4.7 Article

Changes in brain network activity during working memory tasks: A magnetoencephalography study

期刊

NEUROIMAGE
卷 55, 期 4, 页码 1804-1815

出版社

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.neuroimage.2010.10.074

关键词

MEG; Network; Theta; Gamma; Beamformer; Oscillations; Connectivity

资金

  1. Leverhulme Trust
  2. University of Nottingham
  3. Medical Research Council
  4. Medical Research Council [G0901321] Funding Source: researchfish
  5. MRC [G0901321] Funding Source: UKRI

向作者/读者索取更多资源

In this study, we elucidate the changes in neural oscillatory processes that are induced by simple working memory tasks. A group of eight subjects took part in modified versions of the N-back and Sternberg working memory paradigms. Magnetoencephalography (MEG) data were recorded, and subsequently processed using beamformer based source imaging methodology. Our study shows statistically significant increases in 9 oscillations during both N-back and Sternberg tasks. These oscillations were shown to originate in the medial frontal cortex, and further to scale with memory load. We have also shown that increases in theta oscillations are accompanied by decreases in beta and gamma band oscillations at the same spatial coordinate. These decreases were most prominent in the 20-40 Hz frequency range, although spectral analysis showed that gamma band power decrease extends up to at least 80 Hz. beta/gamma Power decrease also scales with memory load. Whilst theta increases were predominately observed in the medial frontal cortex, beta/gamma decreases were associated with other brain areas, including nodes of the default mode network (for the N-back task) and areas associated with language processing (for the Sternberg task). These observations are in agreement with intracranial EEG and fMRI studies. Finally, we have shown an intimate relationship between changes in beta/gamma, band oscillatory power at spatially separate network nodes, implying that activity in these nodes is not reflective of urn-modal task driven changes in spatially separate brain regions, but rather represents correlated network activity. The utility of MEG as a non-invasive means to measure neural oscillatory modulation has been demonstrated and future studies employing this technology have the potential to gain a better understanding of neural oscillatory processes, their relationship to functional and effective connectivity, and their correspondence to BOLD fMRI. (C) 2010 Elsevier Inc. All rights reserved.

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