Multiple visual stimuli are common in natural scenes, yet it remains unclear how multiple stimuli interact to influence neuronal responses. We investigated this question by manipulating relative signal strengths of two stimuli moving simultaneously within the receptive fields (RFs) of neurons in the extrastriate middle temporal (MT) cortex. Visual stimuli were overlapping random-dot patterns moving in two directions separated by 90°. We first varied the motion coherence of each random-dot pattern and characterized, across the direction tuning curve, the relationship between neuronal responses elicited by bidirectional stimuli and by the constituent motion components. The tuning curve for bidirectional stimuli showed response normalization and can be accounted for by a weighted sum of the responses to the motion components. Allowing nonlinear, multiplicative interaction between the two component responses significantly improved the data fit for some neurons, and the interaction mainly had a suppressive effect on the neuronal response. The weighting of the component responses was not fixed but dependent on relative signal strengths. When two stimulus components moved at different coherence levels, the response weight for the higher-coherence component was significantly greater than that for the lower-coherence component. We also varied relative luminance levels of two coherently moving stimuli and found that MT response weight for the higher-luminance component was also greater. These results suggest that competition between multiple stimuli within a neuron's RF depends on relative signal strengths of the stimuli and that multiplicative nonlinearity may play an important role in shaping the response tuning for multiple stimuli.

Natural scenes often contain multiple objects and surfaces. However, how neurons in the visual cortex represent multiple visual stimuli is not well understood. Previous studies have shown that, when multiple stimuli compete in one feature domain, the evoked neuronal response is biased toward the stimulus that has a stronger signal strength. We recorded from two male macaques to investigate how neurons in the middle temporal cortex (MT) represent multiple stimuli that compete in more than one feature domain. Visual stimuli were two random-dot patches moving in different directions. One stimulus had low luminance contrast and moved with high coherence, whereas the other had high contrast and moved with low coherence. We found that how MT neurons represent multiple stimuli depended on the spatial arrangement. When two stimuli were overlapping, MT responses were dominated by the stimulus component that had high contrast. When two stimuli were spatially separated within the receptive fields, the contrast dominance was abolished. We found the same results when using contrast to compete with motion speed. Our neural data and computer simulations using a V1-MT model suggest that the contrast dominance found with overlapping stimuli is due to normalization occurring at an input stage fed to MT, and MT neurons cannot overturn this bias based on their own feature selectivity. The interaction between spatially separated stimuli can largely be explained by normalization within MT. Our results revealed new rules on stimulus competition and highlighted the impact of hierarchical processing on representing multiple stimuli in the visual cortex.

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. However, how neurons in the visual cortex represent multiple visual stimuli within their receptive fields (RFs) is not well understood. Previous studies have shown that, when multiple stimuli compete in one feature domain, the evoked neuronal response is dominated by the stimulus component that has a stronger signal strength, which can be explained by response normalization. Here we investigate how neurons in middle-temporal (MT) cortex of the macaque monkey represent multiple stimuli that compete in more than one feature domain within their RFs. Visual stimuli were two random-dot patches moving in different directions. One stimulus moved at high coherence with low luminance contrast, whereas the other moved at low coherence with high contrast. We found that, although the peak MT response elicited by the "low contrast & high coherence" stimulus alone was stronger than by the "high contrast & low coherence" stimulus, MT response to both stimuli when they were overlapping was almost completely dominated by the high-contrast stimulus. When two stimuli were spatially separated within the RF, the contrast dominance was abolished. We found the same results when using contrast to compete with motion speed. Computer simulations using a V1-MT model suggest that the contrast dominance is due to normalization occurring at input stage fed to MT and MT neurons cannot overturn it according to their own feature selectivity. Our results reveal new rules on stimulus competition and highlight the importance of hierarchical processing on the neural representation of multiple visual stimuli in the extrastriate cortex. SIGNIFICANCE STATEMENTWe investigated the rules by which cortical neurons represent multiple visual stimuli that compete in more than one feature domain. We found that the interaction between multiple stimuli within the RFs of neurons in area MT depends on the spatial arrangement of the stimuli. When multiple stimuli are overlapping, the response tuning curves of MT neurons are strongly dominated by the stimulus component that has higher luminance contrast albeit lower motion coherence or a slower speed than a competing stimulus. When multiple stimuli are spatially separated, the contrast dominance is abolished. These results cannot be explained by response normalization only within MT, but reveal the importance of hierarchical processing on the neural representation of multiple visual stimuli in extrastriate cortex.

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