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Correlating Behavioral Responses to fMRI Signals from Human Prefrontal Cortex: Examining Cognitive Processes Using Task Analysis
Published on: June 20, 2012
Cross-frequency power correlations reveal the right superior temporal gyrus as a hub region during working memory
Hyojin Park1, Eunjoo Kang, Hyejin Kang
1Department of Nuclear Medicine, Seoul National University College of Medicine, and MEG Center, Department of Neurosurgery, Seoul National University Hospital, Seoul, Korea.
Abstract:
In the present study, we characterized within- and cross-frequency power correlations from magnetoencephalography (MEG) data in order to understand how different brain regions cooperate as a network to maintain working memory representations with several features. The working memory items were composed of spatially arranged dots supposedly requiring both the dorsal and the ventral stream to be engaged during maintenance. Using a beamforming technique, we localized memory-dependent sources in the alpha, beta, and gamma bands. After the single-trial power values were extracted from these frequency bands with respect to each source, we calculated the correlations within- and cross-frequency bands. The following general picture emerged: gamma power in right superior temporal gyrus (STG) during working memory maintenance was correlated with numerous other sources in the alpha band in prefrontal, parietal, and posterior regions. In addition, the power correlations within the alpha band showed correlations across posterior-parietal-frontal regions. From these findings, we suggest that the STG dominated by gamma activity serves as a hub region for the network nodes responsible for the retention of the stimulus used in this study, which is likely to depend on both the "where-" and the "what-" visual system simultaneously. The present study demonstrates how oscillatory dynamics reflecting the interaction between cortical areas can be investigated by means of cross-frequency power correlations in source space. This methodological framework could be of general utility when studying functional network properties of the working brain.
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