David R. Wozny

Probability Matching as a Computational Strategy Used in Perception

The question of which strategy is employed in human decision making has been studied extensively in the context of cognitive tasks; however, this question has not been investigated systematically in the context of perceptual tasks. The goal of this study was to gain insight into the decision-making strategy used by human observers in a low-level perceptual task. Data from more than 100 individuals who participated in an auditory-visual spatial localization task was evaluated to examine which of three plausible strategies could account for each observers behavior the best. This task is very suitable for exploring this question because it involves an implicit inference about whether the auditory and visual stimuli were caused by the same object or independent objects, and provides different strategies of how using the inference about causes can lead to distinctly different spatial estimates and response patterns. For example, employing the commonly used cost function of minimizing the mean squared error of spatial estimates would result in a weighted averaging of estimates corresponding to different causal structures. A strategy that would minimize the error in the inferred causal structure would result in the selection of the most likely causal structure and sticking with it in the subsequent inference of location—“model selection.” A third strategy is one that selects a causal structure in proportion to its probability, thus attempting to match the probability of the inferred causal structure. This type of probability matching strategy has been reported to be used by participants predominantly in cognitive tasks. Comparing these three strategies, the behavior of the vast majority of observers in this perceptual task was most consistent with probability matching. While this appears to be a suboptimal strategy and hence a surprising choice for the perceptual system to adopt, we discuss potential advantages of such a strategy for perception.

Influences of Multisensory Experience on Subsequent Unisensory Processing

Multisensory perception has been the focus of intense investigation in recent years. It is now well-established that crossmodal interactions are ubiquitous in perceptual processing and endow the system with improved precision, accuracy, processing speed, etc. While these findings have shed much light on principles and mechanisms of perception, ultimately it is not very surprising that multiple sources of information provides benefits in performance compared to a single source of information. Here, we argue that the more surprising recent findings are those showing that multisensory experience also influences the subsequent unisensory processing. For example, exposure to auditory–visual stimuli can change the way that auditory or visual stimuli are processed subsequently even in isolation. We review three sets of findings that represent three different types of learning ranging from perceptual learning, to sensory recalibration, to associative learning. In all these cases exposure to multisensory stimuli profoundly influences the subsequent unisensory processing. This diversity of phenomena may suggest that continuous modification of unisensory representations by multisensory relationships may be a general learning strategy employed by the brain.

Computational Characterization of Visually Induced Auditory Spatial Adaptation

Recent research investigating the principles governing human perception has provided increasing evidence for probabilistic inference in human perception. For example, human auditory and visual localization judgments closely resemble that of a Bayesian causal inference observer, where the underlying causal structure of the stimuli are inferred based on both the available sensory evidence and prior knowledge. However, most previous studies have focused on characterization of perceptual inference within a static environment, and therefore, little is known about how this inference process changes when observers are exposed to a new environment. In this study we aimed to computationally characterize the change in auditory spatial perception induced by repeated auditory–visual spatial conflict, known as the ventriloquist aftereffect. In theory, this change could reflect a shift in the auditory sensory representations (i.e., shift in auditory likelihood distribution), a decrease in the precision of the auditory estimates (i.e., increase in spread of likelihood distribution), a shift in the auditory bias (i.e., shift in prior distribution), or an increase/decrease in strength of the auditory bias (i.e., the spread of prior distribution), or a combination of these. By quantitatively estimating the parameters of the perceptual process for each individual observer using a Bayesian causal inference model, we found that the shift in the perceived locations after exposure was associated with a shift in the mean of the auditory likelihood functions in the direction of the experienced visual offset. The results suggest that repeated exposure to a fixed auditory–visual discrepancy is attributed by the nervous system to sensory representation error and as a result, the sensory map of space is recalibrated to correct the error.

Biases in Visual, Auditory, and Audiovisual Perception of Space.

Localization of objects and events in the environment is critical for survival, as many perceptual and motor tasks rely on estimation of spatial location. Therefore, it seems reasonable to assume that spatial localizations should generally be accurate. Curiously, some previous studies have reported biases in visual and auditory localizations, but these studies have used small sample sizes and the results have been mixed. Therefore, it is not clear (1) if the reported biases in localization responses are real (or due to outliers, sampling bias, or other factors), and (2) whether these putative biases reflect a bias in sensory representations of space or a priori expectations (which may be due to the experimental setup, instructions, or distribution of stimuli). Here, to address these questions, a dataset of unprecedented size (obtained from 384 observers) was analyzed to examine presence, direction, and magnitude of sensory biases, and quantitative computational modeling was used to probe the underlying mechanism(s) driving these effects. Data revealed that, on average, observers were biased towards the center when localizing visual stimuli, and biased towards the periphery when localizing auditory stimuli. Moreover, quantitative analysis using a Bayesian Causal Inference framework suggests that while pre-existing spatial biases for central locations exert some influence, biases in the sensory representations of both visual and auditory space are necessary to fully explain the behavioral data. How are these opposing visual and auditory biases reconciled in conditions in which both auditory and visual stimuli are produced by a single event? Potentially, the bias in one modality could dominate, or the biases could interact/cancel out. The data revealed that when integration occurred in these conditions, the visual bias dominated, but the magnitude of this bias was reduced compared to unisensory conditions. Therefore, multisensory integration not only improves the precision of perceptual estimates, but also the accuracy.

The effects of selective and divided attention on sensory precision and integration.

In our daily lives, our capacity to selectively attend to stimuli within or across sensory modalities enables enhanced perception of the surrounding world. While previous research on selective attention has studied this phenomenon extensively, two important questions still remain unanswered: (1) how selective attention to a single modality impacts sensory integration processes, and (2) the mechanism by which selective attention improves perception. We explored how selective attention impacts performance in both a spatial task and a temporal numerosity judgment task, and employed a Bayesian Causal Inference model to investigate the computational mechanism(s) impacted by selective attention. We report three findings: (1) in the spatial domain, selective attention improves precision of the visual sensory representations (which were relatively precise), but not the auditory sensory representations (which were fairly noisy); (2) in the temporal domain, selective attention improves the sensory precision in both modalities (both of which were fairly reliable to begin with); (3) in both tasks, selective attention did not exert a significant influence over the tendency to integrate sensory stimuli. Therefore, it may be postulated that a sensory modality must possess a certain inherent degree of encoding precision in order to benefit from selective attention. It also appears that in certain basic perceptual tasks, the tendency to integrate crossmodal signals does not depend significantly on selective attention. We conclude with a discussion of how these results relate to recent theoretical considerations of selective attention.

A simple and efficient method to enhance audiovisual binding tendencies

Individuals vary in their tendency to bind signals from multiple senses. For the same set of sights and sounds, one individual may frequently integrate multisensory signals and experience a unified percept, whereas another individual may rarely bind them and often experience two distinct sensations. Thus, while this binding/integration tendency is specific to each individual, it is not clear how plastic this tendency is in adulthood, and how sensory experiences may cause it to change. Here, we conducted an exploratory investigation which provides evidence that (1) the brain’s tendency to bind in spatial perception is plastic, (2) that it can change following brief exposure to simple audiovisual stimuli, and (3) that exposure to temporally synchronous, spatially discrepant stimuli provides the most effective method to modify it. These results can inform current theories about how the brain updates its internal model of the surrounding sensory world, as well as future investigations seeking to increase integration tendencies.

Adapting to altered image statistics using processed video

Perceptual systems can be altered by immersing observers in environments with statistical properties that differ from those naturally encountered. Here we present a novel method for placing observers in naturalistic audio visual environments whose statistics can be manipulated in very targeted ways. We present the results of a case study that used this method. Observers were exposed to an environment where there was a novel statistical relationship between two simple, visual patterns in otherwise natural scenes. Exposure to this altered environment strengthened perceptual interactions between the two patterns.