Sex differences in anhedonia in bipolar depression: a resting-state fMRI study.

Previous studies about anhedonia symptoms in bipolar depression (BD) ignored the unique role of gender on brain function. This study aims to explore the regional brain neuroimaging features of BD with anhedonia and the sex differences in these patients. The resting-fMRI by applying fractional amplitude of low-frequency fluctuation (fALFF) method was estimated in 263 patients with BD (174 high anhedonia [HA], 89 low anhedonia [LA]) and 213 healthy controls. The effects of two different factors in patients with BD were analyzed using a 3 (group: HA, LA, HC) × 2 (sex: male, female) ANOVA. The fALFF values were higher in the HA group than in the LA group in the right medial cingulate gyrus and supplementary motor area. For the sex-by-group interaction, the fALFF values of the right hippocampus, left medial occipital gyrus, right insula, and bilateral medial cingulate gyrus were significantly higher in HA males than in LA males but not females. These results suggested that the pattern of high activation could be a marker of anhedonia symptoms in BD males, and the sex differences should be considered in future studies of BD with anhedonia symptoms.

Structure-function coupling and hierarchy-specific antidepressant response in major depressive disorder.

BACKGROUND: Extensive research has explored altered structural and functional networks in major depressive disorder (MDD). However, studies examining the relationships between structure and function yielded heterogeneous and inconclusive results. Recent work has suggested that the structure-function relationship is not uniform throughout the brain but varies across different levels of functional hierarchy. This study aims to investigate changes in structure-function couplings (SFC) and their relevance to antidepressant response in MDD from a functional hierarchical perspective. METHODS: We compared regional SFC between individuals with MDD (n = 258) and healthy controls (HC, n = 99) using resting-state functional magnetic resonance imaging and diffusion tensor imaging. We also compared antidepressant non-responders (n = 55) and responders (n = 68, defined by a reduction in depressive severity of >50%). To evaluate variations in altered and response-associated SFC across the functional hierarchy, we ranked significantly different regions by their principal gradient values and assessed patterns of increase or decrease along the gradient axis. The principal gradient value, calculated from 219 healthy individuals in the Human Connectome Project, represents a region's position along the principal gradient axis. RESULTS: Compared to HC, MDD patients exhibited increased SFC in unimodal regions (lower principal gradient) and decreased SFC in transmodal regions (higher principal gradient) (p < 0.001). Responders primarily had higher SFC in unimodal regions and lower SFC in attentional networks (median principal gradient) (p < 0.001). CONCLUSIONS: Our findings reveal opposing SFC alterations in low-level unimodal and high-level transmodal networks, underscoring spatial variability in MDD pathology. Moreover, hierarchy-specific antidepressant effects provide valuable insights into predicting treatment outcomes.

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.

Abnormal stability of spontaneous neuronal activity as a predictor of diagnosis conversion from major depressive disorder to bipolar disorder.

OBJECTIVE: Bipolar disorder (BD) is often misdiagnosed as major depressive disorder (MDD) in the early stage, which may lead to inappropriate treatment. This study aimed to characterize the alterations of spontaneous neuronal activity in patients with depressive episodes whose diagnosis transferred from MDD to BD. METHODS: 532 patients with MDD and 132 healthy controls (HCs) were recruited over 10 years. During the follow-up period, 75 participants with MDD transferred to BD (tBD), and 157 participants remained with the diagnosis of unipolar depression (UD). After excluding participants with poor image quality and excessive head movement, 68 participants with the diagnosis of tBD, 150 participants with the diagnosis of UD, and 130 HCs were finally included in the analysis. The dynamic amplitude of low-frequency fluctuations (dALFF) of spontaneous neuronal activity was evaluated in tBD, UD and HC using functional magnetic resonance imaging at study inclusion. Receiver operating characteristic (ROC) analysis was performed to evaluate sensitivity and specificity of the conversion prediction from MDD to BD based on dALFF. RESULTS: Compared to HC, tBD exhibited elevated dALFF at left premotor cortex (PMC_L), right lateral temporal cortex (LTC_R) and right early auditory cortex (EAC_R), and UD showed reduced dALFF at PMC_L, left paracentral lobule (PCL_L), bilateral medial prefrontal cortex (mPFC), right orbital frontal cortex (OFC_R), right dorsolateral prefrontal cortex (DLPFC_R), right posterior cingulate cortex (PCC_R) and elevated dALFF at LTC_R. Furthermore, tBD exhibited elevated dALFF at PMC_L, PCL_L, bilateral mPFC, bilateral OFC, DLPFC_R, PCC_R and LTC_R than UD. In addition, ROC analysis based on dALFF in differential areas obtained an area under the curve (AUC) of 72.7%. CONCLUSIONS: The study demonstrated the temporal dynamic abnormalities of tBD and UD in the critical regions of the somatomotor network (SMN), default mode network (DMN), and central executive network (CEN). The differential abnormal patterns of temporal dynamics between the two diseases have the potential to predict the diagnosis transition from MDD to BD.

Based on white matter microstructure to early identify bipolar disorder from patients with depressive episode.

OBJECTIVE: Because of similar clinical manifestations, bipolar disorder (BD) patients are often misdiagnosed as major depressive disorder (MDD). This study aimed to compare the difference between depressed patients later converting to BD and unipolar depression (UD) according to diffusion tensor imaging (DTI). METHOD: Patients with MDD (562 participants) in depressive episode states and healthy controls (HCs) (145 participants) were recruited over 10 years. Demographic and magnetic resonance imaging (MRI) data were collected at the time of recruitment. All patients with MDD were followed up for 5 years and classified into the transfer to BD (tBD) group (83 participants) and UD group (160 participants) according to the follow-up results. DTI and functional magnetic resonance imaging at baseline were compared. RESULTS: Common abnormalities were found in both tBD and UD groups, including left superior cerebellar peduncle (SCP.L), right anterior limb of the internal capsule (ALIC.R), right superior fronto-occipital fasciculus (SFOF.R), and right inferior fronto-occipital fasciculus (IFOF.R). The tBD showed more extensive abnormalities than the UD in the body of corpus callosum, fornix, left superior corona radiata, left posterior corona radiata, left superior longitudinal fasciculus, and left superior fronto-occipital fasciculus. CONCLUSION: The study demonstrated the common and distinct abnormalities of tBD and UD when compared to HC. The tBD group showed more extensive disruptions of white matter integrity, which could be a potential biomarker for the early identification of BD.

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.

Capturing the Individual Deviations From Normative Models of Brain Structure for Depression Diagnosis and Treatment.

BACKGROUND: The high heterogeneity of depression prevents us from obtaining reproducible and definite anatomical maps of brain structural changes associated with the disorder, which limits the individualized diagnosis and treatment of patients. In this study, we investigated the clinical issues related to depression according to individual deviations from normative ranges of gray matter volume. METHODS: We enrolled 1092 participants, including 187 patients with depression and 905 healthy control participants. Structural magnetic resonance imaging data of healthy control participants from the Human Connectome Project (n = 510) and REST-meta-MDD Project (n = 229) were used to establish a normative model across the life span in adults 18 to 65 years old for each brain region. Deviations from the normative range for 187 patients and 166 healthy control participants recruited from two local hospitals were captured as normative probability maps, which were used to identify the disease risk and treatment-related latent factors. RESULTS: In contrast to case-control results, our normative modeling approach revealed highly individualized patterns of anatomic abnormalities in depressed patients (less than 11% extreme deviation overlapping for any regions). Based on our classification framework, models trained with individual normative probability maps (area under the receiver operating characteristic curve range, 0.7146-0.7836) showed better performance than models trained with original gray matter volume values (area under the receiver operating characteristic curve range, 0.6800-0.7036), which was verified in an independent external test set. Furthermore, different latent brain structural factors in relation to antidepressant treatment were revealed by a Bayesian model based on normative probability maps, suggesting distinct treatment response and inclination. CONCLUSIONS: Capturing personalized deviations from a normative range could help in understanding the heterogeneous neurobiology of depression and thus guide clinical diagnosis and treatment of depression.

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.

Links among genetic variants and hierarchical brain structural and functional networks for antidepressant treatment: A multivariate study.

BACKGROUND: Antidepressant treatment effects are strongly heritable and have substantial effects on brain function and structure, but the underlying mechanisms are still poorly understood. In this research, we aimed to evaluate the factors of single nucleotide polymorphisms (SNPs) and hierarchical brain structural and functional networks that were associated with antidepressant treatment. Moreover, we further explored the correlations and mediation pattern among "brain structure-brain function-gene" in major depressive disorder (MDD). METHODS: We analysed 405 SNPs and rich club/feeder/local connections of hierarchical structural and functional networks with three-way parallel independent component analysis in 179 MDD patients. The group-discriminative independent components of the three modalities between responders and non-responders of antidepressant treatment were identified. Pearson correlations and mediation analysis were further utilized to investigate the associations among SNPs and connections of the structural and functional networks. RESULTS: Notably, correlations with antidepressant treatment outcomes were found in structural, functional and SNP modalities simultaneously. The features of group-discriminative independent components included the shared feeder connections of hub regions with the inferior frontal orbital gyrus and amygdala in structural and functional modalities and genes enriched in circadian rhythmic processes and dopaminergic synapse pathways. The structural feeder network displayed close correlations with SNPs and the functional feeder network. Furthermore, the structural feeder network could mediate the association between SNPs and the functional feeder network, implying that genetic variants might influence brain function by affecting brain structure in MDD. CONCLUSIONS: These findings provide potential biomarkers for antidepressant therapy and provide a better grasp of the associations among SNPs and hierarchical structural and functional networks in MDD.

Abnormal fractional amplitude of low-frequency fluctuations and regional homogeneity in major depressive disorder with non-suicidal self-injury.

OBJECTIVE: We conducted this resting-state functional magnetic resonance imaging (rsfMRI) study to characterize changes in regional homogeneity (ReHo) or fractional amplitude of low-frequency fluctuations (fALFF) in young adult patients with major depressive disorder (MDD), with or without non-suicidal self-injury (NSSI). METHODS: We recruited 54 MDD patients with NSSI (MDD/NSSI), 68 MDD patients without NSSI, which is referred to as simple MDD (sMDD), and 66 matched healthy controls (HCs). A combination of fALFF and ReHo analyses was conducted. The effects of NSSI on the brain and their relationship to clinical variables were examined in this study. RESULTS: MDD/NSSI patients have decreased fALFF in the right superior frontal gyrus (SFG) and the right inferior parietal lobe (IPL), decreased ReHo in the right SFG and the right middle temporal gyrus (MTG) and the left middle occipital gyrus (MOG). fALFF and ReHo values of the right SFG are positively correlated. The ReHo values of the right SFG and the number of recent self-injuries are positively correlated; the fALFF values of the right SFG are negatively correlated with NSSI severity. CONCLUSIONS: There is a difference in brain activity between MDD/NSSI and sMDD, which may serve as an important physiological marker to determine the risk of self-injury and suicide. SIGNIFICANCE: Abnormal brain activity in patients with NSSI may provide new perspectives and significant implications on the severity of MDD patients and the prevention of self-injury and suicide.

Altered fractional amplitude of low-frequency fluctuations in the superior temporal gyrus: a resting-state fMRI study in anxious depression.

BACKGROUND: Anxious depression, which is a common subtype of major depressive disorder, has distinct clinical features from nonanxious depression. However, little is known about the neurobiological characteristics of anxious depression. In this study, we explored resting-state regional brain activity changes between anxious depression and nonanxious depression. METHOD: Resting-state functional magnetic resonance (rs-fMRI) imaging data were collected from 60 patients with anxious depression, 38 patients with nonanxious depression, and 60 matched healthy controls (HCs). One-way analysis of variance was performed to compare the whole-brain fractional amplitude of low-frequency fluctuation (fALFF) in the three groups. The correlation between the fALFF values and the clinical measures was examined. RESULTS: Compared with those of HCs, the fALFF values in the left superior temporal gyrus (STG) in patients with anxious depression were significantly increased, while the fALFF values in the left middle temporal gyrus (MTG), left STG, and right STG in patients with nonanxious depression were significantly increased. Patients with anxious depression showed reduced fALFF values in the right STG compared with patients with nonanxious depression (p < 0.001, corrected). Within the anxious depression group, fALFF value in the right STG was positively correlated with the cognitive disturbance score (r = 0.36, p = 0.005 corrected). CONCLUSION: The bilateral STG and left MTG, which are related to the default mode network, appear to be key brain regions in nonanxious depression, while the right STG plays an essential role in the neuropathological mechanism of anxious depression.

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.

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

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.

Altered resting-state brain activity in major depressive disorder comorbid with subclinical hypothyroidism: A regional homogeneity analysis.

BACKGROUND: Major depressive disorder (MDD), a common mental disorder worldwide, frequently coexists with various physical illnesses, and recent studies have shown an increased prevalence of subclinical hypothyroidism (SHypo) among MDD patients. However, the neural mechanisms shared and unique to these disorders and the associated alterations in brain function remain largely unknown. This study investigated the potential brain function mechanisms underlying comorbid MDD and SHypo. METHOD: Thirty MDD patients (non-comorbid group), 30 MDD patients comorbid with SHypo (comorbid group), 26 patients with SHypo, and 30 healthy controls were recruited for resting-state functional magnetic resonance imaging (rs-fMRI). We used regional homogeneity (ReHo) to examine differences in internal cerebral activity across the four groups. RESULTS: Compared with the non-comorbid group, the comorbid group exhibited significantly higher ReHo values in the right orbital part of the middle frontal gyrus (ORBmid) and bilateral middle frontal gyrus; decreased ReHo values in the right middle temporal gyrus, right thalamus, and right superior temporal gyrus, and right insula. Within the comorbid group, serum TSH levels were negatively associated with the ReHo values of the right insula; the ReHo values of the right Insula were negatively associated with the retardation factor score; the ReHo values of the right ORBmid were positively correlated with the anxiety/somatization factor scores. CONCLUSIONS: These findings provide valuable clues for exploring the shared neural mechanisms between MDD and SHypo and have important implications for understanding the pathophysiological mechanisms of the comorbidity of the two disorders.

The sex differences in anhedonia in major depressive disorder: A resting-state fMRI study.

OBJECTIVE: The external behavioural manifestations and internal neural mechanisms of anhedonia are sexually dimorphic. This study aimed to explore the sex differences in the regional brain neuroimaging features of anhedonia in the context of major depressive disorder (MDD). METHOD: The resting-fMRI by applying amplitude of low-frequency fluctuation (ALFF) method was estimated in 414 patients with MDD (281 high anhedonia [HA], 133 low anhedonia [LA]) and 213 healthy controls (HC). The effects of two factors in patients with MDD were analysed using a 2 (sex: male, female) × 2 (group: HA, LA) ANOVA concerning the brain regions in which statistical differences were identified between patients with MDD and HC. We followed up with patients with HA at baseline, and 43 patients completed a second fMRI scan in remission. Paired t-test was performed to compare the ALFF values of anhedonia-related brain regions between the baseline and remission periods. RESULTS: For the sex-by-group interaction, the bilateral insula, right hippocampus, right post cingulum cortex, and left putamen showed significant differences. Furthermore, the abnormally elevated ALFF values in anhedonia-related brain regions at baseline decreased in remission. CONCLUSION: Our findings point to the fact that the females showed unique patterns of anhedonia-related brain activity compared to males, which may have clinical implications for interfering with the anhedonia symptoms in MDD. Using task fMRI, we can further examine the distinct characteristics between consumption anhedonia and anticipation anhedonia in MDD.

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.