The potential of electroencephalography coherence to predict the outcome of repetitive transcranial magnetic stimulation in insomnia disorder.

BACKGROUND: It is unknown whether repetitive Transcranial Magnetic Stimulation (rTMS) could improve sleep quality by modulating electroencephalography (EEG) connectivity of insomnia disorder (ID) patients. Great heterogeneity had been found in the clinical outcomes of rTMS for ID. The study aimed to investigate the potential mechanisms of rTMS therapy for ID and develop models to predict clinical outcomes. METHODS: In Study 1, 50 ID patients were randomly divided into active and sham groups, and subjected to 20 sessions of treatment with 1 Hz rTMS over the left dorsolateral prefrontal cortex. EEG during awake, Polysomnography, and clinical assessment were collected and analyzed before and after rTMS. In Study 2, 120 ID patients were subjected to active rTMS stimulation and were then separated into optimal and sub-optimal groups due to the median of Pittsburgh Sleep Quality Index reduction rate. Machine learning models were developed based on baseline EEG coherence to predict rTMS treatment effects. RESULTS: In Study 1, decreased EEG coherence in theta and alpha bands were observed after rTMS treatment, and changes in theta band (F7-O1) coherence were correlated with changes in sleep efficiency. In Study 2, baseline EEG coherence in theta, alpha, and beta bands showed the potential to predict the treatment effects of rTMS for ID. CONCLUSION: rTMS improved sleep quality of ID patients by modulating the abnormal EEG coherence. Baseline EEG coherence between certain channels in theta, alpha, and beta bands could act as potential biomarkers to predict the therapeutic effects.

Brain recovery of the NAc fibers and prediction of craving changes in person with heroin addiction: A longitudinal study.

BACKGROUND: Progress have been made in brain function recovery after long-term abstinence in person with heroin addiction (PHA). However, less is known about whether the nucleus accumbens (NAc) white matter pathways can recover in PHA by prolonged abstinence. METHODS: Forty-two PHA and Thirty-nine age- and gender- matched healthy controls (HCs) were recruited. Two MRI scans were obtained at baseline (PHA1) and 8-month follow-up (PHA2). We employed tractography atlas-based analysis (TABS) method to investigate fractional anisotropy (FA) changes in NAc fiber tracts (i.e., Insula-NAc, ventral tegmental area (VTA)-NAc, medial prefrontal cortex (MPFC)-NAc) in PHA. A partial least square regression (PLSR) analysis was carried to explore whether FA of NAc fiber tracts can predict longitudinal craving changes. RESULTS: Relative to HCs, lower FA was found in the right Insula-NAc and VTA-NAc fiber tracts in PHA1, and PHA2 showed increased FA values in these tracts compared with PHA1. Furthermore, changes of FA of NAc fiber tracts can predict longitudinal craving changes (r = 0.51). Additionally, craving changes can also be predicted from FA changes in the left Insula-NAc (r = 0.601) and VTA-NAc (r = 0.384) fiber alone. CONCLUSIONS: Results indicated that the right Insula-NAc and VTA-NAc fiber tracts are potential biomarkers for brain recovery. Prediction of craving changes highlighted the utility of structural markers to inform clinical decision-making of treatment for PHA.

Reconfigurations of Dynamic Functional Network Connectivity in Large-scale Brain Network after Prolonged Abstinence in Heroin Users.

BACKGROUND: Brain recovery phenomenon after long-term abstinence had been reported in substance use disorders. Yet, few longitudinal studies have been conducted to observe the abnormal dynamic functional connectivity (dFNC) of large-scale brain networks and recovery after prolonged abstinence in heroin users. OBJECTIVE: The current study will explore the brain network dynamic connection reconfigurations after prolonged abstinence in heroin users (HUs). METHODS: The 10-month longitudinal design was carried out for 40 HUs. The 40 healthy controls (HCs) were also enrolled. Group independent component analysis (GICA) and dFNC analysis were employed to detect the different dFNC patterns of addiction-related ICNs between HUs and HCs. The temporal properties and the graph-theoretical properties were calculated. Whether the abnormalities would be reconfigured in HUs after prolonged abstinence was then investigated. RESULTS: Based on eight functional networks extracted from GICA, four states were identified by the dFNC analysis. Lower mean dwell time and fraction rate in state4 were found for HUs, which were increased toward HCs after prolonged abstinence. In this state, HUs at baseline showed higher dFNC of RECN-aSN, aSN- aSN and dDMN-pSN, which decreased after protracted abstinence. A similar recovery phenomenon was found for the global efficiency and path length in abstinence HUs. Mean while, the abnormal dFNC strength was correlated with craving both at baseline and after abstinence. CONCLUSION: Our longitudinal study observed the large-scale brain network reconfiguration from the dynamic perspective in HUs after prolonged abstinence and improved the understanding of the neurobiology of prolonged abstinence in HUs.

Abnormal hippocampal substructure volume in insomnia disorder.

To date, our understanding of the role of abnormal hippocampal volume in imaging studies of insomnia disorders (ID) has remained in apparent contradiction. Given that hippocampal function can be mapped to anatomically defined substructures, the hippocampal substructure volume can be examined in detail at present. In this study, we examined the volumes of hippocampal substructures between IDs and healthy controls (HC) to accurately find hippocampal markers of ID. First, we used the automated hippocampal substructure module in FreeSurfer6.0 to inspect T1-weighted magnetic resonance images between 22 IDs and 30 HC. Then, 12 hippocampal substructures were computed. Volumetric assessment was performed at the hippocampal substructure level between groups. Our study revealed significant reduced volume of the bilateral fimbria in IDs compared with HC (p < 0.05/12, Bonferroni corrected), although there was no difference in the total volume of hippocampus. In addition, the correlation analysis showed that the total hippocampal volume of the left hemisphere was negatively correlated with Pittsburgh Sleep Quality Index (PSQI) scores. With regard to hippocampal substructure results, negative correlations were detected between bilateral fimbria volume and clinical variables (i.e., PSQI, SDS, and SAS) in all subjects. Taken together, we revealed marked differences in the volume of the hippocampal substructure between IDs and HC, which provided a more accurate structural imaging marker for the pathological of ID.

Reduced midbrain functional connectivity and recovery in abstinent heroin users.

Dopaminergic pathways from the midbrain to striatum as well as cortex are involved in addiction. However, the alternations of these pathways and whether the recoveries of aberrant circuits would be detected after prolonged abstinence in heroin users are rarely known. The resting-state functional connectivity (RSFC) patterns of midbrain (i.e., the ventral tegmental area (VTA) and substantia nigra (SN)) were compared between 40 abstinent heroin users with opioid use disorder (HUs) and 35 healthy controls (HCs). Then, we tested the functional recovery hypothesis by both cross-sectional and longitudinal design. For cross-sectional design, HUs were separated into short-term abstainers (STs) (3-15 days) and long-term abstainers (LTs) (>15 days). With regard to longitudinal design, 22 subjects among HUs were followed up for 10 months. A sandwich estimator method was used to analyze the differences between baseline HUs and follow-up HUs. HUs showed lower RSFC between midbrain and several cortical areas (medial orbitofrontal cortex (mOFC) and anterior cingulate cortex) compared with HCs. Besides, lower RSFC of VTA-right nucleus accumbens circuit as well as right SN- caudate circuit was also found in HUs. The enhanced RSFC value of VTA-left mOFC circuit was observed in LTs, compared with STs. Additionally, longitudinal design also revealed the increased RSFC values of the midbrain with frontal cortex after 10 months prolonged abstinence. We revealed abnormal functional organizations of midbrain-striato and midbrain-cortical circuits in HUs. More importantly, partially recovery of these dysfunctions can be found after long-term abstinence.

Disrupted frontostriatal connectivity in primary insomnia: a DTI study.

Dysfunction of the sleep-wake transition is considered to be associated with the pathology of patients with primary insomnia (PI). Previous animal study had reported that brain circuits between the striatum and cortex can regulate sleep-wake transitions. So far, few studies have systematically explored the structural connectivity of the striatum-centered circuits and their potential roles in patients with PI. In this study, we chosen the striatum as the seed and 10 priori target regions as masks to assess the structural connectivity by using seed-based classification with a diffusion tensor imaging (DTI) probabilistic tractography method. Track strengths of the striatum-centered circuits were compared between 22 patients with PI (41.27 ± 9.21 years) and 30 healthy controls (HC) (35.2 ± 8.14 years). Pittsburgh Sleep Quality Index (PSQI) was used to measure the sleep quality in all participants. Lower track strengths (left striatum- anterior cingulate cortex (ACC), left striatum- dorsal anterior cingulate cortex (dACC), left striatum-Hippocampus, and right striatum-Hippocampus) were observed in patients with PI compared to HC. Additionally, the lower track strengths of brain circuits mentioned above were negatively correlated with PSQI. Taken together, our findings revealed the lower tract strength of frontostriatal circuits in patients with PI and HC, which provided the implications of the system-level structural connections of frontostriatal circuits in the pathology of PI. We suggested that the track strengths of the frontostriatal circuits calculated from DTI can be the potential neuroimaging biomarkers of the sleep quality in patients with PI.

Reduced thalamic resting-state functional connectivity and impaired cognition in acute abstinent heroin users.

As a critical component of cortico-striato-thalamo-cortical loop in addiction, our understanding of the thalamus in impaired cognition of heroin users (HU) has been limited. Due to the complex thalamic connection with cortical and subcortical regions, thalamus was divided into prefrontal (PFC), occipital (OC), premotor, primary motor, sensory, temporal, and posterior parietal association subregions according to white matter tractography. We adopted seven subregions of bilateral thalamus as regions of interest to systematically study the implications of distinct thalamic nuclei in acute abstinent HU. The volume and resting-state functional connectivity (RSFC) differences of the thalamus were investigated between age-, gender-, and alcohol-matched 37 HU and 33 healthy controls (HCs). Trail making test-A (TMT-A) was adopted to assess cognitive function deficits, which were then correlated with neuroimaging findings. Although no significant different volumes were found, HU group showed decreased RSFC between left PFC_thalamus and middle temporal gyrus as well as between left OC_thalamus and inferior frontal gyrus and supplementary motor area relative to HCs. Meanwhile, the higher TMT-A scores in HU were negatively correlated with PFC_thalamic RSFC with inferior temporal gyrus, fusiform, and precuneus. Craving scores were negatively correlated with OC_thalamic RSFC with accumbens, hippocampus, and insula. Opiate Withdrawal Scale scores were negatively correlated with left PFC/OC_thalamic RSFC with orbitofrontal cortex and medial PFC. We indicated two thalamus subregions separately involvement in cognitive control and craving to reveal the implications of thalamic subnucleus in pathology of acute abstinent HU.

Identification of internet gaming disorder individuals based on ventral tegmental area resting-state functional connectivity.

Objective neuroimaging markers are imminently in need for more accurate clinical diagnosis of Internet gaming disorder (IGD). Recent neuroimaging evidence suggested that IGD is associated with abnormalities in the mesolimbic dopamine (DA) system. As the key nodes of the DA pathways, ventral tegmental area (VTA) and substantia nigra (SN) and their connected brain regions may serve as potential markers to identify IGD. Therefore, we aimed to develop optimal classifiers to identify IGD individuals by using VTA and bilateral SN resting-state functional connectivity (RSFC) patterns. A dataset including 146 adolescents (66 IGDs and 80 healthy controls (HCs)) was used to build classification models and another independent dataset including 28 subjects (14 IGDs and 14 HCs) was employed to validate the generalization ability of the models. Multi-voxel pattern analysis (MVPA) with linear support vector machine (SVM) was used to select the features. Our results demonstrated that the VTA RSFC circuits successfully identified IGD individuals (mean accuracy: 86.1%, mean sensitivity: 84.5%, mean specificity: 86.6%, the mean area under the receiver operating characteristic curve: 0.91). Furthermore, the independent generalization ability of the VTA RSFC classifier model was also satisfied (accuracy = 78.5%, sensitivity = 71.4%, specificity = 85.8%). The VTA connectivity circuits that were selected as distinguishing features were mainly included bilateral thalamus, right hippocampus, right pallidum, right temporal pole superior gyrus and bilateral temporal superior gyrus. These findings demonstrated that the potential of the resting-state neuroimaging features of VTA RSFC as objective biomarkers for the IGD clinical diagnosis in the future.

Dysfunction of the NAc-mPFC circuit in insomnia disorder.

BACKGROUND: Insomnia disorder (ID) is a prevalent sleep disorder, which seriously affects people's daily life and was found to be associated with increased frequency of sleep stage shifts. Previous findings had revealed the critical role of the nucleus accumbens (NAc) in sleep-wake transition. However, the neuroimaging studies of the NAc in patients with ID have been rare. We hypothesized that structural and functional abnormalities of the NAc would be implicated in ID. METHODS: Twenty-six ID patients and 36 matched healthy controls (HC) were included in the current study. The volumes and corresponding resting-state functional connectivity (RSFC) of the bilateral NAc were compared between the two groups. The abnormal RSFC in ID were then correlated with Pittsburgh Sleep Quality Index (PSQI). RESULTS: Compared with HC, ID patients showed significantly increased volume of right NAc. Several brain regions showed increased RSFC with the NAc in ID patients, such as medial prefrontal cortex (mPFC), anterior cingulate cortex (ACC), caudate and putamen. Meanwhile, the occipital gyrus and temporal gyrus showed decreased RSFC with the NAc. Additionally, the increased RSFC strength between bilateral NAc and left mPFC was significant correlated with PSQI scores in ID patients. CONCLUSION: Dysfunctions of the NAc-mPFC circuit were found in ID patients, which were associated with sleep quality measured by PSQI. The two patterns of increase and decrease of RSFC in ID patients observed in our study may reflect the state of hyperarousal and potential impairment of cognitive function in the patients, respectively. It is hoped that our study focusing on NAc-mPFC circuits could provide new insights for the neural mechanisms of ID and potential novel therapeutic targets for treatment of ID patients.