The Oscillating Brain: Complex and Reliable

By Xi-Nian Zuo, A. di Martino, Clare Kelly, Zarrar Shehzad, Dylan G. Gee, D. F. Klein, F. X. Castellanos, Bharat B. Biswal, Michael P. Milham. NeuroImage, 2009

1,441 citations recorded by the source corpus.

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. Further, 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.

View Paper: https://www.semanticscholar.org/paper/0fe27fbb6a4a59bf4cd94d970d732d51dd9c414f

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Citations in the corpus

Advances and Pitfalls in the Analysis and Interpretation of Resting-State FMRI Data (2010, unknown): “Additionally, some work has suggested that low-frequency measures of resting data may be rather susceptible to cerebral vascular and respiratory artefacts (Zuo et al., 2010a).”
Reliable Intrinsic Connectivity Networks: Test-Retest Evaluation Using ICA and Dual Regression Approach (2009, unknown): “The data were used in our earlier studies to examine the TRT reliability of seed-based correlation measures (Shehzad et al., 2009; Zuo et al., 2010).”
Standardizing the intrinsic brain: Towards robust measurement of inter-individual variation in 1000 functional connectomes (2013, unknown): “…have already emerged in the field including mean division (Zang et al., 2004, 2007); Z-score standardization (Beckmann et al., 2005; Buckner et al., 2009; Calhoun et al., 2001; Zou et al., 2008; Zuo et al., 2010a, 2012, 2013); and Gaussian function fit normalization (Lowe et al., 1998).”
Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: A resting-state fMRI study (2011, methodology): “The signals of slow-6, slow-3, and slow-2 were discarded because they mainly reflect very low frequency drift, WM signals, and high-frequency physiological noises, respectively (Biswal et al., 1995; Zuo et al., 2010).”
Eigenvector Centrality Mapping for Analyzing Connectivity Patterns in fMRI Data of the Human Brain (2010, background): “It should be noted that low frequency fluctuations may also be caused by aliasing effects (undersampling) so that the actual sources of these signals need not be in that same low frequency range. Nonetheless, recent studies have confirmed that oscillations - even at very low frequencies - appear rob”
A Comprehensive Assessment of Regional Variation in the Impact of Head Micromovements on Functional Connectomics (2013, methodology): “This is not surprising, as Z-standardization (i.e., within-subject mean centering and variance normalization) was applied in accord with common practice (e.g., Buckner et al., 2009; Zou et al., 2008; Zuo et al., 2010a, 2012, 2013).”
Functional connectivity hubs in the human brain (2011, unknown): “This reflects higher between-than within-subjects gFCD-variability and is a common measure of reliability in resting-state functional connectivity studies (Zuo et al., 2010).”
Growing together and growing apart: Regional and sex differences in the lifespan developmental trajectories of functional homotopy (2010, methodology): “First, using our TRT R-fMRI dataset (www.nitrc.org/projects/ nyu_trt) (Shehzad et al., 2009; Zuo et al., 2010a,b), we examined the TRT reliability of VMHC. VMHC showed both short- and long-term fair to excellent (0.4 intraclass correlation 1.0) reliability (Rosner, 2005) across most brain cortical…”
The dynamic functional connectome: State-of-the-art and perspectives (2017, unknown): “More recent work also put forward a spatially inhomogeneous frequency distribution within this narrow interval (Zuo et al., 2010), a feature that revealed to be clinically useful (Wee et al., 2012; Han et al., 2011).”
Navigating Into the Future or Driven by the Past (2013, background): “We suggest that taking prospection seriously might reorient thinking and illuminate (a) consciousness and subjectivity, (b) free will, (c) and psychopathology and therapy.”
Toward reliable characterization of functional homogeneity in the human brain: Preprocessing, scan duration, imaging resolution and computational space (2012, methodology): “For more information regarding data collection methods, please refer to Shehzad et al. (2009), Zuo et al. (2010a,b,c, 2012), Zuo and Xing (2011), Wang et al. (2011a).”
The Influence of Head Motion on Intrinsic Functional Connectivity MRI (2011, methodology): “The technique is robust and yields reliable measures within individuals (e.g., Honey et al., 2009; Meindl et al., 2010; Shehzad et al., 2009; Van Dijk et al., 2010; Zuo et al., 2010).”