Disentangling object category representations driven by dynamic and static visual input

AbstractHumans can label and categorize objects in a visual scene with high accuracy and speed—a capacity well-characterized with neuroimaging studies using static images. However, motion is another cue that could be used by the visual system to classify objects. To determine how motion-defined object category information is processed in the brain, we created a novel stimulus set to isolate motion-defined signals from other sources of information. We extracted movement information from videos of 6 object categories and applied the motion to random dot patterns. Using these stimuli, we investigated whether fMRI responses elicited by motion cues could be decoded at the object category level in functionally defined regions of occipitotemporal and parietal cortex. Participants performed a one-back repetition detection task as they viewed motion-defined stimuli or static images from the original videos. Linear classifiers could decode object category for both stimulus formats in all higher order regions of interest. More posterior occipitotemporal and ventral regions showed higher accuracy in the static condition and more anterior occipitotemporal and dorsal regions showed higher accuracy in the dynamic condition. Significantly above chance classification accuracies were also observed in all regions when training and testing the SVM classifier across stimulus formats. These results demonstrate that motion-defined cues can elicit widespread robust category responses on par with those elicited by luminance cues in regions of object-selective visual cortex. The informational content of these responses overlapped with, but also demonstrated interesting distinctions from, those elicited by static cues.Significance StatementMuch research on visual object recognition has focused on recognizing objects in static images. However, motion cues are a rich source of information that humans might also use to categorize objects. Here, we present the first study to compare neural representations of several animate and inanimate objects when category information is presented in two formats: static cues or isolated dynamic cues. Our study shows that while higher order brain regions differentially process object categories depending on format, they also contain robust, abstract category representations that generalize across format. These results expand our previous understanding of motion-derived animate and inanimate object category processing and provide useful tools for future research on object category processing driven by multiple sources of visual information.