Static and Dynamic Changes of Amplitude of Low-Frequency Fluctuations in Cervical Discogenic Pain

Association of dopamine-based genetic risk score with dynamic low-frequency fluctuations in first-episode drug-naïve schizophrenia

Alterations in dynamic intrinsic brain activity and signaling of neurotransmitters, such as dopamine, have been independently detected in schizophrenia patients. Yet, it remains unclear whether the dopamine genetic risk variants have association with brain intrinsic activity. We aimed to investigate the schizophrenia-specific dynamic amplitude of low frequency fluctuation (dALFF) altered pattern, and its association with dopamine genetic risk score in first-episode drug-naïve schizophrenia (FES). Fifty-two FES and 51 healthy controls were included. A sliding-window method based on the dALFF was adopted to estimate the dynamic alterations in intrinsic brain activity. Subjects were genotyped, and a genetic risk score (GRS), which combined the additive effects of ten risk genotypes from five dopamine-related genes, was calculated. We used the voxel-wise correlation analysis to explore the association of dopamine-GRS with dALFF. FES showed significantly increased dALFF left medial prefrontal cortex and significantly decreased dALFF in the right posterior cingulate cortex compared with healthy controls. Greater dopamine GRS in FES was associated with higher dALFF in the left middle frontal gyrus and left inferior parietal gyrus. Our findings indicate that cumulative dopamine genetic risk is associated with a known imaging phenotype for schizophrenia.

Dynamic alterations in the amplitude of low-frequency fluctuation in patients with cerebral small vessel disease

Background and purpose

Previous studies have focused on the changes of dynamic and static functional connections in cerebral small vessel disease (CSVD). However, the dynamic characteristics of local brain activity are poorly understood. The purpose of this study was to investigate the dynamic cerebral activity changes in patients with CSVD using the dynamic amplitude of low-frequency fluctuation (d-ALFF).

Methods

A total of 104 CSVD patients with cognitive impairment (CSVD-CI, n = 52) or normal cognition (CSVD-NC, n = 52) and 63 matched healthy controls (HCs) were included in this study. Every participant underwent magnetic resonance imaging scans and a battery of neuropsychological examinations. The dynamics of spontaneous brain activity were assessed using dynamic changes in the amplitude of low-frequency fluctuation (ALFF) with the sliding-window method. We used voxel-wise one-way analysis of variance (ANOVA) to compare dynamic ALFF variability among the three groups. Post-hoc t-tests were used to evaluate differences between each group pair. Finally, the brain regions with d-ALFF values with differences between CSVD subgroups were taken as regions of interest (ROI), and the d-ALFF values corresponding to the ROI were extracted for partial correlation analysis with memory.

Results

(1) There was no significant difference in age (p = 0.120), sex (p = 0.673) and education (p = 0.067) among CSVD-CI, CSVD-NC and HC groups, but there were significant differences Prevalence of hypertension and diabetes mellitus among the three groups (p < 10-3). There were significant differences in scores of several neuropsychological scales among the three groups (p < 10-3). (2) ANOVA and post-hoc t-test showed that there were dynamic abnormalities of spontaneous activity in several brain regions in three groups, mainly located in bilateral parahippocampal gyrus and bilateral hippocampus, bilateral insular and frontal lobes, and the static activity abnormalities in bilateral parahippocampal gyrus and bilateral hippocampal regions were observed at the same time, suggesting that bilateral parahippocampal gyrus and bilateral hippocampus may be the key brain regions for cognitive impairment caused by CSVD. (3) The correlation showed that d-ALFF in the bilateral insular was slightly correlated with the Mini-Mental State Examination (MMSE) score and disease progression rate. The d-ALFF value of the left postcentral gyrus was negatively correlated with the Clock Drawing Test (CDT) score (r = -0.416, p = 0.004), and the d-ALFF value of the right postcentral gyrus was negatively correlated with the Rey's Auditory Verbal Learning Test (RAVLT) word recognition (r = -0.320, p = 0.028).

Conclusion

There is a wide range of dynamic abnormalities of spontaneous brain activity in patients with CSVD, in which the abnormalities of this activity in specific brain regions are related to memory and execution or emotion.

Altered static and dynamic intrinsic brain activity in unilateral sudden sensorineural hearing loss

Introduction

Sudden sensorineural hearing loss (SSHL) is a critical otologic emergency characterized by a rapid decline of at least 30 dB across three consecutive frequencies in the pure-tone audiogram within a 72-hour period. This audiological condition has been associated with alterations in brain cortical and subcortical structures, as well as changes in brain functional activities involving multiple networks. However, the extent of cerebral intrinsic brain activity disruption in SSHL remains poorly understood. The aimed of this study is to investigate intrinsic brain activity alterations in SSHL using static and dynamic fractional amplitude of low-frequency fluctuation (fALFF) analysis.

Methods

Resting-state functional magnetic resonance imaging (fMRI) data were acquired from a cohort of SSHL patients (unilateral, n = 102) and healthy controls (n = 73). Static and dynamic fALFF methods were employed to analyze the acquired fMRI data, enabling a comprehensive examination of intrinsic brain activity changes in SSHL.

Results

Our analysis revealed significant differences in static fALFF patterns between SSHL patients and healthy controls. SSHL patients exhibited decreased fALFF in the left fusiform gyrus, left precentral gyrus, and right inferior frontal gyrus, alongside increased fALFF in the left inferior frontal gyrus, left superior frontal gyrus, and right middle temporal gyrus. Additionally, dynamic fALFF analysis demonstrated elevated fALFF in the right superior frontal gyrus and right middle frontal gyrus among SSHL patients. Intriguingly, we observed a positive correlation between static fALFF in the left fusiform gyrus and the duration of hearing loss, shedding light on potential temporal dynamics associated with intrinsic brain activity changes.

Discussion

The observed disruptions in intrinsic brain activity and temporal dynamics among SSHL patients provide valuable insights into the functional reorganization and potential compensatory mechanisms linked to hearing loss. These findings underscore the importance of understanding the underlying neural alterations in SSHL, which could pave the way for the development of targeted interventions and rehabilitation strategies aimed at optimizing SSHL management.

Changes in dynamic and static brain fluctuation distinguish minimal hepatic encephalopathy and cirrhosis patients and predict the severity of liver damage

Purpose

Minimal hepatic encephalopathy (MHE) is characterized by mild neuropsychological and neurophysiological alterations that are not detectable by routine clinical examination. Abnormal brain activity (in terms of the amplitude of low-frequency fluctuation (ALFF) has been observed in MHE patients. However, little is known concerning temporal dynamics of intrinsic brain activity. The present study aimed to investigate the abnormal dynamics of brain activity (dynamic ALFF; dALFF) and static measures [static ALFF; (sALFF)] in MHE patients and to strive for a reliable imaging neuromarkers for distinguishing MHE patients from cirrhosis patients. In addition, the present study also investigated whether intrinsic brain activity predicted the severity of liver damage.

Methods

Thirty-four cirrhosis patients with MHE, 28 cirrhosis patients without MHE, and 33 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state magnetic resonance imaging (rs-fMRI). dALFF was estimated by combining the ALFF method with the sliding-window method, in which temporal variability was quantized over the whole-scan timepoints and then compared among the three groups. Additionally, dALFF, sALFF and both two features were utilized as classification features in a support vector machine (SVM) to distinguish MHE patients from cirrhosis patients. The severity of liver damage was reflected by the Child–Pugh score. dALFF, sALFF and both two features were used to predict Child–Pugh scores in MHE patients using a general linear model.

Results

Compared with HCs, MHE patients showed significantly increased dALFF in the left inferior occipital gyrus, right middle occipital gyrus, and right insula; increased dALFF was also observed in the right posterior lobe of the cerebellum (CPL) and right thalamus. Compared with HCs, noMHE patients exhibited decreased dALFF in the right precuneus. In contrast, compared with noMHE patients, MHE patients showed increased dALFF in the right precuneus, right superior frontal gyrus, and right superior occipital gyrus. Furthermore, the increased dALFF values in the left precuneus were positively associated with poor digit-symbol test (DST) scores (r = 0.356, p = 0.038); however, dALFF in the right inferior temporal gyrus (ITG) was negatively associated with the number connection test–A (NCT-A) scores (r = -0.784, p = 0.000). A significant positive correlation was found between dALFF in the left inferior occipital gyrus (IOG) and high blood ammonia levels (r = 0.424, p = 0.012). Notably, dALFF values yielded a higher classification accuracy than sALFF values in distinguishing MHE patients from cirrhosis patients. Importantly, the dALFF values predicted the Child–Pugh score (r = 0.140, p = 0.030), whereas sALFF values did not in the current dataset. Combining two features had high accuracy in classification in distinguishing MHE patients from cirrhotic patients and yielded prediction in the severity of liver damage.

Conclusion

These findings suggest that combining dALFF and sALFF features is a useful neuromarkers for distinguishing MHE patients from cirrhosis patients and highlights the important role of dALFF feature in predicting the severity of liver damage in MHE.

Regional homogeneity alterations in multifrequency bands in patients with extracranial multi-organ tuberculosis: a prospective cross-sectional study

Background

This study aimed to clarify the spontaneous neural activity in the conventional frequency band (0.01-0.08 Hz) and 2 subfrequency bands (slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz) in patients with extracranial multi-organ tuberculosis (EMTB) through regional homogeneity (ReHo) analysis.

Methods

In all, 32 patients with EMTB and 31 healthy controls (HCs) were assessed by resting-state functional magnetic resonance imaging (rs-fMRI) scans to clarify the abnormal spontaneous neural activity through ReHo analysis in the conventional frequency band and 2 subfrequency bands.

Results

Compared with the HCs, the patients with EMTB exhibited decreased ReHo in the left postcentral gyrus [t=-4.79; 95% confidence interval (CI): -0.79 to -0.31] and the left superior cerebellum (t=-4.45; 95% CI: -0.54 to -0.21) in the conventional band. Conversely, increased ReHo was observed in the right middle occipital gyrus (t=3.94; 95% CI: 0.18-0.53). In the slow-4 band, patients with EMTB only exhibited decreased ReHo in the superior cerebellum (t=-4.69; 95% CI: -0.54 to -0.22); meanwhile, in the slow-5 band, these patients exhibited decreased ReHo in the right postcentral gyrus (t=-3.76; 95% CI: -0.74 to -0.21) and the left superior cerebellum (t=-5.20, 95% CI: -0.72 to -0.31). After Bonferroni correction, no significant correlation was observed between the ReHo values in clusters showing significant between-group differences and cognitive test scores.

Conclusions

ReHo showed abnormal synchronous neural activity in patients with EMTB in different frequency bands, which provides a novel understanding of the pathological mechanism of EMTB.

The Predictive Value of Dynamic Intrinsic Local Metrics in Transient Ischemic Attack

Background

Transient ischemic attack (TIA) is known as “small stroke.” However, the diagnosis of TIA is currently difficult due to the transient symptoms. Therefore, objective and reliable biomarkers are urgently needed in clinical practice.

Objective

The purpose of this study was to investigate whether dynamic alterations in resting-state local metrics could differentiate patients with TIA from healthy controls (HCs) using the support-vector machine (SVM) classification method.

Methods

By analyzing resting-state functional MRI (rs-fMRI) data from 48 patients with and 41 demographically matched HCs, we compared the group differences in three dynamic local metrics: dynamic amplitude of low-frequency fluctuation (d-ALFF), dynamic fractional amplitude of low-frequency fluctuation (d-fALFF), and dynamic regional homogeneity (d-ReHo). Furthermore, we selected the observed alterations in three dynamic local metrics as classification features to distinguish patients with TIA from HCs through SVM classifier.

Results

We found that TIA was associated with disruptions in dynamic local intrinsic brain activities. Compared with HCs, the patients with TIA exhibited increased d-fALFF, d-fALFF, and d-ReHo in vermis, right calcarine, right middle temporal gyrus, opercular part of right inferior frontal gyrus, left calcarine, left occipital, and left temporal and cerebellum. These alternations in the dynamic local metrics exhibited an accuracy of 80.90%, sensitivity of 77.08%, specificity of 85.37%, precision of 86.05%, and area under curve of 0.8501 for distinguishing the patients from HCs.

Conclusion

Our findings may provide important evidence for understanding the neuropathology underlying TIA and strong support for the hypothesis that these local metrics have potential value in clinical diagnosis.

Abnormal dynamic brain activity and functional connectivity of primary motor cortex in blepharospasm

BACKGROUND

Accumulating evidence indicates that dynamic amplitude of low-frequency fluctuations (dALFF) or functional connectivity (dFC) can provide complementary information, distinct from static ALFF (sALFF) or FC (sFC), in detecting brain functional abnormalities in brain diseases. We aimed to examine whether dALFF and dFC can offer valuable information for the detection of functional brain abnormalities in patients with blepharospasm.

METHODS

We collected resting-state functional magnetic resonance imaging data from 46 patients each of blepharospasm, hemifacial spasm (HFS), and healthy controls (HCs). We examined inter-group differences in sALFF and dALFF to investigate abnormal regional brain activity in patients with blepharospasm. Based on the dALFF results, we conducted seed-based sFC and dFC analyses to identify static and dynamic connectivity changes in brain networks centered on areas showing abnormal temporal variability of local brain activity in patients with blepharospasm.

RESULTS

Compared with HCs, patients with blepharospasm displayed different brain functional change patterns characterized by increased sALFF in the left primary motor cortex (PMC) but increased dALFF variance in the right PMC. However, differences were not found between patients with HFS and HCs. Additionally, patients with blepharospasm exhibited decreased dFC strength, but no change in sFC, between right PMC and ipsilateral cerebellum compared with HCs; these findings were replicated when patients with blepharospasm were compared to those with HFS.

CONCLUSIONS

Our findings highlight that dALFF and dFC are complementary to sALFF and sFC and can provide valuable information for detecting brain functional abnormalities in blepharospasm. Blepharospasm may be a network disorder involving the cortico-ponto-cerebello-thalamo-cortical circuit.

Abnormal static and dynamic brain function in patients with temporomandibular disorders: a resting-state functional magnetic resonance imaging study

OBJECTIVES

This study was conducted to investigate the brain function of patients with temporomandibular disorders (TMD) by combining the static and dynamic amplitudes of low-frequency fluctuation (ALFF).

METHODS

Thirty patients with TMD and 20 healthy controls were enrolled. All the participants completed their questionnaires, received clinical examinations, and underwent resting-state functional magnetic resonance imaging scanning. We compared the static and dynamic ALFF between the patients and healthy controls by conducting a two-sample t-test with AlphaSim correction for multiple comparisons. The correlation between the static and dynamic ALFF of the brain regions with significant group differences and clinical measurements was analyzed.

RESULTS

The patients with TMD showed increased static and dynamic ALFF in the posterior cingulate cortex compared with that of the controls (whole-brain level, uncorrected P=0.005; region of interest level with AlphaSim correction, voxel level P<0.005, cluster level P<0.05). The dynamic ALFF of the posterior cingulate cortex was negatively correlated with bilateral condylar vertical discrepancies. The dynamic ALFF in the medial orbitofrontal cortex of the patients with TMD was greater than that of the controls (whole-brain level AlphaSim correction, voxel level P<0.005, cluster level P<0.05).

CONCLUSIONS

Our findings revealed that the resting-state brain function of the posterior cingulate cortex and the medial orbitofrontal cortex of patient with TMD increased. These changes probably indicated the potential central mechanisms underlying the increased self-relevant thoughts, negative emotion, and abnormal emotion regulation in TMD.

Abnormal Intrinsic Functional Interactions Within Pain Network in Cervical Discogenic Pain

Cervical discogenic pain (CDP) is mainly induced by cervical disc degeneration. However, how CDP modulates the functional interactions within the pain network remains unclear. In the current study, we studied the changed resting-state functional connectivities of pain network with 40 CDP patients and 40 age-, gender-matched healthy controls. We first defined the pain network with the seeds of the posterior insula (PI). Then, whole brain and seed-to-target functional connectivity analyses were performed to identify the differences in functional connectivity between CDP and healthy controls. Finally, correlation analyses were applied to reveal the associations between functional connectivities and clinical measures. Whole-brain functional connectivity analyses of PI identified increased functional connectivity between PI and thalamus (THA) and decreased functional connectivity between PI and middle cingulate cortex (MCC) in CDP patients. Functional connectivity analyses within the pain network further revealed increased functional connectivities between bilateral PI and bilateral THA, and decreased functional connectivities between left PI and MCC, between left postcentral gyrus (PoCG) and MCC in CDP patients. Moreover, we found that the functional connectivities between right PI and left THA, between left PoCG and MCC were negatively and positively correlated with the visual analog scale, respectively. Our findings provide direct evidence of how CDP modulates the pain network, which may facilitate understanding of the neural basis of CDP.

Altered Dynamic Amplitude of Low-Frequency Fluctuations in Patients With Migraine Without Aura

Migraine is a chronic and idiopathic disorder leading to cognitive and affective problems. However, the neural basis of migraine without aura is still unclear. In this study, dynamic amplitude of low-frequency fluctuations (dALFF) analyses were performed in 21 patients with migraine without aura and 21 gender- and age-matched healthy controls to identify the voxel-level abnormal functional dynamics. Significantly decreased dALFF in the bilateral anterior insula, bilateral lateral orbitofrontal cortex, bilateral medial prefrontal cortex, bilateral anterior cingulate cortex, and left middle frontal cortex were found in patients with migraine without aura. The dALFF values in the anterior cingulate cortex were negatively correlated with pain intensity, i.e., visual analog scale. Finally, support vector machine was used to classify patients with migraine without aura from healthy controls and achieved an accuracy of 83.33%, sensitivity of 90.48%, and specificity of 76.19%. Our findings provide the evidence that migraine influences the brain functional activity dynamics and reveal the neural basis for migraine, which could facilitate understanding the neuropathology of migraine and future treatment.