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A functional dissociation of face- body- and scene-selective brain areas based on their response to moving and static stimuli

机译:根据脸部身体和场景选择性大脑区域对运动和静态刺激的反应对它们进行功能分离

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摘要

The human brain contains areas that respond selectively to faces, bodies and scenes. Neuroimaging studies have shown that a subset of these areas preferentially respond more to moving than static stimuli, but the reasons for this functional dissociation remain unclear. In the present study, we simultaneously mapped the responses to motion in face-, body- and scene-selective areas in the right hemisphere using moving and static stimuli. Participants (N = 22) were scanned using functional magnetic resonance imaging (fMRI) while viewing videos containing bodies, faces, objects, scenes or scrambled objects, and static pictures from the beginning, middle and end of each video. Results demonstrated that lateral areas, including face-selective areas in the posterior and anterior superior temporal sulcus (STS), the extrastriate body area (EBA) and the occipital place area (OPA) responded more to moving than static stimuli. By contrast, there was no difference between the response to moving and static stimuli in ventral and medial category-selective areas, including the fusiform face area (FFA), occipital face area (OFA), amygdala, fusiform body area (FBA), retrosplenial complex (RSC) and parahippocampal place area (PPA). This functional dissociation between lateral and ventral/medial brain areas that respond selectively to different visual categories suggests that face-, body- and scene-selective networks may be functionally organized along a common dimension.
机译:人脑包含对脸部,身体和场景有选择性反应的区域。神经影像学研究表明,这些区域的一部分比静态刺激对移动的反应更好,但这种功能分离的原因尚不清楚。在本研究中,我们同时使用运动和静态刺激在右半球的面部,身体和场景选择区域中同时绘制了对运动的响应。使用功能磁共振成像(fMRI)对参与者(N = 22)进行扫描,同时观看包含身体,面部,物体,场景或混乱物体的视频,以及从每个视频的开头,中间和结尾开始的静态图片。结果表明,外侧区域,包括后颞上颞沟(STS)和前颞上沟(STS)的面部选择区域,躯干外区(EBA)和枕骨部位(OPA)对移动的反应比静态刺激要大。相比之下,在腹侧和内侧类别选择区域,包括梭形面部区域(FFA),枕面部区域(OFA),杏仁核,梭形身体区域(FBA),脾后区域,对运动和静态刺激的反应之间没有差异复合体(RSC)和海马旁区域(PPA)。选择性响应不同视觉类别的外侧和腹侧/内侧脑区域之间的这种功能分离表明,脸部,身体和场景选择网络可以沿一个共同的维度进行组织。

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