Christopher R. Fetsch

Dynamic Reweighting of Visual and Vestibular Cues during Self-Motion Perception

The perception of self-motion direction, or heading, relies on integration of multiple sensory cues, especially from the visual and vestibular systems. However, the reliability of sensory information can vary rapidly and unpredictably, and it remains unclear how the brain integrates multiple sensory signals given this dynamic uncertainty. Human psychophysical studies have shown that observers combine cues by weighting them in proportion to their reliability, consistent with statistically optimal integration schemes derived from Bayesian probability theory. Remarkably, because cue reliability is varied randomly across trials, the perceptual weight assigned to each cue must change from trial to trial. Dynamic cue reweighting has not been examined for combinations of visual and vestibular cues, nor has the Bayesian cue integration approach been applied to laboratory animals, an important step toward understanding the neural basis of cue integration. To address these issues, we tested human and monkey subjects in a heading discrimination task involving visual (optic flow) and vestibular (translational motion) cues. The cues were placed in conflict on a subset of trials, and their relative reliability was varied to assess the weights that subjects gave to each cue in their heading judgments. We found that monkeys can rapidly reweight visual and vestibular cues according to their reliability, the first such demonstration in a nonhuman species. However, some monkeys and humans tended to over-weight vestibular cues, inconsistent with simple predictions of a Bayesian model. Nonetheless, our findings establish a robust model system for studying the neural mechanisms of dynamic cue reweighting in multisensory perception.

Neural correlates of reliability-based cue weighting during multisensory integration

Integration of multiple sensory cues is essential for precise and accurate perception and behavioral performance, yet the reliability of sensory signals can vary across modalities and viewing conditions. Human observers typically employ the optimal strategy of weighting each cue in proportion to its reliability, but the neural basis of this computation remains poorly understood. We trained monkeys to perform a heading discrimination task from visual and vestibular cues, varying cue reliability randomly. The monkeys appropriately placed greater weight on the more reliable cue, and population decoding of neural responses in the dorsal medial superior temporal area closely predicted behavioral cue weighting, including modest deviations from optimality. We found that the mathematical combination of visual and vestibular inputs by single neurons is generally consistent with recent theories of optimal probabilistic computation in neural circuits. These results provide direct evidence for a neural mechanism mediating a simple and widespread form of statistical inference.

Bridging the gap between theories of sensory cue integration and the physiology of multisensory neurons

The richness of perceptual experience, as well as its usefulness for guiding behaviour, depends on the synthesis of information across multiple senses. Recent decades have witnessed a surge in our understanding of how the brain combines sensory cues. Much of this research has been guided by one of two distinct approaches: one is driven primarily by neurophysiological observations, and the other is guided by principles of mathematical psychology and psychophysics. Conflicting results and interpretations have contributed to a conceptual gap between psychophysical and physiological accounts of cue integration, but recent studies of visual–vestibular cue integration have narrowed this gap considerably.

Decoding of MSTd population activity accounts for variations in the precision of heading perception.

Humans and monkeys use both vestibular and visual motion (optic flow) cues to discriminate their direction of self-motion during navigation. A striking property of heading perception from optic flow is that discrimination is most precise when subjects judge small variations in heading around straight ahead, whereas thresholds rise precipitously when subjects judge heading around an eccentric reference. We show that vestibular heading discrimination thresholds in both humans and macaques also show a consistent, but modest, dependence on reference direction. We used computational methods (Fisher information, maximum likelihood estimation, and population vector decoding) to show that population activity in area MSTd predicts the dependence of heading thresholds on reference eccentricity. This dependence arises because the tuning functions for most neurons have a steep slope for directions near straight forward. Our findings support the notion that population activity in extrastriate cortex limits the precision of both visual and vestibular heading perception.

Visual–vestibular cue integration for heading perception: applications of optimal cue integration theory

The perception of self‐motion is crucial for navigation, spatial orientation and motor control. In particular, estimation of one’s direction of translation, or heading, relies heavily on multisensory integration in most natural situations. Visual and nonvisual (e.g., vestibular) information can be used to judge heading, but each modality alone is often insufficient for accurate performance. It is not surprising, then, that visual and vestibular signals converge frequently in the nervous system, and that these signals interact in powerful ways at the level of behavior and perception. Early behavioral studies of visual–vestibular interactions consisted mainly of descriptive accounts of perceptual illusions and qualitative estimation tasks, often with conflicting results. In contrast, cue integration research in other modalities has benefited from the application of rigorous psychophysical techniques, guided by normative models that rest on the foundation of ideal‐observer analysis and Bayesian decision theory. Here we review recent experiments that have attempted to harness these so‐called optimal cue integration models for the study of self‐motion perception. Some of these studies used nonhuman primate subjects, enabling direct comparisons between behavioral performance and simultaneously recorded neuronal activity. The results indicate that humans and monkeys can integrate visual and vestibular heading cues in a manner consistent with optimal integration theory, and that single neurons in the dorsal medial superior temporal area show striking correlates of the behavioral effects. This line of research and other applications of normative cue combination models should continue to shed light on mechanisms of self‐motion perception and the neuronal basis of multisensory integration.

Effects of Cortical Microstimulation on Confidence in a Perceptual Decision

Decisions are often associated with a degree of certainty, or confidence--an estimate of the probability that the chosen option will be correct. Recent neurophysiological results suggest that the central processing of evidence leading to a perceptual decision also establishes a level of confidence. Here we provide a causal test of this hypothesis by electrically stimulating areas of the visual cortex involved in motion perception. Monkeys discriminated the direction of motion in a noisy display and were sometimes allowed to opt out of the direction choice if their confidence was low. Microstimulation did not reduce overall confidence in the decision but instead altered confidence in a manner that mimicked a change in visual motion, plus a small increase in sensory noise. The results suggest that the same sensory neural signals support choice, reaction time, and confidence in a decision and that artificial manipulation of these signals preserves the quantitative relationship between accumulated evidence and confidence.

Spatiotemporal Properties of Vestibular Responses in Area MSTd

Recent studies have shown that many neurons in the primate dorsal medial superior temporal area (MSTd) show spatial tuning during inertial motion and that these responses are vestibular in origin. Given their well-studied role in processing visual self-motion cues (i.e., optic flow), these neurons may be involved in the integration of visual and vestibular signals to facilitate robust perception of self-motion. However, the temporal structure of vestibular responses in MSTd has not been characterized in detail. Specifically, it is not known whether MSTd neurons encode velocity, acceleration, or some combination of motion parameters not explicitly encoded by vestibular afferents. In this study, we have applied a frequency-domain analysis to single-unit responses during translation in three dimensions (3D). The analysis quantifies the stimulus-driven temporal modulation of each response as well as the degree to which this modulation reflects the velocity and/or acceleration profile of the stimulus. We show that MSTd neurons signal a combination of velocity and acceleration components with the velocity component being stronger for most neurons. These two components can exist both within and across motion directions, although their spatial tuning did not show a systematic relationship across the population. From these results, vestibular responses in MSTd appear to show characteristic features of spatiotemporal convergence, similar to previous findings in the brain stem and thalamus. The predominance of velocity encoding in this region may reflect the suitability of these signals to be integrated with visual signals regarding self-motion perception.

Predicting the Accuracy of a Decision: A Neural Mechanism of Confidence

The quantitative study of decision-making has traditionally rested on three key behavioral measures: accuracy, response time, and confidence. Of these, confidence--defined as the degree of belief, prior to feedback, that a decision is correct-is least well understood at the level of neural mechanism, although recent years have seen a surge in interest in the topic among theoretical and systems neuroscientists. Here we review some of these developments and highlight a particular candidate mechanism for assigning confidence in a perceptual decision. The mechanism is appealing because it is rooted in the same decision-making framework--bounded accumulation of evidence--that successfully explains accuracy and reaction time in many tasks, and it is validated by neurophysiology and microstimulation experiments.

The influence of evidence volatility on choice, reaction time and confidence in a perceptual decision

Many decisions are thought to arise via the accumulation of noisy evidence to a threshold or bound. In perception, the mechanism explains the effect of stimulus strength, characterized by signal-to-noise ratio, on decision speed, accuracy and confidence. It also makes intriguing predictions about the noise itself. An increase in noise should lead to faster decisions, reduced accuracy and, paradoxically, higher confidence. To test these predictions, we introduce a novel sensory manipulation that mimics the addition of unbiased noise to motion-selective regions of visual cortex, which we verified with neuronal recordings from macaque areas MT/MST. For both humans and monkeys, increasing the noise induced faster decisions and greater confidence over a range of stimuli for which accuracy was minimally impaired. The magnitude of the effects was in agreement with predictions of a bounded evidence accumulation model. DOI: http://dx.doi.org/10.7554/eLife.17688.001

Training scientists in a science center improves science communication to the public

the language of science is inherently academic and often inefficient in its delivery of key concepts to nonscientists (10a). When President Obama spoke at the National Academy of Sciences in April 2009 (15b), he issued the following call to think of new ways to engage young people in science,