five

Body shape as a visual feature: Evidence from spatially-global attentional modulation in human visual cortex

收藏
DataCite Commons2025-02-22 更新2024-07-13 收录
下载链接:
https://data.ru.nl/collections/di/dcc/DSC_2019.00052_491
下载链接
链接失效反馈
官方服务:
资源简介:
Raw fMRI data accompanying the NeuroImage 2022 paper. Information about the structure of data acquisition (run types, etc.) can be found in the paper. Processed data (to produce the figures in the paper and any further analysis) can be found on OSF: https://doi.org/10.17605/OSF.IO/HJ5VC Feature-based attention modulates visual processing beyond the focus of spatial attention. Previous work has reported such spatially-global effects for low-level features such as color and orientation, as well as for faces. Here, using fMRI, we provide evidence for spatially-global attentional modulation for human bodies. Participants were cued to search for one of six object categories in two vertically-aligned images. Two additional, horizontally-aligned, images were simultaneously presented but were never task-relevant across three experimental sessions. Analyses time-locked to the objects presented in these task-irrelevant images revealed that responses evoked by body silhouettes were modulated by the participants’ top-down attentional set, becoming more body-selective when participants searched for bodies in the task-relevant images. These effects were observed both in univariate analyses of the body-selective cortex and in multivariate analyses of the object-selective visual cortex. Additional analyses showed that this modulation reflected response gain rather than a bias induced by the cues, and that it reflected enhancement of body responses rather than suppression of non-body responses. These findings provide evidence for a spatially-global attention mechanism for body shapes, supporting the rapid and parallel detection of conspecifics in our environment.
提供机构:
Radboud University
创建时间:
2022-04-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作