Amplitude of low-frequency oscillations in schizophrenia: A resting state fMRI study

Division of Clinical Research, Nathan Kline Institute, 140 Old Orangeburg Road, Orangeburg, NY 10962, USA.
Schizophrenia Research (Impact Factor: 4.43). 10/2009; 117(1):13-20. DOI: 10.1016/j.schres.2009.09.030
Source: PubMed

ABSTRACT Recently, a great deal of interest has arisen in resting state fMRI as a measure of tonic brain function in clinical populations. Most studies have focused on the examination of temporal correlation between resting state fMRI low-frequency oscillations (LFOs). Studies on the amplitudes of these low-frequency oscillations are rarely reported. Here, we used amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF; the relative amplitude that resides in the low frequencies) to examine the amplitude of LFO in schizophrenia. Twenty-six healthy controls and 29 patients with schizophrenia or schizoaffective disorder participated. Our findings show that patients showed reduced low-frequency amplitude in proportion to the total frequency band investigated (i.e., fALFF) in the lingual gyrus, left cuneus, left insula/superior temporal gyrus, and right caudate and increased fALFF in the medial prefrontal cortex and the right parahippocampal gyrus. ALFF was reduced in patients in the lingual gyrus, cuneus, and precuneus and increased in the left parahippocampal gyrus. These results suggest LFO abnormalities in schizophrenia. The implication of these abnormalities for schizophrenic symptomatology is further discussed.

  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: To test the hypothesis that brain activity is modulated by trait social anxiety, we measured the Hurst Exponent (HE), an index of complexity in time series, in healthy individuals at rest in the absence of any social trigger. Functional magnetic resonance imaging (fMRI) time series were recorded in 36 subjects at rest. All volunteers were healthy without any psychiatric, medical or neurological disorder. Subjects completed the Liebowitz Social Anxiety Scale (LSAS) and the Brief Fear of Negative Evaluation (BFNE) to assess social anxiety and thoughts in social contexts. We also obtained the fractional Amplitude of Low Frequency Fluctuations (fALFF) of the BOLD signal as an independent control measure for HE data. BFNE scores correlated positively with HE in the posterior cingulate/precuneus, while LSAS scores correlated positively with HE in the precuneus, in the inferior parietal sulci and in the parahippocamus. Results from fALFF were highly consistent with those obtained using LSAS and BFNE to predict HE. Overall our data indicate that spontaneous brain activity is influenced by the degree of social anxiety, on a continuum and in the absence of social stimuli. These findings suggest that social anxiety is a trait characteristic that shapes brain activity and predisposes to different reactions in social contexts. Copyright © 2015. Published by Elsevier Ireland Ltd.
    Psychiatry Research Neuroimaging 03/2015; 232(2). DOI:10.1016/j.pscychresns.2015.03.005 · 2.83 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Major depressive disorder is associated with aberrant topological organizations of brain networks. However, whether this aberrance is shown in broader frequency bands or in a specific frequency band remains unknown. Fifty patients and fifty gender, age and education matched normal controls underwent resting state functional magnetic resonance imaging. Frequency dependent topological measures based on graph theory were calculated from wavelet decomposed resting state functional brain signals. In the specific frequency band of 0.03-0.06 14Hz, the clustering coefficient and the global efficiency were reduced while the characteristic path length was increased. Furthermore, patients showed aberrant nodal centralities in the default mode network, executive network and occipital network. Network based statistical analysis revealed system-wise topological alterations in these networks. The finding provides the first systematic evidence that depression is associated with frequency specific global and local topological disruptions and highlights the importance of frequency information in investigating major depressive disorders.
    Scientific Reports 04/2015; 5:9710. DOI:10.1038/srep09710 · 5.08 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain.
    PLoS ONE 01/2015; 10(3):e0121757. DOI:10.1371/journal.pone.0121757 · 3.53 Impact Factor

Full-text (2 Sources)

Available from
May 31, 2014