Bayesian and “Anti-Bayesian” Biases in Sensory Integration for Action and Perception in the Size–Weight Illusion

Abstract

Brayanov JB, Smith MA. Bayesian and "anti-Bayesian" biases in sensory integration for action and perception in the size-weight illusion. J Neurophysiol 103: 1518 -1531, 2010. First published January 20, 2010 doi:10.1152/jn.00814.2009. Which is heavier: a pound of lead or a pound of feathers? This classic trick question belies a simple but surprising truth: when lifted, the pound of lead feels heavier-a phenomenon known as the size-weight illusion. To estimate the weight of an object, our CNS combines two imperfect sources of information: a prior expectation, based on the object's appearance, and direct sensory information from lifting it. Bayes' theorem (or Bayes' law) defines the statistically optimal way to combine multiple information sources for maximally accurate estimation. Here we asked whether the mechanisms for combining these information sources produce statistically optimal weight estimates for both perceptions and actions. We first studied the ability of subjects to hold one hand steady when the other removed an object from it, under conditions in which sensory information about the object's weight sometimes conflicted with prior expectations based on its size. Since the ability to steady the supporting hand depends on the generation of a motor command that accounts for lift timing and object weight, hand motion can be used to gauge biases in weight estimation by the motor system. We found that these motor system weight estimates reflected the integration of prior expectations with real-time proprioceptive information in a Bayesian, statistically optimal fashion that discounted unexpected sensory information. This produces a motor sizeweight illusion that consistently biases weight estimates toward prior expectations. In contrast, when subjects compared the weights of two objects, their perceptions defied Bayes' law, exaggerating the value of unexpected sensory information. This produces a perceptual size-weight illusion that biases weight perceptions away from prior expectations. We term this effect "anti-Bayesian" because the bias is opposite that seen in Bayesian integration. Our findings suggest that two fundamentally different strategies for the integration of prior expectations with sensory information coexist in the nervous system for weight estimation.

Mass and density estimates contribute to perceived heaviness with weights that depend on the densities' reliability

“…As the authors note this variant at the same time contradicts Bayes' law and, thus, contrasts with its manifold evidence [10,33]. While Bayes' law predicts that perception is biased towards prior expectations, the explanation suggests "anti-Bayesian" perception shifted away from expectations [31,36]. Furthermore, a strict application of Bayes' formalisms predicts an additive effect of mass expected from volume on perceived mass [31], which is usually not observed ( [28], below).…”

“…While Bayes' law predicts that perception is biased towards prior expectations, the explanation suggests "anti-Bayesian" perception shifted away from expectations [31,36]. Furthermore, a strict application of Bayes' formalisms predicts an additive effect of mass expected from volume on perceived mass [31], which is usually not observed ( [28], below). Finally, the illusion vanishes when (visual) volume information is given immediately before, but not during lifting an object [35], which does also not seem to fit the notion of prior expectations very well.…”

“…The illusion, however, persists after participants have quickly learnt to match the forces to novel objects [26,27]. Recent authors suggest a "Bayesianlike" perceptual variant of the theory, in that discrepancies between perceptual prior expectations from volume and actual sensory information on mass are responsible for the illusion [31,36]. As the authors note this variant at the same time contradicts Bayes' law and, thus, contrasts with its manifold evidence [10,33].…”

The material-weight illusion is a Bayes-optimal percept under competing density priors

“…Models positing a role for topdown processing in heaviness perception (Ross, 1969; Ellis & Lederman, 1998 or 'antiBayesian' biases (Brayanov & Smith, 2010) have been explored. Likewise, a number of early models claimed to describe especially the SWI (which is more robust and larger in magnitude than the MWI) in a cue combination framework by arbitrarily placing a negative weight on the expectancy cue (Anderson, 1970) or other similar assumptions (Cross & Rotkin, 1975) .…”

Computer Graphic and PHANToM Haptic Displays: Powerful Tools to Understand How Humans Perceive Heaviness

“…Ross, 1969), Information Integration Theory (Anderson, 1970;Masion & Crestoni, 1988), Density Theory (J. Ross & Di Lollo, 1970), Gain Adjustment Theory (Burgess & Jones, 1997), Inertia Tensor Theory (Amazeen, 1999), Bayesian Approach (Brayanov & Smith, 2010), and Throwing Affordance Theory (Zhu & Bingham, 2011). The reasons for these ongoing differences of opinion are that heaviness is affected by various factors (as noted in Sec.…”