Distinct computational principles govern multisensory integration in primary sensory and association cortices

Human observers typically integrate sensory signals in a statistically optimal fashion into a coherent percept by weighting them in proportion to their reliabilities [1, 2, 3 and 4]. An emerging debate in neuroscience is to which extent multisensory integration emerges already in primary sensory areas or is deferred to higher-order association areas [5, 6, 7, 8 and 9]. This fMRI study used multivariate pattern decoding to characterize the computational principles that define how auditory and visual signals are integrated into spatial representations across the cortical hierarchy. Our results reveal small multisensory influences that were limited to a spatial window of integration in primary sensory areas. By contrast, parietal cortices integrated signals weighted by their sensory reliabilities and task relevance in line with behavioral performance and principles of statistical optimality. Intriguingly, audiovisual integration in parietal cortices was attenuated for large spatial disparities when signals were unlikely to originate from a common source. Our results demonstrate that multisensory interactions in primary and association cortices are governed by distinct computational principles. In primary visual cortices, spatial disparity controlled the influence of non-visual signals on the formation of spatial representations, whereas in parietal cortices, it determined the influence of task-irrelevant signals. Critically, only parietal cortices integrated signals weighted by their bottom-up reliabilities and top-down task relevance into multisensory spatial priority maps to guide spatial orienting

Causal inference in multisensory perception and the brain

To build coherent and veridical multisensory representations of the environment, human observers consider the causal structure of multisensory signals: If they infer a common source of the signals, observers integrate them weighted by their reliability. Otherwise, they segregate the signals. Generally, observers infer a common source if the signals correspond structurally and spatiotemporally. In six projects, the current PhD thesis investigated this causal inference model with the help of audiovisual spatial signals presented to human observers in a ventriloquist paradigm. A first psychophysical study showed that sensory reliability determines causal inference via two mechanisms: Sensory reliability modulates how observers infer the causal structure from spatial signal disparity. Further, sensory reliability determines the weight of audiovisual signals if observers integrate the signals under assumption of a common source. Using multivariate decoding of fMRI signals, three PhD projects revealed that auditory and visual cortical hierarchies jointly implement causal inference. Specific regions of the hierarchies represented constituent spatial estimates of the causal inference model. In line with this model, anterior regions of intraparietal sulcus (IPS) represent audiovisual signals dependent on visual reliability, task-relevance, and spatial disparity of the signals. However, even in case of small signal discrepancies suggesting a common source, reliability-weighting in IPS was suboptimal as compared to a Maximum Estimation Likelihood model. By temporally manipulating visual reliability, the fifth PhD project demonstrated that human observers learn sensory reliability from current and past signals in order to weight audiovisual signals, consistent with a Bayesian learner. Finally, the sixth project showed that if visual flashes were rendered unaware by continuous flash suppression, the visual bias of the perceived auditory location was strongly reduced but still significant. The reduced ventriloquist effect was presumably mediated by the drop of visual reliability accompanying perceptual unawareness. In conclusion, the PhD thesis suggests that human observers integrate multisensory signals according to their causal structure and temporal regularity: They integrate the signals if a common source is likely by weighting them proportional to the reliability which they learnt from the signals’ history. Crucially, specific regions of cortical hierarchies jointly implement these multisensory processes

The Curious Incident of Attention in Multisensory Integration:Bottom-up vs. Top-down

The role attention plays in our experience of a coherent, multisensory world is still controversial. On the one hand, a subset of inputs may be selected for detailed processing and multisensory integration in a top-down manner, i.e., guidance of multisensory integration by attention. On the other hand, stimuli may be integrated in a bottom-up fashion according to low-level properties such as spatial coincidence, thereby capturing attention. Moreover, attention itself is multifaceted and can be described via both top-down and bottom-up mechanisms. Thus, the interaction between attention and multisensory integration is complex and situation-dependent. The authors of this opinion paper are researchers who have contributed to this discussion from behavioural, computational and neurophysiological perspectives. We posed a series of questions, the goal of which was to illustrate the interplay between bottom-up and top-down processes in various multisensory scenarios in order to clarify the standpoint taken by each author and with the hope of reaching a consensus. Although divergence of viewpoint emerges in the current responses, there is also considerable overlap: In general, it can be concluded that the amount of influence that attention exerts on MSI depends on the current task as well as prior knowledge and expectations of the observer. Moreover stimulus properties such as the reliability and salience also determine how open the processing is to influences of attention.</p

The neural basis of audio-visual integration and adaptation

The brain integrates or segregates audio-visual signals effortlessly in everyday life. In order to do so, it needs to infer the causal structure by which the signals were generated. Although behavioural studies extensively characterized causal inference in audio-visual perception, the neural mechanisms are barely explored. The current thesis sheds light on these neural processes and demonstrates how the brain adapts to dynamic as well as long-term changes in the environmental statistics of audio-visual signals. In Chapter 1, I introduce the causal inference problem and demonstrate how spatial audiovisual signals are integrated at the behavioural as well as neural level. In Chapter 2, I describe methodological foundations for the following empirical chapters. In Chapter 3, I present the neural mechanisms of explicit causal inference and the representations of audio-visual space along the human cortical hierarchy. Chapter 4 reveals that the brain is able to use recent past to adapt to the dynamically changing environment. In Chapter 5, I discuss the neural substrates of encoding auditory space and its adaptive changes in response to spatially conflicting visual signals. Finally, in Chapter 6, I summarize the findings of the thesis, its contributions to the literature, and I outline directions for future research

An Object-Based Interpretation of Audiovisual Processing

Visual cues help listeners follow conversation in a complex acoustic environment. Many audiovisual research studies focus on how sensory cues are combined to optimize perception, either in terms of minimizing the uncertainty in the sensory estimate or maximizing intelligibility, particularly in speech understanding. From an auditory perception perspective, a fundamental question that has not been fully addressed is how visual information aids the ability to select and focus on one auditory object in the presence of competing sounds in a busy auditory scene. In this chapter, audiovisual integration is presented from an object-based attention viewpoint. In particular, it is argued that a stricter delineation of the concepts of multisensory integration versus binding would facilitate a deeper understanding of the nature of how information is combined across senses. Furthermore, using an object-based theoretical framework to distinguish binding as a distinct form of multisensory integration generates testable hypotheses with behavioral predictions that can account for different aspects of multisensory interactions. In this chapter, classic multisensory illusion paradigms are revisited and discussed in the context of multisensory binding. The chapter also describes multisensory experiments that focus on addressing how visual stimuli help listeners parse complex auditory scenes. Finally, it concludes with a discussion of the potential mechanisms by which audiovisual processing might resolve competition between concurrent sounds in order to solve the cocktail party problem

Defining Auditory-Visual Objects: Behavioral Tests and Physiological Mechanisms

Crossmodal integration is a term applicable to many phenomena in which one sensory modality influences task performance or perception in another sensory modality. We distinguish the term binding as one that should be reserved specifically for the process that underpins perceptual object formation. To unambiguously differentiate binding form other types of integration, behavioral and neural studies must investigate perception of a feature orthogonal to the features that link the auditory and visual stimuli. We argue that supporting true perceptual binding (as opposed to other processes such as decision-making) is one role for cross-sensory influences in early sensory cortex. These early multisensory interactions may therefore form a physiological substrate for the bottom-up grouping of auditory and visual stimuli into auditory-visual (AV) objects

A spatially collocated sound thrusts a flash into awareness

To interact effectively with the environment the brain integrates signals from multiple senses. It is currently unclear to what extent spatial information can be integrated across different senses in the absence of awareness. Combining dynamic continuous flash suppression and spatial audiovisual stimulation, the current study investigated whether a sound facilitates a concurrent visual flash to elude flash suppression and enter perceptual awareness depending on audiovisual spatial congruency. Our results demonstrate that a concurrent sound boosts unaware visual signals into perceptual awareness. Critically, this process depended on the spatial congruency of the auditory and visual signals pointing towards low level mechanisms of audiovisual integration. Moreover, the concurrent sound biased the reported location of the flash as a function of flash visibility. The spatial bias of sounds on reported flash location was strongest for flashes that were judged invisible. Our results suggest that multisensory integration is a critical mechanism that enables signals to enter conscious perception