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

Abstract

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.

Spinning versus Wobbling: How the Brain Solves a Geometry Problem

“…This estimate can be used to extract the inertial and gravitational components of the otolith afferent signals, in agreement with previous studies (Angelaki et al, , 2002(Angelaki et al, , 2004Merfeld et al, 1999). Our analysis suggests that conflicting motion signals are resolved by a process of optimal estimation, similar as shown in numerous previous studies (Ernst and Banks, 2002;Weiss et al, 2002;MacNeilage et al, 2007;Angelaki et al, 2009;Fetsch et al, 2009) as well as in modeling work on vestibular information processing (Laurens et al, 2007. By demonstrating that the brain effectively uses geometrically consistent three-dimensional representations, this study supports the notion that the internal model hypothesis as formulated in the general context of motor control (Ito, 1989;Kawato, 1999;Davidson and Wolpert, 2005) is also an important concept for understanding how the brain solves spatial orientation problems.…”

How Optic Flow and Inertial Cues Improve Motion Perception

“…Indeed, empirically measured heading discrimination thresholds during combined vestibular -visual heading perception were close to the predictions produced by a statistically optimal cue combination rule (Gu et al 2008;Fetsch et al 2009Fetsch et al , 2011Fetsch et al , 2013Butler et al 2010Butler et al , 2015de Winkel et al 2013). …”

“…Psychophysical studies of heading discrimination using two-alternative forcedchoice tasks have reported vestibular heading discrimination thresholds in darkness that are as small as a few degrees Fetsch et al 2009;Butler et al 2010Butler et al , 2015de Winkel et al 2010;Drugowitsch et al 2014). Such threshold values are comparable (although larger) with those described in visual heading discrimi-nation tasks (Warren and Hannon 1990;Royden et al 1992;van den Berg and Brenner 1994;Stone and Perrone 1997).…”

“…In particular, as illustrated by the psychometric functions in Figure 2C, the precision of perception in a heading discrimination task (Fig. 2B) increases when both vestibular (i.e., inertial) and visual (i.e., optic flow) signals indicate self-motion as compared with when either cue is present alone (Gu et al 2008;Fetsch et al 2009Fetsch et al , 2011Fetsch et al , 2013Butler et al 2010Butler et al , 2015de Winkel et al 2013). Precision is the sensitivity or threshold (also called "reliability," computed as the "sigma" of the cumulative Gaussian fit of a psychometric function) (C, vertical dashed lines).…”

Hummingbirds control hovering flight by stabilizing visual motion

“…Birds have large regions of the brain dedicated to visual processing, suggesting parallels with insects, such as a leading role for optic flow in controlling flight paths (2,3). It has recently been demonstrated that birds exhibit visually mediated position control much like bees (4,5), even though they have complex spatial mapping in the hippocampal formation (6), and a much larger brain for interpreting visual input and dynamically integrating vision with proprioceptive and vestibular feedback (7)(8)(9).…”