The contribution of dynamics to macaque body and face patch responses

Bodies in motion: Unraveling the distinct roles of motion and shape in dynamic body responses in the temporal cortex

“…Neurons responding to a hand interacting with an object were reported in the ventral middle STS, 22 but evidence for motion-related responses is lacking for other body parts and in anterior IT. We 6 found stronger fMRI activations also in the ventral STS in response to dynamic naturalistic body stimuli compared with static ones. These fMRI data raised the possibility that body dynamics also contribute to the IT neurons’ responses.…”

“… 7 The latter “dynamic social perception” stream 7 has been linked to the human STS and likely corresponds to the dorsal bank/fundus of the macaque STS. This proposal and our recent fMRI findings 6 underscore the importance of assessing and comparing the contributions of dynamic and static features to body responses in and between IT and dorsal-bank STS, which is the aim of this study.…”

“…Despite the social relevance of moving bodies, their visual processing remains poorly understood due to the focus on static images. 3 Recently, employing fMRI to map patches that are activated specifically by dynamic monkey bodies, 6 we observed patches in the dorsal-bank STS that were activated less by static images.…”

Theta activity discriminates high-level, species-specific body processes

“…To control for the contribution of low-level visual features, mosaic-scrambled images were included. Mosaic-scrambled images destroyed the whole shape of each body/face/object stimulus, but preserved the low-level features of luminance, contrast, texture, and non-background area (Bognár et al, 2023). This resulted in a total of twelve experimental conditions (human/monkey * body/face/object * normal/scrambled).…”

“…There were ten different stimuli per condition, which resulted in 120 unique images. All images were adapted from video stimuli used in a previous body perception study (Li et al, 2023; see also Bognár et al, 2023; Kret et al, 2011; Zhu et al, 2013). The images for the present study were extracted from the midpoint (frame 30) of each original video (60 fps).…”