Article

The oscillating brain: Complex and reliable

Phyllis Green and Randolph Cōwen Institute for Pediatric Neuroscience at the New York University Child Study Center, New York, NY, USA.
NeuroImage (Impact Factor: 6.36). 09/2009; 49(2):1432-45. DOI: 10.1016/j.neuroimage.2009.09.037
Source: PubMed

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.

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    • "The interest in the spectral properties of the BOLD signal was also extended to functional connectivity studies. Specifically, there have been reports analyzing the spectral components of the BOLD signal in the defaultmode (DMN) and other networks using typical EPI with TR = 2 s (Baria et al., 2011; Chang and Glover, 2010; Salvador et al., 2008; Zuo et al., 2010) and fast MRI method (Lee et al., 2013), which can estimate frequency components up to 0.5 Hz and 5 Hz, respectively. Frequencydependent subcomponents were identified in the DMN network (Barbaresi et al., 1995). "
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    • "This phenomenon is not unique to the fMRI signal (Fox et al., 2007; Zarahn et al., 1997) but rather is a common feature observed in electrophysiological studies (Leopold et al., 2003; Linkenkaer-Hansen et al., 2001), implying a common biological feature of neural oscillations (Buzsáki and Draguhn, 2004). Previous studies have shown the spectral behavior in resting-state fMRI signal over a relatively wide frequency range (0–1.25 Hz), demonstrating the effects of both slow fluctuations and physiological noise on a variety of networks (Cordes et al., 2001; Salvador et al., 2008; Wu et al., 2008; Zuo et al., 2010). However, due to the lack of spectral resolution, uncertainty of the frequency range specific to spontaneous fluctuations makes it difficult to relate fMRI fluctuations with underlying electrophysiology signals. "
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    • "Although the DMN is the best characterized of these RSNs, model-free connectivity analysis methods have identified a diverse array of such networks (Allen et al., 2011; Beckmann et al., 2005; Damoiseaux et al., 2006; De Luca et al., 2006; Kiviniemi et al., 2009; Pendse et al., 2011; Zuo et al., 2010) that have also been shown to interact with each other (Allen et al., 2012a; Doucet et al., 2011), revealing the brain to be a complex, highly interconnected neural system. "
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