Dynamic changes of amplitude of low‐frequency fluctuations in patients with generalized anxiety disorder

Abstract

Previous neuroimaging studies have mainly focused on alterations of static and dynamic functional connectivity in patients with generalized anxiety disorder (GAD). However, the characteristics of local brain activity over time in GAD are poorly understood. This study aimed to investigate the abnormal time‐varying local brain activity of GAD by using the amplitude of low‐frequency fluctuation (ALFF) method combined with sliding‐window approach. Group comparison results showed that compared with healthy controls (HCs), patients with GAD exhibited increased dynamic ALFF (dALFF) variability in widespread regions, including the bilateral dorsomedial prefrontal cortex, hippocampus, thalamus, striatum; and left orbital frontal gyrus, inferior parietal lobule, temporal pole, inferior temporal gyrus, and fusiform gyrus. The abnormal dALFF could be used to distinguish between patients with GAD and HCs. Increased dALFF variability values in the striatum were positively correlated with GAD symptom severity. These findings suggest that GAD patients are associated with abnormal temporal variability of local brain activity in regions implicated in executive, emotional, and social function. This study provides insight into the brain dysfunction of GAD from the perspective of dynamic local brain activity, highlighting the important role of dALFF variability in understanding neurophysiological mechanisms and potentially informing the diagnosis of GAD.

Improved Resting-State Functional Dynamics in Post-stroke Depressive Patients After Shugan Jieyu Capsule Treatment

“…Functional connectivity (FC) is characterized by the synchronization of activities in functional brain regions and is often used to reflect direct or indirect connections between brain regions (Marrelec et al, 2016). Furthermore, the dynamic ALFF (dALFF) based on time-variant brain activity emphasize the abnormal functional activity in psychological and cognitive disorders (Cui et al, 2019). Dynamic functional connectivity (dFC), an emerging functional connectivity technology, can be used to measure the strength of functional connectivity and the variability of spatial dynamic organization (Cohen, 2018).…”

Relationship Between Basic Properties of BOLD Fluctuations and Calculated Metrics of Complexity in the Human Connectome Project

“…In line with this hypothesis, areas like the posterior cingulate cortex (PCC) that exhibit high resting state metabolism in PET scans also have higher ALFF and fALFF than other cortical areas (Zou et al, 2008). Furthermore, these measures of low frequency power can discriminate between patient groups and healthy controls or between rest and task performance (Zang et al, 2007;Cui et al, 2019;Li et al, 2019;Zhou et al, 2019).…”

Dynamic Alterations of Amplitude of Low-Frequency Fluctuations in Patients With Drug-Naïve First-Episode Early Onset Schizophrenia

“…Previous research has suggested that the window length is a critical parameter to acquire dynamic spontaneous brain activity ( Li et al, 2018 ; Cui et al, 2019 ), in which too short a window length might not allow for sufficient estimation of dynamic changes, and too long a window length may not be sufficiently sensitive to detect dynamic activity ( Zhang et al, 2019a ). Therefore, to calculate the dALFF of each participant, we applied 50 TR (125 s) as a moderate sliding window length and 5 TR (10 s) as the step size ( Li et al, 2018 ; Cui et al, 2019 ; Yao et al, 2020 ). The post-processed 202 volume of each participant was divided into 31 windows, and the ALFF map was computed within each window.…”

“…According to previous findings, ALFF is an established approach to characterizing spontaneous neural activity and effectively delineating the potential pathophysiological mechanisms of EOS. However, most of the aforementioned studies rely on the hypothesis that neural activity remains stationary during fMRI scanning ( Cui et al, 2019 ; Chen et al, 2020 ), while, in fact, human neural activity is dynamic and correlated to ongoing rhythmic activity over time ( Hutchison et al, 2013 ; Calhoun et al, 2014 ; Li et al, 2018 ). Recently, abnormal dynamic spontaneous neural activity has been identified in adult schizophrenia ( Shen et al, 2014 ; Hare et al, 2017 ; Zhang et al, 2019b ), but the nature of the contribution of abnormal dynamic neural activity to the onset of EOS is poorly understood.…”