Neuronal connectivity in major depressive disorder: a systematic review

Comparative analysis of resting-state EEG functional connectivity in depression and obsessive-compulsive disorder

Major depressive disorder (MDD) and obsessive-compulsive disorder (OCD) are psychiatric disorders that often co-occur. We aimed to investigate whether their high comorbidity could be traced not only by clinical manifestations, but also at the level of functional brain activity. In this paper, we examined the differences in functional connectivity (FC) at the whole-brain level and within the default mode network (DMN). Resting-state EEG was obtained from 43 controls, 26 OCD patients, and 34 MDD patients. FC was analyzed between 68 cortical sources, and between-group differences in the 4-30 Hz range were assessed via the Network Based Statistic method. The strength of DMN intra-connectivity was compared between groups in the theta, alpha and beta frequency bands. A cluster of 67 connections distinguished the OCD, MDD and control groups. The majority of the connections, 8 of which correlated with depressive symptom severity, were found to be weaker in the clinical groups. Only 3 connections differed between the clinical groups, and one of them correlated with OCD severity. The DMN strength was reduced in the clinical groups in the alpha and beta bands. It can be concluded that the high comorbidity of OCD and MDD can be traced at the level of FC.

Phenomena of hypo- and hyperconnectivity in basal ganglia-thalamo-cortical circuits linked to major depression: a 7T fMRI study

Major depressive disorder (MDD) typically manifests itself in depressed affect, anhedonia, low energy, and additional symptoms. Despite its high global prevalence, its pathophysiology still gives rise to questions. Current research places alterations in functional connectivity among MDD's most promising biomarkers. However, given the heterogeneity of previous findings, the use of higher-resolution imaging techniques, like ultra-high field (UHF) fMRI (≥7 Tesla, 7T), may offer greater specificity in delineating fundamental impairments. In this study, 7T UHF fMRI scans were conducted on 31 MDD patients and 27 age-gender matched healthy controls to exploratorily contrast cerebral resting-state functional connectivity patterns between both groups. The CONN toolbox was used to generate functional network connectivity (FNC) analysis based on the region of interest (ROI)-to-ROI correlations in order to enable the identification of clusters of significantly different connections. Correction for multiple comparisons was implemented at the cluster level using a false discovery rate (FDR). The analysis revealed three significant clusters differentiating MDD patients and healthy controls. In Clusters 1 and 2, MDD patients exhibited between-network hypoconnectivity in basal ganglia-cortical pathways as well as hyperconnectivity in thalamo-cortical pathways, including several individual ROI-to-ROI connections. In Cluster 3, they showed increased occipital interhemispheric within-network connectivity. These findings suggest that alterations in basal ganglia-thalamo-cortical circuits play a substantial role in the pathophysiology of MDD. Furthermore, they indicate potential MDD-related deficits relating to a combination of perception (vision, audition, and somatosensation) as well as more complex functions, especially social-emotional processing, modulation, and regulation. It is anticipated that these findings might further inform more accurate clinical procedures for addressing MDD.

Resting-state dynamic functional connectivity in major depressive disorder: A systematic review

As a novel measure, dynamic functional connectivity (dFC) provides insight into the dynamic nature of brain networks and their interactions in resting-state, surpassing traditional static functional connectivity in pathological conditions such as depression. Since a comprehensive review is still lacking, we then reviewed forty-five eligible papers to explore pathological mechanisms of major depressive disorder (MDD) from perspectives including abnormal brain regions and functional networks, brain state, topological properties, relevant recognition, along with longitudinal studies. Though inconsistencies could be found, common findings are: (1) From different perspectives based on dFC, default-mode network (DMN) with its subregions exhibited a close relation to the pathological mechanism of MDD. (2) With a corrupted integrity within large-scale functional networks and imbalance between them, longer fraction time in a relatively weakly-connected state may be a possible property of MDD concerning its relation with DMN. Abnormal transition frequencies between states were correlated to the severity of MDD. (3) Including dynamic properties in topological network metrics enhanced recognition effect. In all, this review summarized its use for clinical diagnosis and treatment, elucidating the non-stationary of MDD patients' aberrant brain activity in the absence of stimuli and bringing new views into its underlying neuro mechanism.

Elucidating genetic and molecular basis of altered higher-order brain structure-function coupling in major depressive disorder

Previous studies have shown that major depressive disorder (MDD) patients exhibit structural and functional impairments, but few studies have investigated changes in higher-order coupling between structure and function. Here, we systematically investigated the effect of MDD on higher-order coupling between structural connectivity (SC) and functional connectivity (FC). Each brain region was mapped into embedding vector by the node2vec algorithm. We used support vector machine (SVM) with the brain region embedding vector to distinguish MDD patients from health controls (HCs) and identify the most discriminative brain regions. Our study revealed that MDD patients had decreased higher-order coupling in connections between the most discriminative brain regions and local connections in rich-club organization and increased higher-order coupling in connections between the ventral attentional network and limbic network compared with HCs. Interestingly, transcriptome-neuroimaging association analysis demonstrated the correlations between regional rSC-FC coupling variations between MDD patients and HCs and α/β-hydrolase domain-containing 6 (ABHD6), β 1,3-N-acetylglucosaminyltransferase-9(β3GNT9), transmembrane protein 45B (TMEM45B), the correlation between regional dSC-FC coupling variations and retinoic acid early transcript 1E antisense RNA 1(RAET1E-AS1), and the correlations between regional iSC-FC coupling variations and ABHD6, β3GNT9, katanin-like 2 protein (KATNAL2). In addition, correlation analysis with neurotransmitter receptor/transporter maps found that the rSC-FC and iSC-FC coupling variations were both correlated with neuroendocrine transporter (NET) expression, and the dSC-FC coupling variations were correlated with metabotropic glutamate receptor 5 (mGluR5). Further mediation analysis explored the relationship between genes, neurotransmitter receptor/transporter and MDD related higher-order coupling variations. These findings indicate that specific genetic and molecular factors underpin the observed disparities in higher-order SC-FC coupling between MDD patients and HCs. Our study confirmed that higher-order coupling between SC and FC plays an important role in diagnosing MDD. The identification of new biological evidence for MDD etiology holds promise for the development of innovative antidepressant therapies.

Gray matter volumetric correlates of the polygenic risk of depression: A study of the Human Connectome Project data

Genetic factors confer risks for depression. Understanding the neural endophenotypes, including brain morphometrics, of genetic predisposition to depression would help in unraveling the pathophysiology of depression. We employed voxel-based morphometry (VBM) to examine how gray matter volumes (GMVs) were correlated with the polygenic risk score (PRS) for depression in 993 young adults of the Human Connectome Project. The phenotype of depression was quantified with a DSM-oriented scale of the Achenbach Adult Self-Report. The PRS for depression was computed for each subject using the Psychiatric Genomics Association Study as the base sample. In multiple regression with age, sex, race, drinking severity, and total intracranial volume as covariates, regional GMVs in positive correlation with the PRS were observed in bilateral hippocampi and right gyrus rectus. Regional GMVs in negative correlation with the PRS were observed in a wide swath of brain regions, including bilateral frontal and temporal lobes, anterior cingulate cortex, thalamus, lingual gyri, cerebellum, and the left postcentral gyrus, cuneus, and parahippocampal gyrus. We also found sex difference in anterior cingulate volumes in manifesting the genetic risk of depression. In addition, the GMV of the right cerebellum crus I partially mediated the link from PRS to depression severity. These findings add to the literature by highlighting 1) a more diverse pattern of the volumetric markers of depression, with most regions showing lower but others higher GMVs in association with the genetic risks of depression, and 2) the cerebellar GMV as a genetically informed neural phenotype of depression, in neurotypical individuals.

EEG complexity in emotion conflict task in individuals with psychiatric disorders

Analyzing EEG complexity may help to elucidate complex brain dynamics in individuals with psychiatric disorders and provide insight into neural connectivity and its relationship with deficits such as emotion-related impulsivity. EEG complexity was calculated through multiscale entropy and compared between a heterogeneous psychiatric patient group and a healthy control group during the emotion conflict resolution task. Twenty-eight healthy adults and ten psychiatric patients were recruited and compared on the multiscale entropy of EEG acquired in the task. Our results revealed a lower multiscale entropy in the psychiatric patient group compared to the healthy group during the task. This decrease in multiscale entropy suggests reduced long-range interaction between the left frontal region and other brain regions during the emotion conflict resolution task among psychiatric patients. Notably, a positive correlation was observed between multiscale entropy and impulsivity measures in the psychiatric patient group, where the higher the EEG complexity during the emotion regulation task, the higher the level of self-reported impulsivity in the psychiatric patients. Such impulsivity was evident in both healthy individuals and psychiatric patients, with healthy individuals showing shorter reaction times on incongruent conditions compared to congruent conditions and psychiatric patients displaying similar reaction times in both conditions, This study highlights the significance of investigating EEG complexity and its potential applications in the transdiagnostic exploration of impulsivity in psychiatric disorders.

Sex differences in aberrant functional connectivity of three core networks and subcortical networks in medication-free adolescent-onset major depressive disorder

Major depressive disorder demonstrated sex differences in prevalence and symptoms, which were more pronounced during adolescence. Yet, research on sex-specific brain network characteristics in adolescent-onset major depressive disorder remains limited. This study investigated sex-specific and nonspecific alterations in resting-state functional connectivity of three core networks (frontoparietal network, salience network, and default mode network) and subcortical networks in adolescent-onset major depressive disorder, using seed-based resting-state functional connectivity in 50 medication-free patients with adolescent-onset major depressive disorder and 56 healthy controls. Irrespective of sex, compared with healthy controls, adolescent-onset major depressive disorder patients showed hypoconnectivity between bilateral hippocampus and right superior temporal gyrus (default mode network). More importantly, we further found that females with adolescent-onset major depressive disorder exhibited hypoconnectivity within the default mode network (medial prefrontal cortex), and between the subcortical regions (i.e. amygdala, striatum, and thalamus) with the default mode network (angular gyrus and posterior cingulate cortex) and the frontoparietal network (dorsal prefrontal cortex), while the opposite patterns of resting-state functional connectivity alterations were observed in males with adolescent-onset major depressive disorder, relative to their sex-matched healthy controls. Moreover, several sex-specific resting-state functional connectivity changes were correlated with age of onset, sleep disturbance, and anxiety in adolescent-onset major depressive disorder with different sex. These findings suggested that these sex-specific resting-state functional connectivity alterations may reflect the differences in brain development or processes related to early illness onset, underscoring the necessity for sex-tailored diagnostic and therapeutic approaches in adolescent-onset major depressive disorder.

Induced neural progenitor cells and iPS-neurons from major depressive disorder patients show altered bioenergetics and electrophysiological properties

The molecular pathomechanisms of major depressive disorder (MDD) are still not completely understood. Here, we follow the hypothesis, that mitochondria dysfunction which is inevitably associated with bioenergetic disbalance is a risk factor that contributes to the susceptibility of an individual to develop MDD. Thus, we investigated molecular mechanisms related to mitochondrial function in induced neuronal progenitor cells (NPCs) which were reprogrammed from fibroblasts of eight MDD patients and eight non-depressed controls. We found significantly lower maximal respiration rates, altered cytosolic basal calcium levels, and smaller soma size in NPCs derived from MDD patients. These findings are partially consistent with our earlier observations in MDD patient-derived fibroblasts. Furthermore, we differentiated MDD and control NPCs into iPS-neurons and analyzed their passive biophysical and active electrophysiological properties to investigate whether neuronal function can be related to altered mitochondrial activity and bioenergetics. Interestingly, MDD patient-derived iPS-neurons showed significantly lower membrane capacitance, a less hyperpolarized membrane potential, increased Na+ current density and increased spontaneous electrical activity. Our findings indicate that functional differences evident in fibroblasts derived from MDD patients are partially present after reprogramming to induced-NPCs, could relate to altered function of iPS-neurons and thus might be associated with the aetiology of major depressive disorder.

The Role of Subgenual Resting-State Connectivity Networks in Predicting Prognosis in Major Depressive Disorder

Background

A seminal study found higher subgenual frontal cortex resting-state connectivity with 2 left ventral frontal regions and the dorsal midbrain to predict better response to psychotherapy versus medication in individuals with treatment-naïve major depressive disorder (MDD). Here, we examined whether these subgenual networks also play a role in the pathophysiology of clinical outcomes in MDD with early treatment resistance in primary care.

Methods

Forty-five people with current MDD who had not responded to ≥2 serotonergic antidepressants (n = 43, meeting predefined functional magnetic resonance imaging minimum quality thresholds) were enrolled and followed over 4 months of standard care. Functional magnetic resonance imaging resting-state connectivity between the preregistered subgenual frontal cortex seed and 3 previously identified left ventromedial, ventrolateral prefrontal/insula, and dorsal midbrain regions was extracted. The clinical outcome was the percentage change on the self-reported 16-item Quick Inventory of Depressive Symptomatology.

Results

We observed a reversal of our preregistered hypothesis in that higher resting-state connectivity between the subgenual cortex and the a priori ventrolateral prefrontal/insula region predicted favorable rather than unfavorable clinical outcomes (rs39 = -0.43, p = .006). This generalized to the sample including participants with suboptimal functional magnetic resonance imaging quality (rs43 = -0.35, p = .02). In contrast, no effects (rs39 = 0.12, rs39 = -0.01) were found for connectivity with the other 2 preregistered regions or in a whole-brain analysis (voxel-based familywise error-corrected p < .05).

Conclusions

Subgenual connectivity with the ventrolateral prefrontal cortex/insula is relevant for subsequent clinical outcomes in current MDD with early treatment resistance. Its positive association with favorable outcomes could be explained primarily by psychosocial rather than the expected pharmacological changes during the follow-up period.

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.

Improved clinical outcome prediction in depression using neurodynamics in an emotional face-matching functional MRI task

Introduction

Approximately one in six people will experience an episode of major depressive disorder (MDD) in their lifetime. Effective treatment is hindered by subjective clinical decision-making and a lack of objective prognostic biomarkers. Functional MRI (fMRI) could provide such an objective measure but the majority of MDD studies has focused on static approaches, disregarding the rapidly changing nature of the brain. In this study, we aim to predict depression severity changes at 3 and 6 months using dynamic fMRI features.

Methods

For our research, we acquired a longitudinal dataset of 32 MDD patients with fMRI scans acquired at baseline and clinical follow-ups 3 and 6 months later. Several measures were derived from an emotion face-matching fMRI dataset: activity in brain regions, static and dynamic functional connectivity between functional brain networks (FBNs) and two measures from a wavelet coherence analysis approach. All fMRI features were evaluated independently, with and without demographic and clinical parameters. Patients were divided into two classes based on changes in depression severity at both follow-ups.

Results

The number of coherence clusters (nCC) between FBNs, reflecting the total number of interactions (either synchronous, anti-synchronous or causal), resulted in the highest predictive performance. The nCC-based classifier achieved 87.5% and 77.4% accuracy for the 3- and 6-months change in severity, respectively. Furthermore, regression analyses supported the potential of nCC for predicting depression severity on a continuous scale. The posterior default mode network (DMN), dorsal attention network (DAN) and two visual networks were the most important networks in the optimal nCC models. Reduced nCC was associated with a poorer depression course, suggesting deficits in sustained attention to and coping with emotion-related faces. An ensemble of classifiers with demographic, clinical and lead coherence features, a measure of dynamic causality, resulted in a 3-months clinical outcome prediction accuracy of 81.2%.

Discussion

The dynamic wavelet features demonstrated high accuracy in predicting individual depression severity change. Features describing brain dynamics could enhance understanding of depression and support clinical decision-making. Further studies are required to evaluate their robustness and replicability in larger cohorts.

The role of serotonin in depression-A historical roundup and future directions

Depression is one of the most common psychiatric disorders worldwide, affecting approximately 280 million people, with probably much higher unrecorded cases. Depression is associated with symptoms such as anhedonia, feelings of hopelessness, sleep disturbances, and even suicidal thoughts. Tragically, more than 700 000 people commit suicide each year. Although depression has been studied for many decades, the exact mechanisms that lead to depression are still unknown, and available treatments only help a fraction of patients. In the late 1960s, the serotonin hypothesis was published, suggesting that serotonin is the key player in depressive disorders. However, this hypothesis is being increasingly doubted as there is evidence for the influence of other neurotransmitters, such as noradrenaline, glutamate, and dopamine, as well as larger systemic causes such as altered activity in the limbic network or inflammatory processes. In this narrative review, we aim to contribute to the ongoing debate on the involvement of serotonin in depression. We will review the evolution of antidepressant treatments, systemic research on depression over the years, and future research applications that will help to bridge the gap between systemic research and neurotransmitter dynamics using biosensors. These new tools in combination with systemic applications, will in the future provide a deeper understanding of the serotonergic dynamics in depression.

Vertigo During Pregnancy: A Narrative Review of the Etiology, Pathophysiology, and Treatment

From the time of conception until the time of labor, a woman's body and mind undergo a variety of hormonal and other changes. Patients may also experience vertigo and a lack of balance during this period. Disabling and physically painful, these symptoms may strike at any moment. Pregnancy-related vertigo has been the focus of several studies. We looked at the research on vertigo in pregnant women in detail. This narrative review aims to examine the causes, pathophysiology, and current treatments for vertigo during pregnancy. Vertigo during pregnancy has a diverse etiology, with typical causes including hormonal changes and modifications in vascular dynamics. Vertigo may start to appear due to pathophysiological mechanisms involving vestibular and central nervous system adaptations. Numerous alternatives for treatment are available, including dietary changes, vestibular therapy, medicines, and surgical procedures. The thorough assessment of the current research on vertigo during pregnancy provided by this narrative review will help medical practitioners make wise clinical decisions.

A structural equation modeling approach using behavioral and neuroimaging markers in major depressive disorder

Major depressive disorder (MDD) has consistently proven to be a multifactorial and highly comorbid disease. Despite recent depression-related research demonstrating causalities between MDD-related factors and a small number of variables, including brain structural changes, a high-statistical power analysis of the various factors is yet to be conducted. We retrospectively analyzed data from 155 participants (84 healthy controls and 71 patients with MDD). We used magnetic resonance imaging and diffusion tensor imaging data, scales assessing childhood trauma, depression severity, cognitive dysfunction, impulsivity, and suicidal ideation. To simultaneously evaluate the causalities between multivariable, we implemented two types of MDD-specified structural equation models (SEM), the behavioral and neurobehavioral models. Behavioral SEM showed significant results in the MDD group: Comparative Fit Index [CFI] = 1.000, Root Mean Square Error of Approximation [RMSEA]) = 0.000), with a strong correlation in the scales for childhood trauma, depression severity, suicidal ideation, impulsivity, and cognitive dysfunction. Based on behavioral SEM, we established neurobehavioral models showing the best-fit in MDD, especially including the right cingulate cortex, central to the posterior corpus callosum, right putamen, pallidum, whole brainstem, and ventral diencephalon, including the thalamus (CFI >0.96, RMSEA <0.05). Our MDD-specific model revealed that the limbic-associated regions are strongly connected with childhood trauma rather than depression severity, and that they independently affect suicidal ideation and cognitive dysfunction. Furthermore, cognitive dysfunction could affect impulsivity.

White matter integrity and medication response to antidepressants in major depressive disorder: a review of the literature

Major Depressive Disorder (MDD) is a severe psychiatric disorder characterized by selective impairments in mood regulation, cognition and behavior. Although it is well-known that antidepressants can effectively treat moderate to severe depression, the biochemical effects of these medications on white matter (WM) integrity are still unclear. Therefore, the aim of the study is to review the main scientific evidence on the differences in WM integrity in responders and non-responders to antidepressant medications. A record search was performed on three datasets (PubMed, Scopus and Web of Science) and ten records matched our inclusion criteria. Overall, the reviewed studies highlighted a good efficacy of antidepressants in MDD treatment. Furthermore, there were differences in WM integrity between responders and non-responders, mainly localized in cingulate cortices, hippocampus and corpus callosum, where the former group showed higher fractional anisotropy and lower axial diffusivity values. Modifications in WM integrity might be partially explained by branching and proliferation as well as neurogenesis of axonal fibers mediated by antidepressants, which in turn may have positively affected brain metabolism and increase the quantity of the serotonergic neurotransmitter within synaptic clefts. However, the reviewed studies suffer from some limitations, including the heterogeneity in treatment duration, antidepressant administration, medical posology, and psychiatric comorbidities. Therefore, future studies are needed to reduce confounding effects of antidepressant medications and to adopt longitudinal and multimodal approaches in order to better characterize the differences in WM integrity between responders and non-responders.

Major depressive disorder associated alterations in the effective connectivity of the face processing network: a systematic review

Major depressive disorder (MDD) is marked by altered processing of emotional stimuli, including facial expressions. Recent neuroimaging research has attempted to investigate how these stimuli alter the directional interactions between brain regions in those with MDD; however, methodological heterogeneity has made identifying consistent effects difficult. To address this, we systematically examined studies investigating MDD-associated differences present in effective connectivity during the processing of emotional facial expressions. We searched five databases: PsycINFO, EMBASE, PubMed, Scopus, and Web of Science, using a preregistered protocol (registration number: CRD42021271586). Of the 510 unique studies screened, 17 met our inclusion criteria. These studies identified that compared with healthy controls, participants with MDD demonstrated (1) reduced connectivity from the dorsolateral prefrontal cortex to the amygdala during the processing of negatively valenced expressions, and (2) increased inhibitory connectivity from the ventromedial prefrontal cortex to amygdala during the processing of happy facial expressions. Most studies investigating the amygdala and anterior cingulate cortex noted differences in their connectivity; however, the precise nature of these differences was inconsistent between studies. As such, commonalities observed across neuroimaging modalities warrant careful investigation to determine the specificity of these effects to particular subregions and emotional expressions. Future research examining longitudinal connectivity changes associated with treatment response may provide important insights into mechanisms underpinning therapeutic interventions, thus enabling more targeted treatment strategies.

Quantitative Electroencephalography Markers for an Accurate Diagnosis of Frontotemporal Dementia: A Spectral Power Ratio Approach

Background and Objectives: Frontotemporal dementia (FTD) is the second most common form of presenile dementia; however, its diagnosis has been poorly investigated. Previous attempts to diagnose FTD using quantitative electroencephalography (qEEG) have yielded inconsistent results in both spectral and functional connectivity analyses. This study aimed to introduce an accurate qEEG marker that could be used to diagnose FTD and other neurological abnormalities. Materials and Methods: We used open-access electroencephalography data from OpenNeuro to investigate the power ratio between the frontal and temporal lobes in the resting state of 23 patients with FTD and 29 healthy controls. Spectral data were extracted using a fast Fourier transform in the delta (0.5 ≤ 4 Hz), theta (4 ≤ 8 Hz), alpha (8-13 Hz), beta (>13-30 Hz), and gamma (>30-45 Hz) bands. Results: We found that the spectral power ratio between the frontal and temporal lobes is a promising qEEG marker of FTD. Frontal (F)-theta/temporal (T)-alpha, F-alpha/T-theta, F-theta/F-alpha, and T-beta/T-gamma showed a consistently high discrimination score for the diagnosis of FTD for different parameters and referencing methods. Conclusions: The study findings can serve as reference for future research focused on diagnosing FTD and other neurological anomalies.

Decreased cortical gyrification in major depressive disorder

BACKGROUND

Early neurodevelopmental deviations, such as abnormal cortical folding patterns, are candidate biomarkers of major depressive disorder (MDD). We aimed to investigate the association of MDD with the local gyrification index (LGI) in each cortical region at the whole-brain level, and the association of the LGI with clinical characteristics of MDD.

METHODS

We obtained T1-weighted images from 234 patients with MDD and 215 healthy controls (HCs). The LGI values from 66 cortical regions in the bilateral hemispheres were automatically calculated according to the Desikan-Killiany atlas. We compared the LGI values between the MDD and HC groups using analysis of covariance, including age, sex, and years of education as covariates. The association between the clinical characteristics and LGI values was investigated in the MDD group.

RESULTS

Compared with HCs, patients with MDD showed significantly decreased LGI values in the cortical regions, including the bilateral ventrolateral and dorsolateral prefrontal cortices, medial and lateral orbitofrontal cortices, insula, right rostral anterior cingulate cortex, and several temporal and parietal regions, with the largest effect size in the left pars triangularis (Cohen's f2 = 0.361; p = 1.78 × 10-13). Regarding the association of clinical characteristics with LGIs within the MDD group, recurrence and longer illness duration were associated with increased gyrification in several occipital and temporal regions, which showed no significant difference in LGIs between the MDD and HC groups.

CONCLUSIONS

These findings suggest that the LGI may be a relatively stable neuroimaging marker associated with MDD predisposition.

Neural responses to acute stress predict chronic stress perception in daily life over 13 months

The importance of amygdala, hippocampus, and medial prefrontal cortex (mPFC) for the integration of neural, endocrine, and affective stress processing was shown in healthy participants and patients with stress-related disorders. The present manuscript which reports on one study-arm of the LawSTRESS project, aimed at investigating the predictive value of acute stress responses in these regions for biopsychological consequences of chronic stress in daily life. The LawSTRESS project examined law students either in preparation for their first state examination (stress group [SG]) or in the mid-phase of their study program (control group [CG]) over 13 months. Ambulatory assessments comprising perceived stress measurements and the cortisol awakening response (CAR) were administered on six sampling points (t1 = - 1 year, t2 = - 3 months, t3 = - 1 week, t4 = exam, t5 =  + 1 week, t6 =  + 1 month). In a subsample of 124 participants (SG: 61; CG: 63), ScanSTRESS was applied at baseline. In the SG but not in the CG, amygdala, hippocampus, and (post-hoc analyzed) right mPFC activation changes during ScanSTRESS were significantly associated with the trajectory of perceived stress but not with the CAR. Consistent with our finding in the total LawSTRESS sample, a significant increase in perceived stress and a blunted CAR over time could be detected in the SG only. Our findings suggest that more pronounced activation decreases of amygdala, hippocampus, and mPFC in response to acute psychosocial stress at baseline were related to a more pronounced increase of stress in daily life over the following year.

Exploring the association between early exposure to material hardship and psychopathology through indirect effects of fronto-limbic functional connectivity during fear learning

Experiencing family material hardship has been shown to be associated with disruptions in physical and psychological development. However, the association between material hardship and functional connectivity in the fronto-limbic circuit during fear learning is unclear. A total of 161 healthy young adults aged 17-28 were recruited in our brain imaging study, using the Fear Conditioning Task to test the associations between material hardship and connectivity in fronto-limbic circuit and psychopathology. The results showed that family material hardship was linked to higher positive connectivity between the left amygdala and bilateral dorsal anterior cingulate cortex, as well as higher negative connectivity between the left hippocampus and right ventromedial prefrontal cortex. A mediation analysis showed that material hardship was associated with depression via amygdala functional connectivity (indirect effect = 0.228, P = 0.016), and also indirectly associated with aggression and anger-hostility symptoms through hippocampal connections (aggression: indirect effect = 0.057, P = 0.001; anger-hostility: indirect effect = 0.169, P = 0.048). That is, family material hardship appears to affect fronto-limbic circuits through changes in specific connectivity, and these specific changes, in turn, could lead to specific psychological symptoms. The findings have implications for designing developmentally sensitive interventions to mitigate the emergence of psychopathological symptoms.

Influences of resting-state intrinsic functional brain connectivity on the antidepressant treatment response in late-life depression

BACKGROUND

Late-life depression (LLD) is characterized by differences in resting state functional connectivity within and between intrinsic functional networks. This study examined whether clinical improvement to antidepressant medications is associated with pre-randomization functional connectivity in intrinsic brain networks.

METHODS

Participants were 95 elders aged 60 years or older with major depressive disorder. After clinical assessments and baseline MRI, participants were randomized to escitalopram or placebo with a two-to-one allocation for 8 weeks. Non-remitting participants subsequently entered an 8-week trial of open-label bupropion. The main clinical outcome was depression severity measured by MADRS. Resting state functional connectivity was measured between a priori key seeds in the default mode (DMN), cognitive control, and limbic networks.

RESULTS

In primary analyses of blinded data, lower post-treatment MADRS score was associated with higher resting connectivity between: (a) posterior cingulate cortex (PCC) and left medial prefrontal cortex; (b) PCC and subgenual anterior cingulate cortex (ACC); (c) right medial PFC and subgenual ACC; (d) right orbitofrontal cortex and left hippocampus. Lower post-treatment MADRS was further associated with lower connectivity between: (e) the right orbitofrontal cortex and left amygdala; and (f) left dorsolateral PFC and left dorsal ACC. Secondary analyses associated mood improvement on escitalopram with anterior DMN hub connectivity. Exploratory analyses of the bupropion open-label trial associated improvement with subgenual ACC, frontal, and amygdala connectivity.

CONCLUSIONS

Response to antidepressants in LLD is related to connectivity in the DMN, cognitive control and limbic networks. Future work should focus on clinical markers of network connectivity informing prognosis.

REGISTRATION

ClinicalTrials.gov NCT02332291.

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.

The Ponto-Geniculo-Occipital (PGO) Waves in Dreaming: An Overview

Rapid eye movement (REM) sleep is the main sleep correlate of dreaming. Ponto-geniculo-occipital (PGO) waves are a signature of REM sleep. They represent the physiological mechanism of REM sleep that specifically limits the processing of external information. PGO waves look just like a message sent from the pons to the lateral geniculate nucleus of the visual thalamus, the occipital cortex, and other areas of the brain. The dedicated visual pathway of PGO waves can be interpreted by the brain as visual information, leading to the visual hallucinosis of dreams. PGO waves are considered to be both a reflection of REM sleep brain activity and causal to dreams due to their stimulation of the cortex. In this review, we summarize the role of PGO waves in potential neural circuits of two major theories, i.e., (1) dreams are generated by the activation of neural activity in the brainstem; (2) PGO waves signaling to the cortex. In addition, the potential physiological functions during REM sleep dreams, such as memory consolidation, unlearning, and brain development and plasticity and mood regulation, are discussed. It is hoped that our review will support and encourage research into the phenomenon of human PGO waves and their possible functions in dreaming.

The association of white matter connectivity with prevalence, incidence and course of depressive symptoms: The Maastricht Study

BACKGROUND

Altered white matter brain connectivity has been linked to depression. The aim of this study was to investigate the association of markers of white matter connectivity with prevalence, incidence and course of depressive symptoms.

METHODS

Markers of white matter connectivity (node degree, clustering coefficient, local efficiency, characteristic path length, and global efficiency) were assessed at baseline by 3 T MRI in the population-based Maastricht Study (n = 4866; mean ± standard deviation age 59.6 ± 8.5 years, 49.0% women; 17 406 person-years of follow-up). Depressive symptoms (9-item Patient Health Questionnaire; PHQ-9) were assessed at baseline and annually over seven years of follow-up. Major depressive disorder (MDD) was assessed with the Mini-International Neuropsychiatric Interview at baseline only. We used negative binominal, logistic and Cox regression analyses, and adjusted for demographic, cardiovascular, and lifestyle risk factors.

RESULTS

A lower global average node degree at baseline was associated with the prevalence and persistence of clinically relevant depressive symptoms [PHQ-9 ⩾ 10; OR (95% confidence interval) per standard deviation = 1.21 (1.05-1.39) and OR = 1.21 (1.02-1.44), respectively], after full adjustment. On the contrary, no associations were found of global average node degree with the MDD at baseline [OR 1.12 (0.94-1.32) nor incidence or remission of clinically relevant depressive symptoms [HR = 1.05 (0.95-1.17) and OR 1.08 (0.83-1.41), respectively]. Other connectivity measures of white matter organization were not associated with depression.

CONCLUSIONS

Our findings suggest that fewer white matter connections may contribute to prevalent depressive symptoms and its persistence but not to incident depression. Future studies are needed to replicate our findings.

Depression diagnosis based on electroencephalography power ratios

BACKGROUND

Depression is a common mental disorder that impacts millions of people across the world. However, its diagnosis is difficult due to the dependence on subjective testing. Although quantitative electroencephalography (EEG) has been investigated as a promising diagnostic tool for depression, the associated results have proven contradictory. The current study determines whether the alpha/beta (ABR), alpha/theta (ATR), and theta/beta (TBR) ratios can serve as biological markers of depression.

METHODS

We used open-access EEG data from OpenNeuro to investigate power ratios in the resting state of 46 patients with depression and 75 healthy controls. Spectral data were extracted by fast Fourier transform at the theta band (4-8 Hz), alpha band (8-13 Hz), and beta band (13-32 Hz). Neural network, logistic regression, and receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracies of each suggested index. Additionally, the cutoff point, sensitivity, specificity, positive predictive value, and negative predictive value at the maximized Youden index were compared for each variable.

RESULTS

Decreased anterior frontal, frontal, central, parietal, occipital, and temporal ABR and decreased central and parietal TBR were observed in the depression group. The area under the curve of the ROC curves further revealed that these ratios could all effectively differentiate depression. In particular, the central, frontal, and parietal ABR exhibited high discrimination scores. Multiple logistic regression analysis demonstrated that the Beck Depression Inventory and Spielberger Trait Anxiety Inventory scores, as well as the probability of depression, increased with a decrease in the central ABR. Moreover, neural network analysis revealed that the global ABR was the most effective index for diagnosing depression among the three global EEG power ratios.

CONCLUSIONS

The central, frontal, and parietal ABR represent potential biomarkers to differentiate patients with depression from healthy controls.

Cortico-muscular coherence and brain networks in familial adult myoclonic epilepsy and progressive myoclonic epilepsy

OBJECTIVE

Familial Adult Myoclonic Epilepsy (FAME) presents with action-activated myoclonus, often associated with epilepsy, sharing various features with Progressive Myoclonic Epilepsy (PMEs), but with slower course and limited motor disability. We aimed our study to identify measures suitable to explain the different severity of FAME2 compared to EPM1, the most common PME, and to detect the signature of the distinctive brain networks.

METHODS

We analyzed the EEG-EMG coherence (CMC) during segmental motor activity and indexes of connectivity in the two patient groups, and in healthy subjects (HS). We also investigated the regional and global properties of the network.

RESULTS

In FAME2, differently from EPM1, we found a well-localized distribution of beta-CMC and increased betweenness-centrality (BC) on the sensorimotor region contralateral to the activated hand. In both patient groups, compared to HS, there was a decline in the network connectivity indexes in the beta and gamma band, which was more obvious in FAME2.

CONCLUSIONS

In FAME2, better localized CMC and increased BC in comparison with EPM1 patients could counteract the severity and the spreading of the myoclonus. Decreased indexes of cortical integration were more severe in FAME2.

SIGNIFICANCE

Our measures correlated with different motor disabilities and identified distinctive brain network impairments.

Deconvoluting human Brodmann area 8 based on its unique structural and functional connectivity

Brodmann area 8 (BA8) is traditionally defined as the prefrontal region of the human cerebrum just anterior to the premotor cortices and enveloping most of the superior frontal gyrus. Early studies have suggested the frontal eye fields are situated at its most caudal aspect, causing many to consider BA8 as primarily an ocular center which controls contralateral gaze and attention. However, years of refinement in cytoarchitectural studies have challenged this traditional anatomical definition, providing a refined definition of its boundaries with neighboring cortical areas and the presence of meaningful subdivisions. Furthermore, functional imaging studies have suggested its involvement in a diverse number of higher-order functions, such as motor, cognition, and language. Thus, our traditional working definition of BA8 has likely been insufficient to truly understand the complex structural and functional significance of this area. Recently, large-scale multi-modal neuroimaging approaches have allowed for improved mapping of the neural connectivity of the human brain. Insight into the structural and functional connectivity of the brain connectome, comprised of large-scale brain networks, has allowed for greater understanding of complex neurological functioning and pathophysiological diseases states. Simultaneously, the structural and functional connectivity of BA8 has recently been highlighted in various neuroimaging studies and detailed anatomic dissections. However, while Brodmann's nomenclature is still widely used today, such as for clinical discussions and the communication of research findings, the importance of the underlying connectivity of BA8 requires further review.

Chronic Gq activation of ventral hippocampal neurons and astrocytes differentially affects memory and behavior

Network dysfunction is implicated in numerous diseases and psychiatric disorders, and the hippocampus serves as a common origin for these abnormalities. To test the hypothesis that chronic modulation of neurons and astrocytes induces impairments in cognition, we activated the hM3D(Gq) pathway in CaMKII+ neurons or GFAP+ astrocytes within the ventral hippocampus across 3, 6, and 9 months. CaMKII-hM3Dq activation impaired fear extinction at 3 months and acquisition at 9 months. Both CaMKII-hM3Dq manipulation and aging had differential effects on anxiety and social interaction. GFAP-hM3Dq activation impacted fear memory at 6 and 9 months. GFAP-hM3Dq activation impacted anxiety in the open field only at the earliest time point. CaMKII-hM3Dq activation modified the number of microglia, while GFAP-hM3Dq activation impacted microglial morphological characteristics, but neither affected these measures in astrocytes. Overall, our study elucidates how distinct cell types can modify behavior through network dysfunction, while adding a more direct role for glia in modulating behavior.

Flavonols in Action: Targeting Oxidative Stress and Neuroinflammation in Major Depressive Disorder

Major depressive disorder is one of the most common mental illnesses that highly impairs quality of life. Pharmacological interventions are mainly focused on altered monoamine neurotransmission, which is considered the primary event underlying the disease's etiology. However, many other neuropathological mechanisms that contribute to the disease's progression and clinical symptoms have been identified. These include oxidative stress, neuroinflammation, hippocampal atrophy, reduced synaptic plasticity and neurogenesis, the depletion of neurotrophic factors, and the dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis. Current therapeutic options are often unsatisfactory and associated with adverse effects. This review highlights the most relevant findings concerning the role of flavonols, a ubiquitous class of flavonoids in the human diet, as potential antidepressant agents. In general, flavonols are considered to be both an effective and safe therapeutic option in the management of depression, which is largely based on their prominent antioxidative and anti-inflammatory effects. Moreover, preclinical studies have provided evidence that they are capable of restoring the neuroendocrine control of the HPA axis, promoting neurogenesis, and alleviating depressive-like behavior. Although these findings are promising, they are still far from being implemented in clinical practice. Hence, further studies are needed to more comprehensively evaluate the potential of flavonols with respect to the improvement of clinical signs of depression.

Increased BDNF and hippocampal dendritic spine density are associated with the rapid antidepressant-like effect of iron-citalopram and iron-imipramine combinations in mice

Iron supplementation previously demonstrated antidepressant-like effects in post-partum rats. The present study evaluates the possible synergistic antidepressant effect of sub-therapeutic dose of iron co-administered with citalopram or imipramine in female Institute of Cancer Research mice. Depression-like symptoms were induced in the forced swim (FST), tail suspension (TST), and open space swim (OSST) tests while open field test (OFT) was used to assess locomotor activity. Mice (n=8) received iron (0.8- 7.2 mg/kg), citalopram (3-30 mg/kg), imipramine (3-30 mg/kg), desferrioxamine (50 mg/kg) or saline in the single treatment phase of each model and subsequently a sub-therapeutic dose of iron co-administered with citalopram or imipramine. Assessment of serum BDNF and dendritic spine density was done using ELISA and Golgi staining techniques respectively. Iron, citalopram and imipramine, unlike desferrioxamine, reduced immobility score in the TST, FST and OSST without affecting locomotor activity, suggesting antidepressant-like effect. Sub-therapeutic dose of iron in combination with citalopram or imipramine further enhanced the antidepressant-like effect, producing a more rapid effect when compared to the iron, citalopram or imipramine alone. Iron, citalopram and imipramine or their combinations increased serum BDNF concentration, hippocampal neuronal count and dendritic spine densities. Our study provides experimental evidence that iron has antidepressant-like effect and sub-therapeutic dose of iron combined with citalopram or imipramine produces more rapid antidepressant-like effect. We further show that iron alone or its combination with citalopram or imipramine attenuates the neuronal loss associated with depressive conditions, increases dendritic spines density and BDNF levels. These finding suggest iron-induced neuronal plasticity in the mice brain.

Effects of a probiotic add-on treatment on fronto-limbic brain structure, function, and perfusion in depression: Secondary neuroimaging findings of a randomized controlled trial

BACKGROUND

Probiotics are suggested to improve depressive symptoms via the microbiota-gut-brain axis. We have recently shown a beneficial clinical effect of probiotic supplementation in patients with depression. Their underlying neural mechanisms remain unknown.

METHODS

A multimodal neuroimaging approach including diffusion tensor imaging, resting-state functional MRI, and arterial spin labeling was used to investigate the effects of a four-weeks probiotic supplementation on fronto-limbic brain structure, function, and perfusion and whether these effects were related to symptom changes.

RESULTS

Thirty-two patients completed both imaging assessments (18 placebo and 14 probiotics group). Probiotics maintained mean diffusivity in the left uncinate fasciculus, stabilized it in the right uncinate fasciculus, and altered resting-state functional connectivity (rsFC) between limbic structures and the temporal pole to a cluster in the precuneus. Moreover, a cluster in the left superior parietal lobule showed altered rsFC to the subcallosal cortex, the left orbitofrontal cortex, and limbic structures after probiotics. In the probiotics group, structural and functional changes were partly related to decreases in depressive symptoms.

LIMITATIONS

This study has a rather small sample size. An additional follow-up MRI session would be interesting for seeing clearer changes in the relevant brain regions as clinical effects were strongest in the follow-up.

CONCLUSION

Probiotic supplementation is suggested to prevent neuronal degeneration along the uncinate fasciculus and alter fronto-limbic rsFC, effects that are partly related to the improvement of depressive symptoms. Elucidating the neural mechanisms underlying probiotics' clinical effects on depression provide potential targets for the development of more precise probiotic treatments.

Effective Connectivity Between the Orbitofrontal Cortex and the Precuneus Differentiates Major Psychiatric Disorders: Results from a Transdiagnostic Spectral DCM Study

BACKGROUND & OBJECTIVE

We have previously identified aberrant connectivity of the left precuneus, ventrolateral prefrontal cortex, anterior cingulate cortex, and anterior insula in patients with either a paranoid (schizophrenia), or a depressive syndrome (both unipolar and bipolar). In the current study, we attempted to replicate and expand these findings by including a healthy control sample and separating the patients in a depressive episode into two groups: unipolar and bipolar depression. We hypothesized that the connections between those major nodes of the resting state networks would demonstrate different patterns in the three patient groups compared to the healthy subjects.

METHODS

Resting-state functional MRI was performed on a sample of 101 participants, of which 26 patients with schizophrenia (current psychotic episodes), 24 subjects with Bipolar Disorder (BD), 33 with Major Depressive Disorder (MDD) (both BD and MDD patients were in a current depressive episode), and 21 healthy controls. Spectral Dynamic Causal Modeling was used to calculate the coupling values between eight regions of interest, including the anterior precuneus (PRC), anterior hippocampus, anterior insula, angular gyrus, lateral Orbitofrontal Cortex (OFC), middle frontal gyrus, planum temporale, and anterior thalamus.

RESULTS & CONCLUSION

We identified disturbed effective connectivity from the left lateral orbitofrontal cortex to the left anterior precuneus that differed significantly between unipolar depression, where the influence was inhibitory, and bipolar depression, where the effect was excitatory. A logistic regression analysis correctly classified 75% of patients with unipolar and bipolar depression based solely on the coupling values of this connection. In addition, patients with schizophrenia demonstrated negative effective connectivity from the anterior PRC to the lateral OFC, which distinguished them from healthy controls and patients with major depression. Future studies with unmedicated patients will be needed to establish the replicability of our findings.

The thalamocortical inhibitory network controls human conscious perception

Although conscious perception is a fundamental cognitive function, its neural correlates remain unclear. It remains debatable whether thalamocortical interactions play a decisive role in conscious perception. To clarify this, we used functional magnetic resonance imaging (fMRI) where flickering red and green visual cues could be perceived either as a non-fused colour or fused colour. Here we show significantly differentiated fMRI neurodynamics only in higher-order thalamocortical regions, compared with first-order thalamocortical regions. Anticorrelated neurodynamic behaviours were observed between the visual stream network and default-mode network. Its dynamic causal modelling consistently provided compelling evidence for the involvement of higher-order thalamocortical iterative integration during conscious perception of fused colour, while inhibitory control was revealed during the non-fusion condition. Taken together with our recent magnetoencephalography study, our fMRI findings corroborate a thalamocortical inhibitory model for consciousness, where both thalamic inhibitory regulation and integrative signal iterations across higher-order thalamocortical regions are essential for conscious perception.

Lack of robust associations between prepandemic coping strategies and frontolimbic circuitry with depression and anxiety symptoms during the COVID-19 pandemic: A preregistered longitudinal study

The COVID-19 pandemic is an ongoing stressor that has resulted in the exacerbation of mental health problems worldwide. However, longitudinal studies that identify preexisting behavioral and neurobiological factors associated with mental health outcomes during the pandemic are lacking. Here, we examined associations between prepandemic coping strategy engagement and frontolimbic circuitry with internalizing symptoms during the pandemic. In 85 adults (71.8% female; age 18-30 years), we assessed prototypically adaptive coping strategies (Connor-Davidson Resilience Scale), resting-state functional magnetic resonance imaging functional connectivity (FC) of frontolimbic circuitry, and depression and anxiety symptoms (Beck Depression Inventory, Screen for Child Anxiety-Related Emotional Disorders-Adult, respectively). We conducted general linear models to test preregistered hypotheses that (1) lower coping engagement prepandemic and (2) weaker frontolimbic FC prepandemic would predict elevated symptoms during the pandemic; and (3) coping would interact with FC to predict symptoms during the pandemic. Depression and anxiety symptoms worsened during the pandemic (ps < .001). Prepandemic adaptive coping engagement and frontolimbic FC were not associated with depression or anxiety symptoms during the pandemic (uncorrected ps > .05). Coping interacted with insula-rostral anterior cingulate cortex (ACC) FC (p = .003, pFDR = .014) and with insula-ventral ACC FC (p < .001, pFDR < .001) to predict depression symptoms, but these findings did not survive FDR correction after removal of outliers. Findings from our preregistered study suggest that specific prepandemic factors, particularly adaptive coping and frontolimbic circuitry, are not robustly associated with emotional responses to the pandemic. Additional studies that identify preexisting neurobehavioral factors implicated in mental health outcomes during global health crises are needed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Altered functional connectivity in common resting-state networks in patients with major depressive disorder: A resting-state functional connectivity study

The neural correlates of major depressive disorder (MDD) remain disputed. In the absence of reliable biological markers, the dysfunction and interaction of neural networks have been proposed as pathophysiological neural mechanisms in depression. Here, we examined the functional connectivity (FC) of brain networks. 51 healthy volunteers (mean age 33.57 ± 7.80) and 55 individuals diagnosed with MDD (mean age 33.89 ± 11.00) participated by performing a resting-state (rs) fMRI scan. Seed to voxel FC analyses were performed. Compared to healthy control (HC), MDD patients showed higher connectivity between the hippocampus and the anterior cingulate cortex (ACC) and lower connectivity between the insula and the ACC. The MDD group displayed lower connectivity between the inferior parietal lobule (IPL) and the superior frontal gyrus (SFG). The current data replicate previous findings regarding the cortico-limbic network (hippocampus - ACC connection) and the salience network (insula - ACC connection) and provide novel insight into altered rsFC in MDD, in particular involving the hippocampus - ACC and the insula - ACC connection. Furthermore, altered connectivity between the IPL and SFG indicates that the processing in higher cognitive processes such as attention and working memory is affected in MDD. These data further support dysfunctional neuronal networks as an interesting pathophysiological marker in depression.

Beneficial effects and neurobiological aspects of environmental enrichment associated to major depressive disorder and autism spectrum disorder

A suitable enriched environment favors development but can also influence behavior and neuronal circuits throughout development. Studies have shown that environmental enrichment (EE) can be used as an essential tool or combined with conventional treatments to improve psychiatric and neurological symptoms, including major depressive disorder (MDD) and autism spectrum disorder (ASD). Both disorders affect a significant percentage of the world's population and have complex pathophysiology. Moreover, the available treatments for MDD and ASD are still inadequate for many affected individuals. Experimental models demonstrate that EE has significant positive effects on behavioral modulation. In addition, EE has effects on neurobiology, including improvement in synaptic connections and neuroplasticity, modulation of neurotransmissions, a decrease in inflammation and oxidative stress, and other neurobiology effects that can be involved in the pathophysiology of MDD and ASD. Thus, this review aims to describe the leading behavioral and neurobiological effects associated with EE in MDD and ASD.

Contrasting the amygdala activity and functional connectivity profile between antidepressant-free participants with major depressive disorder and healthy controls: A systematic review of comparative fMRI studies

Functional neuroimaging research suggests that the amygdala is implicated in the pathophysiology of major depressive disorder (MDD). This systematic review aimed to identify consistently reported amygdala activity and functional connectivity (FC) abnormalities in antidepressant-free participants with MDD as compared to healthy controls at baseline (i.e., before treatment initiation or experimental manipulation). A search for relevant published studies and registered clinical trials was conducted through OVID (MEDLINE, PsycINFO, and Embase) and ClinicalTrials.gov with an end date of March 7th, 2022. Fifty published studies and two registered clinical trials were included in this review. Participants with MDD frequently exhibited amygdala hyperactivity in response to negative stimuli, abnormal event-related amygdala-anterior cingulate cortex (ACC) FC, and abnormal resting-state amygdala FC with the insula and the prefrontal, temporal, and parietal cortices. Decreased resting-state FC was consistently found between the amygdala and the orbitofrontal cortex, striatum, cerebellum, and middle/inferior frontal gyri. Due to the limited number of studies examining resting-state amygdala activity and FC with specific subregions of interest, including those within the ACC, further investigation is warranted.

Time-varying connectivity of the precuneus and its association with cognition and depressive symptoms in neuromyelitis optica: A pilot MRI study

Background:

The precuneus is involved in cognition and depression; static functional connectivity (SFC) abnormalities of this region have been observed in neuromyelitis optica spectrum disorders (NMOSD). Time-varying functional connectivity (TVC) underpins dynamic variations of brain connectivity.

Objective:

The aim of this study was to explore precuneus SFC and TVC in NMOSD patients and their associations with neuropsychological features.

Methods:

This retrospective study includes 27 NMOSD patients and 30 matched healthy controls undergoing resting state functional magnetic resonance imaging (MRI) and a neuropsychological evaluation of cognitive performance and depressive symptoms. A sliding-window correlation analysis using bilateral precuneus as seed region assessed TVC, which was quantified by the standard deviation of connectivity across windows. Mean connectivity indicated SFC.

Results:

Compared to controls, patients had reduced SFC between precuneus, temporal lobe, putamen and cerebellum, and reduced TVC between precuneus and prefronto-parietal-temporo-occipital cortices and caudate. Patients also had increased intra-precuneal TVC and increased TVC between the precuneus and the temporal cortex. More severe depressive symptoms correlated with increased TVC between the precuneus and the temporal lobe; worse cognitive performance mainly correlated with higher TVC between the precuneus and the parietal lobe.

Conclusion:

TVC rather than SFC of the precuneus correlates with NMOSD neuropsychological features; different TVC abnormalities underlie depressive symptoms and cognitive impairment.

The Laterality of Age-Related Hearing Loss and Depression

OBJECTIVE

There is a known association between hearing loss (HL) and depressive symptoms. The objective was to establish if there is a stronger association with the left or right ear.

STUDY DESIGN

Cross-sectional analysis of an ongoing prospective epidemiologic cohort study.

SETTING

Hispanic Community Health Study (US, multicentered).

PATIENTS

Five thousand three hundred and twenty-eight adults 2:50 years old.

INTERVENTIONS

None.

MAIN OUTCOME MEASURES

The main outcome was depressive symptoms, measured by the 10-Item Center for Epidemiologic Studies Depression Scale-10 (CESD-10) and defined continuously and binarily. Subjects with CESD-10 2: 10 were categorized as having clinically significant depressive symptoms (CSDS). Linear and logistic regressions were performed to assess the association between depressive symptoms and hearing in each ear, controlling for hearing aid use, age, sex, educational level, study site, geographic background, cardiovascular disease, and antidepressant use.

RESULTS

Mean age was 58.5 ± 6.3 years. Mean pure-tone average (PTA) was 20.3 ± 11.7 dB (range = 0 - 125) in the right ear and 20.3 ± 12.4 dB (range = -2.5 to 120) in the left. Multivariable regression adjusting for covariates demonstrated significant associations between depressive symptoms and HL in both the left and right ear. For every 20-dB worsening in right ear PTA, there was 0.89-point increase in CESD-10 (95% confidence interval = 0.59 - 1.2), and odds of CSDS increased 1.31 times (1.17 - 1.46). For every 20-dB worsening in left ear PTA, there was a 0.85-point increase in CESD-10 (0.55 - 1.14), and odds of CSDS increased 1.34 times (1.20 - 1.49).

CONCLUSIONS

Worsening hearing in the right and left ears individually was associated with increased depressive symptoms and odds of CSDS. No ear laterality was demonstrated.

Impaired robust interhemispheric function integration of depressive brain from REST-meta-MDD database in China

BACKGROUND

Recently, functional homotopy (FH) architecture, defined as robust functional connectivity (FC) between homotopic regions, has been frequently reported to be altered in MDD patients (MDDs) but with divergent locations.

METHODS

In this study, we obtained resting-state functional magnetic resonance imaging (R-fMRI) data from 1004 MDDs (mean age, 33.88 years; age range, 18-60 years) and 898 matched healthy controls (HCs) from an aggregated dataset from 20 centers in China. We focused on interhemispheric function integration in MDDs and its correlation with clinical characteristics using voxel-mirrored homotopic connectivity (VMHC) devised to inquire about FH patterns.

RESULTS

As compared with HCs, MDDs showed decreased VMHC in visual, motor, somatosensory, limbic, angular gyrus, and cerebellum, particularly in posterior cingulate gyrus/precuneus (PCC/PCu) (false discovery rate [FDR] q < 0.002, z = -7.07). Further analysis observed that the reduction in SMG and insula was more prominent with age, of which SMG reflected such age-related change in males instead of females. Besides, the reduction in MTG was found to be a male-special abnormal pattern in MDDs. VMHC alterations were markedly related to episode type and illness severity. The higher Hamilton Depression Rating Scale score, the more apparent VMHC reduction in the primary visual cortex. First-episode MDDs revealed stronger VMHC reduction in PCu relative to recurrent MDDs.

CONCLUSIONS

We confirmed a significant VMHC reduction in MDDs in broad areas, especially in PCC/PCu. This reduction was affected by gender, age, episode type, and illness severity. These findings suggest that the depressive brain tends to disconnect information exchange across hemispheres.

Electroconvulsive Therapy for Neuropsychiatric Symptoms due to Major Neurocognitive Disorder: A Prospective, Observational Study

OBJECTIVES

Neuropsychiatric symptoms (NPSs) in those with major neurocognitive disorder (MNCD) include the responsive behaviors of agitation and aggression. Electroconvulsive therapy (ECT) has shown some effectiveness based on retrospective studies and one open label prospective study. We hypothesized that ECT will reduce NPSs between baseline and after treatment in those with medication-refractory behaviors.

METHOD/DESIGN

This Canadian prospective multicenter study included MNCD patients admitted to geriatric psychiatry units for the management of refractory NPSs. All treatment-refractory participants suffered from advanced MNCD. We conducted the Neuropsychiatric Inventory-Clinician version and the Pittsburgh Agitation Scale at baseline, and during and after the ECT course. A bitemporal or bifrontal ECT series based on dose titration to 1.5 to 2.5 times seizure threshold was administered.

RESULTS

Data were collected for 33 patients with a mean age of 73 and categorized with severe MNCD using the Functional Assessment Staging of Alzheimer's Disease scale (stages 6 and 7). The data showed a drop in mean Neuropsychiatric Inventory-Clinician version from 58.36 to 24.58 (P < 0.0001). Mean Neuropsychiatric Inventory agitation subscale dropped from 7.12 to 3.09 (P = 0.007). Mean Neuropsychiatric Inventory aggression subscale dropped from 6.94 to 0.97 (P < 0.0001). There was a concomitant significant decline in Pittsburgh Agitation Scale scores. No participants dropped out because of intolerance of ECT. One participant died from pneumonia, which did not appear related to ECT.

CONCLUSIONS

In this naturalistic study, ECT was found to be a safe and effective treatment for certain NPSs in people with MNCD. This can translate into improving quality of life.

Is paradoxical sleep setting up innate and acquired complex sensorimotor and adaptive behaviours?: A proposed function based on literature review

We summarize here the progress in identifying the neuronal network as well as the function of paradoxical sleep and the gaps of knowledge that should be filled in priority. The core system generating paradoxical sleep localized in the brainstem is now well identified, and the next step is to clarify the role of the forebrain in particular that of the hypothalamus including the melanin-concentrating hormone neurons and of the basolateral amygdala. We discuss these two options, and also the discovery that cortical activation during paradoxical sleep is restricted to a few limbic cortices activated by the lateral supramammillary nucleus and the claustrum. Such activation nicely supports the findings recently obtained showing that neuronal reactivation occurs during paradoxical sleep in these structures, and induces both memory consolidation of important memory and forgetting of less relevant ones. The question that still remains to be answered is whether paradoxical sleep is playing more crucial roles in processing emotional and procedural than other types of memories. One attractive hypothesis is that paradoxical sleep is responsible for erasing negative emotional memories, and that this function is not properly functioning in depressed patients. On the other hand, the presence of a muscle atonia during paradoxical sleep is in favour of a role in procedural memory as new types of motor behaviours can be tried without harm during the state. In a way, it also fits with the proposed role of paradoxical sleep in setting up the sensorimotor system during development.

Neural Networks to Recognize Patterns in Topographic Images of Cortical Electrical Activity of Patients with Neurological Diseases

Software such as EEGLab has enabled the treatment and visualization of the tracing and cortical topography of the electroencephalography (EEG) signals. In particular, the topography of the cortical electrical activity is represented by colors, which make it possible to identify functional differences between cortical areas and to associate them with various diseases. The use of cortical topography with EEG origin in the investigation of diseases is often not used due to the representation of colors making it difficult to classify the disease. Thus, the analyses have been carried out, mainly, based on the EEG tracings. Therefore, a computer system that recognizes disease patterns through cortical topography can be a solution to the diagnostic aid. In view of this, this study compared five models of Convolutional Neural Networks (CNNs), namely: Inception v3, SqueezeNet, LeNet, VGG-16 and VGG-19, in order to know the patterns in cortical topography images obtained with EEG, in Parkinson's disease, Depression and Bipolar Disorder. SqueezeNet performed better in the 3 diseases analyzed, with Parkinson's disease being better evaluated for Accuracy (88.89%), Precison (86.36%), Recall (91.94%) and F1 Score (89.06%), the other CNNs had less performance. In the analysis of the values of the Area under ROC Curve (AUC), SqueezeNet reached (93.90%) for Parkinson's disease, (75.70%) for Depression and (72.10%) for Bipolar Disorder. We understand that there is the possibility of classifying neurological diseases from cortical topographies with the use of CNNs and, thus, creating a computational basis for the implementation of software for screening and possible diagnostic assistance.

Network Diffusion Embedding Reveals Transdiagnostic Subnetwork Disruption and Potential Treatment Targets in Internalizing Psychopathologies

Network diffusion models are a common and powerful way to study the propagation of information through a complex system and they offer straightforward approaches for studying multimodal brain network data. We developed an analytic framework to identify brain subnetworks with perturbed information diffusion capacity using the structural basis that best maps to resting state functional connectivity and applied it towards a heterogeneous dataset of internalizing psychopathologies (IPs), a set of psychiatric conditions in which similar brain network deficits are found across the swath of the disorders, but a unifying neuropathological substrate for transdiagnostic symptom expression is currently unknown. This research provides preliminary evidence of a transdiagnostic brain subnetwork deficit characterized by information diffusion impairment of the right area 8BM, a key brain region involved in organizing a broad spectrum of cognitive tasks, which may underlie previously reported dysfunction of multiple brain circuits in the IPs. We also demonstrate that models of neuromodulation involving targeting this brain region normalize IP diffusion dynamics towards those of healthy controls. These analyses provide a framework for multimodal methods that identify both brain subnetworks with disrupted information diffusion and potential targets of these subnetworks for therapeutic neuromodulatory intervention based on previously well-characterized methodology.

Use of machine learning in predicting the efficacy of repetitive transcranial magnetic stimulation on treating depression based on functional and structural thalamo-prefrontal connectivity: A pilot study

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive, safe, and efficacious treatment for major depressive disorder (MDD). However, the antidepressant efficacy of rTMS greatly varies across individual patients. Thus, markers that can be used to predict the outcome of rTMS treatment at the individual level must be identified. Thalamo-cortical connectivity was abnormal in patients with MDD, and was normalized after rTMS treatment. In the current study, we investigated whether the resting-state functional and structural thalamo-cortical connectivity could be utilized to predict the rTMS treatment efficacy by employing support vector machine regression analysis. Results showed that the Hamilton Depression Scale scores of patients with MDD decreased after rTMS treatment. The functional connectivity of mediodorsal nucleus with prefrontal cortex predicted the rTMS treatment improvement, whereas the functional connectivity of other thalamic nuclei with cerebral cortex did not predict the treatment efficacy. The brain areas that contributed the most to the prediction were dorsal lateral prefrontal cortex, ventral lateral, and orbital and medial prefrontal areas. The improvement in the outcome of rTMS treatment could also be predicted by the thalamo-prefrontal structural connectivity. No statistically significantly difference in thalamo-cortical connectivity was observed between early improvers and early non-improvers. These results suggested that the thalamo-prefrontal connectivity can predict the rTMS treatment improvement. This study highlighted the crucial role of the thalamo-prefrontal connectivity as a neuroimaging marker in the treatment of depression via rTMS.

Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions

BACKGROUND

Electrophysiological resting state functional connectivity using high density electroencephalography (hdEEG) is gaining momentum. The increased resolution offered by hdEEG, usually either 128 or 256 channels, permits source localization of EEG signals on the cortical surface. However, the number of methodological options for the acquisition and analysis of resting state hdEEG is extremely large. These include acquisition duration, eyes open/closed, channel density, source localization methods, and functional connectivity metric.

NEW METHODS

We undertake an extensive examination of the test-retest reliability and methodological agreement of all these options for regional measures of functional connectivity.

RESULTS

Power envelope connectivity shows larger test-retest reliability than imaginary coherence across all bands. While channel density doesn't strongly impact reliability or agreement, source localization methods produce systematically different functional connectivity, highlighting an important obstacle for replicating results in the literature. Most importantly, reliability and agreement often plateaus at or after 6 minutes of acquisition, well beyond the typical duration of 3 minutes. Finally, our study demonstrates that resting EEG can be as or more reliable than resting fMRI acquired in the same individuals.

CONCLUSIONS

The competitive reliability and agreement of power envelope connectivity greatly increases our confidence in measuring resting state connectivity using EEG and its capacity to find individual differences.

Depression Diagnosis Modeling With Advanced Computational Methods: Frequency-Domain eMVAR and Deep Learning

Electroencephalogram (EEG)-based automated depression diagnosis systems have been suggested for early and accurate detection of mood disorders. EEG signals are highly irregular, nonlinear, and nonstationary in nature and are traditionally studied from a linear viewpoint by means of statistical and frequency features. Since, linear metrics present certain limitations and nonlinear methods have proven to be an efficient tool in understanding the complexities of the brain in the identification of underlying behavior of biological signals, such as electrocardiogram, EEG and magnetoencephalogram and thus, can be applied to all nonstationary signals. Various nonlinear algorithms can be used in the analysis of EEG signals. In this research paper, we aim to develop a novel methodology for EEG-based depression diagnosis utilizing 2 advanced computational techniques: frequency-domain extended multivariate autoregressive (eMVAR) and deep learning (DL). We proposed a hybrid method comprising a pretrained ResNet-50 and long-short term memory (LSTM) to capture depression-specific information and compared with a strong conventional machine learning (ML) framework having eMVAR connectivity features. The following 8 causality measures, which interpret the interaction mechanisms among spectrally decomposed oscillations, were used to extract features from multivariate EEG time series: directed coherence (DC), directed transfer function (DTF), partial DC (PDC), generalized PDC (gPDC), extended DC (eDC), delayed DC (dDC), extended PDC (ePDC), and delayed PDC (dPDC). The classification accuracies were 84% with DC, 85% with DTF, 95.3% with PDC, 95.1% with gPDC, 84.8% with eDC, 84.6% with dDC, 84.2% with ePDC, and 95.9% with dPDC for the eMVAR framework. Through a DL framework (ResNet-50 + LSTM), the classification accuracy was achieved as 90.22%. The results demonstrate that our DL methodology is a competitive alternative to the strong feature extraction-based ML methods in depression classification.

Abnormal core functional connectivity on the pathology of MDD and antidepressant treatment: A systematic review

RATIONALE/IMPORTANCE

Researches have highlighted communication deficits between resting-state brain networks in major depressive disorder (MDD), as reflected in abnormal functional connectivity (FC). However, it is unclear whether impaired FC is associated with MDD pathology or is simply incidental to MDD symptoms. Moreover, there is no generalized theory to analyze the impact of treatment modalities on MDD.

OBJECTIVES

To address the issues, we conducted a systematic review of 49 eligible papers to provide insight into the pathological mechanisms of MDD patients by summarizing resting-state FC alterations involving mood and cognitive abnormalities and the effects of medications on them.

RESULTS

Mood disorders in MDD were characterized by abnormal FC between the amygdala, insula, anterior cingulate cortex (ACC), and prefrontal cortex (PFC). Cognitive impairment manifests as deficits in executive function, attention, memory, and rumination, primarily modulated by dysfunction between the fronto-parietal network and default mode network. Especially, we proposed the set of core abnormal FC (CA-FC) contributing to mood and cognitive impairment in MDD, currently including ACC-left precuneus/amygdala, rostral ACC-left dorsolateral PFC, left subgenual ACC-left cerebellar, left PFC- anterior subcallosal, and left precuneus-left pulvinar. After treatment, patients with normalized CA-FC showed remission of depressive symptoms.

CONCLUSIONS

We propose a CA-FC set for possible causative principle of MDD, which unifies the FC results from specific, difficult-to-analyze conditions into one outcome set for screening. Furthermore, CA-FC varies from person to person, and the low success rate of a single treatment may be due to the inability to cover too many CA-FC.