通过分析人脑活动，法国一些科研人员能知晓人们刚刚看到多少个圆点。
这些科研人员来自法国首都巴黎西南郊区的巴黎南大学。他们请10名志愿者观看屏幕上的圆点或数字，同时用设备扫描志愿者大脑负责处理数字的部位。然后，科研人员分析这一过程中志愿者的脑部活动，对这些活动加以“破译”。
研究人员发现，当志愿者看到的是圆点时，随着圆点数量增加，志愿者大脑活动与之呼应地逐渐变化。例如，科研人员能明确知晓志愿者看5个圆点时，脑部活动活跃程度处于看4个圆点时和看6个圆点时之间。
不过，当志愿者看到抽象的数字时，研究人员无法探测到志愿者大脑活动的上述变化模式。这可能有两方面原因，一是研究人员的探测方法敏感度不够，二是抽象数字在人脑中编码方式有所不同。
研究者之一伊夫琳埃格尔对趣味科学网站说，同看到抽象数字相比，当志愿者看到具体数目的圆点时，他们大脑的活动“似乎更强烈”，也更易于分辨。
研究人员说，他们这套实验方法可能最终破解人脑如何实现复杂运算之谜，还可能弄清人们在学习数学过程中大脑究竟如何变化。
相关研究报告发表在24日出版的《当代生物学》杂志上。
心理学之家 推荐原文原始出处：
Current Biology, 24 September 2009 doi:10.1016/j.cub.2009.08.047
Deciphering Cortical Number Coding from Human Brain Activity Patterns
Evelyn Eger1, 2, 3, , , Vincent Michel2, 3, 4, Bertrand Thirion2, 4, Alexis Amadon2, 5, Stanislas Dehaene1, 2, 3 and Andreas Kleinschmidt1, 2, 3
1 INSERM U562, F-91191 Gif/Yvette, France
2 NeuroSpin, Institut d'Imagerie Biomédicale, Direction des Sciences du Vivant, Commissariat à l'énergie Atomique, F-91191 Gif/Yvette, France
3 Université Paris-Sud, F-91405 Orsay, France
4 Parietal Team, Institut National de Recherche en Informatique et en Automatique (INRIA) Saclay-?le-de-France, F-91893 Orsay, France
5 Laboratoire de Résonance Magnétique Nucléaire, F-91191 Gif/Yvette, France
Neuropsychology and human functional neuroimaging have implicated human parietal cortex in numerical processing, and macaque electrophysiology has shown that intraparietal areas house neurons tuned to numerosity. Yet although the areas responding overall during numerical tasks have been well defined by neuroimaging, a direct demonstration of individual number coding by spatial patterns has thus far been elusive.We used multivariate pattern recognition on high-resolution functional imaging data to decode the information content of fine-scale signals evoked by different individual numbers. Parietal activation patterns for individual numerosities could be accurately discriminated and generalized across changes in low-level stimulus parameters. Distinct patterns were evoked by symbolic and nonsymbolic number formats, and individual digits were less accurately decoded (albeit still with significant accuracy) than numbers of dots. Interestingly, the numerosity of dot sets could be predicted above chance from the brain activation patterns evoked by digits, but not vice versa. Finally, number-evoked patterns changed in a gradual fashion as a function of numerical distance for the nonsymbolic notation, compatible with some degree of orderly layout of individual number representations.Our findings demonstrate partial format invariance of individual number codes that is compatible with more numerous but more broadly tuned populations for nonsymbolic than for symbolic numbers, as postulated by recent computational models. In more general terms, our results illustrate the potential of functional magnetic resonance imaging pattern recognition to understand the detailed format of representations within a single semantic category, and beyond sensory cortical areas for which columnar architectures are well established.
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