An adaptive model of sensory integration in a dynamic environment applied to human stance control

An adaptive estimator model of human spatial orientation is presented. The adaptive model dynamically weights sensory error signals. More specific, th e model weights the difference between expected and actual sensory signals as a function of environmental conditions. The model does not require any c hanges in model parameters. Differences with existing models of spatial ori entation are that: (1) environmental conditions are not specified but estim ated, (2) the sensor noise characteristics are the only parameters supplied by the model designer, (3) history-dependent effects and mental resources can be modelled, and (4) vestibular thresholds are not included in the mode l; instead vestibular-related threshold effects are predicted by the model. The model was applied to human stance control and evaluated with results o f a visually induced sway experiment. From these experiments it is known th at the amplitude of visually induced sway reaches a saturation level as the stimulus level increases. This saturation level is higher when the support base is sway referenced. For subjects experiencing vestibular loss, these saturation effects do not occur. Unknown sensory noise characteristics were found by matching model predictions with these experimental results. Using only five model parameters, far more than five data points were successful ly predicted. Model predictions showed that both the saturation levels are vestibular related since removal of the vestibular organs in the model remo ved the saturation effects, as was also shown in the experiments. It seems that the nature of these vestibular-related threshold effects is not physic al, since in the model no threshold is included. The model results suggest that vestibular-related thresholds are the result of the processing of nois y sensory and motor output signals. Model analysis suggests that, especiall y for slow and small movements, the environment postural orientation can no t be estimated optimally, which causes sensory illusions. The model also co nfirms the experimental finding that postural orientation is history depend ent and can be shaped by instruction or mental knowledge. In addition the m odel predicts that: (1) vestibular-loss patients cannot handle sensory conf licting situations and will fall down, (2) during sinusoidal support-base t ranslations vestibular function is needed to prevent falling, (3) loss of s omatosensory information from the feet results in larger postural sway for sinusoidal support-base translations, and (4) loss of vestibular function r esults in falling for large support-base rotations with the eyes closed. Th ese predictions are in agreement with experimental results.