Brain activity and learning of mathematical rules—Effects on the frequencies of EEG

脑电图 Morlet小波 可分性规则 心理学 模式识别(心理学) 人工智能 小波 任务(项目管理) 语音识别 数学 计算机科学 听力学 神经科学 小波变换 离散小波变换 医学 组合数学 经济 管理
作者
Wolfgang Skrandies,Alexander Klein
出处
期刊:Brain Research [Elsevier]
卷期号:1603: 133-140 被引量:14
标识
DOI:10.1016/j.brainres.2014.11.015
摘要

We investigated the change of evoked EEG frequencies induced by learning to solve mathematical tasks by applying divisibility rules. The performance on easy (divisibility by 2, 3, or 5) and hard tasks (divisibility by 9 or by 11) was compared. In a behavioral experiment on 52 adults we found a significant increase in performance from 67% to 90% correct responses induced by rule learning. Subsequently, the EEG data recorded from 30 additional volunteers were analyzed. EEG recordings were performed in two parts: First, subjects had to solve 200 tasks without knowing the divisibility rules. Then the rules were explained, followed by another set of 200 tasks. EEG was measured simultaneously in 30 channels, artifacts were removed offline, and the data before and after rule learning were compared. A wavelet transformation with the Morlet-5 wavelet was computed, and the scalp topography of the maximal frequency and its occurrence time was compared. Largest effects were observed with frequencies between about 6 and 18 Hz. In the frequency band between 12 and 30 Hz maximal frequencies were significantly different after successful learning over frontal and centro-parietal scalp areas of the right hemisphere. These changes were paralleled by decreased response times. In summary, our data illustrate a significant relation between successful learning divisibility rules and changes in the frequency content of the task-related EEG. Significant effects were observed after a very short training period of less than 10 min.
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