Dataset Information

The oscillating brain: complex and reliable.

ABSTRACT: The human brain is a complex dynamic system capable of generating a multitude of oscillatory waves in support of brain function. Using fMRI, we examined the amplitude of spontaneous low-frequency oscillations (LFO) observed in the human resting brain and the test-retest reliability of relevant amplitude measures. We confirmed prior reports that gray matter exhibits higher LFO amplitude than white matter. Within gray matter, the largest amplitudes appeared along mid-brain structures associated with the "default-mode" network. Additionally, we found that high-amplitude LFO activity in specific brain regions was reliable across time. Furthermore, parcellation-based results revealed significant and highly reliable ranking orders of LFO amplitudes among anatomical parcellation units. Detailed examination of individual low frequency bands showed distinct spatial profiles. Intriguingly, LFO amplitudes in the slow-4 (0.027-0.073 Hz) band, as defined by Buzsáki et al., were most robust in the basal ganglia, as has been found in spontaneous electrophysiological recordings in the awake rat. These results suggest that amplitude measures of LFO can contribute to further between-group characterization of existing and future "resting-state" fMRI datasets.

SUBMITTER: Zuo XN

PROVIDER: S-EPMC2856476 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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The oscillating brain: complex and reliable.

Zuo Xi-Nian XN Di Martino Adriana A Kelly Clare C Shehzad Zarrar E ZE Gee Dylan G DG Klein Donald F DF Castellanos F Xavier FX Biswal Bharat B BB Milham Michael P MP

NeuroImage 20090924 2

The human brain is a complex dynamic system capable of generating a multitude of oscillatory waves in support of brain function. Using fMRI, we examined the amplitude of spontaneous low-frequency oscillations (LFO) observed in the human resting brain and the test-retest reliability of relevant amplitude measures. We confirmed prior reports that gray matter exhibits higher LFO amplitude than white matter. Within gray matter, the largest amplitudes appeared along mid-brain structures associated wi ...[more]

PMID: 19782143

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Project description:Voxel-based morphometry (VBM) is a popular non-invasive magnetic resonance imaging technique to investigate brain gray matter (GM) differences between groups. Recently, two VBM studies in migraine have been published in The Journal of Headache and Pain. Reviewing the two and those previous published VBM studies, we found considerable variations of the results. Spatially diverse brain regions with decreased and increased GM alterations and null findings have been reported. It is interesting to know whether there is a reliable brain morphological signature for migraine. Coordinate-based meta-analysis (CBMA) is increasingly used to quantitatively pool individual neuroimaging studies to identify consistent and reliable findings. Several CBMA have been conducted, however, their results were inconsistent. The algorithms for CBMA have evolved and more eligible VBM studies in migraine have been published. We therefore conducted an updated CBMA using the latest algorithms for CBMA, seed-based d mapping with permutation of subject images (SDM-PSI). The present CBMA of 32 VBM studies (41 datasets comprising 1252 patients and 1025 healthy controls) found no evidence of consistent GM alterations in migraine. Sensitivity analysis, subgroup meta-analyses, and meta-regression analyses revealed that the result was robust. This negative result indicates that there is no reliable brain morphological signature for migraine. VBM investigations in migraine remain a heterogeneous field. Many potential confounding factors, such as underpowered sample sizes, variations in demographic and clinical characteristics, and differences in MRI scanners, head coils, scanning parameters, preprocessing procedures, and statistical strategies may cause the inconsistences of the results. Future VBM studies are warranted to enroll well-characterized and homogeneous subtype samples with appropriate sample sizes, comprehensively assess comorbidities and medication status, and use well-validated and standardized imaging protocols and processing and analysis pipelines to produce robust and replicable results in migraine.

Dataset Information

The oscillating brain: complex and reliable.

Publications

The oscillating brain: complex and reliable.

Similar Datasets

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