Abstract
The motion energy sensor has been shown to account for a wide range of physiological and psychophysical results in motion detection and discrimination studies. It has become established as the standard computational model for retinal movement sensing in the human visual system. Adaptation effects have been extensively studied in the psychophysical literature on motion perception, and play a crucial role in theoretical debates, but the current implementation of the energy sensor does not provide directly for modelling adaptation-induced changes in output. We describe an extension of the model to incorporate changes in output due to adaptation. The extended model first computes a space-time representation of the output to a given stimulus, and then a RC gain-control circuit (“leaky integrator”) is applied to the time-dependent output. The output of the extended model shows effects which mirror those observed in psychophysical studies of motion adaptation: a decline in sensor output during stimulation, and changes in the relative of outputs of different sensors following this adaptation.
Highlights
The motion energy model [1] has become established as the standard computational model for low-level motion sensing in the human visual system
Georgeson and Scott-Samuel [7] added a normalization stage to the model, in which opponent energy is normalised with flicker energy, because they found that opponent energy was a poor predictor of psychophysical direction discrimination performance
This updated version of the motion energy model provides a good account of a wide range of psychophysical tasks, such as direction discrimination and lateral masking [9,10] a crucial limitation of the model in its current form is that it cannot account for the well-known and dramatic effects of prolonged exposure to unidirectional motion, such as the motion after-effect (MAE)
Summary
The motion energy model [1] has become established as the standard computational model for low-level motion sensing in the human visual system. Motion contrast was found to be a good predictor of direction discrimination performance over a wide range of contrast levels This updated version of the motion energy model provides a good account of a wide range of psychophysical tasks, such as direction discrimination and lateral masking [9,10] a crucial limitation of the model in its current form is that it cannot account for the well-known and dramatic effects of prolonged exposure to unidirectional motion (i.e., motion adaptation), such as the motion after-effect (MAE). These effects have played a pivotal role in both empirical and theoretical studies of motion perception for nearly 150 years [11,12], so their exclusion from the energy model is a major limitation of the dominant theoretical scheme (previous attempts to apply the model to MAE data [15] have used the magnitude of sensor output during adaptation as a proxy for the strength of the resulting adaptation)
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