Micheloyannis Sifis, Vourkas Michael, Bizas Manolis, Simos Panagiotis, Stam Cornelis J
University of Crete, Medical Division, Clinical Neurophysiological Labor (L.Widen) Iraklion, Greece.
Brain Topogr. 2003 Summer;15(4):239-47. doi: 10.1023/a:1023962125598.
The purpose of the present study was threefold: First, to replicate previous findings of changes in local gamma band power as a function of the complexity of a visuo-semantic processing task, second, to extend these findings in tasks delivered in the auditory modality, and third to explore the use of non-linear algorithms as indices of complexity and distant synchronization in the EEG signal. EEG was recorded from 28 scalp locations as participants performed three visual discrimination tasks designed to tap into increasingly more complex operations regularly involved in the recognition of living animate objects. Two auditory processing tasks involving the same stimuli, but requiring no semantic processing, served as controls. The degree of complexity of the semantic decision was associated with the predicted changes in local gamma power, as well as with broadband changes in the non-linear predictability of the signal (an index derived using an artificial neural network algorithm). These changes were observed at all scalp regions, a finding consistent with the wide cortical distribution of component processes involved in the tasks. In addition, the synchronization between temporal and parieto-occipital electrodes and the remaining recording sites was highest in the gamma bands and lowest in the alpha bands for the task that required the most complex visuo-semantic decision. This trend reversed with reduced task complexity, consistent with the view that multidimensional semantic decisions require the involvement of distributed cortical networks in auditory and visual association areas and in the frontal lobes.
第一，复制先前关于局部伽马波段功率随视觉语义处理任务复杂性变化的研究结果；第二，将这些结果扩展到听觉模态的任务中；第三，探索使用非线性算法作为脑电图信号复杂性和远距离同步的指标。在参与者执行三项视觉辨别任务时，从28个头皮位置记录脑电图，这些任务旨在挖掘识别有生命的活体物体时通常涉及的越来越复杂的操作。两项涉及相同刺激但不需要语义处理的听觉处理任务作为对照。语义决策的复杂程度与局部伽马功率的预测变化以及信号非线性可预测性的宽带变化（使用人工神经网络算法得出的指标）相关。在所有头皮区域都观察到了这些变化，这一发现与任务中涉及的组成过程的广泛皮质分布一致。此外，对于需要最复杂视觉语义决策的任务，颞叶和顶枕叶电极与其余记录部位之间的同步在伽马波段最高，在阿尔法波段最低。随着任务复杂性的降低，这种趋势发生逆转，这与多维语义决策需要听觉和视觉联合区域以及额叶中分布式皮质网络参与的观点一致。
