Objects are perceived within rich visual contexts, and statistical associa"/>

Neural Signatures of Learning Novel Object-Scene Associations.

Journal of cognitive neuroscience(2020)

引用 1|浏览0
暂无评分
摘要
Objects are perceived within rich visual contexts, and statistical associations may be exploited to facilitate their rapid recognition. Recent work using natural scene–object associations suggests that scenes can prime the visual form of associated objects, but it remains unknown whether this relies on an extended learning process. We asked participants to learn categorically structured associations between novel objects and scenes in a paired associate memory task while ERPs were recorded. In the test phase, scenes were first presented (2500 msec), followed by objects that matched or mismatched the scene; degree of contextual mismatch was manipulated along visual and categorical dimensions. Matching objects elicited a reduced N300 response, suggesting visuostructural priming based on recently formed associations. Amplitude of an extended positivity (onset ∼200 msec) was sensitive to visual distance between the presented object and the contextually associated target object, most likely indexing visual template matching. Results suggest recent associative memories may be rapidly recruited to facilitate object recognition in a top–down fashion, with clinical implications for populations with impairments in hippocampal-dependent memory and executive function.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要