Wellcome Centre for Integrative Neuroimaging

The authors have retracted this article.After conducting replication experiments and reanalysing the original data, the authors discovered that the voltage imaging results, as presented in Figs.3a through 3f and Figs.4a andb, and discussed in the "Neurons gain cross-modal activation" section, are not reproducible.Additional voltage imaging work by the authors and their collaborators, for the conditions associated with Figs.3a through 3d, has not produced robust signals.Furthermore, errors in the pipeline originally used for data analysis could have led to the contamination of the F/F 0 data.A complete reanalysis by the authors of the voltage imaging data independently from the original pipeline did not replicate the original analysis.Although the authors have replicated the behavioural and connectomic data and consider that the general conclusions of the article are substantiated, the authors have no confidence in the voltage imaging data.

Abstract Background High-dose high-intensity upper limb neurorehabilitation can lead to meaningful clinical gains even in chronic stroke, yet substantial variability in recovery remains unexplained. Identifying neurophysiological markers linked to neuroplasticity and recovery could provide mechanistic insights and guide personalised rehabilitation. Objective To characterise stroke-related alterations in β-activity during movement and neural activity at rest and explore associations between brain activity and changes in upper limb clinical outcomes in chronic stroke survivors undergoing three-week high-dose rehabilitation. Methods Electroencephalography (EEG) was recorded during the three-week rehabilitation programme in 40 chronic stroke survivors participating in the Queen Square Upper Limb (QSUL) Programme, as well as in 26 healthy controls. Recordings were taken during passive movement of the affected and unaffected index fingers (∼70 movements per hand) and at rest (∼7 min). Clinical assessments included the Fugl-Meyer Upper Limb Assessment (FM-UE), reflecting impairment-level deficits, and the Chedoke Arm and Hand Activity Inventory (CAHAI-13), capturing real-world upper limb activity, to examine their differential relationships with movement-related β-activity. Results Stroke survivors showed significant improvements in FM-UE and CAHAI scores following the rehabilitation programme (Mean Δ: FM-UE = 7.5, CAHAI = 7.4), exceeding minimum clinically important differences. Compared to controls, stroke survivors exhibited less strong β-event-related desynchronization/synchronization (β-ERD/ERS) during passive movement of the affected and unaffected index finger, with effects lateralised to the lesioned hemisphere. No significant differences at rest were observed between stroke participants and healthy controls. Only improvements in CAHAI, but not FM-UE, were associated with stronger β-ERD (more negative) and stronger β-ERS (more positive) responses during passive movement. Conclusions Stronger movement-related β-activity is associated with improvements in upper limb activity following high-dose high-intensity neurorehabilitation, suggesting β-activity as a potential marker of neuroplasticity.

Abstract Non-invasive measurement of neurotransmitter-specific glucose metabolism in the human brain remains a major challenge, limiting mechanistic insight into excitatory–inhibitory imbalance across neurological and psychiatric disorders. Current methods lack the ability to selectively and precisely resolve neurotransmitter-specific metabolic pathways, particularly GABA, while remaining compatible with clinically feasible acquisitions. Here, we introduce a clinically compatible approach which enables targeted and non-invasive detection of glutamate, GABA, and lactate metabolism in the human brain. Called proton-observed proton-edited ¹³C-magnetic resonance spectroscopy (POPE-¹³C-MRS), the method uses an exogenous ¹³C-glucose probe combined with standard proton radiofrequency hardware and widely available MR pulse sequences. We use a cross-species validation framework to first calibrate POPE-¹³C-MRS in mice and then demonstrate its feasibility in humans at ultra-high field. While in vivo GABA labelling has been previously reported, POPE-¹³C-MRS provides, for the first time, robust access to GABAergic metabolism using standard MRI hardware, feasible within clinical constraints, including applicability to deep brain regions. By refining existing indirect ¹H-¹³C-MRS strategies and enabling targeted probing of excitatory and inhibitory metabolic pathways, POPE-¹³C-MRS opens new opportunities for studying neurometabolic coupling and excitatory–inhibitory balance in vivo , with broad implications for translational and clinical neuroscience.

Neuroimaging has revealed that major depression is underpinned by dysfunctional brain networks, with symptom variability stemming from altered interactions within and between brain regions. While the effect of depression severity is well-studied, the effect of depression duration (chronicity) is relatively neglected, despite its clinical significance. This study examined how severity, chronicity, and their interaction affect brain network connectivity and grey matter volume. Forty-six patients (31 females, mean age 40.5) were assessed using whole-brain network modeling and voxel-based morphometry (VBM). Severity was measured via the Hamilton Depression Rating Scale, and chronicity was defined as an episode lasting over 24 months. The key finding was that chronicity moderated the impact of severity on functional connectivity between the Central Executive Network (CEN) and the precuneus (part of the Default Mode Network, DMN). Chronic versus non-chronic patients showed opposite patterns. Non-chronic patients showed stronger CEN-Default Mode Precuneus connectivity at low severity and weaker at high severity; chronic patients showed the reverse. This study reveals a novel impact of chronicity on CEN-DMN interactions, a neglected moderator of brain-symptom severity correlations in depression.

Abstract Highlights We introduce the TMS-RAT, a reporting (assessment) tool for TMS studies Developed within a community-informed, iterative process rating 333 TMS studies Empirically evaluated for usability, inter-rater, and test-retest reliability A validated subset enables reliable retrospective assessment of reporting The modular structure enables use across a wide range of TMS study designs Background A standardised tool for comprehensive reporting can improve transparency, support consistent documentation, and enable comparison across transcranial magnetic stimulation (TMS) studies. The most used reporting checklist lacks clear definitions of full reporting and was not initially evaluated for usability or inter-rater reliability. A scoping review of studies using this checklist shows that its items are reported only 50% of the time, suggesting that method descriptions are often incomplete. Methods We developed the TMS Reporting Assessment Tool (TMS-RAT), a comprehensive reporting framework that provides clear definitions and examples for its items, covering a wide range of TMS protocols. We tested the usability and reliability of the TMS-RAT by rating all studies published between 1991 and 2025 using afferent conditioning (n = 333), a protocol encompassing many reporting categories identified during tool development. Seventeen independent raters contributed across three development phases, a validation phase, and a retest phase, with naïve raters introduced in each phase. Iterative refinements of the tool were informed by inter-rater reliability, qualitative rater feedback, and consultation with external TMS experts. Results We present two versions of the tool: the 72-item TMS-RAT v1.0, designed to guide comprehensive reporting, and the TMS-RAT v1.1, a subset of 50 items with the highest inter-rater (overall AC1 = 0.78, range = [0.60–0.99]) and test-retest reliability (overall AC1 = 0.82, range = [0.65–1.0]), intended for retrospective evaluation of reporting in systematic reviews, meta-analyses. Conclusion The TMS-RAT is a comprehensive, reliable tool that seeks to improve transparency and reproducibility in TMS research.

Transcranial magnetic stimulation (TMS) is a novel approved therapy for treatment-resistant depression. Little is known about its neurocognitive mechanisms of action. The existing literature has focused on resting-state neuroimaging. It therefore remains unknown what information processing changes TMS induces during treatment that drive mood change. Here we tested the hypothesis that transcranial magnetic stimulation (TMS) treatment changes emotional bias, increasing the focus on positive (versus negative) information processing. 49 patients with major depression received 20 daily sessions of open-label intermittent theta-burst TMS to left dorsolateral prefrontal cortex. Emotional bias was measured using behavioural and functional magnetic resonance imaging tasks of emotional face processing, both at baseline and after eight days of treatment. We tested whether early changes in these measures after the first week predicted clinical outcome at the end of treatment (4 weeks). As predicted, an increase in behavioural and neural measures of positive bias after one week predicted clinical response after four weeks of treatment. Behaviourally, response to TMS treatment was associated with a bias towards interpreting ambiguous facial expressions as positive. Neurally, clinical improvement was related to increased neuroimaging response for the contrast of positive versus negative emotional faces in rostral anterior cingulate cortex (rACC), and a positive bias in task-related functional connectivity between rACC and posterior default mode network. These early neurocognitive changes predicted clinical outcomes after four weeks of treatment, beyond early symptom reduction. Thus, clinical response to TMS treatment was linked to increases in positive bias in emotional processing early during treatment which might represent a neurocognitive mechanism of TMS depression treatment, potentially neurally distinct from antidepressant drugs.

Abstract Neuroimaging has revealed that major depression is underpinned by dysfunctional brain networks, with symptom variability stemming from altered interactions within and between brain regions. While the effect of depression severity is well-studied, the effect of depression duration (chronicity) is relatively neglected, despite its clinical significance. This study examined how severity, chronicity, and their interaction affect brain network connectivity and grey matter volume. Forty-six patients (31 females, mean age 40.5) were assessed using whole-brain network modeling and voxel-based morphometry (VBM). Severity was measured via the Hamilton Depression Rating Scale, and chronicity was defined as an episode lasting over 24 months. The key finding was that chronicity moderated the impact of severity on functional connectivity between the Central Executive Network (CEN) and the precuneus (part of the Default Mode Network, DMN). Chronic versus non-chronic patients showed opposite patterns. Non-chronic patients showed stronger CEN-Default Mode Precuneus connectivity at low severity and weaker at high severity; chronic patients showed the reverse. This study reveals a novel impact of chronicity on CEN-DMN interactions, a neglected moderator of brain-symptom severity correlations in depression.

ObjectivesTo investigate the causal relationship between alcohol consumption and dementia.DesignProspective cohort analysis combined with linear and nonlinear Mendelian randomization.SettingTwo large-scale population-based cohorts: the US Million Veteran Program and UK Biobank. Genetic analyses used summary statistics from genome-wide association studies (GWAS).Participants559,559 adults aged 56–72 years at baseline were included in observational analyses (mean follow-up: 4 years in the US cohort; 12 years in the UK cohort). Genetic analyses used summary data from multiple large GWAS consortia (2.4 million participants).Main outcome measuresIncident all-cause dementia, determined through health record linkage, and genetic proxies.ResultsDuring follow-up, 14,540 participants developed dementia and 48,034 died. Observational analyses revealed U-shaped associations between alcohol and dementia risk: higher risk was observed among non-drinkers, heavy drinkers (>40 drinks per week; hazard ratio [HR]=1.41, 95% confidence interval[CI] 1.15-1.74), and those with alcohol use disorder (AUD) (HR=1.51[CI 1.42-1.60]) compared with light drinkers. In contrast, Mendelian randomization analysis identified a monotonic increase in dementia risk with greater alcohol consumption. A two-fold increase in AUD prevalence was associated with a 16% increase in dementia risk (inverse-variance weighted [IVW] OR=1.16[1.03-1.30]). A one standard deviation increase in log-transformed drinks per week was associated with a 15% increase (IVW OR=1.15[1.03-1.27]). Furthermore, individuals who developed dementia experienced a greater decline in alcohol intake over time, suggesting reverse causation—where early cognitive decline leads to reduced alcohol consumption—underlies the protective effects observed in observational studies.ConclusionsThese findings provide evidence for a causal relationship between alcohol use and increased dementia risk. While observational data suggested a protective effect of light drinking, genetic analyses did not support this, indicating that any level of alcohol consumption may contribute to dementia risk. Public health strategies that reduce the prevalence of alcohol use disorder could potentially lower the incidence of dementia by up to 16%.