Frequency-dependent alterations in the amplitude of low-frequency fluctuations in social anxiety disorder

Abstract

Background

Recent studies on resting-state functional magnetic resonance imaging (fMRI) have found an abnormal temporal correlation between low-frequency oscillations (LFO) in social anxiety disorder (SAD). However, alterations in the amplitudes of these LFO remain unclear.

Methods

This study included 20 SAD patients and 20 age-, gender-, and education-matched healthy controls. Resting-state fMRI data were acquired using a gradient-echo echo-planar imaging sequence, and the amplitudes of LFO were investigated using the amplitude of low-frequency fluctuation (ALFF) approach. Two frequency bands (slow-5: 0.01–0.027 Hz; slow-4: 0.027–0.073 Hz) were analyzed.

Results

Significant differences in ALFF were observed between the two bands in widespread regions including the postcentral gyrus, precentral gyrus, medial prefrontal cortex (MPFC), orbitofrontal cortex, hippocampus, thalamus, caudate, putamen, and insula. Compared with the healthy controls, the SAD patients showed lower ALFF in the dorsolateral prefrontal cortex (DLPFC), MPFC, superior temporal gyrus, and insula but higher ALFF in the middle occipital gyrus. Furthermore, we found that the SAD patients had reduced ALFF in the MPFC in the slow-5 band.

Limitation

The small sample size may decrease the statistical power of the results.

Conclusions

SAD patients had frequency-dependent alteration in intrinsic brain activity. This finding may provide insights into the understanding of the pathophysiology of SAD.

Introduction

Social anxiety disorder (SAD) or social phobia is a common and pervasive mental disorder characterized by excessive fear and avoidance of different social situations (Stein and Stein, 2008). Epidemiological research has revealed that the lifetime prevalence of SAD ranges between 4% and 16% (Ohayon and Schatzberg, 2010). Individuals with SAD typically fear and avoid the scrutiny of others, leading to significant functional impairment. However, the pathophysiological mechanism underlying SAD remains largely unclear.

Resting-state functional magnetic resonance imaging (fMRI) has recently been suggested as an important avenue to explore the pathophysiological mechanisms underlying psychiatric and neurological diseases (Barkhof et al., 2014, Guo et al., 2011, Liu et al., 2012, Zhang et al., 2012). In contrast to conventional task-based fMRI, resting-state fMRI is easier to implement and requires minimal patient compliance; thus, using resting-state fMRI avoids potential performance confounders related to the task paradigms in clinical studies. Resting-state functional connectivity, defined as the temporal correlation of a neurophysiological index measured in different brain areas in the resting state, is a promising way to detect biomarkers in neuropsychiatric disorders (Greicius, 2008, Guo et al., 2013, Liu et al., 2014a). Using resting-state functional connectivity, scholars have found abnormal functional couplings in the default mode network (Liu et al., 2013a, Liu et al., 2014b, Zhao et al., 2007), the fronto-amygdala circuit (Hahn et al., 2011), and the dorsal attention network (Liao et al., 2010). These data indicate that SAD is associated with disrupted functional brain networks. However, these findings are based on investigations of low-frequency oscillations (LFO) from the perspective of temporal synchronization (functional connectivity) and not regional activity. Although aberrant functional connectivity between two regions is found in SAD, no conclusion can be drawn about which region is abnormal. Thus, other methods are needed to characterize regional signal dynamics in SAD.

The amplitude of low-frequency fluctuation (ALFF) of the blood-oxygenation level-dependent approach is effective and powerful for examining disease-related local brain activity (Zang et al., 2007). Previous studies have observed abnormal ALFF in neuropsychiatric diseases, such as attention-deficit/hyperactivity disorder (Zang et al., 2007), major depressive disorder (Liu et al., 2013b), Alzheimer׳s disease (He et al., 2007), and schizophrenia (Guo et al., 2014). However, these studies typically utilized a low frequency band of 0.01–0.08 Hz; thus, their findings lack frequency specificity. LFO show different properties and physiological functions at different frequency bands (Buzsáki and Draguhn, 2004, Penttonen and Buzsáki, 2003). Recently, Zuo et al. (Zuo et al., 2010) have revealed that ALFF has distinct patterns in different low frequency bands and is more robust in the basal ganglia at the frequency band of 0.027–0.073 Hz. To date, ALFF has not been used to examine regional activity in SAD at different frequency bands.

Motivated by previous work, the present study employed ALFF to examine regional spontaneous neural activity at different frequency bands in SAD patients. On the basis of the previous findings, we hypothesized that SAD patients exhibited significant frequency-dependent changes in ALFF compared with healthy controls.