Exploring potential neuroimaging biomarkers for the response to non-steroidal anti-inflammatory drugs in episodic migraine.

BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are considered first-line medications for acute migraine attacks. However, the response exhibits considerable variability among individuals. Thus, this study aimed to explore a machine learning model based on the percentage of amplitude oscillations (PerAF) and gray matter volume (GMV) to predict the response to NSAIDs in migraine treatment. METHODS: Propensity score matching was adopted to match patients having migraine with response and nonresponse to NSAIDs, ensuring consistency in clinical characteristics and migraine-related features. Multimodal magnetic resonance imaging was employed to extract PerAF and GMV, followed by feature selection using the least absolute shrinkage and selection operator regression and recursive feature elimination algorithms. Multiple predictive models were constructed and the final model with the smallest predictive residuals was chosen. The model performance was evaluated using the area under the receiver operating characteristic (ROCAUC) curve, area under the precision-recall curve (PRAUC), balance accuracy (BACC), sensitivity, F1 score, positive predictive value (PPV), and negative predictive value (NPV). External validation was performed using a public database. Then, correlation analysis was performed between the neuroimaging predictors and clinical features in migraine. RESULTS: One hundred eighteen patients with migraine (59 responders and 59 non-responders) were enrolled. Six features (PerAF of left insula and left transverse temporal gyrus; and GMV of right superior frontal gyrus, left postcentral gyrus, right postcentral gyrus, and left precuneus) were observed. The random forest model with the lowest predictive residuals was selected and model metrics (ROCAUC, PRAUC, BACC, sensitivity, F1 score, PPV, and NPV) in the training and testing groups were 0.982, 0.983, 0.927, 0.976, 0.930, 0.889, and 0.973; and 0.711, 0.648, 0.639, 0.667,0.649, 0.632, and 0.647, respectively. The model metrics of external validation were 0.631, 0.651, 0.611, 0.808, 0.656, 0.553, and 0.706. Additionally, a significant positive correlation was found between the GMV of the left precuneus and attack time in non-responders. CONCLUSIONS: Our findings suggest the potential of multimodal neuroimaging features in predicting the efficacy of NSAIDs in migraine treatment and provide novel insights into the neural mechanisms underlying migraine and its optimized treatment strategy.

Abnormal causal connectivity of anterior cingulate cortex-visual cortex circuit related to nonsteroidal anti-inflammatory drug efficacy in migraine.

The anterior cingulate cortex (ACC) and visual cortex are integral components of the neurophysiological mechanisms underlying migraine, yet the impact of altered connectivity patterns between these regions on migraine treatment remains unknown. To elucidate this issue, we investigated the abnormal causal connectivity between the ACC and visual cortex in patients with migraine without aura (MwoA), based on the resting-state functional magnetic resonance imaging data, and its predictive ability for the efficacy of nonsteroidal anti-inflammatory drugs (NSAIDs). The results revealed increased causal connectivity from the bilateral ACC to the lingual gyrus (LG) and decreased connectivity in the opposite direction in nonresponders compared with the responders. Moreover, compared with the healthy controls, nonresponders exhibited heightened causal connectivity from the ACC to the LG, right inferior occipital gyrus (IOG) and left superior occipital gyrus, while connectivity patterns from the LG and right IOG to the ACC were diminished. Based on the observed abnormal connectivity patterns, the support vector machine (SVM) models showed that the area under the receiver operator characteristic curves for the ACC to LG, LG to ACC and bidirectional models were 0.857, 0.898, and 0.939, respectively. These findings indicate that neuroimaging markers of abnormal causal connectivity in the ACC-visual cortex circuit may facilitate clinical decision-making regarding NSAIDs administration for migraine management.

Disrupted resting-state functional connectivity of the thalamus in patients with coronary heart disease.

Background: Although homeostasis of the cardiovascular system is regulated by the cerebral cortex via the autonomic nervous system, the role of abnormal brain functional connectivity (FC) networks in patients with cardiac dysfunction remains unclear. Here, we report thalamus-based FC alterations and their relationship with clinical characteristics in patients with coronary heart disease (CHD). Methods: We employed resting-state functional magnetic resonance imaging (rs-fMRI) to acquire imaging data in twenty-six patients with CHD alongside sixteen healthy controls (HCs). Next, we performed a thalamus-based FC analysis to profile abnormal FC patterns in the whole brain. Subsequently, the mean time series of the brain regions that survived in the FC analysis were used to determine correlations with clinical parameters in patients with CHD. Results: We found no statistically significant differences in demographic and clinical data between patients with CHD and HCs. Patients with CHD showed decreased FC patterns between bilateral thalami and left hemisphere, encompassing supplementary motor area, superior frontal gyrus, superior parietal gyrus, inferior parietal gyrus, middle cingulate cortex, lingual gyrus and calcarine sulcus. Conclusions: These findings not only have implications in clarifying the relationship between cerebral functional imbalance and cardiovascular system, but also provide valuable insights to guide future evaluation and management of cardiac autonomic regulation via the brain-heart axis.

Altered static functional network connectivity predicts the efficacy of non-steroidal anti-inflammatory drugs in migraineurs without aura.

Brain networks have significant implications for the understanding of migraine pathophysiology and prognosis. This study aimed to investigate whether large-scale network dysfunction in patients with migraine without aura (MwoA) could predict the efficacy of non-steroidal anti-inflammatory drugs (NSAIDs). Seventy patients with episodic MwoA and 33 healthy controls (HCs) were recruited. Patients were divided into MwoA with effective NSAIDs (M-eNSAIDs) and with ineffective NSAIDs (M-ieNSAIDs). Group-level independent component analysis and functional network connectivity (FNC) analysis were used to extract intrinsic networks and detect dysfunction among these networks. The clinical characteristics and FNC abnormalities were considered as features, and a support vector machine (SVM) model with fivefold cross-validation was applied to distinguish the subjects at an individual level. Dysfunctional connections within seven networks were observed, including default mode network (DMN), executive control network (ECN), salience network (SN), sensorimotor network (SMN), dorsal attention network (DAN), visual network (VN), and auditory network (AN). Compared with M-ieNSAIDs and HCs, patients with M-eNSAIDs displayed reduced DMN-VN and SMN-VN, and enhanced VN-AN connections. Moreover, patients with M-eNSAIDs showed increased FNC patterns within ECN, DAN, and SN, relative to HCs. Higher ECN-SN connections than HCs were revealed in patients with M-ieNSAIDs. The SVM model demonstrated that the area under the curve, sensitivity, and specificity were 0.93, 0.88, and 0.89, respectively. The widespread FNC impairment existing in the modulation of medical treatment suggested FNC disruption as a biomarker for advancing the understanding of neurophysiological mechanisms and improving the decision-making of therapeutic strategy.

Disrupted intra- and inter-network connectivity in unilateral acute tinnitus with hearing loss.

Purpose: Currently, the underlying neurophysiological mechanism of acute tinnitus is still poorly understood. This study aimed to explore differences in brain functional connectivity (FC) within and between resting-state networks (RSNs) in acute tinnitus patients with hearing loss (ATHL). Furthermore, it also evaluated the correlations between FC alterations and clinical characteristics. Methods: Two matched groups of 40 patients and 40 healthy controls (HCs) were included. Independent component analysis (ICA) was employed to obtain RSNs and FC differences were calculated within RSNs. In addition, the relationships between networks were conducted using functional network connectivity (FNC) analysis. Finally, an analysis of correlation was used to evaluate the relationship between FNC abnormalities and clinical data. Results: Results of this study found that seven major RSNs including the auditory network (AN), cerebellum network (CN), default mode network (DMN), executive control network (ECN), sensorimotor network (SMN), ventral attention network (VAN), and visual network (VN) were extracted using the group ICA in both groups. Furthermore, it was noted that the ATHL group showed aberrant FC within the CN, ECN, and VN as compared with HCs. Moreover, different patterns of network interactions were observed between groups, including the SMN-ECN, SMN-CN, ECN-AN, DMN-VAN, and DMN-CN connections. The correlations between functional disconnection and clinical characteristics in ATHL were also found in this study. Conclusion: In conclusion, this study indicated widespread alterations of intra- and inter-network connectivity in ATHL, suggesting that multiple large-scale network dysfunctions and interactions are involved in the early stage. Furthermore, our findings may provide new perspectives to understand the neuropathophysiological mechanism of acute tinnitus.

Disrupted Functional Connectivity of the Amygdala Predicts the Efficacy of Non-steroidal Anti-inflammatory Drugs in Migraineurs Without Aura.

Machine learning (ML) has been largely applied for predicting migraine classification. However, the prediction of efficacy of non-steroidal anti-inflammatory drugs (NSAIDs) in migraine is still in the early stages. This study aims to evaluate whether the combination of machine learning and amygdala-related functional features could help predict the efficacy of NSAIDs in patients with migraine without aura (MwoA). A total of 70 MwoA patients were enrolled for the study, including patients with an effective response to NSAIDs (M-eNSAIDs, n = 35) and MwoA patients with ineffective response to NSAIDs (M-ieNSAIDs, n = 35). Furthermore, 33 healthy controls (HCs) were matched for age, sex, and education level. The study participants were subjected to resting-state functional magnetic resonance imaging (fMRI) scanning. Disrupted functional connectivity (FC) patterns from amygdala-based FC analysis and clinical characteristics were considered features that could promote classification through multivariable logistic regression (MLR) and support vector machine (SVM) for predicting the efficacy of NSAIDs. Further, receiver operating characteristic (ROC) curves were drawn to evaluate the predictive ability of the models. The M-eNSAIDs group exhibited enhanced FC with ipsilateral calcarine sulcus (CAL), superior parietal gyrus (SPG), paracentral lobule (PCL), and contralateral superior frontal gyrus (SFG) in the left amygdala. However, the M-eNSAIDs group showed decreased FC with ipsilateral caudate nucleus (CAU), compared to the M-ieNSAIDs group. Moreover, the M-eNSAIDs group showed higher FC with left pre-central gyrus (PreCG) and post-central gyrus (PoCG) compared to HCs. In contrast, the M-ieNSAIDs group showed lower FC with the left anterior cingulate cortex (ACC) and right SFG. Furthermore, the MwoA patients showed increased FC with the left middle frontal gyrus (MFG) in the right amygdala compared to HCs. The disrupted left amygdala-related FC patterns exhibited significant correlations with migraine characteristics in the M-ieNSAIDs group. The MLR and SVM models discriminated clinical efficacy of NSAIDs with an area under the curve (AUC) of 0.891 and 0.896, sensitivity of 0.971 and 0.833, and specificity of 0.629 and 0.875, respectively. These findings suggest that the efficacy of NSAIDs in migraine could be predicted using ML algorithm. Furthermore, this study highlights the role of amygdala-related neural function in revealing underlying migraine-related neuroimaging mechanisms.

Disrupted Dynamic Functional Connectivity of the Visual Network in Episodic Patients with Migraine without Aura.

Background: Visual symptoms are common in patients with migraine, even in interictal periods. The purpose was to assess the association between dynamic functional connectivity (dFC) of the visual cortex and clinical characteristics in migraine without aura (MwoA) patients. Methods: We enrolled fifty-five MwoA patients as well as fifty gender- and age-matched healthy controls. Regional visual cortex alterations were investigated using regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF). Then, significant regions were selected as seeds for conducting dFC between the visual cortex and the whole brain. Results: Relative to healthy controls, MwoA patients exhibited decreased ReHo and ALFF values in the right lingual gyrus (LG) and increased ALFF values in the prefrontal cortex. The right LG showed abnormal dFC within the visual cortex and with other core brain networks. Additionally, ReHo values for the right LG were correlated with duration of disease and ALFF values of the right inferior frontal gyrus and middle frontal gyrus were correlated with headache frequency and anxiety scores, respectively. Moreover, the abnormal dFC of the right LG with bilateral cuneus was positively correlated with anxiety scores. Conclusions: The dFC abnormalities of the visual cortex may be involved in pain integration with multinetworks and associated with anxiety disorder in episodic MwoA patients.

Aberrant functional and effective connectivity of the frontostriatal network in unilateral acute tinnitus patients with hearing loss.

PURPOSE: The present study combined resting-state functional connectivity (FC) and Granger causality analysis (GCA) to explore frontostriatal network dysfunction in unilateral acute tinnitus (AT) patients with hearing loss. METHODS: The participants included 42 AT patients and 43 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging (fMRI) scans. Based on the seed regions in the frontostriatal network, FC and GCA were conducted between the AT patients and HC subjects. Correlation analyses were used to examine correlations among altered FC values, GCA values, and clinical features in AT patients. RESULTS: Compared with HCs, AT patients showed a general reduction in FC between the seed regions in the frontostriatal network and nonauditory areas, including the frontal cortices, midcingulate cortex (MCC), supramarginal gyrus, and postcentral gyrus (PoCG). Using the GCA algorithm, we detected abnormal effective connectivity (EC) in the inferior occipital gyrus, MCC, Cerebelum_Crus1, and PoCG. Furthermore, correlations between disrupted FC/EC and clinical characteristics, especially tinnitus distress-related characteristics, were found in AT patients. CONCLUSIONS: Our work demonstrated abnormal FC and EC between the frontostriatal network and several nonauditory regions in AT patients with hearing loss, suggesting that multiple large-scale network dysfunctions and interactions are involved in the perception of tinnitus. These findings not only enhance the current understanding of the frontostriatal network in tinnitus but also serve as a reminder of the importance of focusing on tinnitus at an early stage.

Aberrant Brain Functional Connectivity Strength and Effective Connectivity in Patients with Type 2 Diabetes Mellitus.

Alterations of brain functional connectivity in patients with type 2 diabetes mellitus (T2DM) have been reported by resting-state functional magnetic resonance imaging studies, but the underlying precise neuropathological mechanism remains unclear. This study is aimed at investigating the implicit alterations of functional connections in T2DM by integrating functional connectivity strength (FCS) and Granger causality analysis (GCA) and further exploring their associations with clinical characteristics. Sixty T2DM patients and thirty-three sex-, age-, and education-matched healthy controls (HC) were recruited. Global FCS analysis of resting-state functional magnetic resonance imaging was performed to explore seed regions with significant differences between the two groups; then, GCA was applied to detect directional effective connectivity (EC) between the seeds and other brain regions. Correlations of EC with clinical variables were further explored in T2DM patients. Compared with HC, T2DM patients showed lower FCS in the bilateral fusiform gyrus, right superior frontal gyrus (SFG), and right postcentral gyrus, but higher FCS in the right supplementary motor area (SMA). Moreover, altered directional EC was found between the left fusiform gyrus and bilateral lingual gyrus and right medial frontal gyrus (MFG), as well as between the right SFG and bilateral frontal regions. In addition, triglyceride, insulin, and plasma glucose levels were correlated with the abnormal EC of the left fusiform, while disease duration and cognitive function were associated with the abnormal EC of the right SFG in T2DM patients. These results suggest that T2DM patients show aberrant brain function connectivity strength and effective connectivity which is associated with the diabetes-related metabolic characteristics, disease duration, and cognitive function, providing further insights into the complex neural basis of diabetes.

Functional connectivity of the visual cortex differentiates anxiety comorbidity from episodic migraineurs without aura.

BACKGROUND: Migraine is a common neurological disease that is often accompanied by psychiatric comorbidities. However, the relationship between abnormal brain function and psychiatric comorbidities in migraine patients remains largely unclear. Therefore, the present study sought to explore the correlations between the resting-state functional deficits and psychiatric comorbidities in migraine without aura (MwoA) patients. METHODS: Resting-state functional magnetic resonance images were obtained. In addition, the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values were obtained. Thereafter regional abnormalities in MwoA patients with and without anxiety (MwoA-A and MwoA-OA) were chosen as seeds to conduct functional connectivity (FC) analysis. RESULTS: Compared to the healthy controls (HCs), the MwoA-A and MwoA-OA patients had abnormal ALFF and ReHo values in the right lingual gyrus (LG). They also had abnormal FC of the right LG with the ipsilateral superior frontal gyrus (SFG) and middle cingulate cortex (MCC). Additionally, the MwoA-A patients showed higher ReHo values in the left posterior intraparietal sulcus (pIPS) and abnormal FC of the right LG with ipsilateral pIPS and primary visual cortex, compared to the MwoA-OA patients. Moreover, the MwoA-OA patients showed an increase in the FC with the right posterior cingulate cortex/precuneus (PCC/PCUN), left middle frontal gyrus (MFG) and left inferior temporal gyrus (ITG) relative to the HCs. Furthermore, the ALFF values of the right LG positively were correlated with anxiety scores in MwoA-A patients. The abnormal LG-related FCs with the PCC/PCUN, MFG and ITG were negatively associated with the frequency of headaches in MwoA-OA patients. CONCLUSIONS: This study identified abnormal visual FC along with other core networks differentiating anxiety comorbidity from MwoA. This may therefore enhance the understanding of the neuropsychological basis of psychiatric comorbidities and provide novel insights that may help in the discovery of new marks or even treatment targets.

Aberrant activity within auditory network is associated with psychiatric comorbidities in interictal migraineurs without aura.

The present study aimed to explore associations between brain activity in the auditory cortex and clinical and psychiatric characteristics in patients with migraine without aura (MwoA) during interictal periods. Resting-state data were acquired from patients with episodic MwoA (n = 34) and healthy controls (n = 30). Independent component analysis was used to extract and calculate the resting-state auditory network. Subsequently, we analyzed the correlations between spontaneous activity in the auditory cortex and clinical and psychiatric features in interictal MwoA. Compared with healthy controls, patients with MwoA showed increased activity in the left superior temporal gyrus (STG), postcentral gyrus (PoCG) and insula. Brain activity in the left STG was positively correlated with anxiety scores, and activity in the left PoCG was negatively correlated with anxiety and depression scores. No significant differences were found in intracranial volume between the two groups. This study indicated that functional impairment and altered integration linked to the auditory cortex existed in patients with MwoA in the interictal period, suggesting that auditory-associated cortex disruption as a biomarker may be implemented for the early diagnosis and prediction of neuropsychiatric impairment in interictal MwoA patients.

Impaired effective functional connectivity of the sensorimotor network in interictal episodic migraineurs without aura.

BACKGROUND: Resting-state functional magnetic resonance imaging (Rs-fMRI) has confirmed sensorimotor network (SMN) dysfunction in migraine without aura (MwoA). However, the underlying mechanisms of SMN effective functional connectivity in MwoA remain unclear. We aimed to explore the association between clinical characteristics and effective functional connectivity in SMN, in interictal patients who have MwoA. METHODS: We used Rs-fMRI to acquire imaging data in 40 episodic patients with MwoA in the interictal phase and 34 healthy controls (HCs). Independent component analysis was used to profile the distribution of SMN and calculate the different SMN activity between the two groups. Subsequently, Granger causality analysis was used to analyze the effective functional connectivity between the SMN and other brain regions. RESULTS: Compared to the HCs, MwoA patients showed higher activity in the bilateral postcentral gyri (PoCG), but lower activity in the left midcingulate cortex (MCC). Moreover, MwoA patients showed decreased effective functional connectivity from the SMN to left middle temporal gyrus, right putamen, left insula and bilateral precuneus, but increased effective functional connectivity to the right paracentral lobule. There was also significant effective functional connectivity from the primary visual cortex, right cuneus and right putamen to the SMN. In the interictal period, there was positive correlation between the activity of the right PoCG and the frequency of headache. The disease duration was positively correlated with abnormal effective functional connectivity from the left PoCG to right precuneus. In addition, the headache impact scores were negatively correlated with abnormal effective functional connectivity from the left MCC to right paracentral lobule, as well as from the right precuneus to left PoCG. CONCLUSIONS: These differential, resting-state functional activities of the SMN in episodic MwoA may contribute to the understanding of migraine-related intra- and internetwork imbalances associated with nociceptive regulation and chronification.

Impaired functional connectivity of limbic system in migraine without aura.

Aberrant functional connectivity of brain networks has been demonstrated in migraine sufferers. Functional magnetic resonance imaging (fMRI) may illustrate altered connectivity in patients suffering from migraine without aura (MwoA). Here, we applied a seed-based approach based on limbic regions to investigate disrupted functional connectivity between spontaneous migraine attacks. Resting-state fMRI data were obtained from 28 migraine patients without aura and 23 well-matched healthy controls (HC). The functional connectivity of the limbic system was characterized using a seed-based whole-brain correlation method. The resulting functional connectivity measurements were assessed for correlations with other clinical features. Neuropsychological data revealed significantly increased connectivity between the limbic system (bilateral amygdala and right hippocampus) and left middle occipital gyrus (MOG), and a positive correlation was revealed between disease duration and connective intensity of the left amygdala and the ipsilateral MOG. There was decreased functional connectivity between the right amygdala and contralateral orbitofrontal cortex (OFC). In addition, resting-state fMRI showed that, compared to HC, patients without aura had significant functional connectivity consolidation between the bilateral hippocampus and cerebellum, and a negative correlation was detected between scores on the headache impact test (HIT) and connectivity intensity of the right hippocampus and bilateral cerebellum. There was decreased functional connectivity between the left hippocampus and three brain areas, encompassing the bilateral inferior parietal gyri (IPG) and contralateral supplementary motor area (SMA). There were no structural differences between the two groups. Our data suggest that migraine patients have disrupted limbic functional connectivity to pain-related regions of the modulatory and encoding cortices, which are associated with specific clinical characteristics. Disturbances of resting-state functional connectivity may play a key role in neuropathological features, perception and affection of migraine. The current study provides further insights into the complex scenario of migraine mechanisms. .

Impaired intrinsic functional connectivity between the thalamus and visual cortex in migraine without aura.

BACKGROUND: Resting-state functional magnetic resonance imaging (fMRI) has confirmed disrupted visual network connectivity in migraine without aura (MwoA). The thalamus plays a pivotal role in a number of pain conditions, including migraine. However, the significance of altered thalamo-visual functional connectivity (FC) in migraine remains unknown. The goal of this study was to explore thalamo-visual FC integrity in patients with MwoA and investigate its clinical significance. METHODS: Resting-state fMRI data were acquired from 33 patients with MwoA and 22 well-matched healthy controls. After identifying the visual network by independent component analysis, we compared neural activation in the visual network and thalamo-visual FC and assessed whether these changes were linked to clinical characteristics. We used voxel-based morphometry to determine whether functional differences were dependent on structural differences. RESULTS: The visual network exhibited significant differences in regions (bilateral cunei, right lingual gyrus and left calcarine sulcus) by inter-group comparison. The patients with MwoA showed significantly increased FC between the left thalami and bilateral cunei and between the right thalamus and the contralateral calcarine sulcus and right cuneus. Furthermore, the neural activation of the left calcarine sulcus was positively correlated with visual analogue scale scores (r = 0.319, p = 0.043), and enhanced FC between the left thalamus and right cuneus in migraine patients was negatively correlated with Generalized Anxiety Disorder scores (r = - 0.617, p = 0.005). CONCLUSION: Our data suggest that migraine distress is exacerbated by aberrant feedback projections to the visual network, playing a crucial role in migraine physiological mechanisms. The current study provides further insights into the complex scenario of migraine mechanisms.

Disrupted Intraregional Brain Activity and Functional Connectivity in Unilateral Acute Tinnitus Patients With Hearing Loss.

PURPOSE: The present study combined fractional amplitude of low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) to explore brain functional abnormalities in acute tinnitus patients (AT) with hearing loss. METHODS: We recruited twenty-eight AT patients and 31 healthy controls (HCs) and ran resting-state functional magnetic resonance imaging (fMRI) scans. fALFF, ReHo, and FC were conducted and compared between AT patients and HCs. After that, we calculated correlation analyses among abnormal fALFF, ReHo, FC, and clinical data in AT patients. RESULTS: Compared with HCs, AT showed increased fALFF values in the right inferior temporal gyrus (ITG). In contrast, significantly decreased ReHo values were observed in the cerebellar vermis, the right calcarine cortex, the right precuneus, the right supramarginal gyrus (SMG), and the right middle frontal gyrus (MFG). Based on the differences in the fALFF and ReHo maps, the latter of which we defined as region-of-interest (ROI) for FC analysis, the right ITG exhibited increased connectivity with the right precentral gyrus. In addition, the right MFG demonstrated decreased connectivity with both the bilateral anterior cingulate cortex (ACC) and the left precentral gyrus. CONCLUSION: By combining ReHo, fALFF, and FC analyses, our work indicated that AT with hearing loss had abnormal intraregional neural activity and disrupted connectivity in several brain regions which mainly involving the non-auditory area, and these regions are major components of default mode network (DMN), attention network, visual network, and executive control network. These findings will help us enhance the understanding of the neuroimaging mechanism in tinnitus populations. Moreover, these abnormalities remind us that we should focus on the early stages of this hearing disease.