Theta burst stimulation for depression: a systematic review and network and pairwise meta-analysis.

In clinical practice, theta burst stimulation (TBS) presents as a more efficient and potentially more effective therapeutic modality than conventional repetitive transcranial magnetic stimulation (rTMS), as it allows for the delivery of more stimuli in less time and at similar intensities. To date, accelerated treatment plans according to various continuous (cTBS) and intermittent TBS (iTBS) protocols for depression have been proposed. To investigate which of the TBS protocols provided a favorable risk-benefit balance for individuals with depression, this systematic review and random-effects model network meta-analysis was conducted. The study outcomes included response rate (primary), depression symptom improvement, remission rate, all-cause discontinuation rate, incidence of switch to mania, and incidence of headache/discomfort at treatment site. In this meta-analysis, a total of 23 randomized controlled trials (n = 960, mean age = 41.88 years, with 60.78% females) were included. Approximately 69.57% of the trials included individuals with an exclusive diagnosis of major depressive disorder. The following six TBS protocols (target) were evaluated: cTBS (right-dorsolateral prefrontal cortex [R-DLPFC]), cTBS (R-DLPFC) + iTBS (left-DLPFC [L-DLPFC]), iTBS (L-DLPFC), iTBS (L-DLPFC) + iTBS (R-DLPFC), iTBS (left-dorsomedial prefrontal cortex) + iTBS (right-dorsomedial prefrontal cortex), and iTBS (occipital lobe). Compared to sham, cTBS (R-DLPFC) + iTBS (L-DLPFC), iTBS (L-DLPFC), and iTBS (occipital lobe) had a higher response rate (k = 23); cTBS (R-DLPFC) + iTBS (L-DLPFC) and iTBS (L-DLPFC) dominated in the depression symptom improvement (k = 23); and iTBS (L-DLPFC) had a higher remission rate (k = 15). No significant differences were found for all-cause discontinuation rate (k = 17), incidence of switch to mania (k = 7), and incidence of headache/discomfort at treatment site (k = 10) between any TBS protocols and sham. Thus, cTBS (R-DLPFC) + iTBS (L-DLPFC) and iTBS (L-DLPFC) demonstrate favorable risk-benefit balance for the treatment of depression.

Bioinformatics Analysis Reveals E6 and E7 of HPV 16 Regulate Metabolic Reprogramming in Cervical Cancer, Head and Neck Cancer, and Colorectal Cancer through the PHD2-VHL-CUL2-ELOC-HIF-1α Axis.

Human papillomavirus 16 (HPV 16) infection is associated with several types of cancer, such as head and neck, cervical, anal, and penile cancer. Its oncogenic potential is due to the ability of the E6 and E7 oncoproteins to promote alterations associated with cell transformation. HPV 16 E6 and E7 oncoproteins increase metabolic reprogramming, one of the hallmarks of cancer, by increasing the stability of hypoxia-induced factor 1 α (HIF-1α) and consequently increasing the expression levels of their target genes. In this report, by bioinformatic analysis, we show the possible effect of HPV 16 oncoproteins E6 and E7 on metabolic reprogramming in cancer through the E6-E7-PHD2-VHL-CUL2-ELOC-HIF-1α axis. We proposed that E6 and E7 interact with VHL, CUL2, and ELOC in forming the E3 ubiquitin ligase complex that ubiquitinates HIF-1α for degradation via the proteasome. Based on the information found in the databases, it is proposed that E6 interacts with VHL by blocking its interaction with HIF-1α. On the other hand, E7 interacts with CUL2 and ELOC, preventing their binding to VHL and RBX1, respectively. Consequently, HIF-1α is stabilized and binds with HIF-1ß to form the active HIF1 complex that binds to hypoxia response elements (HREs), allowing the expression of genes related to energy metabolism. In addition, we suggest an effect of E6 and E7 at the level of PHD2, VHL, CUL2, and ELOC gene expression. Here, we propose some miRNAs targeting PHD2, VHL, CUL2, and ELOC mRNAs. The effect of E6 and E7 may be the non-hydroxylation and non-ubiquitination of HIF-1α, which may regulate metabolic processes involved in metabolic reprogramming in cancer upon stabilization, non-degradation, and translocation to the nucleus.

Motor performance and functional connectivity between the posterior cingulate cortex and supplementary motor cortex in bipolar and unipolar depression.

Although implicated in unsuccessful treatment, psychomotor deficits and their neurobiological underpinnings in bipolar (BD) and unipolar (UD) depression remain poorly investigated. Here, we hypothesized that motor performance deficits in depressed patients would relate to basal functional coupling of the hand primary motor cortex (M1) and the posterior cingulate cortex (PCC) with the supplementary motor area (SMA). We performed a longitudinal, naturalistic study in BD, UD and matched healthy controls comprising of two resting-state functional MRI measurements five weeks apart and accompanying assessments of motor performance using a finger tapping task (FTT). A subject-specific seed-based analysis describing functional connectivity between PCC-SMA as well as M1-SMA was conducted. The basal relationships with motor performance were investigated using linear regression models and all measures were compared across groups. Performance in FTT was impaired in BD in comparison to HC in both sessions. Behavioral performance across groups correlated significantly with resting state functional coupling of PCC-SMA, but not of M1-SMA regions. This relationship was partially reflected in a reduced PCC-SMA connectivity in BD vs HC in the second session. Exploratory evaluation of large-scale networks coupling (SMN-DMN) exhibited no correlation to motor performance. Our results shed new light on the association between the degree of disruption in the SMA-PCC anticorrelation and the level of motor impairment in BD.

Estimating uncertainty in read-out patterns: Application to controls-based denoising and voxel-based morphometry patterns in neurodegenerative and neuropsychiatric diseases.

Quantifying pathology-related patterns in patient data with pattern expression score (PES) is a standard approach in medical image analysis. In order to estimate the PES error, we here propose to express the uncertainty contained in read-out patterns in terms of the expected squared Euclidean distance between the read-out pattern and the unknown "true" pattern (squared standard error of the read-out pattern, SE2 ). Using SE2 , we predicted and optimized the net benefit (NBe) of the recently suggested method controls-based denoising (CODE) by weighting patterns of nonpathological variance (NPV). Multi-center MRI (1192 patients with various neurodegenerative and neuropsychiatric diseases, 1832 healthy controls) were analysed with voxel-based morphometry. For each pathology, accounting for SE2 , NBe correctly predicted classification improvement and allowed to optimize NPV pattern weights. Using these weights, CODE improved classification performances in all but one analyses, for example, for prediction of conversion to Alzheimer's disease (AUC 0.81 vs. 0.75, p = .01), diagnosis of autism (AUC 0.66 vs. 0.60, p < .001), and of major depressive disorder (AUC 0.62 vs. 0.50, p = .03). We conclude that the degree of uncertainty in a read-out pattern should generally be reported in PES-based analyses and suggest using weighted CODE as a complement to PES-based analyses.

TET Enzymes and 5hmC Levels in Carcinogenesis and Progression of Breast Cancer: Potential Therapeutic Targets.

Breast Cancer (BC) was the most common female cancer in incidence and mortality worldwide in 2020. Similarly, BC was the top female cancer in the USA in 2022. Risk factors include earlier age at menarche, oral contraceptive use, hormone replacement therapy, high body mass index, and mutations in BRCA1/2 genes, among others. BC is classified into Luminal A, Luminal B, HER2-like, and Basal-like subtypes. These BC subtypes present differences in gene expression signatures, which can impact clinical behavior, treatment response, aggressiveness, metastasis, and survival of patients. Therefore, it is necessary to understand the epigenetic molecular mechanism of transcriptional regulation in BC, such as DNA demethylation. Ten-Eleven Translocation (TET) enzymes catalyze the oxidation of 5-methylcytosine (5mC) to 5-hydroxymethylcytosine (5hmC) on DNA, which in turn inhibits or promotes the gene expression. Interestingly, the expression of TET enzymes as well as the levels of the 5hmC epigenetic mark are altered in several types of human cancers, including BC. Several studies have demonstrated that TET enzymes and 5hmC play a key role in the regulation of gene expression in BC, directly (dependent or independent of DNA de-methylation) or indirectly (via interaction with other proteins such as transcription factors). In this review, we describe our recent understanding of the regulatory and physiological function of the TET enzymes, as well as their potential role as biomarkers in BC biology.

Regional gene expression patterns are associated with task-specific brain activation during reward and emotion processing measured with functional MRI.

The exploration of the spatial relationship between gene expression profiles and task-evoked response patterns known to be altered in neuropsychiatric disorders, for example depression, can guide the development of more targeted therapies. Here, we estimated the correlation between human transcriptome data and two different brain activation maps measured with functional magnetic resonance imaging (fMRI) in healthy subjects. Whole-brain activation patterns evoked during an emotional face recognition task were associated with topological mRNA expression of genes involved in cellular transport. In contrast, fMRI activation patterns related to the acceptance of monetary rewards were associated with genes implicated in cellular localization processes, metabolism, translation, and synapse regulation. An overlap of these genes with risk genes from major depressive disorder genome-wide association studies revealed the involvement of the master regulators TCF4 and PAX6 in emotion and reward processing. Overall, the identification of stable relationships between spatial gene expression profiles and fMRI data may reshape the prospects for imaging transcriptomics studies.

Suicidality and relief of depressive symptoms with intermittent theta burst stimulation in a sham-controlled randomized clinical trial.

OBJECTIVES: Suicidality is a serious public health problem and is closely associated with the severity of depression. In this work, we examined the effects of accelerated intermittent theta burst stimulation (iTBS) on suicidal status, risk factors for suicide, and severity of depressive symptoms in subjects with major depressive disorder (MDD). METHODS: We present data from a quadruple-blind (patient, care provider, investigator, rater) sham-controlled crossover randomized clinical trial. During a 6-week observation period, each participant underwent 2 weeks of stimulation - each week with 20 sessions of active or sham iTBS. A suicide score was created using a composite of individual items from Montgomery-Åsberg Depression Scale (MADRS), Hamilton Depression Scale, and Beck Depression Inventory. The severity of depression was determined by MADRS total scores. In addition, we used demographic and Columbia Suicidality Rating Scale information to assess suicide risk. RESULTS: Among 81 participants, we observed a significant reduction in suicidality and this change was positively correlated with a change in depressive symptoms. A significant difference between active and sham iTBS provided evidence for antidepressant effects. Higher changes in levels of anxiety and impulsiviness also correlated with larger changes in suicidality. CONCLUSIONS: As neither suicide nor other serious adverse events were evidenced, this intervention was a safe and viable procedure to reduce suicidality and severity of depressive symptoms. Moreover, we identified more pronounced anti-suicidal effects in those with higher risk profiles. Unlike MADRS, composite suicidal scores did not provide evidence of an effect between stimulation conditions in this crossover design study. Even so, based on our promising results, parallel and larger studies could contribute to a better characterization of the anti-suicidal placebo effect and the benefit of using iTBS against suicidal symptoms.

From Sensor Data to Educational Insights.

Technology is gradually becoming an integral part of learning at all levels of educational [...].

A new, reliable, and high-throughput strategy to screen bacteria for antagonistic activity against Staphylococcus aureus.

BACKGROUND: Antibiotic-resistant Staphylococcus aureus clones have emerged globally over the last few decades. Probiotics have been actively studied as an alternative to antibiotics to prevent and treat S. aureus infections, but identifying new probiotic bacteria, that have antagonistic activity against S. aureus, is difficult since traditional screening strategies are time-consuming and expensive. Here, we describe a new plasmid-based method which uses highly stable plasmids to screen bacteria with antagonistic activity against S. aureus. RESULTS: We have created two recombinant plasmids (pQS1 and pQS3) which carry either gfpbk or mCherry under the control of a S. aureus quorum-sensing (QS) promoter (agrP3). Using this recombinant plasmid pair, we tested 81 bacteria isolated from Holstein dairy milk to identify bacteria that had growth-inhibiting activity against S. aureus and suggest potential explanations for the growth inhibition. The stability test illustrated that pQS1 and pQS3 remained highly stable for at least 24 h in batch culture conditions without selection pressure from antibiotics. This allowed co-culturing of S. aureus with other bacteria. Using the newly developed pQS plasmids, we found commensal bacteria, isolated from raw bovine milk, which had growth-inhibiting activity (n = 13) and quorum-quenching (QQ) activity (n = 13) towards both S. aureus Sa25 (CC97) and Sa27 (CC151). The pQS-based method is efficient and effective for simultaneously screening growth-inhibiting and QQ bacteria against S. aureus on agar media. CONCLUSIONS: It was shown that growth-inhibiting and QQ activity toward pQS plasmid transformants of S. aureus can be simultaneously monitored by observing the zone of growth inhibition and reporter protein inhibition on agar plates. Newly identified antagonistic bacteria and their functional biomolecules are promising candidates for future development of probiotic drugs and prophylactics/therapeutics for bacterial infections including S. aureus. Furthermore, this new approach can be a useful method to find bacteria that can be used to prevent and treat S. aureus infections in both humans and animals.

Transcranial Magnetic and Direct Current Stimulation in the Treatment of Depression: Basic Mechanisms and Challenges of Two Commonly Used Brain Stimulation Methods in Interventional Psychiatry.

Noninvasive neuromodulation, including repetitive trans-cranial magnetic stimulation (rTMS) and direct current stimulation (tDCS), provides researchers and health care professionals with the ability to gain unique insights into brain functions and treat several neurological and psychiatric conditions. Undeniably, the number of published research and clinical papers on this topic is increasing exponentially. In parallel, several methodological and scientific caveats have emerged in the transcranial stimulation field; these include less robust and reliable effects as well as contradictory clinical findings. These inconsistencies are maybe due to the fact that research exploring the relationship between the methodological aspects and clinical efficacy of rTMS and tDCS is far from conclusive. Hence, additional work is needed to understand the mechanisms underlying the effects of magnetic stimulation and low-intensity transcranial electrical stimulation (TES) in order to optimize dosing, methodological designs, and safety aspects.

Polymeric synthetic nanoparticles for the induction of antigen-specific immunological tolerance.

Current treatments to control pathological or unwanted immune responses often use broadly immunosuppressive drugs. New approaches to induce antigen-specific immunological tolerance that control both cellular and humoral immune responses are desirable. Here we describe the use of synthetic, biodegradable nanoparticles carrying either protein or peptide antigens and a tolerogenic immunomodulator, rapamycin, to induce durable and antigen-specific immune tolerance, even in the presence of potent Toll-like receptor agonists. Treatment with tolerogenic nanoparticles results in the inhibition of CD4+ and CD8+ T-cell activation, an increase in regulatory cells, durable B-cell tolerance resistant to multiple immunogenic challenges, and the inhibition of antigen-specific hypersensitivity reactions, relapsing experimental autoimmune encephalomyelitis, and antibody responses against coagulation factor VIII in hemophilia A mice, even in animals previously sensitized to antigen. Only encapsulated rapamycin, not the free form, could induce immunological tolerance. Tolerogenic nanoparticle therapy represents a potential novel approach for the treatment of allergies, autoimmune diseases, and prevention of antidrug antibodies against biologic therapies.

Disruptions in the left frontoparietal network underlie resting state endophenotypic markers in schizophrenia.

Advances in functional brain imaging have improved the search for potential endophenotypic markers in schizophrenia. Here, we employed independent component analysis (ICA) and dynamic causal modeling (DCM) in resting state fMRI on a sample of 35 schizophrenia patients, 20 first-degree relatives and 35 control subjects. Analysis on ICA-derived networks revealed increased functional connectivity between the left frontoparietal network (FPN) and left temporal and parietal regions in schizophrenia patients (P < 0.001). First-degree relatives shared this hyperconnectivity, in particular in the supramarginal gyrus (SMG; P = 0.008). DCM analysis was employed to further explore underlying effective connectivity. Results showed increased inhibitory connections to the left angular gyrus (AG) in schizophrenia patients from all other nodes of the left FPN (P < 0.001), and in particular from the left SMG (P = 0.001). Relatives also showed a pattern of increased inhibitory connections to the left AG (P = 0.008). Furthermore, the patient group showed increased excitatory connectivity between the left fusiform gyrus and the left SMG (P = 0.002). This connection was negatively correlated to inhibitory afferents to the left AG (P = 0.005) and to the negative symptom score on the PANSS scale (P = 0.001, r = -0.51). Left frontoparietotemporal dysfunction in schizophrenia has been previously associated with a range of abnormalities, including formal thought disorder, working memory dysfunction and sensory hallucinations. Our analysis uncovered new potential endophenotypic markers of schizophrenia and shed light on the organization of the left FPN in patients and their first-degree relatives. Hum Brain Mapp 38:1741-1750, 2017. © 2017 Wiley Periodicals, Inc.

CREB1 Genotype Modulates Adaptive Reward-Based Decisions in Humans.

Cyclic AMP response element-binding protein (CREB) contributes to adaptation of mesocorticolimbic networks by modulating activity-regulated transcription and plasticity in neurons. Activity or expression changes of CREB in the nucleus accumbens (NAc) and orbital frontal cortex (OFC) interact with behavioral changes during reward-motivated learning. However, these findings from animal models have not been evaluated in humans. We tested whether CREB1 genotypes affect reward-motivated decisions and related brain activation, using BOLD fMRI in 224 young and healthy participants. More specifically, participants needed to adapt their decision to either pursue or resist immediate rewards to optimize the reward outcome. We found significant CREB1 genotype effects on choices to pursue increases of the reward outcome and on BOLD signal in the NAc, OFC, insula cortex, cingulate gyrus, hippocampus, amygdala, and precuneus during these decisions in comparison with those decisions avoiding total reward loss. Our results suggest that CREB1 genotype effects in these regions could contribute to individual differences in reward- and associative memory-based decision-making.

Differentiating unipolar and bipolar depression by alterations in large-scale brain networks.

BACKGROUND: Misdiagnosing bipolar depression can lead to very deleterious consequences of mistreatment. Although depressive symptoms may be similarly expressed in unipolar and bipolar disorder, changes in specific brain networks could be very distinct, being therefore informative markers for the differential diagnosis. We aimed to characterize specific alterations in candidate large-scale networks (frontoparietal, cingulo-opercular, and default mode) in symptomatic unipolar and bipolar patients using resting state fMRI, a cognitively low demanding paradigm ideal to investigate patients. METHODS: Networks were selected after independent component analysis, compared across 40 patients acutely depressed (20 unipolar, 20 bipolar), and 20 controls well-matched for age, gender, and education levels, and alterations were correlated to clinical parameters. RESULTS: Despite comparable symptoms, patient groups were robustly differentiated by large-scale network alterations. Differences were driven in bipolar patients by increased functional connectivity in the frontoparietal network, a central executive and externally-oriented network. Conversely, unipolar patients presented increased functional connectivity in the default mode network, an introspective and self-referential network, as much as reduced connectivity of the cingulo-opercular network to default mode regions, a network involved in detecting the need to switch between internally and externally oriented demands. These findings were mostly unaffected by current medication, comorbidity, and structural changes. Moreover, network alterations in unipolar patients were significantly correlated to the number of depressive episodes. CONCLUSION: Unipolar and bipolar groups displaying similar symptomatology could be clearly distinguished by characteristic changes in large-scale networks, encouraging further investigation of network fingerprints for clinical use. Hum Brain Mapp 37:808-818, 2016. © 2015 Wiley Periodicals, Inc.

Imbalance in subregional connectivity of the right temporoparietal junction in major depression.

Major depressive disorder (MDD) involves impairment in cognitive and interpersonal functioning. The right temporoparietal junction (RTPJ) is a key brain region subserving cognitive-attentional and social processes. Yet, findings on the involvement of the RTPJ in the pathophysiology of MDD have so far been controversial. Recent connectivity-based parcellation data revealed a topofunctional dualism within the RTPJ, linking its anterior and posterior part (aRTPJ/pRTPJ) to antagonistic brain networks for attentional and social processing, respectively. Comparing functional resting-state connectivity of the aRTPJ and pRTPJ in 72 MDD patients and 76 well-matched healthy controls, we found a seed (aRTPJ/pRTPJ) × diagnosis (MDD/controls) interaction in functional connectivity for eight regions. Employing meta-data from a large-scale neuroimaging database, functional characterization of these regions exhibiting differentially altered connectivity with the aRTPJ/pRTPJ revealed associations with cognitive (dorsolateral prefrontal cortex, parahippocampus) and behavioral (posterior medial frontal cortex) control, visuospatial processing (dorsal visual cortex), reward (subgenual anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex), as well as memory retrieval and social cognition (precuneus). These findings suggest that an imbalance in connectivity of subregions, rather than disturbed connectivity of the RTPJ as a whole, characterizes the connectional disruption of the RTPJ in MDD. This imbalance may account for key symptoms of MDD in cognitive, emotional, and social domains. Hum Brain Mapp 37:2931-2942, 2016. © 2016 Wiley Periodicals, Inc.

Dissociating pathomechanisms of depression with fMRI: bottom-up or top-down dysfunctions of the reward system.

Depression is a debilitating psychiatric disorder characterized among other aspects by the inability to properly experience or respond to reward. However, it remains unclear whether patients with depression present impaired reward system due to abnormal modulatory mechanisms. We investigated the activation of the nucleus accumbens (NAcc), a crucial region involved in reward processing, with functional magnetic resonance imaging using the desire-reason-dilemma paradigm. This task allows tracking the activity of the NAcc during the acceptance or the rejection of previously conditioned reward stimuli. Patients were assigned into subgroups of lower (LA) or higher (HA) NAcc activation according to beta weights. LA patients presented significant hypoactivation in the ventral tegmental area in addition to bilateral ventral striatum, confirming impairments in the bottom-up input to the NAcc. Conversely, HA patients presented significant hyperactivation in prefrontal areas such as the rostral anterior cingulate cortex and the anterior ventral prefrontal cortex in addition to bilateral ventral striatum, suggesting disturbances in the top-down regulation of the NAcc. Demographic and clinical differences explaining the abnormal co-activations of midbrain and prefrontal regions were not identified. Therefore, we provide evidence for dysfunctional bottom-up processing in one potential neurobiological subtype of depression (LA) and dysfunctional top-down modulation in another subtype (HA). We suggest that the midbrain and prefrontal regions are more specific pathophysiological substrates for each depression subtype. Above all, our results encourage the segregation of patients by similar dysfunctional mechanisms of the dopaminergic system, which would finally contribute to disentangle more specific pathogeneses and guide the development of more personalized targets for future therapies.

Antimalarial Drug Combination Predictions Using the Machine Learning Synergy Predictor (MLSyPred©) tool.

PURPOSE: Antimalarial drug resistance is a global public health problem that leads to treatment failure. Synergistic drug combinations can improve treatment outcomes and delay the development of drug resistance. Here, we describe the implementation of a freely available computational tool, Machine Learning Synergy Predictor (MLSyPred©), to predict potential synergy in antimalarial drug combinations. METHODS: The MLSyPred© synergy prediction method extracts molecular fingerprints from the drugs' biochemical structures to use as features and also cleans and prepares the raw data. Five machine learning algorithms (Logistic Regression, Random Forest, Support vector machine, Ada Boost, and Gradient Boost) were implemented to build prediction models. Implementation and application of the MLSyPred© tool were tested using datasets from 1540 combinations of 79 drugs and compounds biologically evaluated in pairs for three strains of Plasmodium falciparum (3D7, HB3, and Dd2). RESULTS: The best prediction models were obtained using Logistic Regression for antimalarials with the strains Dd2 and HB3 (0.81 and 0.70 AUC, respectively) and Random Forest for antimalarials with 3D7 (0.69 AUC). The MLSyPred© tool yielded 45% precision for synergistically predicted antimalarial drug combinations that were annotated and biologically validated, thus confirming the functionality and applicability of the tool. CONCLUSION:  The MLSyPred© tool is freely available and represents a promising strategy for discovering potential synergistic drug combinations for further development as novel antimalarial therapies.

Unexpected role of clathrin adaptor AP-1 in MHC-dependent positive selection of T cells.

Trafficking of transmembrane receptors to a specific intracellular compartment is conducted by adaptor molecules that bind to target motifs within the cytoplasmic domains of cargo proteins. We generated mice containing a lymphoid-specific deficiency of AP-1 using RNAi knockdown technology. Inhibition of AP-1 expression in thymocytes blocks progression from double-positive immature thymocytes, resulting in complete absence of CD4(+) single-positive thymocytes and severe reduction of CD3(+)CD8(+) single-positive thymocytes. Analysis of the contribution of AP-1 deficiency on the interaction between mature CD4(+) T cells and antigen-presenting cells revealed that AP-1 is essential to efficient immune synapse formation and associated T cell activation, suggesting a possible mechanism of AP-1 function in thymocyte development.

Brain connectivity in major depressive disorder: a precision component of treatment modalities?

Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an enormous burden on individuals, society, and health care systems. Most patients benefit from commonly used treatment methods such as pharmacotherapy, psychotherapy, electroconvulsive therapy (ECT), and repetitive transcranial magnetic stimulation (rTMS). However, the clinical decision on which treatment method to use remains generally informed and the individual clinical response is difficult to predict. Most likely, a combination of neural variability and heterogeneity in MDD still impedes a full understanding of the disorder, as well as influences treatment success in many cases. With the help of neuroimaging methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the brain can be understood as a modular set of functional and structural networks. In recent years, many studies have investigated baseline connectivity biomarkers of treatment response and the connectivity changes after successful treatment. Here, we systematically review the literature and summarize findings from longitudinal interventional studies investigating the functional and structural connectivity in MDD. By compiling and discussing these findings, we recommend the scientific and clinical community to deepen the systematization of findings to pave the way for future systems neuroscience roadmaps that include brain connectivity parameters as a possible precision component of the clinical evaluation and therapeutic decision.

Subject-specific whole-brain parcellations of nodes and boundaries are modulated differently under 10 Hz rTMS.

Repetitive transcranial magnetic stimulation (rTMS) has gained considerable importance in the treatment of neuropsychiatric disorders, including major depression. However, it is not yet understood how rTMS alters brain's functional connectivity. Here we report changes in functional connectivity captured by resting state functional magnetic resonance imaging (rsfMRI) within the first hour after 10 Hz rTMS. We apply subject-specific parcellation schemes to detect changes (1) in network nodes, where the strongest functional connectivity of regions is observed, and (2) in network boundaries, where functional transitions between regions occur. We use support vector machine (SVM), a widely used machine learning algorithm that is robust and effective, for the classification and characterization of time intervals of changes in node and boundary maps. Our results reveal that changes in connectivity at the boundaries are slower and more complex than in those observed in the nodes, but of similar magnitude according to accuracy confidence intervals. These results were strongest in the posterior cingulate cortex and precuneus. As network boundaries are indeed under-investigated in comparison to nodes in connectomics research, our results highlight their contribution to functional adjustments to rTMS.