Neural correlates of mathematical problem solving

Chun Ling Lin, Melody Jung, Ying Choon Wu, Hsiao-Ching She, Tzyy Ping Jung*


研究成果: Article同行評審

11 引文 斯高帕斯(Scopus)


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-θ (4-7 Hz), α (8-13 Hz) and β (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.

期刊International journal of neural systems
出版狀態Published - 25 3月 2015


深入研究「Neural correlates of mathematical problem solving」主題。共同形成了獨特的指紋。