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Qing Lu

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13 papers
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13

YNIMG Journal 2026 Journal Article

Aberrant thalamic GABA–network coupling as a neural signature of insomnia severity in major depressive disorder

  • Yingying Huang
  • Yi Xia
  • Yiwen Wang
  • Yishan Du
  • Junling Sheng
  • Tingting Xiong
  • Lingling Hua
  • Wenyue Gong

Insomnia is one of the most common and debilitating symptoms of major depressive disorder (MDD), with its severity closely associated with both the onset and course of the illness. However, its underlying neurobiological mechanisms remain poorly understood. This study employed a multimodal neuroimaging approach, combining magnetoencephalography and magnetic resonance spectroscopy, to separately examine the associations between insomnia severity and both thalamic functional connectivity (FC) with large-scale brain networks in the gamma frequency band, and thalamic gamma-aminobutyric acid (GABA) concentrations. Hierarchical regression analyses revealed a group-specific neurobiological mechanism, marked by opposing associations of insomnia severity with thalamic FC with large-scale brain networks and GABA⁺ levels between patients with MDD and healthy controls (HCs). Furthermore, the intrinsic coupling between thalamic GABA⁺ and thalamic-default mode network FC was reversed between groups, as evidenced by a negative association in HCs that trended toward a positive association in MDD patients. These findings indicate that insomnia in MDD constitutes a distinct pathological state, in which elevated thalamic GABA⁺ levels may represent a compensatory yet maladaptive response that disrupts thalamic GABA-network coupling. Our results provide a novel neurobiological framework for MDD-related insomnia and highlight the potential of therapies aimed at restoring thalamic neurochemical-functional coordination.

YNIMG Journal 2025 Journal Article

Association of spatiotemporal interaction of gamma oscillations with heart rate variability during response inhibition processing in patients with major depressive disorder: An MEG study

  • Junling Sheng
  • Yi Xia
  • Lingling Hua
  • Hongliang Zhou
  • Qian Liao
  • Shui Tian
  • Yishan Du
  • Xiaoqin Wang

BACKGROUND: Impairment in response inhibition function is highly prevalent in patients with major depressive disorder (MDD), yet the spatiotemporal neural activity underlying response inhibition and its relationship with the autonomic nervous system (ANS) remains unclear. METHODS: 35 MDD participants and 35 healthy controls (HC) were included with magnetoencephalography (MEG) and electrocardiogram (ECG) data collecting during a go/no-go task. Heart rate variability (HRV) indices were calculated from the ECG data. Differences in functional connectivity (FC) of gamma oscillations (60-90 Hz) between 0-200 ms, 200-400 ms, and 400-600 ms in the two groups after no-go stimuli were analyzed, and the correlation between FC and HRV indices was examined. RESULTS: The MDD group exhibited poorer task performance and lower HRV indices than the HC group. During the 200-400 ms period, compared to the HC group, the MDD group exhibited decreased FC between the left inferior frontal gyrus (opercular part) and right temporal pole (middle temporal gyrus) (t = 3.62, p < 0.05), and increased FC between the right superior frontal gyrus (orbital part) and right superior occipital gyrus (t = 3.68, p < 0.05). Additionally, a significant positive correlation was found between FC of the left inferior frontal gyrus (opercular part) and right middle temporal gyrus (temporal pole) and the HRV index RMSSD in the MDD group (r = 0.491, p < 0.05). CONCLUSION: Abnormal spatiotemporal interactions in gamma oscillations related to response inhibition are observed in MDD patients and abnormal gamma oscillations showed task-dependent covariation with ANS indices, suggesting their potential interplay in MDD pathophysiology.

YNIMG Journal 2025 Journal Article

Motor-related neural oscillations in mood disorders

  • Yi Xia
  • Xiaoqin Wang
  • Shujia Hu
  • Shuangyu Cai
  • Tingting Xiong
  • Junling Sheng
  • Rui Yan
  • Zhijian Yao

Motor symptoms are common in mood disorders and are related to poor treatment responses, unfavourable illness prognosis, and increased suicidal ideation. However, neural mechanisms of impaired motor function remain unclear. Neural oscillatory activity in the theta and beta band within the cortico-cortical motor circuit is believed to reflect aspects of motor control. Here, we explored motor function and motor-related neural oscillations in individuals with mood disorders. 144 patients with bipolar disorder (BD), 136 patients with major depressive disorder (MDD), and 125 control subjects completed a Go/No-Go task during magnetoencephalography recording. Moreover, 21 MDD patients and 16 BD patients underwent the second MEG scanning during follow-up. Trail Making Test A and B were used to measure motor performance. Oscillation-derived measures such as inter trial phase coherence, event-related spectral perturbation, phase locking value and phase amplitude coupling (PAC) within the supplementary motor area (SMA) and primary motor cortex (M1) were compared across the groups. Patients with BD exhibited poorer motor performance compared to those with MDD. BD patients showed reduced theta event-related synchronization and ITPC, along with enhanced beta event-related desynchronization. Conversely, a reduction in theta-beta PAC within SMA was observed in the MDD group. These divergent patterns underscore distinct neurophysiological alterations associated with motor function impairments across the two mood disorder groups, highlighting the complexity and specificity of oscillatory and connectivity changes linked to their pathophysiology. Future research should investigate the potential value of neural oscillations in predicting clinical and functional outcomes to guide the development of neurobiologically informed interventions.

YNIMG Journal 2025 Journal Article

The modulatory role of GABA in the triple network and its impact on anhedonia and cognitive function in depression

  • Yiwen Wang
  • Mengzhi Zhang
  • Azi Shen
  • Yingying Huang
  • Wenyue Gong
  • Qinghua Zhai
  • Rui Yan
  • Qing Lu

BACKGROUND: GABAergic dysfunction contributes to Major Depressive Disorder (MDD). This study examines excitatory/inhibitory (E/I) imbalance, specifically GABA deficits in the left dorsolateral prefrontal cortex (DLPFC), and their link to anhedonia and cognitive impairment in MDD. It also investigates alterations in the coupling between local E/I activity and functional connectivity (FC) within the triple network. METHODS: We included 41 medication-naïve MDD patients and 33 healthy controls (HCs). Participants underwent Snaith-Hamilton Pleasure Scale (SHAPS) and cognitive assessments. GABA+/Cr, Glx, and GABA+/Glx ratios were measured in the left DLPFC using proton magnetic resonance spectroscopy (¹H-MRS). Resting-state functional magnetic resonance imaging (fMRI) data were analyzed via independent component analysis (ICA), identifying five major brain networks. RESULTS: Female MDD patients exhibited reduced GABA+/Cr in the left DLPFC (p = 0.021). GABA+/Cr negatively correlated with SHAPS scores (r = -0.33, p = 0.04) and Trail Making Test Part B (TMT-B) completion times (r = -0.36, p = 0.03) in MDD patients. HCs showed positive correlations between GABA+/Cr and FC within the LECN (r = 0.41, p = 0.02) and between the LECN-dDMN (r = 0.39, p = 0.03) and LECN-pSN (r = 0.46, p = 0.01); these correlations were absent in the MDD group. CONCLUSIONS: Female patients with MDD exhibit a specific reduction in GABA levels in the left DLPFC. Furthermore, these lower GABA levels are associated with increased anhedonia and poorer executive function. Critically, the neurochemical coupling between GABA and large-scale brain networks is also disrupted in MDD.

YNICL Journal 2024 Journal Article

Aberrant high-beta band functional connectivity during reward processing in melancholic major depressive disorder: An MEG study

  • Qiaoyang Zhang
  • Yishan Du
  • Ciqing Bao
  • Lingling Hua
  • Rui Yan
  • Zhongpeng Dai
  • Yi Xia
  • Haowen Zou

OBJECTIVE: To identify the spatial-temporal pattern variation of whole-brain functional connectivity (FC) during reward processing in melancholic major depressive disorder (MDD) patients, and to determine the clinical correlates of connectomic differences. METHODS: 61 MDD patients and 32 healthy controls were enrolled into the study. During magnetoencephalography (MEG) scanning, all participants completed the facial emotion recognition task. The MDD patients were further divided into two groups: melancholic (n = 31) and non-melancholic (n = 30), based on the Mini International Neuropsychiatric Interview (M.I.N.I.) assessment. Melancholic symptoms were examined by using the 6-item melancholia subscale from the Hamilton Depression Rating Scale (HAM-D6). The whole-brain orthogonalized power envelope connections in the high-beta band (20-35 Hz) were constructed in each period after the happy emotional stimuli (0-200 ms, 100-300 ms, 200-400 ms, 300-500 ms, and 400-600 ms). Then, the network-based statistic (NBS) was used to determine the specific abnormal connection patterns in melancholic MDD patients. RESULTS: The NBS identified a sub-network difference at the mid-late period (300-500 ms) in response to happy faces among the three groups (corrected P = 0.035). Then, the post hoc and correlation analyses found five FCs were decreased in melancholic MDD patients and were related to HAM-D6 score, including FCs of left fusiform gyrus-right orbital inferior frontal gyrus (r = -0.52, P < 0.001), left fusiform gyrus-left amygdala (r = -0.26, P = 0.049), left posterior cingulate gyrus-right precuneus (r = -0.32, P = 0.025), left precuneus-right precuneus (r = -0.27, P = 0.049), and left precuneus-left inferior occipital gyrus (r = -0.32, P = 0.025). CONCLUSION: In response to happy faces, melancholic MDD patients demonstrated a disrupted functional connective pattern (20-35 Hz, 300-500 ms), which involved brain regions in visual information processing and the limbic system. The aberrant functional connective pattern in reward processing might be a biomarker of melancholic MDD.

YNICL Journal 2024 Journal Article

Neural responses to decision-making in suicide attempters with youth major depressive disorder

  • Ciqing Bao
  • Qiaoyang Zhang
  • Chen He
  • Haowen Zou
  • Yi Xia
  • Rui Yan
  • Lingling Hua
  • Xiaoqin Wang

An improved understanding of the factors associated with suicidal attempts in youth suffering from depression is crucial for the identification and prevention of future suicide risk. However, there is limited understanding of how neural activity is modified during the process of decision-making. Our study aimed to investigate the neural responses in suicide attempters with major depressive disorder (MDD) during decision-making. Electroencephalography (EEG) was recorded from 79 individuals aged 16-25 with MDD, including 39 with past suicide attempts (SA group) and 40 without (NSA group), as well as from 40 age- and sex- matched healthy controls (HCs) during the Iowa Gambling Task (IGT). All participants completed diagnostic interviews, self-report questionnaires. Our study examined feedback processing by measuring the feedback-related negativity (FRN), ΔFN (FRN-loss minus FRN-gain), and the P300 as electrophysiological indicators of feedback evaluation. The SA group showed poorest IGT performance. SA group and NSA group, compared with HC group, exhibited specific deficits in decision-making (i.e., exhibited smaller (i.e., blunted) ΔFN). Post hoc analysis found that the SA group was the least sensitive to gains and the most sensitive to losses. In addition, we also found that the larger the value of ΔFN, the better the decision-making ability and the lower the impulsivity. Our study highlights the link between suicide attempts and impaired decision-making in individuals with major depressive disorder. These findings constitute an important step in gaining a better understanding of the specific reward-related abnormalities that could contribute to the young MDD patients with suicide attempts.

YNICL Journal 2023 Journal Article

Spontaneous beta power, motor-related beta power and cortical thickness in major depressive disorder with psychomotor disturbance

  • Yi Xia
  • Hao Sun
  • Lingling Hua
  • Zhongpeng Dai
  • Xiaoqin Wang
  • Hao Tang
  • Yinglin Han
  • Yishan Du

INTRODUCTION: The psychomotor disturbance is a common symptom in patients with major depressive disorder (MDD). The neurological mechanisms of psychomotor disturbance are intricate, involving alterations in the structure and function of motor-related regions. However, the relationship among changes in the spontaneous activity, motor-related activity, local cortical thickness, and psychomotor function remains unclear. METHOD: A total of 140 patients with MDD and 68 healthy controls performed a simple right-hand visuomotor task during magnetoencephalography (MEG) scanning. All patients were divided into two groups according to the presence of psychomotor slowing. Spontaneous beta power, movement-related beta desynchronization (MRBD), absolute beta power during movement and cortical characteristics in the bilateral primary motor cortex were compared using general linear models with the group as a fixed effect and age as a covariate. Finally, the moderated mediation model was tested to examine the relationship between brain metrics with group differences and psychomotor performance. RESULTS: The patients with psychomotor slowing showed higher spontaneous beta power, movement-related beta desynchronization and absolute beta power during movement than patients without psychomotor slowing. Compared with the other two groups, significant decreases were found in cortical thickness of the left primary motor cortex in patients with psychomotor slowing. Our moderated mediation model showed that the increased spontaneous beta power indirectly affected impaired psychomotor performance by abnormal MRBD, and the indirect effects were moderated by cortical thickness. CONCLUSION: These results suggest that patients with MDD have aberrant cortical beta activity at rest and during movement, combined with abnormal cortical thickness, contributing to the psychomotor disturbance observed in this patient population.

YNICL Journal 2023 Journal Article

The relationship between disrupted anhedonia-related circuitry and suicidal ideation in major depressive disorder: A network-based analysis

  • Xiaoqin Wang
  • Yi Xia
  • Rui Yan
  • Huan Wang
  • Hao Sun
  • Yinghong Huang
  • Lingling Hua
  • Hao Tang

BACKGROUND: Several epidemiological studies and psychological models have suggested that major depressive disorder (MDD) with anhedonia is associated with suicidal ideation (SI). However, little is known about whether the functional network pattern and intrinsic topologically disrupted in patients with anhedonia are related to SI. METHODS: The resting-fMRI by applying network-based statistic (NBS) and graph-theory analyses was estimated in 273 patients with MDD (144 high anhedonia [HA], 129 low anhedonia [LA]) and 150 healthy controls. In addition, we quantified the SI scores of each patient. Finally, the mediation analysis assessed whether anhedonia symptoms could mediate the relationship between anhedonia-related network metrics and SI. RESULT: The NBS analysis demonstrated that individuals with HA have a single abnormally increased functional connectivity component in a frontal-limbic circuit (termed the "anhedonia-related network", including the frontal cortex, striatum, anterior cingulate cortex and amygdala). The graph-theory analysis demonstrated that the anhedonia-related network showed a significantly disrupted topological organization (lower gamma and lambda), which the small-world property trend randomized. Furthermore, the anhedonia symptoms could mediate the relationship between the anhedonia-related network metrics (the mean functional connectivity values, the area under the curves values of gamma and nodal local efficiency in nucleus accumbens) and SI. CONCLUSIONS: We found that disruption of the reward-related network in MDD leads to SI through anhedonia symptoms. These findings show the abnormal topological construction of functional brain network organization in anhedonia, shedding light on the neurological processes underlying SI in MDD patients with anhedonia symptoms.

YNIMG Journal 2021 Journal Article

Dynamic analysis on simultaneous iEEG-MEG data via hidden Markov model

  • Siqi Zhang
  • Chunyan Cao
  • Andrew Quinn
  • Umesh Vivekananda
  • Shikun Zhan
  • Wei Liu
  • Bomin Sun
  • Mark Woolrich

BACKGROUND: Intracranial electroencephalography (iEEG) recordings are used for clinical evaluation prior to surgical resection of the focus of epileptic seizures and also provide a window into normal brain function. A major difficulty with interpreting iEEG results at the group level is inconsistent placement of electrodes between subjects making it difficult to select contacts that correspond to the same functional areas. Recent work using time delay embedded hidden Markov model (HMM) applied to magnetoencephalography (MEG) resting data revealed a distinct set of brain states with each state engaging a specific set of cortical regions. Here we use a rare group dataset with simultaneously acquired resting iEEG and MEG to test whether there is correspondence between HMM states and iEEG power changes that would allow classifying iEEG contacts into functional clusters. METHODS: Simultaneous MEG-iEEG recordings were performed at rest on 11 patients with epilepsy whose intracranial electrodes were implanted for pre-surgical evaluation. Pre-processed MEG sensor data was projected to source space. Time delay embedded HMM was then applied to MEG time series. At the same time, iEEG time series were analyzed with time-frequency decomposition to obtain spectral power changes with time. To relate MEG and iEEG results, correlations were computed between HMM probability time courses of state activation and iEEG power time course from the mid contact pair for each electrode in equally spaced frequency bins and presented as correlation spectra for the respective states and iEEG channels. Association of iEEG electrodes with HMM states based on significant correlations was compared to that based on the distance to peaks in subject-specific state topographies. RESULTS: test for independence). Despite the potentially atypical functional anatomy and physiological abnormalities related to epilepsy, HMM model estimated from the patient group was very similar to that estimated from healthy subjects. CONCLUSION: Epilepsy does not preclude HMM analysis of interictal data. The resulting group functional states are highly similar to those reported for healthy controls. Power changes recorded with iEEG correlate with HMM state time courses in the alpha-theta band and the presence of this correlation can be related to the spatial location of electrode contacts close to the individual peaks of the corresponding state topographies. Thus, the hypothesized relation between iEEG contacts and HMM states exists and HMM could be further explored as a method for identifying comparable iEEG channels across subjects for the purposes of group analysis.

YNICL Journal 2019 Journal Article

An enriched granger causal model allowing variable static anatomical constraints

  • Kun Bi
  • Guoping Luo
  • Shui Tian
  • Siqi Zhang
  • Xiaoxue Liu
  • Qiang Wang
  • Qing Lu
  • Zhijian Yao

The anatomical connectivity constrains but does not fully determine functional connectivity, especially when one explores into the dynamics over the course of a trial. Therefore, an enriched granger causal model (GCM) integrated with anatomical prior information is proposed in this study, to describe the dynamic effective connectivity to distinguish the depression and explore the pathogenesis of depression. In the proposed frame, the anatomical information was converted via an optimized transformation model, which was then integrated into the normal GCM by variational bayesian model. Magnetoencephalography (MEG) signals and diffusion tensor imaging (DTI) of 24 depressive patients and 24 matched controls were utilized for performance comparison. Together with the sliding windowed MEG signals under sad facial stimuli, the enriched GCM was applied to calculate the regional-pair dynamic effective connectivity, which were repeatedly sifted via feature selection and fed into different classifiers. From the aspects of model errors and recognition accuracy rates, results supported the superiority of the enriched GCM with anatomical priors over the normal GCM. For the effective connectivity with anatomical priors, the best subject discrimination accuracy of SVM was 85.42% (the sensitivity was 87.50% and the specificity was 83.33%). Furthermore, discriminative feature analysis suggested that the enriched GCM that detect the variable anatomical constraint on function could better detect more stringent and less dynamic brain function in depression. The proposed approach is valuable in dynamic functional dysfunction exploration in depression and could be useful for depression recognition.

EAAI Journal 2012 Journal Article

Multivariable self-organizing fuzzy logic control using dynamic performance index and linguistic compensators

  • Qing Lu
  • Mahdi Mahfouf

As far as fuzzy logic based multivariable control systems are concerned, it is not always an easy task to express control strategies in the form of related multi-situations to multi-actions control rules. Decoupled control is one possible and attractive strategy to simplify this problem. However, the control performance of the decoupled controller relies greatly on ‘a prior’ knowledge of the system dynamics to build suitable compensators. This paper aims at introducing a new model-independent decoupled control architecture with the ability of on-line learning, which ensures a fast tracking performance. In this architecture, the dominating controller is developed using a new model-free Self-Organizing Fuzzy Logic Control (SOFLC) architecture whereby the Performance Index table is ‘dynamic’, of a free structure, and starting from no knowledge. Furthermore, a switching mode scheme, with a compensating action triggered by the interaction between the channels, is proposed to improve the tracking performance of the closed-loop system. A series of simulations are carried out on a two-input and two-output biomedical process, with the conclusion that the proposed control mechanism has the ability to deal with varying system dynamics and noise and is tolerant to the choice of the compensator gains effectively.