Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/426866

Comparative efficacy and acceptability of non-surgical brain stimulation for the acute treatment of adult major depressive episodes: A systematic review and network meta-analysis of 113 randomised clinical trials

Mutz, J.·Vipulananthan, V.·Carter, B.·Hurlemann, R.·Fu, C. H. Y.·Young, A. H.
View original source ↗Export metadata ↓

Abstract

Background: Non-surgical brain stimulation techniques have been applied as tertiary treatments in major depression. However, the relative efficacy and acceptability of individual protocols is uncertain. Our aim was to estimate the comparative clinical efficacy and acceptability of non-surgical brain stimulation for the acute treatment of major depressive episodes in adults.\n\nMethods: Embase, PubMed/MEDLINE and PsycINFO were searched up until May 8, 2018, supplemented by manual searches of bibliographies of recent reviews and included trials. We included clinical trials with random allocation to electroconvulsive therapy (ECT), repetitive transcranial magnetic stimulation (rTMS), accelerated TMS (aTMS), priming TMS (pTMS), deep TMS (dTMS), theta burst stimulation (TBS), synchronised TMS (sTMS), magnetic seizure therapy (MST) or transcranial direct current stimulation (tDCS) protocols or sham. Data were extracted from published reports and outcomes were synthesised using pairwise and network random-effects meta-analysis. Primary outcomes were response (efficacy) and all-cause discontinuation (acceptability). We computed odds ratios (OR) with 95% confidence intervals (CI). Remission and continuous post-treatment depression severity scores were also examined.\n\nResults: 113 trials (262 treatment arms) randomising 6,750 patients (mean age = 47.9 years; 59% female) with major depressive disorder or bipolar depression met our inclusion criteria. In terms of efficacy, 10 out of 18 treatment protocols were associated with higher response relative to sham in network meta-analysis: bitemporal ECT (OR=8.91, 95%CI 2.57-30.91), high-dose right-unilateral ECT (OR=7.27, 1.90-27.78), pTMS (OR=6.02, 2.21-16.38), MST (OR=5.55, 1.06-28.99), bilateral rTMS (OR=4.92, 2.93-8.25), bilateral TBS (OR=4.44, 1.47-13.41), low-frequency right rTMS (OR=3.65, 2.13-6.24), intermittent TBS (OR=3.20, 1.45-7.08), high-frequency left rTMS (OR=3.17, 2.29-4.37) and tDCS (OR=2.65, 1.55-4.55). Comparing active treatments, bitemporal ECT and high-dose right-unilateral ECT were associated with increased response. All treatment protocols were at least as acceptable as sham treatment.\n\nConclusion: We found that non-surgical brain stimulation techniques constitute viable alternative or add-on treatments for adult patients with major depressive episodes. Our findings also highlight the need to consider other patient and treatment-related factors in addition to antidepressant efficacy and acceptability when making clinical decisions; and emphasize important research priorities in the field of brain stimulation.\n\nO_LSTTreatment abbreviationsC_LSTECT = Electroconvulsive Therapy O_LIBF ECT = bifrontal ECT (1)\nC_LIO_LIBT ECT = bitemporal ECT (2)\nC_LIO_LIRUL ECT= right unilateral ECT O_LIH-RUL = high-dose RUL ECT (3)\nC_LIO_LILM-RUL = low to moderate-dose RUL ECT (4)\nC_LI\nC_LI\nrTMS = repetitive Transcranial Magnetic Stimulation O_LIHF-L rTMS = high-frequency rTMS of the left DLPFC (5)\nC_LIO_LIHF-R rTMS = high-frequency rTMS of the right DLPFC (6)\nC_LIO_LILF-R rTMS = low-frequency rTMS of the right DLPFC (7)\nC_LIO_LILF-L rTMS = low-frequency rTMS of the left DLPFC (8)\nC_LIO_LIBL rTMS = bilateral rTMS of the DLPFC (9)\nC_LI\ndTMS = deep Transcranial Magnetic Stimulation (10)\npTMS = priming Transcranial Magnetic Stimulation (11)\naTMS = accelerated Transcranial Magnetic Stimulation (12)\nsTMS = synchronised Transcranial Magnetic Stimulation (13)\nTBS = Theta Burst Stimulation O_LIiTBS = intermittent TBS of the left DLPFC (14)\nC_LIO_LIcTBS = continuous TBS of the right DLPFC (15)\nC_LIO_LIblTBS = bilateral TBS of the DLPFC (16)\nC_LI\nMST = Magnetic Seizure Therapy (17)\ntDCS = transcranial Direct Current Stimulation (18)\n\n\nKey points\n\nQuestion: What is the clinical efficacy and acceptability of non-surgical brain stimulation protocols for the acute treatment of major depressive episodes in adults?\n\nFindings: In this network meta-analysis, 10 out of 18 treatment protocols were associated with higher response rates relative to sham, most notably bitemporal and high-dose right unilateral electroconvulsive therapy. All treatment protocols were at least as acceptable as sham treatment.\n\nMeaning: Non-surgical brain stimulation techniques constitute viable alternative or add-on treatment strategies for adult patients with major depressive episodes.

Source connections

Explore related subjects

neurosciencePreprint

Keep this discovery

BibTeXRIS

Mutz, J., Vipulananthan, V., Carter, B., Hurlemann, R., Fu, C. H. Y., Young, A. H.. 2018-09-27. Comparative efficacy and acceptability of non-surgical brain stimulation for the acute treatment of adult major depressive episodes: A systematic review and network meta-analysis of 113 randomised clinical trials. https://doi.org/10.1101/426866

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗
bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗
bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗