Speed tuning in head coordinates as an alternative explanation of depth selectivity from motion parallax in area MT
Abstract
There are two distinct sources of retinal image motion: motion of objects in the world and movement of the observer. In cases where an object moves in a scene and the eyes also move, a coordinate transformation that involves smooth eye movements and retinal motion will be needed in order to estimate object motion in world coordinates. More recently, interactions between retinal and eye velocity signals have also been suggested to generate depth selectivity from motion parallax (MP) in the macaque middle temporal (MT) area. We explored whether the nature of the interaction between eye and retinal velocities in MT neurons favors one of these two possibilities or a mixture of both. We analyzed responses of MT neurons to retinal and eye velocities in a viewing context in which the observer translates laterally while maintaining visual fixation on a world-fixed target. In this scenario, the depth of an object can be inferred from the ratio between retinal velocity and eye velocity, according to the motion-pursuit law. Previous studies have shown that MT responses to retinal motion are gain-modulated by the direction of eye movement, suggesting a potential mechanism for depth tuning from MP. However, our analysis of the joint tuning profile for retinal and eye velocities reveals that some MT neurons show a partial coordinate transformation toward head coordinates. We formalized a series of computational models to predict neural spike trains as well as selectivity for depth, and we used factorial model comparisons to quantify the relative importance of each model component. Our findings for many MT neurons reveal that the data are equally well explained by gain modulation or a partial coordinate transformation toward head coordinates, although some responses can only be well fit by the coordinate transform model. Our results highlight the potential role of MT neurons in representing multiple higher-level sensory variables, including depth from MP and object motion in the world.
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