BOLD frequency power indexes working memory performance

被引:23
作者
Balsters, Joshua Henk [1 ,2 ]
Robertson, Ian H. [1 ]
Calhoun, Vince D. [3 ,4 ]
机构
[1] Univ Dublin Trinity Coll, Sch Psychol, Inst Neurosci, Dublin 2, Ireland
[2] ETH, Dept Hlth Sci & Technol, Neural Control Movement Lab, Zurich, Switzerland
[3] Mind Res Network, Albuquerque, NM USA
[4] Univ New Mexico, Dept Elect & Comp Engn, Albuquerque, NM 87131 USA
关键词
BOLD oscillations; ICA; fMRI; delayed match-to-sample; aging; RESTING STATE NETWORKS; SCALE BRAIN SYSTEMS; FUNCTIONAL CONNECTIVITY; DEFAULT-MODE; ALZHEIMERS-DISEASE; TIME-SERIES; INDEPENDENT COMPONENTS; HEMODYNAMIC-RESPONSES; COGNITIVE CONTROL; IMAGING DATA;
D O I
10.3389/fnhum.2013.00207
中图分类号
Q189 [神经科学];
学科分类号
071006 [神经生物学];
摘要
Electrophysiology studies routinely investigate the relationship between neural oscillations and task performance. However, the sluggish nature of the BOLD response means that few researchers have investigated the spectral properties of the BOLD signal in a similar manner. For the first time we have applied group ICA to fMRI data collected during a standard working memory task (delayed match-to-sample) and using a multivariate analysis, we investigate the relationship between working memory performance (accuracy and reaction time) and BOLD spectral power within functional networks. Our results indicate that BOLD spectral power within specific networks (visual, temporal-parietal, posterior default-mode network, salience network, basal ganglia) correlated with task accuracy. Multivariate analyses show that the relationship between task accuracy and BOLD spectral power is stronger than the relationship between BOLD spectral power and other variables (age, gender, head movement, and neuropsychological measures). A traditional General Linear Model (GLM) analysis found no significant group differences, or regions that covaried in signal intensity with task accuracy, suggesting that BOLD spectral power holds unique information that is lost in a standard GLM approach. We suggest that the combination of ICA and BOLD spectral power is a useful novel index of cognitive performance that may be more sensitive to brain behavior relationships than traditional approaches.
引用
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页数:16
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