4.5 Article

Tuning to non-symbolic proportions in the human frontoparietal cortex

期刊

EUROPEAN JOURNAL OF NEUROSCIENCE
卷 30, 期 7, 页码 1432-1442

出版社

WILEY-BLACKWELL PUBLISHING, INC
DOI: 10.1111/j.1460-9568.2009.06932.x

关键词

fMRI adaptation; human cerebral cortex; intraparietal sulcus; numerosity; proportions

资金

  1. German Research Foundation (DFG) [C11/SFB 550]
  2. International Human Frontier Science Program Organization (HFSP)

向作者/读者索取更多资源

Humans share with many species a non-verbal system to estimate absolute quantity. This sense of number has been linked to the activity of quantity-selective neurons that respond maximally to preferred numerosities. With functional magnetic resonance imaging adaptation, we now show that populations of neurons in the human parietal and frontal cortex are also capable of encoding quantity ratios, or proportions, using the same non-verbal analog code as for absolute number. Following adaptation to visually presented constant proportions (specified by the ratio of line lengths or numerosities), we introduced novel relative magnitudes to examine the tuning characteristics of the population of stimulated neurons. In bilateral parietal and frontal cortex we found that blood oxygenation level-dependent signal recovery from adaptation was a function of numerical distance between the deviant proportion and the adaptation stimulus. The strongest effects were observed in the cortex surrounding the anterior intraparietal sulcus, a region considered pivotal for the processing of absolute magnitudes. Overall, there was substantial overlap of frontoparietal structures representing whole numbers and proportions. The identification of tuning to non-symbolic ratio stimuli, irrespective of notation, adds to the magnitude system a remarkable level of sophistication by demonstrating automatic access to a composite, derived quantitative measure. Our results argue that abstract concepts of both absolute and relative number are deeply rooted in the primate brain as fundamental determinants of higher-level numerical cognition.

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