The visual system of many species, including humans, exhibits motion adaptation when exposed to high image velocities. While the features of the mechanisms that act to produce motion adaptation have been described in dipterous insects, the neuronal processes that produce adaptation are unknown. We present a neuronally-based model of motion adaptation based on a network of cells that have been previously identified and proposed to be part of the motion detection circuits in flies. The transmedulary cell Tm1, which is part of the neuronally-based model of elementary motion detection (EMD), is identified to have the desired properties to generate the adaptation signal. Using an array of EMDs to simulate a tangential cell, a model of motion adaptation is proposed based on frequency dependent synaptic depression of the Tm1 synapses. Synaptic depression is modeled as an activity dependent decrease in the amplitude of the Tm1 modulations which recovers exponentially. The model, which also incorporates a saturating nonlinearity that produces contrast saturation, has all the features of the electrophysiology, including the right frequency and contrast dependency. The modeled adaptation is non directional while responding stronger to motion than to flicker, as observed in the recordings, and capturing details of the time-course of the tangential cell step response. Furthermore, we show that an imbalance in the subtraction stage, believed to occur in the dendrites of the tangential cell, produces changes in the rate of decay of the simulated tangential cell impulse response, which agree with available recordings. These changes in the tangential cell impulse response were previously attributed to adaptation of the filters in the motion detection pathway.
Zuley Rivera-Alvidrez and C. M. Higgins, "Motion adaptation in a neuronally-based model of elementary motion detection" (poster), 3rd Gordon Conference on Neuroethology, Magdalen College, Oxford University, UK, August 2005.