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数量估计和数量直觉的神经关联是否可以分离?一项功能性近红外光谱研究。

Are the neural correlates of subitizing and estimation dissociable? An fNIRS investigation.

机构信息

Department of General Psychology, University of Padova, Italy.

出版信息

Neuroimage. 2014 Jan 15;85 Pt 1:391-9. doi: 10.1016/j.neuroimage.2013.08.027. Epub 2013 Aug 23.

Abstract

Human performance in visual enumeration tasks typically shows two distinct patterns as a function of set size. For small sets, usually up to 4 items, numerosity judgments are extremely rapid, precise and confident, a phenomenon known as subitizing. When this limit is exceeded and serial counting is precluded, exact enumeration gives way to estimation: performance becomes error-prone and more variable. Surprisingly, despite the importance of subitizing and estimation in numerical cognition, only few neuroimaging studies have examined whether the neural activity related to these two phenomena can be dissociated. In the present work, we used multi-channel near-infrared spectroscopy (fNIRS) to measure hemodynamic activity of the bilateral parieto-occipital cortex during a visual enumeration task. Participants had to judge the numerosity of dot arrays and indicate it by means of verbal response. We observed a different hemodynamic pattern in the parietal cortex, both in terms of amplitude modulation and temporal profile, for numerosities below and beyond the subitizing range. Crucially, the neural dissociation between subitizing and estimation was strongest at the level of right IPS. The present findings confirm that fNIRS can be successfully used to detect subtle temporal differences in hemodynamic activity and to produce inferences on the neural mechanisms underlying cognitive functions.

摘要

人类在视觉计数任务中的表现通常会随着集合大小呈现出两种截然不同的模式。对于小集合,通常不超过 4 个项目,数量判断非常迅速、准确和自信,这种现象被称为“数觉”。当超过这个限制且禁止序列计数时,精确计数会让位于估计:表现变得容易出错且更具变异性。令人惊讶的是,尽管“数觉”和“估计”在数值认知中非常重要,但只有少数神经影像学研究探讨了与这两种现象相关的神经活动是否可以区分开来。在本研究中,我们使用多通道近红外光谱(fNIRS)测量了视觉计数任务中双侧顶枕叶皮层的血流动力学活动。参与者必须判断点数组的数量,并通过口头反应表示出来。我们观察到,在数量低于和超过数觉范围时,顶叶皮层的血流动力学模式在幅度调制和时间分布方面存在不同。至关重要的是,在右侧 IPS 水平上,“数觉”和“估计”之间的神经分离最强。本研究结果证实,fNIRS 可以成功用于检测血流动力学活动中的细微时间差异,并对认知功能的神经机制做出推断。

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