Activity in the fronto-parietal network indicates numerical inductive reasoning beyond calculation: An fMRI study combined with a cognitive model

被引:16
|
作者
Liang, Peipeng [1 ,2 ]
Jia, Xiuqin [1 ,2 ]
Taatgen, Niels A. [3 ]
Borst, Jelmer P. [3 ]
Li, Kuncheng [1 ,2 ]
机构
[1] Capital Med Univ, Xuanwu Hosp, Dept Radiol, Beijing 100053, Peoples R China
[2] Beijing Key Lab MRI & Brain Informat, Beijing 100053, Peoples R China
[3] Univ Groningen, Inst Artificial Intelligence, Nijenborgh 9, NL-9747 AG Groningen, Netherlands
来源
SCIENTIFIC REPORTS | 2016年 / 6卷
基金
“十二五”国家科技支撑计划重点项目”; 中国博士后科学基金;
关键词
DORSOLATERAL PREFRONTAL CORTEX; SYMBOL MANIPULATION; MEMORY; COMPLEXITY;
D O I
10.1038/srep25976
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Numerical inductive reasoning refers to the process of identifying and extrapolating the rule involved in numeric materials. It is associated with calculation, and shares the common activation of the frontoparietal regions with calculation, which suggests that numerical inductive reasoning may correspond to a general calculation process. However, compared with calculation, rule identification is critical and unique to reasoning. Previous studies have established the central role of the fronto-parietal network for relational integration during rule identification in numerical inductive reasoning. The current question of interest is whether numerical inductive reasoning exclusively corresponds to calculation or operates beyond calculation, and whether it is possible to distinguish between them based on the activity pattern in the fronto-parietal network. To directly address this issue, three types of problems were created: numerical inductive reasoning, calculation, and perceptual judgment. Our results showed that the fronto-parietal network was more active in numerical inductive reasoning which requires more exchanges between intermediate representations and long-term declarative knowledge during rule identification. These results survived even after controlling for the covariates of response time and error rate. A computational cognitive model was developed using the cognitive architecture ACT-R to account for the behavioral results and brain activity in the fronto-parietal network.
引用
收藏
页数:10
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