Mathematical modelling for the integration of psychophysics and physiology in kinesthesia
This thesis examines the movement cues underlying human kinesthesia, using a combination
of psychophysical methods and an analyticrrl framework for math<'1l1aticHI
and statistical modelling of functional aspects of underlying physiological sensory
mechanisms. Using an innovative psychophysical paradigm, the first experiment
examines whether people are more sensitive to the occurrence of movement than to
movement direction. Contrary to previous investigations, the findings are that the
underlying sensitivity for movement detection and direction discrimination is the
An analytical tool for investigating what are the sensory cues for movement detection
is developed as a physiologically plausible model of movement perception.
The model accounts for performance in terms of displacement and velocity sensitive
directionally tuned channels and probability summation over time. Statistical analysis
of optimized model parameters indicates that the dominant cue for movement
detection is velocity and that the contribution of displacement information is insignificant.
An extended version of a previous movement detection model based on
temporal integration is also applied to data from experiment l. Derived estimates of
this model's parameters suggest that displacement information does make a significant
contribution to movement detection. The conflict between the two models is
resolved in favour of the probability summation model, based on statistical comparisons
regarding model accuracy and parsimony, and an analysis of the physiological
plausibility of underlying assumptions.
A second experiment investigates whether manipulation of movement acceleration
affects movement detection. The probability summation model is extended
to account for processing of acceleration. Estimates of the model's parameters reveal that acceleration information does not contribute significantly to velocity based movement detection.