Distinct MRI-based functional and structural connectivity for antidepressant response prediction in major depressive disorder.

OBJECTIVE: Emerging studies have identified treatment-related connectome predictors in major depressive disorder (MDD). However, quantifying treatment-responsive patterns in structural connectivity (SC) and functional connectivity (FC) simultaneously remains underexplored. We aimed to evaluate whether spatial distributions of FC and SC associated treatment responses are shared or unique. METHODS: Diffusion tensor imaging and resting-state functional magnetic resonance imaging were collected from 210 patients with MDD at baseline. We separately developed connectome-based prediction models (CPM) to predict reduction of depressive severity after 6-week monotherapy based on structural, functional, and combined connectomes, then validated them on the external dataset. We identified the predictive SC and FC from CPM with high occurrence frequencies during the cross-validation. RESULTS: Structural connectomes (r = 0.2857, p < 0.0001), functional connectomes (r = 0.2057, p = 0.0025), and their combined CPM (r = 0.4, p < 0.0001) can significantly predict a reduction of depressive severity. We didn't find shared connectivity between predictive FC and SC. Specifically, the most predictive FC stemmed from the default mode network, while predictive SC was mainly characterized by within-network SC of fronto-limbic networks. CONCLUSIONS: These distinct patterns suggest that SC and FC capture unique connectivity concerning the antidepressant response. SIGNIFICANCE: Our findings provide comprehensive insights into the neurophysiology of antidepressants response.

Impulsivity and neural correlates of response inhibition in bipolar disorder and their unaffected relatives: A MEG study.

BACKGROUND: Response inhibition is a core cognitive impairment in bipolar disorder (BD), leading to increased impulsivity in BD. However, the relationship between the neural mechanisms underlying impaired response inhibition and impulsivity in BD is not yet clear. Individuals who are genetically predisposed to BD give a way of identifying potential endophenotypes. METHODS: A total of 97 participants, including 39 patients with BD, 22 unaffected relatives (UR) of patients with BD, and 36 healthy controls performed a Go/No-Go task during magnetoencephalography. We carried out time-frequency and connectivity analysis on MEG data. RESULTS: Decreased beta power, prolonged latency and increased peak frequency in rIFG, decreased beta power in pre-SMA and reduced rIFG-to-pre-SMA connectivity were found in BD relative to healthy controls. In the UR group, we found a decrease in the beta power of pre-SMA and prolonged latency of rIFG. Furthermore, increased motor impulsiveness in BD was related to abnormal alterations in beta oscillatory activity of rIFG and functional connectivity between rIFG and pre-SMA. CONCLUSIONS: Hypoactivity activity in rIFG and impaired dominant role of rIFG in the prefrontal control network may underlie the neuropathology of response inhibition dysfunction, resulting increased motor impulsivity in BD. Our findings point to measuring rIFG dysfunction as a potential means of identifying individuals at genetic high risk for transition to BD disease expression.

Response inhibition related neural oscillatory patterns show reliable early identification of bipolar from unipolar depression in a Go/No-Go task.

BACKGROUND: Response inhibition is a key neurocognitive factor contributing to impulsivity in mood disorders. Here, we explored the common and differential alterations of neural circuits associated with response inhibition in bipolar disorder (BD) and unipolar disorder (UD) and whether the oscillatory signatures can be used as early biomarkers in BD. METHODS: 39 patients with BD, 36 patients with UD, 29 patients initially diagnosed with UD who later underwent diagnostic conversion to BD, and 36 healthy controls performed a Go/No-Go task during MEG scanning. We carried out time-frequency and connectivity analysis on MEG data. Further, we performed machine learning using oscillatory features as input to identify bipolar from unipolar depression at the early clinical stage. RESULTS: Compared to healthy controls, patients had reduced rIFG-to-pre-SMA connectivity and delayed activity of rIFG. Among patients, lower beta power and higher peak frequency were observed in BD patients than in UD patients. These changes enabled accurate classification between BD and UD with an accuracy of approximately 80 %. CONCLUSIONS: The inefficiency of the prefrontal control network is a shared mechanism in mood disorders, while the abnormal activity of rIFG is more specific to BD. Neuronal responses during response inhibition could serve as a diagnostic biomarker for BD in early stage.

Brain-heart interaction disruption in major depressive disorder: disturbed rhythm modulation of the cardiac cycle on brain transient theta bursts.

Brain neurons support arousal and cognitive activity in the form of spectral transient bursts and cooperate with the peripheral nervous system to adapt to the surrounding environment. However, the temporal dynamics of brain-heart interactions have not been confirmed, and the mechanism of brain-heart interactions in major depressive disorder (MDD) remains unclear. This study aimed to provide direct evidence for brain-heart synchronization in temporal dynamics and clarify the mechanism of brain-heart interaction disruption in MDD. Eight-minute resting-state (closed eyes) electroencephalograph and electrocardiogram signals were acquired simultaneously. The Jaccard index (JI) was used to measure the temporal synchronization between cortical theta transient bursts and cardiac cycle activity (diastole and systole) in 90 MDD patients and 44 healthy controls (HCs) at rest. The deviation JI was used to reflect the equilibrium of brain activity between diastole and systole. The results showed that the diastole JI was higher than the systole JI in both the HC and MDD groups; compared to HCs, the deviation JI attenuated at F4, F6, FC2, and FC4 in the MDD patients. The eccentric deviation JI was negatively correlated with the despair factor scores of the HAMD, and after 4 weeks of antidepressant treatment, the eccentric deviation JI was positively correlated with the despair factor scores of the HAMD. It was concluded that brain-heart synchronization existed in the theta band in healthy individuals and that disturbed rhythm modulation of the cardiac cycle on brain transient theta bursts at right frontoparietal sites led to brain-heart interaction disruption in MDD.

The altered temporal properties of dynamic functional connectivity associated with suicide attempt in bipolar disorders.

OBJECTIVE: The suicide risk in bipolar disorder (BD) is the highest among psychiatric disorders, and the neurobiological mechanism of suicide in BD remains unclear. The study aimed to investigate the underlying relevance between the implicated abnormalities of dynamic functional connectivity (FC) and suicide attempt (SA) in BD. METHODS: We used the sliding window method to analyze the dynamic FC patterns from resting-state functional MRI data in 81 healthy controls (HC) and 114 BD patients (50 with SA and 64 with none SA). Then, the temporal properties of dynamic FC and the relationship between altered measures and clinical variables were explored. RESULTS: We found that one of the five captured brain functional states was more associated with SA. The SA patients showed significantly increased fractional window and dwell time in the suicide-related state, along with increased number of state transitions compared with none SA (NSA). In addition, the connections within subcortical network-subcortical network (SubC-SubC), default mode network-subcortical network (DMN-SubC), and attention network-subcortical network (AN-SubC) were significantly changed in SA patients relative to NSA and HC in the suicide-related state. Crucially, the above-altered measures were significantly correlated with suicide risk. CONCLUSIONS: Our findings suggested that the impaired dynamic FC within SubC-SubC, DMN-SubC, and AN-SubC were the important underlying mechanism in understanding SA for BD patients. It highlights the temporal properties of whole-brain dynamic FC could serve as the valuable biomarker for suicide risk assessment in BD.

Classification of bipolar disorders using the multilayer modularity in dynamic minimum spanning tree from resting state fMRI.

The diagnosis of bipolar disorders (BD) mainly depends on the clinical history and behavior observation, while only using clinical tools often limits the diagnosis accuracy. The study aimed to create a novel BD diagnosis framework using multilayer modularity in the dynamic minimum spanning tree (MST). We collected 45 un-medicated BD patients and 47 healthy controls (HC). The sliding window approach was utilized to construct dynamic MST via resting-state functional magnetic resonance imaging (fMRI) data. Firstly, we used three null models to explore the effectiveness of multilayer modularity in dynamic MST. Furthermore, the module allegiance exacted from dynamic MST was applied to train a classifier to discriminate BD patients. Finally, we explored the influence of the FC estimator and MST scale on the performance of the model. The findings indicated that multilayer modularity in the dynamic MST was not a random process in the human brain. And the model achieved an accuracy of 83.70% for identifying BD patients. In addition, we found the default mode network, subcortical network (SubC), and attention network played a key role in the classification. These findings suggested that the multilayer modularity in dynamic MST could highlight the difference between HC and BD patients, which opened up a new diagnostic tool for BD patients. Supplementary Information: The online version contains supplementary material available at 10.1007/s11571-022-09907-x.

Local and large-scale resting-state oscillatory dysfunctions for early antidepressant response prediction in major depressive disorder.

BACKGROUND: Magnetoencephalography (MEG) could explore and resolve brain signals with realistic temporal resolution to investigate the underlying electrophysiology of major depressive disorder (MDD) and the treatment efficacy. Here, we explore whether neuro-electrophysiological features of MDD at baseline can be used as a neural marker to predict their early antidepressant response. METHODS: Sixty-six medication-free patients with MDD and 48 healthy controls were enrolled and underwent resting-state MEG scans. Hamilton depression rating scale (HAMD-17) was assessed at both baseline and after two-week pharmacotherapy. We measured local and large-scale resting-state oscillatory dysfunctions with a data-driven model, the Fitting Oscillations & One-Over F algorithm. Then, we quantified band-limited regional power and functional connectivity between brain regions. RESULTS: After two-week follow-up, 52 patients completed the re-interviews. Thirty-one patients showed early response (ER) to pharmacotherapy and 21 patients did not. Treatment response was defined as at least 50 % reduction of severity reflected by HAMD-17. We observed decreased regional periodic power in patients with MDD comparing to controls. However, patients with ER exhibited that functional couplings across brain regions in both alpha and beta band were increased and significantly correlated with severity of depressive symptoms after treatment. Receiver operating characteristic curves (ROC) further confirmed the predictive ability of baseline large-scale functional connectivity for early antidepressant efficacy (AUC = 0.9969). LIMITATIONS: Relatively small sample size and not a double-blind design. CONCLUSIONS: The current study demonstrated the electrophysiological dysfunctions of local neural oscillatory related with depression and highlighted the identification ability of large-scale couplings biomarkers in early antidepressant response prediction.

Attenuated post-movement beta rebound reflects psychomotor alterations in major depressive disorder during a simple visuomotor task: a MEG study.

BACKGROUND: Psychomotor alterations are a common symptom in patients with major depressive disorder (MDD). The primary motor cortex (M1) plays a vital role in the mechanism of psychomotor alterations. Post-movement beta rebound (PMBR) in the sensorimotor cortex is abnormal in patients with motor abnormalities. However, the changes in M1 beta rebound in patients with MDD remain unclear. This study aimed to primarily explore the relationship between psychomotor alterations and PMBR in MDD. METHODS: One hundred thirty-two subjects were enrolled in the study, comprising 65 healthy controls (HCs) and 67 MDD patients. All participants performed a simple right-hand visuomotor task during MEG scanning. PMBR was measured in the left M1 at the source reconstruction level with the time-frequency analysis method. Retardation factor scores and neurocognitive test performance, including the Digit Symbol Substitution Test (DSST), the Making Test Part A (TMT-A), and the Verbal Fluency Test (VFT), were used to measure psychomotor functions. Pearson correlation analyses were used to assess relationships between PMBR and psychomotor alterations in MDD. RESULTS: The MDD group showed worse neurocognitive performance than the HC group in all three neurocognitive tests. The PMBR was diminished in patients with MDD compared to HCs. In a group of MDD patients, the reduced PMBR was negatively correlated with retardation factor scores. Further, there was a positive correlation between the PMBR and DSST scores. PMBR is negatively associated with the TMT-A scores. CONCLUSION: Our findings suggested that the attenuated PMBR in M1 could illustrate the psychomotor disturbance in MDD, possibly contributing to clinical psychomotor symptoms and deficits of cognitive functions.

Altered beta band spatial-temporal interactions during negative emotional processing in major depressive disorder: An MEG study.

BACKGROUND: The mood-concordance bias is a key feature of major depressive disorder (MDD), but the spatiotemporal neural activity associated with emotional processing in MDD remains unclear. Understanding the dysregulated connectivity patterns during emotional processing and their relationship with clinical symptoms could provide insights into MDD neuropathology. METHODS: We enrolled 108 MDD patients and 64 healthy controls (HCs) who performed an emotion recognition task during magnetoencephalography recording. Network-based statistics (NBS) was used to analyze whole-brain functional connectivity (FC) across different frequency ranges during distinct temporal periods. The relationship between the aberrant FC and affective symptoms was explored. RESULTS: MDD patients exhibited decreased FC strength in the beta band (13-30 Hz) compared to HCs. During the early stage of emotional processing (0-100 ms), reduced FC was observed between the left parahippocampal gyrus and the left cuneus. In the late stage (250-400 ms), aberrant FC was primarily found in the cortex-limbic-striatum systems. Moreover, the FC strength between the right fusiform gyrus and left thalamus, and between the left calcarine fissure and left inferior temporal gyrus were negatively associated with Hamilton Depression Rating Scale (HAMD) scores. LIMITATIONS: Medication information was not involved. CONCLUSION: MDD patients exhibited abnormal temporal-spatial neural interactions in the beta band, ranging from early sensory to later cognitive processing stages. These aberrant interactions involve the cortex-limbic-striatum circuit. Notably, aberrant FC in may serve as a potential biomarker for assessing depression severity.

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

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.

Hampered gamma oscillations induced by sad emotion underlying suicide attempt in major depressive disorder.

AIM: Major depressive disorder (MDD) is associated with high suicidality, especially for those with suicide attempt (SA). Although impaired oscillatory activity has been previously reported in patients with SA, little is known about precise temporal-spatial variability of its neural dynamics. To solve this, the current study probed the spectral power and network interactions underlying SA in MDD. METHODS: The present study recruited 104 subjects including 56 subjects with MDD (30 with SA and 26 without SA) and 48 healthy controls, who performed sad expressions recognition task during magnetoencephalography (MEG) recording. By investigating source-reconstructed MEG-data, brain states representing different task stages were estimated from a Hidden Markov model. Spectrum power and network connectivity were compared via Gaussian Mixture Models, and fractional occupancy (FO) of states were compared via an independent F-test. RESULTS: Brain states were corresponding to various frequencies (theta/beta/low gamma/ high gamma). In low gamma band (35-45 Hz), the early visual state exhibited increased activation and hyper inter-network connectivity between visual regions and the limbic system, while the middle fronto-parietal state exhibited attenuated activation and decreased intra-network connectivity within fronto-parietal regions in SA group. Crucially, FO values of these two states were significantly correlated with the suicide risks. CONCLUSIONS: Suicide behavior of patients with MDD was significantly associated with aberrant oscillations in low gamma band. Elevated oscillations in occipital cortices and attenuated oscillations in fronto-parietal cortices were significantly associated with SA. Manifesting sadness indulging and reckless decision-making, the hampered temporal characteristics could help explain the neural-electric basis of SA.

Gamma band VMPFC-PreCG.L connection variation after the onset of negative emotional stimuli can predict mania in depressive patients.

OBJECTIVE: Because of the similar clinical symptoms, it is difficult to distinguish unipolar disorder (UD) from bipolar disorder (BD) in the depressive episode using the available clinical features, especially for those who meet the diagnostic criteria of UD, however, experience the manic episode during the follow-up (tBD). METHODS: Magnetoencephalography recordings during a sad expression recognition task were obtained from 81 patients (27 BD, 24 tBD, 30 UD) and 26 healthy controls (HCs). Source analysis was applied to localize 64 regions of interest in the low gamma band (30-50 Hz). Regional functional connections (FCs) were constructed respectively within three time periods (early: 0-200 ms, middle: 200-400 ms, and post: 400-600 ms). The network-based statistic method was used to explore the abnormal connection patterns in tBD compared to UD and HC. BD was applied to explore whether such abnormality is still significant between every two groups of BD, tBD, UD, and HC. RESULTS: The VMPFC-PreCG.L connection was found to be a significantly different connection between tBD and UD in the early time period and between tBD and BD in the middle time period. Furthermore, the middle/early time period ratio of FC value of VMPFC-PreCG.L connection was negatively correlated with the bipolarity index in tBD. CONCLUSIONS: The VMPFC-PreCG.L connection in different time periods after the onset of sad facial stimuli may be a potential biomarker to distinguish the different states of BD. The FC ratio of VMPFC-PreCG.L connection may predict whether patients with depressive episodes subsequently develop mania.

Alpha-beta decoupling relevant to inhibition deficits leads to suicide attempt in major depressive disorder.

BACKGROUND: One devastating outcome of major depressive disorder (MDD) is high suicidality, especially for patients with suicide attempt (SA). Evidence indicated that SA may be strongly associated with inhibitory control deficits. We hypothesized that the inhibition function deficits of patient with SA might be underpinned by abnormal neuronal oscillations. METHODS: Our study recruited 111 subjects including 74 patients and 37 controls, who performed a GO/NOGO task during magnetoencephalography recording. Time-frequency-representations and phase-amplitude-coupling were measured for the brain circuits involved in the inhibitory function. Phase-slope-indexes were calculated between regions to determine the direction of power flow. RESULTS: Significant increased reaction time and decreased judgment accuracy were observed in SA group. During the perception stage of GO task (approximately 125 ms), SA group manifested elevated alpha power in ventral prefrontal cortex (VPFC) and attenuated beta power in dorsal anterior cingulate (dACC) compared with other groups (p < 0.01). In the processing stage of NOGO task (approximately 300 ms), they showed decreased beta power in VPFC and increased alpha power in dACC (p < 0.01). Alpha-beta decoupling during both tasks was observed in SA group. Furthermore, the decoupling from VPFC to dACC under NOGO tasks was significantly correlated with suicide risk level. LIMITATIONS: The number of participants was relatively small, and psychological elements were not involved in current study. CONCLUSION: Dysregulated oscillatory activities of dACC and VPFC suggested deficits in execution and inhibition functions triggering high suicide risks. The alpha-beta decoupling from VPFC to dACC could be served as a neuro-electrophysiological biomarker for identifying potential suicide risk.

Interoception Dysfunction Contributes to the Negative Emotional Bias in Major Depressive Disorder.

Background: Previous research studies have demonstrated that impaired interoception is involved in emotional information processing in major depressive disorder (MDD). Heartbeat-evoked potential (HEP) amplitudes, an index for interoception, could be manipulated by emotional faces in healthy people. Considering negative emotional bias is the core characteristic in MDD, we hypothesized that interoception dysfunction was associated with the negative emotional bias in MDD. Methods: An electroencephalogram (EEG) study under an emotional faces task was applied to explore the relationship between interoception and emotional bias. HEPs before emotional faces stimuli were used to predict the late positive potential (LPP) amplitudes and it worked as an index of emotional bias. Twenty-seven patients with MDD and 27 healthy controls (HCs) participated in this study. Source analysis gave an auxiliary description for results in sensory level. Results: Major depressive disorders (MDDs) had poor performance in the heartbeat count task (HCT) and attenuate HEP average amplitudes (455-550 ms). Compared with HCs, cluster-based permutation t-tests revealed that MDDs had attenuated LPP amplitudes (300-1,000 ms) over centroparietal regions and enhanced LPP amplitudes over frontocentral regions. Furthermore, abnormal attenuated HEPs could predict aberrant LPPs under sad face stimuli in MDDs, which could be associated with the dysfunction of the anterior cingulate cortex (ACC) and right insula. Conclusion: Mediated by ACC and insula, interoception dysfunction contributes to the negative emotional bias of MDD, highlighting the importance of interoception in the disorder.

Highly selective enrichment of surface proteins from living cells by photo-crosslinking probe enabled in-depth analysis of surfaceome.

Cell surface-exposed proteins (CSPs), termed the surfaceome, play a key role in many cellular processes. In-depth CSP analysis is significant for screening candidate biomarkers and drug targets. Highly selective enrichment of CSPs in physiological cellular environments is attractive but remains technically challenging. Here, we present a photocrosslinking-assisted cell surface protein enrichment (PCSPE) strategy. In this strategy, CSP labeling would be achieved within 2 min of UV irradiation by developing a new photocrosslinking probe (SDB) followed by one-step enrichment. The enrichment selectivity of CSPs reached 70.5%, and we identified up to 1017 CSPs from living HEK-293T cells, attributed to the high photocrosslinking reactivity and inherent impermeability of SDB, as well as the high cell viability maintained after rapid cell surface labeling to decrease the interference of intracellular proteins. Finally, this strategy was successfully applied to sorafenib-resistance cells for quantitative surfaceome analysis. All results demonstrated that our developed PCSPE method might provide a valuable toolkit for in-depth surfaceome profiling and comprehensive functional analysis.

Dynamic connectivity alterations in anterior cingulate cortex associated with suicide attempts in bipolar disorders with a current major depressive episode.

OBJECTIVE: Considering that the physiological mechanism of the anterior cingulate cortex (ACC) in suicide brain remains elusive for bipolar disorder (BD) patients. The study aims to investigate the intrinsic relevance between ACC and suicide attempts (SA) through transient functional connectivity (FC). METHODS: We enrolled 50 un-medicated BD patients with at least one SA, 67 none-suicide attempt patients (NSA) and 75 healthy controls (HCs). The sliding window approach was utilized to study the dynamic FC of ACC via resting-state functional MRI data. Subsequently, we probed into the temporal properties of dynamic FC and then estimated the relationship between dynamic characteristics and clinical variables using the Pearson correlation. RESULTS: We found six distinct FC states in all populations, with one of them being more associated with SA. Compared with NSA and HCs, the suicide-related functional state showed significantly reduced dwell time in SA patients, accompanied by a significantly increased FC strength between the right ACC and the regions within the subcortical (SubC) network. In addition, the number of transitions was significantly increased in SA patients relative to other groups. All these altered indicators were significantly correlated with the suicide risk. CONCLUSIONS: The results suggested that the dysfunction of ACC was relevant to SA from a dynamic FC perspective in BD patients. It highlights the temporal properties in dynamic FC of ACC that could be used as a putative target of suicide risk assessment for BD patients.

Spontaneous transient states of fronto-temporal and default-mode networks altered by suicide attempt in major depressive disorder.

Major depressive disorder (MDD) is associated with increased suicidality, and it's still challenging to identify suicide in clinical practice. Although suicide attempt (SA) is the most relevant precursor with multiple functional abnormalities reported from neuroimaging studies, little is known about how the spontaneous transient activated patterns organize and coordinate brain networks underlying SA. Thus, we obtained resting-state magnetoencephalography data for two MDD subgroups of 44 non-suicide patients and 34 suicide-attempted patients, together with 49 matched health-controls. For the source-space signals, Hidden Markov Model (HMM) helped to capture the sub-second dynamic activity via a hidden sequence of finite number of states. Temporal parameters and spectral activation were acquired for each state and then compared between groups. Here, HMM states characterized the spatiotemporal signatures of eight networks. The activity of suicide attempters switches more frequently into the fronto-temporal network, as the time spent occupancy of fronto-temporal state is increased and interval time is decreased compared with the non-suicide patients. Moreover, these changes are significantly correlated with Nurses' Global Assessment of Suicide Risk scores. Suicide attempters also exhibit increased state-wise activations in the theta band (4-8 Hz) in the posterior default mode network centered on posterior cingulate cortex, which can't be detected in the static spectral analysis. These alternations may disturb the time allocations of cognitive control regulations and cause inflexible decision making to SA. As the better sensitivity of dynamic study in reflecting SA diathesis than the static is validated, dynamic stability could serve as a potential neuronal marker for SA.

Attenuated alpha-gamma coupling in emotional dual pathways with right-Amygdala predicting ineffective antidepressant response.

AIMS: The diversity of treatment outcomes for major depressive disorder (MDD) remains uncertain in neuropathology. The current study aimed at exploring electrophysiological biomarkers associated with treatment response. METHODS: The present study recruited 130 subjects including 100 MDD patients and 30 healthy controls. All subjects participated in a sad expression recognition task while their magnetoencephalography data were recorded. Patients who had a reduction of at least 50% in disorder severity at endpoint (>2 weeks) were considered as responders. Within-frequency power and phase-amplitude coupling were measured for the brain regions involved in the emotional visual information processing pathways. RESULTS: The significant alpha-gamma decoupling from the right thalamus to the right amygdala in unconscious processing and from right orbital frontal cortices to the right amygdala in conscious processing was found in non-responders relative to responders and healthy controls. These kinds of dysregulation could also predict the potential treatment response. CONCLUSION: The attenuated alpha-gamma coupling in dual pathways indicated increased sensitivity to the negative emotional information and reduced moderated effect of the amygdala, which might cause insensitivity to antidepressant treatment and could be regarded as potential neural mechanisms for treatment response prediction.

Disrupted fronto-parietal network and default-mode network gamma interactions distinguishing suicidal ideation and suicide attempt in depression.

BACKGROUND: Precise suicide risk evaluation struggled in Major depressive disorder (MDD), especially for patients with only suicidal-ideation (SI) but without suicide attempt (SA). MDD patients have deficits in negative emotion processing, which is associated with the generation of SI and SA. Given the critical role of gamma oscillations in negative emotion processing, we hypothesize that the transition from SI to SA in MDD could be characterized by abnormal gamma interactions. METHODS: We recruited 162 participants containing 106 MDD patients and 56 healthy controls (HCs). Participants performed facial recognition tasks while magnetoencephalography data were recorded. Time-frequency-representation (TFR) analysis was conducted to identify the dominant spectra differences between MDD and HCs, and then source analysis was applied to localize the region of interests. Furthermore, frequency-specific functional connectivity network were constructed and a semi-supervised clustering algorithm was utilized to predict potential suicide risk. RESULTS: Gamma (50-70 Hz) power was found significantly increased in MDD, mainly residing in regions from fronto-parietal-control-network (FPN), visual-network (VN), default-mode-network (DMN) and salience-network (SN). Based on impaired gamma functional connectivity network between well-established SA group and non-SI group, semi-supervised algorithm clustered patients with only SI into two groups with different suicide risks. Moreover, Inter-network gamma connectivity between FPN and DMN significantly negatively correlated with suicide risk and not confounded by depression severity. CONCLUSION: Inter-network gamma connectivity with FPN and DMN might be the key neuropathological interactions underling the progression from SI to SA. By applying semi-supervised clustering to electrophysiological data, it is possible to predict individual suicide risk.

Differences in verbal and spatial working memory in patients with bipolar II and unipolar depression: an MSI study.

BACKGROUND: Depressive symptoms could be similarly expressed in bipolar and unipolar disorder. However, changes in cognition and brain networks might be quite distinct. We aimed to find out the difference in the neural mechanism of impaired working memory in patients with bipolar and unipolar disorder. METHOD: According to diagnostic criteria of bipolar II disorder of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) and assessments, 13 bipolar II depression (BP II), 8 unipolar depression (UD) patients and 15 healthy controls (HC) were recruited in the study. We used 2-back tasks and magnetic source imaging (MSI) to test working memory functions and get the brain reactions of the participants. RESULTS: Compared with HC, only spatial working memory tasks accuracy was significantly worse in both UD and BP II (p = 0.001). Pearson correlation showed that the stronger the FCs' strength of MFG-IPL and IPL-preSMA, the higher accuracy of SWM task within left FPN in patients with UD (r = 0.860, p = 0.006; r = 0.752, p = 0.031). However, the FC strength of IFG-IPL was negatively correlated with the accuracy of SWM task within left FPN in patients with BP II (r = - 0.591, p = 0.033). CONCLUSIONS: Our study showed that the spatial working memory of patients with whether UD or BP II was impaired. The patterns of FCs within these two groups of patients were different when performing working memory tasks.