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首页> 外文期刊>Current Biology: CB >Shaping of Object Representations in the Human Medial Temporal Lobe Based on Temporal Regularities
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Shaping of Object Representations in the Human Medial Temporal Lobe Based on Temporal Regularities

机译:基于时间规律的人内侧颞叶对象表示的成形

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Regularities are gradually represented in cortex after extensive experience [1], and yet they can influence behavior after minimal exposure [2 and 3]. What kind of representations support such rapid statistical learning The medial temporal lobe (MTL) can represent information from even a single experience [4], making it a good candidate system for assisting in initial learning about regularities. We combined anatomical segmentation of the MTL, high-resolution fMRI, and multivariate pattern analysis to identify representations of objects in cortical and hippocampal areas of human MTL, assessing how these representations were shaped by exposure to regularities. Subjects viewed a continuous visual stream containing hidden temporal relationships—pairs of objects that reliably appeared nearby in time. We compared the pattern of blood oxygen level-dependent activity evoked by each object before and after this exposure, and found that perirhinal cortex, parahippocampal cortex, subiculum, CA1, and CA2/CA3/dentate gyrus (CA2/3/DG) encoded regularities by increasing the representational similarity of their constituent objects. Most regions exhibited bidirectional associative shaping, whereas CA2/3/DG represented regularities in a forward-looking predictive manner. These findings suggest that object representations in MTL come to mirror the temporal structure of the environment, supporting rapid and incidental statistical learning.
机译:丰富的经验[1]后,皮层中的规律性逐渐体现出来,但是在最小程度的暴露后它们仍会影响行为[2和3]。什么样的表示支持这种快速的统计学习内侧颞叶(MTL)甚至可以从单一的经验中表示信息[4],使其成为协助初步学习规律性的良好候选系统。我们将MTL的解剖学分割,高分辨率fMRI和多变量模式分析相结合,以识别人类MTL皮质和海马区域中物体的表示,评估暴露于规律性如何塑造这些表示。受试者观看了包含隐藏的时间关系的连续视觉流,这些时间关系是可靠地及时出现在附近的成对物体。我们比较了每次暴露前后每个对象引起的血氧水平依赖性活动的模式,发现皮层,皮层,CA1和CA2 / CA3 /齿状回(CA2 / 3 / DG)编码的规律性通过增加其构成对象的表示相似性。大多数区域都表现出双向关联成形,而CA2 / 3 / DG以前瞻性的预测方式代表规律性。这些发现表明,MTL中的对象表示可以反映环境的时间结构,从而支持快速和偶然的统计学习。

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