Altered Brain Signal Variability in Patients With Generalized Anxiety Disorder

Imbalanced temporal states of cortical blood-oxygen-level-dependent signal variability during rest in episodic migraine

BACKGROUND

Migraine has been associated with functional brain changes including altered connectivity and activity both during and between headache attacks. Recent studies established that the variability of the blood-oxygen-level-dependent (BOLD) signal is an important attribute of brain activity, which has so far been understudied in migraine. In this study, we investigate how time-varying measures of BOLD variability change interictally in episodic migraine patients.

METHODS

Two independent resting state functional MRI datasets acquired on 3T (discovery cohort) and 1.5T MRI scanners (replication cohort) including 99 episodic migraine patients (n3T = 42, n1.5T=57) and 78 healthy controls (n3T = 46, n1.5T=32) were analyzed in this cross-sectional study. A framework using time-varying measures of BOLD variability was applied to derive BOLD variability states. Descriptors of BOLD variability states such as dwell time and fractional occupancy were calculated, then compared between migraine patients and healthy controls using Mann-Whitney U-tests. Spearman's rank correlation was calculated to test associations with clinical parameters.

RESULTS

Resting-state activity was characterized by states of high and low BOLD signal variability. Migraine patients in the discovery cohort spent more time in the low variability state (mean dwell time: p = 0.014, median dwell time: p = 0.022, maximum dwell time: p = 0.013, fractional occupancy: p = 0.013) and less time in the high variability state (mean dwell time: p = 0.021, median dwell time: p = 0.021, maximum dwell time: p = 0.025, fractional occupancy: p = 0.013). Higher uptime of the low variability state was associated with greater disability as measured by MIDAS scores (maximum dwell time: R = 0.45, p = 0.007; fractional occupancy: R = 0.36, p = 0.035). Similar results were observed in the replication cohort.

CONCLUSION

Episodic migraine patients spend more time in a state of low BOLD variability during rest in headache-free periods, which is associated with greater disability. BOLD variability states show potential as a replicable functional imaging marker in episodic migraine.

BOLD signal variability as potential new biomarker of functional neurological disorders

BACKGROUND

Functional neurological disorder (FND) is a common neuropsychiatric condition with established diagnostic criteria and effective treatments but for which the underlying neuropathophysiological mechanisms remain incompletely understood. Recent neuroimaging studies have revealed FND as a multi-network brain disorder, unveiling alterations across limbic, self-agency, attentional/salience, and sensorimotor networks. However, the relationship between identified brain alterations and disease progression or improvement is less explored.

METHODS

This study included resting-state functional magnetic resonance imaging (fMRI) data from 79 patients with FND and 74 age and sex-matched healthy controls (HC). First, voxel-wise BOLD signal variability was computed for each participant and the group-wise difference was calculated. Second, we investigated the potential of BOLD signal variability to serve as a prognostic biomarker for clinical outcome in 47 patients who attended a follow-up measurement after eight months.

RESULTS

The results demonstrated higher BOLD signal variability in key networks, including the somatomotor, salience, limbic, and dorsal attention networks, in patients compared to controls. Longitudinal analysis revealed an increase in BOLD signal variability in the supplementary motor area (SMA) in FND patients who had an improved clinical outcome, suggesting SMA variability as a potential state biomarker. Additionally, higher BOLD signal variability in the left insula at baseline predicted a worse clinical outcome.

CONCLUSION

This study contributes to the understanding of FND pathophysiology, emphasizing the dynamic nature of neural activity and highlighting the potential of BOLD signal variability as a valuable research tool. The insula and SMA emerge as promising regions for further investigation as prognostic and state markers.

Comparative Analysis of High-Frequency and Low-Frequency Transcutaneous Electrical Stimulation of the Right Median Nerve in the Regression of Clinical and Neurophysiological Manifestations of Generalized Anxiety Disorder

Background/Objectives: The anxiolytic effect of transcutaneous electrical nerve stimulation (TENS) is associated with the activation of endogenous inhibitory mechanisms in the central nervous system. Both low-frequency, high-amplitude TENS (LF-TENS) and high-frequency, low-amplitude TENS (HF-TENS) are capable of activating opioid, GABA, serotonin, muscarinic, and cannabinoid receptors. However, there has been no comparative analysis of the effectiveness of HF-TENS and LF-TENS in the treatment of GAD. The purpose of our research was to study the effectiveness of direct HF-TENS and LF-TENS of the right median nerve in the treatment of patients with GAD compared with sham TENS. Methods: The effectiveness of direct HF-TENS and LF-TENS of the right median nerve in the treatment of GAD was studied using Generalized Anxiety Disorder 7-item scale (GAD-7) and the Hamilton Anxiety Rating Scale (HAM-A). 40 patients underwent sham TENS, 40 patients passed HF-TENS (50 Hz-50 μs-sensory response) and 41 patients completed LF -TENS (1 Hz-200 μs-motor response) for 30 days daily. After completion of treatment, half of the patients received weekly maintenance therapy for 6 months. Electroencephalography was performed before and after treatment. Results: Our study showed that a significant reduction in the clinical symptoms of GAD as assessed by GAD-7 and HAM-A was observed after HF-TENS and LF-TENS by an average of 42.4%, and after sham stimulation only by 13.5% for at least 2 months after the end of treatment. However, LF-TENS turned out to be superior in effectiveness to HF-TENS by 51% and only on electroencephalography leads to an increase in PSD for the alpha rhythm in the occipital regions by 24% and a decrease in PSD for the beta I rhythm in the temporal and frontal regions by 28%. The prolonged effect of HF-TENS and LF-TENS was maintained without negative dynamics when TENS treatment was continued weekly throughout the entire six-month observation period. Conclusions: A prolonged anxiolytic effect of direct TENS of the right median nerve has been proven with greater regression of clinical and neurophysiological manifestations of GAD after LF-TENS compared to HF-TENS. Minimal side effects, low cost, safety, and simplicity of TENS procedures are appropriate as a home treatment modality.

Frequency-dependent alterations of global signal topography in patients with major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is associated not only with disorders in multiple brain networks but also with frequency-specific brain activities. The abnormality of spatiotemporal networks in patients with MDD remains largely unclear.

METHODS

We investigated the alterations of the global spatiotemporal network in MDD patients using a large-sample multicenter resting-state functional magnetic resonance imaging dataset. The spatiotemporal characteristics were measured by the variability of global signal (GS) and its correlation with local signals (GSCORR) at multiple frequency bands. The association between these indicators and clinical scores was further assessed.

RESULTS

The GS fluctuations were reduced in patients with MDD across the full frequency range (0-0.1852 Hz). The GSCORR was also reduced in the MDD group, especially in the relatively higher frequency range (0.0728-0.1852 Hz). Interestingly, these indicators showed positive correlations with depressive scores in the MDD group and relative negative correlations in the control group.

CONCLUSION

The GS and its spatiotemporal effects on local signals were weakened in patients with MDD, which may impair inter-regional synchronization and related functions. Patients with severe depression may use the compensatory mechanism to make up for the functional impairments.

820-nm Transcranial Near-infrared Stimulation on the Left DLPFC Relieved Anxiety: A Randomized, Double-blind, Sham-controlled Study

OBJECTIVE

Generalized anxiety disorder (GAD) is a chronic mood disease associated with abnormal brain network connections, including decreased activity in the left dorsolateral prefrontal cortex (DLPFC). Cortical excitability can be increased with 820-nm transcranial near-infrared stimulation (tNIRS), while transcranial magnetic stimulation with electroencephalography (TMS-EEG) can help evaluate time-varying brain network connectivity. A randomized, double-blind, sham-controlled trial was conducted to assess the efficacy of tNIRS on the left DLPFC and the impact on time-varying brain network connections in GAD patients.

METHODS

A total of 36 GAD patients were randomized to receive active or sham tNIRS for 2 weeks. Clinical psychological scales were assessed before, after, and at the 2-, 4-, and 8-week follow-ups. TMS-EEG was performed for 20minutes before and immediately after tNIRS treatment. The healthy controls did not receive tNIRS and only had TMS-EEG data collected once in the resting state.

RESULTS

The Hamilton Anxiety Scale (HAMA) scores of the active stimulation group decreased post-treatment compared with the sham group (P=0.021). The HAMA scores of the active stimulation group at the 2-, 4-, and 8-week follow-up assessments were lower than those before treatment (P<0.05). The time-varying EEG network pattern showed an information outflow from the left DLPFC and the left posterior temporal region after active treatment.

CONCLUSION

Herein, 820-nm tNIRS targeting the left DLPFC had significant positive effects on therapy for GAD that lasted at least 2 months. tNIRS may reverse the abnormality of time-varying brain network connections in GAD.

Resting-state neural signal variability in women with depressive disorders

Aberrant activity and connectivity in default mode (DMN), frontoparietal (FPN), and salience (SN) network regions is well-documented in depression. Recent neuroimaging research suggests that altered variability in the blood oxygen level-dependent (BOLD) signal may disrupt normal network integration and be an important novel predictor of psychopathology. However, no studies have yet determined the relationship between resting-state BOLD signal variability and depressive disorders nor applied BOLD signal variability features to the classification of depression history using machine learning (ML). We collected resting-state fMRI data for 79 women with different depression histories: no history, past history, and current depressive disorder. We tested voxelwise differences in BOLD signal variability related to depression group and severity. We also investigated whether BOLD signal variability of DMN, FPN, and SN regions could predict depression history group using a supervised random forest ML model. Results indicated that individuals with any history of depression had significantly decreased BOLD signal variability in the left and right cerebellum and right parietal cortex (pFWE <0.05). Furthermore, greater depression severity was also associated with reduced BOLD signal variability in the cerebellum. A random forest model classified participant depression history with 74% accuracy, with the ventral anterior cingulate cortex of the DMN as the most important variable in the model. These findings provide novel support for resting-state BOLD signal variability as a marker of neural dysfunction in depression and implicate decreased neural signal variability in the pathophysiology of depression.

Spatial variability of low frequency brain signal differentiates brain states

Temporal variability of the neural signal has been demonstrated to be closely related to healthy brain function. Meanwhile, the evolving brain functions are supported by dynamic relationships among brain regions. We hypothesized that the spatial variability of brain signal might provide important information about brain function. Here we used the spatial sample entropy (SSE) to investigate the spatial variability of neuroimaging signal during a steady-state presented face detection task. Lower SSE was found during task state than during resting state, associating with more repetitive functional interactions between brain regions. The standard deviation (SD) of SSE during the task was negatively related to the SD of reaction time, suggesting that the spatial pattern of neural activity is reorganized according to particular cognitive function and supporting the previous theory that greater variability is associated with better task performance. These results were replicated with reordered data, implying the reliability of SSE in measuring the spatial organization of neural activity. Overall, the present study extends the research scope of brain signal variability from the temporal dimension to the spatial dimension, improving our understanding of the spatiotemporal characteristics of brain activities and the theory of brain signal variability.

Acute Alcohol Intake Produces Widespread Decreases in Cortical Resting Signal Variability in Healthy Social Drinkers

BACKGROUND

Acute alcohol intoxication has wide-ranging neurobehavioral effects on psychomotor, attentional, inhibitory, and memory-related cognitive processes. These effects are mirrored in disruption of neural metabolism, functional activation, and functional network coherence. Metrics of intraregional neural dynamics such as regional signal variability (RSV) and brain entropy (BEN) may capture unique aspects of neural functional capacity in healthy and clinical populations; however, alcohol's influence on these metrics is unclear. The present study aimed to elucidate the influence of acute alcohol intoxication on RSV and to clarify these effects with subsequent BEN analyses.

METHODS

26 healthy adults between 25 and 45 years of age (65.4% women) participated in 2 counterbalanced sessions. In one, participants consumed a beverage containing alcohol sufficient to produce a breath alcohol concentration of 0.08 g/dl. In the other, they consumed a placebo beverage. Approximately 35 minutes after beverage consumption, participants completed a 9-minute resting-state fMRI scan. Whole-brain, voxel-wise standard deviation was used to assess RSV, which was compared between sessions. Within clusters displaying alterations in RSV, sample entropy was calculated to assess BEN.

RESULTS

Compared to the placebo, alcohol intake resulted in widespread reductions in RSV in the bilateral middle frontal, right inferior frontal, right superior frontal, bilateral posterior cingulate, bilateral middle temporal, right supramarginal gyri, and bilateral inferior parietal lobule. Within these clusters, significant reductions in BEN were found in the bilateral middle frontal and right superior frontal gyri. No effects were noted in subcortical or cerebellar areas.

CONCLUSIONS

Findings indicate that alcohol intake produces diffuse reductions in RSV among structures associated with attentional processes. Within these structures, signal complexity was also reduced in a subset of frontal regions. Neurobehavioral effects of acute alcohol consumption may be partially driven by disruption of intraregional neural dynamics among regions involved in higher-order cognitive and attentional processes.

White Matter Structural Brain Connectivity of Young Healthy Individuals With High Trait Anxiety

Background: Although functional brain connectivity in anxiety-related disorders has been studied, brain connectivity in non-clinical populations with high trait anxiety has been rarely reported. Whether structural brain connectivity changes in young healthy individuals with high trait anxiety remains unknown.

Methods: Thirty-eight young healthy individuals with high anxiety levels and 34 healthy subjects with low anxiety levels who were matched by age, gender, and educational level were recruited. Diffusion tensor images were acquired to analyze white matter connectivity. A two-sample t-test was used for group comparison of weighted networks and graph properties.

Results: Different connections were detected in fractional anisotropy- and fiber number-weighted networks. These connections were widely distributed in various regions, where relative significance was located in the inter-hemispheric frontal lobe, the frontal-limbic lobe in the right intra-hemisphere, and the frontal-temporal lobe in the ipsilateral hemisphere. However, no significant difference was found in fiber length-weighted network and in graph properties among the three networks.

Conclusions: The structural connectivity of white matter may be a vulnerability marker. Hence, healthy individuals with high trait anxiety levels are susceptible to anxiety-related psychopathology. The findings may help elucidate the pathological mechanism of anxiety and establish interventions for populations susceptible to anxiety disorders.