Perceiving Instability: How Expectations Bias Sensorimotor Processing in Balance Control

Maintaining balance requires rapid integration of sensory input with top-down sensorimotor predictions. Predictive coding frameworks propose that mismatches between expected and actual sensory input (“prediction errors”) drive perceptual inference. Although these frameworks have been highly influential in sensory neuroscience, it remains unclear whether they operate similarly in fast-acting sensorimotor systems such as human balance. Using electroencephalography (EEG) and discrete postural perturbations via support surface translations, we independently manipulated expectations and sensory input. Participants were primed to expect small or large perturbations, with occasional violations in which the delivered perturbation differed from expectation. We found that subjective perception of instability was shaped by expectation alone, regardless of perturbation magnitude. Similarly, pre-perturbation beta-band suppression and post-perturbation gamma activity tracked expected perturbation magnitude, with the latter strongly associated with expectation-induced perceptual biases ( r = 0.69, p _BON = 0.001). In contrast, both the balance N1 (a well-established stimulus-evoked cortical potential linked to the postural response) and objective behavioural markers of postural instability were determined primarily by perturbation magnitude. Crucially, neither perception nor early neural or behavioural markers appeared to encode prediction errors arising from expectation violations. Together, these findings identify boundary conditions on predictive coding in sensorimotor control, showing that during fast, reactive behaviour, perceptual inference may be shaped more strongly by expectations than by mismatch signals, even as early neural and motor responses remain driven primarily by sensory input.