標題: Neural Correlates of Mathematical Problem Solving
作者: Lin, Chun-Ling
Jung, Melody
Wu, Ying Choon
She, Hsiao-Ching
Jung, Tzyy-Ping
教育研究所
Institute of Education
關鍵字: Mathematical problem solving;electroencephalogram (EEG);solution latencies (SLs)
公開日期: 1-三月-2015
摘要: This study explores electroencephalography (EEG) brain dynamics associated with mathematical problem solving. EEG and solution latencies (SLs) were recorded as 11 neurologically healthy volunteers worked on intellectually challenging math puzzles that involved combining four single-digit numbers through basic arithmetic operators (addition, subtraction, division, multiplication) to create an arithmetic expression equaling 24. Estimates of EEG spectral power were computed in three frequency bands - theta (4-7Hz), alpha (8-13Hz) and beta (14-30 Hz) - over a widely distributed montage of scalp electrode sites. The magnitude of power estimates was found to change in a linear fashion with SLs - that is, relative to a base of power spectrum, theta power increased with longer SLs, while alpha and beta power tended to decrease. Further, the topographic distribution of spectral fluctuations was characterized by more pronounced asymmetries along the left-right and anterior-posterior axes for solutions that involved a longer search phase. These findings reveal for the first time the topography and dynamics of EEG spectral activities important for sustained solution search during arithmetical problem solving.
URI: http://dx.doi.org/10.1142/S0129065715500045
http://hdl.handle.net/11536/124309
ISSN: 0129-0657
DOI: 10.1142/S0129065715500045
期刊: INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Volume: 25
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