Segmenting visual objects from each other and their background is critical for vision. Motion speed provides a salient cue for scene segmentation- an object moving at a speed different from its background is easier to be perceived. However, how the visual system represents and differentiates multiple speeds to achieve segmentation is largely unknown. We first characterized the perceptual capacity in segmenting overlapping stimuli moving simultaneously at different speeds. We then investigated the rule of how neurons in the motion-sensitive, middle-temporal (MT) cortex of macaque monkeys represent multiple speeds. We found that the responses of neurons to two speeds showed a robust bias toward the faster speed component when both speeds were slow (< 20⁰/s). Our finding can be explained by a divisive normalization model with a novel implication that the weights for the speed components are proportional to the responses of a population of neurons elicited by the individual components and the neurons in the population have a broad range of speed preferences. We also showed that it was possible to decode two speeds from MT population response in a way consistent with perception when the speed separation was large, but not when it was small. Our results provide strong support for the theoretical framework of coding multiplicity and probability distribution of visual features in neuronal populations and raise new questions for future investigation. The faster-speed bias would benefit figure-ground segregation if figural objects tend to move faster than the background in the natural environment.
Natural scenes often contain multiple objects and surfaces in 3-dimensional space. A fundamental process of vision is to segment visual scenes into distinct objects and surfaces. The stereoscopic depth and motion cues are particularly important for segmentation. However, how the primate visual system represents multiple moving stimuli located at different depths is poorly understood. Here we investigated how neurons in the middle temporal (MT) cortex represented two overlapping surfaces located at different horizontal disparities and moved simultaneously in different directions. We recorded the neuronal activities in MT of three male macaque monkeys while two of them performed a discrimination task to report the motion direction of an attended surface of two overlapping stimuli, and the third animal performed a behavioral task with the attention directed away from the receptive fields of MT neurons. We found that neuronal responses to overlapping surfaces showed a robust bias toward the horizontal disparity of one of the two surfaces. For all animals, the disparity bias in response to two surfaces was positively correlated with the disparity preference of the neurons to single surfaces. For two animals, neurons that preferred the near disparities of single surfaces (near neurons) showed a near bias to overlapping stimuli, and neurons that preferred the far disparities (far neurons) showed a far bias. For another animal, both near and far neurons showed a near bias to overlapping stimuli, although near neurons showed a stronger near bias. The disparity bias to overlapping stimuli was delayed relative to the response onset and was more delayed when the angular separation between two motion directions was smaller. Interestingly, for all three animals, both near and far neurons showed an initial near bias in comparison to the average of the responses to individual surfaces. We also found that the effect of attention directed to the disparity of one of two surfaces was object-based rather than feature-based. Although attention can modulate neuronal response to better represent the attended surface, the disparity bias cannot be explained by attention modulation. Our results can be explained by a unified model with a variable pooling size to weigh the response to individual stimulus components and divisive normalization. Our results revealed the encoding rule for multiple horizontal disparities and motion directions of overlapping stimuli. The disparity bias would allow subgroups of neurons to better represent different surfaces of multiple stimuli and therefore provide a population code that aids segmentation. The tendency for MT neurons to better represent the near-surface of overlapping stimuli in one animal and during the early response period in all three animals suggests that the neural representation of multiple stimuli at different depths may be beneficial to figure-ground segregation since figural objects are more likely to be in front of the ground in natural scenes.
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