanisms control how signals are combined for perceptual inference at different levels of the cortical hierarchy.

Perceptual Inference, Learning, and Attention in a Multisensory World

Adaptive behavior in a complex, dynamic, and multisensory world poses some of the most fundamental computational challenges for the brain, notably inference, decision-making, learning, binding, and attention. We first discuss how the brain integrates sensory signals from the same source to support perceptual inference and decision-making by weighting them according to their momentary sensory uncertainties. We then show how observers solve the binding or causal inference problem-deciding whether signals come from common causes and should hence be integrated or else be treated independently. Next, we describe the multifarious interplay between multisensory processing and attention. We argue that attentional mechanisms are crucial to compute approximate solutions to the binding problem in naturalistic environments when complex time-varying signals arise from myriad causes. Finally, we review how the brain dynamically adapts multisensory processing to a changing world across multiple timescales.

Gray matter volume in the right angular gyrus is associated with differential patterns of multisensory integration with aging

Multisensory perception might provide an important marker of brain function in aging. However, the cortical structures supporting multisensory perception in aging are poorly understood. In this study, we compared regional gray matter volume in a group of middle-aged (n = 101; 49-64 years) and older (n = 116; 71-87 years) adults from The Irish Longitudinal Study on Aging using voxel-based morphometry. Participants completed a measure of multisensory integration, the sound-induced flash illusion, and were grouped as per their illusion susceptibility. A significant interaction was observed in the right angular gyrus; in the middle-aged group, larger gray matter volume corresponded to stronger illusion perception while in older adults larger gray matter corresponded to less illusion susceptibility. This interaction remained significant even when controlling for a range of demographic, sensory, cognitive, and health variables. These findings show that multisensory integration is associated with specific structural differences in the aging brain and highlight the angular gyrus as a possible "cross-modal hub" associated with age-related change in multisensory perception.