TY - GEN
T1 - The neural mechanism of human numerical inductive reasoning process
T2 - 1st WICI International Workshop on Web Intelligence meets Brain Informatics, WImBI 2006
AU - Liang, Peipeng
AU - Zhong, Ning
AU - Lu, Shengfu
AU - LIU, Jiming
AU - Yao, Yiyu
AU - Li, Kuncheng
AU - Yang, Yanhui
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2007
Y1 - 2007
N2 - Inductive reasoning is one of the most important higher level cognitive functions of the human brain, and we still know very little about its neural mechanism. In the present study, event-related potential (ERP) and event-related fMRI are used to explore the dynamic spatiotemporal characteristics of inductive reasoning process. We hypothesize that the process of numerical inductive reasoning is partially dissociable over time and space. A typical task of inductive reasoning, function-finding, was adopted. Induction tasks and calculation tasks were performed in the experiments, respectively. ERP results suggest that the time course of inductive reasoning process is partially dissociable as the following three sub-processes: number recognition (the posterior P100 and N200), strategy formation (P300) and hypothesis generation and verification (the positive slow waves). fMRI results show many activations, including prefrontal gyrus (BA 6), inferior parietal lobule (BA 7, 40), and occipital cortex (BA 18). After the respective discussions, the two kinds of data are combined qualitatively, then the dynamic spatiotemporal characteristic of inductive reasoning process are depicted using a conceptual figure. This study is a preliminary effort towards deeply understanding the dynamic information processing mechanism of human inductive reasoning process.
AB - Inductive reasoning is one of the most important higher level cognitive functions of the human brain, and we still know very little about its neural mechanism. In the present study, event-related potential (ERP) and event-related fMRI are used to explore the dynamic spatiotemporal characteristics of inductive reasoning process. We hypothesize that the process of numerical inductive reasoning is partially dissociable over time and space. A typical task of inductive reasoning, function-finding, was adopted. Induction tasks and calculation tasks were performed in the experiments, respectively. ERP results suggest that the time course of inductive reasoning process is partially dissociable as the following three sub-processes: number recognition (the posterior P100 and N200), strategy formation (P300) and hypothesis generation and verification (the positive slow waves). fMRI results show many activations, including prefrontal gyrus (BA 6), inferior parietal lobule (BA 7, 40), and occipital cortex (BA 18). After the respective discussions, the two kinds of data are combined qualitatively, then the dynamic spatiotemporal characteristic of inductive reasoning process are depicted using a conceptual figure. This study is a preliminary effort towards deeply understanding the dynamic information processing mechanism of human inductive reasoning process.
UR - http://www.scopus.com/inward/record.url?scp=38349063024&partnerID=8YFLogxK
U2 - 10.1007/978-3-540-77028-2_12
DO - 10.1007/978-3-540-77028-2_12
M3 - Conference proceeding
AN - SCOPUS:38349063024
SN - 9783540770275
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 223
EP - 243
BT - Web Intelligence Meets Brain Informatics - First WICI International Workshop, WImBI 2006, Revised Selected and Invited Papers
PB - Springer Verlag
Y2 - 15 December 2006 through 16 December 2006
ER -