Associations between contralesional neuroplasticity and motor impairment through deep learning-derived MRI regional brain age in chronic stroke (ENIGMA): a multicohort, retrospective, observational study

The Lancet Digital Health · 2026-01-01

BACKGROUND: Stroke leads to complex chronic structural and functional brain changes that specifically affect motor outcomes. The brain predicted age difference (PAD) has emerged as a sensitive biomarker of both sensorimotor and cognitive function after stroke. Our previous study showed a higher global brain PAD associated with poorer motor function after stroke. However, the association between local stroke lesion load, regional brain age, and motor impairment is unclear. This study aimed to investigate the associations between focal lesion damage, regional brain PAD in both hemispheres, and motor outcomes in chronic stroke, and to identify key predictors of motor impairment. METHODS: In this multicohort, retrospective, observational study, we included individuals with chronic unilateral stroke (>180 days post stroke) from the ENIGMA Stroke Recovery Working Group dataset and used individuals from the UK Biobank cohort to train the regional brain age prediction model. Structural T1-weighted MRI scans were used to estimate regional brain PAD in 18 predefined functional subregions via a graph convolutional network algorithm. Lesion load for each region was calculated on the basis of lesion overlap. Linear mixed-effects models assessed associations between lesion size, local lesion load, and regional brain PAD. Machine learning classifiers predicted motor outcomes using lesion loads and regional brain PADs. Structural equation modelling examined directional relationships among corticospinal tract lesion load, ipsilesional brain PAD, motor outcomes, and contralesional brain PAD. FINDINGS: We included 501 individuals from the ENIGMA Stroke Recovery Working Group dataset (34 cohorts in eight countries) and 17 791 individuals from the UK Biobank dataset. Larger total lesion size was positively associated with higher ipsilesional regional brain PADs (older brain age) across most regions (β=0·5420 to 0·9458 across significantly correlated regions, false discovery rate [FDR]-corrected p<0·05), and with lower brain PAD in the contralesional ventral attention and language network region (β=-0·3747, 95% CI -0·6961 to -0·0534, FDR-corrected p<0·05). Higher local lesion loads showed similar patterns. Specifically, lesion load in the salience network significantly influenced regional brain PADs across both hemispheres. Machine learning models identified corticospinal tract lesion load (adjusted mean difference -0·0905, 95% CI -0·1221 to -0·0589, p<0·0001), salience network lesion load (-0·0632, -0·0906 to -0·0358, p<0·0001), and regional brain PAD in the contralesional frontoparietal network (0·9939, 0·4929 to 1·4950, p=0·0001) as the top three predictors of motor outcomes. Structural equation modelling revealed that higher corticospinal tract lesion load was associated with poorer motor outcomes (β=-0·355, 95% CI -0·446 to -0·267, p<0·0001), which were further linked to younger contralesional brain age (0·204, 0·111 to 0·295, p<0·0001), suggesting that severe motor impairment is linked to compensatory decreases in contralesional brain age. INTERPRETATION: Our findings reveal that larger stroke lesions are associated with accelerated ageing in the ipsilesional hemisphere and paradoxically decelerated brain ageing in the contralesional hemisphere, suggesting compensatory neural mechanisms. Assessing regional brain age might serve as a biomarker for neuroplasticity and inform targeted interventions to enhance motor recovery after stroke. FUNDING: US National Institutes of Health.

Pre-Treatment Heart Rate Dynamics and Their Association with rTMS Treatment Response in Major Depressive Disorder: Evidence from a Concurrent fMRI-EEG-TMS Study

Brain stimulation · 2025-01-01

Background: Major depressive disorder (MDD) is a debilitating and often chronic condition that impacts millions of individuals globally.Pre-treatment biomarkers predicting the outcomes of repetitive Transcranial Magnetic Stimulation (rTMS) treatment for MDD have remained elusive.Recent studies have demonstrated that high-frequency (HF) rTMS can reduce HR in MDD patients and have reported a trend suggesting a correlation between HF-rTMS-induced HR deceleration and treatment outcomes.However, no conclusive evidence directly links HR measures with treatment efficacy.Furthermore, despite its safety and tolerability advantages over HF-rTMS, the impact of single-pulse TMS on HR has yet to be extensively investigated.Objective: We hypothesized that pre-treatment HR (e.g., HR at TMS onset and pulse-induced HR changes) correlates with specific neurophysiological signal changes and clinical outcomes.Methods: We recorded pre-treatment HR using a photoplethysmograph (PPG) concurrently during a simultaneous fMRI-EEG-TMS (fET) session in 25 MDD patients before initiating rTMS treatment.Six runs (276 total pulses) were acquired.Twenty-three patients underwent a six-week daily EEG-guided rTMS treatment (five days per week) over the left dorsolateral prefrontal cortex at 120% of the resting motor threshold.Clinical outcomes were assessed using the Hamilton Rating Scale for Depression (HRSD).Using a generalized linear mixed-effects model, we tested the difference in pre-treatment HR between clinical responders (i.e., more than 50% reduction in HRSD from baseline) and non-responders.Results: Consistent with previous studies, we observe a significant reduction in HR across multiple runs.Additionally, we find that HR significantly correlates with the EEG alpha phase at the TMS onset.Notably, there is a slight instantaneous increase in HR following each TMS pulse, with this increase being significantly greater in responders than non-responders.Conclusion: Changes in HR in response to single-pulse TMS measured prior to treatment may be a promising biomarker for predicting clinical improvement from rTMS in MDD patients.

The clinical efficacy of heart rate as a biomarker for TMS

Transcranial magnetic stimulation . · 2025-06-26

TMS-induced modulation of brain networks and its associations to rTMS treatment for depression: a concurrent fMRI-EEG-TMS study

Brain stimulation · 2025-10-17 · 9 citations

INTRODUCTION: Transcranial magnetic stimulation (TMS) over the left dorsolateral prefrontal cortex (L-DLPFC) is an established intervention for treatment-resistant depression (TRD), yet the underlying therapeutic mechanisms remain not fully understood. METHODS: This study employs an integrative approach that combines TMS with concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), aimed at assessing the acute/immediate effects of TMS on brain network dynamics and their correlation with clinical outcomes. Furthermore, this study explored the brain-state dependent effects of TMS, as the brain-state indexed by the phase of EEG prefrontal alpha oscillation. RESULTS: Our study demonstrates that TMS acutely modulates connectivity within vital brain circuits, particularly the cognitive control and default mode networks. We found that the baseline TMS-evoked responses in the cognitive control and limbic networks significantly predicted clinical improvement in patients receiving a novel EEG-synchronized repetitive TMS treatment. Clinical outcomes in this novel treatment were linked to state-specific TMS-modulated functional connectivity within a pivotal brain circuit of the L-DLPFC and the posterior subgenual anterior cingulate cortex within the limbic system. CONCLUSIONS: These findings contribute to our understanding of the therapeutic effects underlying TMS treatment in depression and support the potential of assessing state-dependent TMS effects. This study emphasizes the importance of personalized timing of TMS for optimizing target engagement of specific clinically relevant brain circuits. Our results are crucial for future research into the development of personalized neuromodulation therapies for TRD patients.

Severe motor impairment is associated with lower contralesional brain age in chronic stroke

medRxiv · 2024-10-28

Background: Stroke leads to complex chronic structural and functional brain changes that specifically affect motor outcomes. The brain-predicted age difference (brain-PAD) has emerged as a sensitive biomarker. Our previous study showed higher global brain-PAD associated with poorer motor function post-stroke. However, the relationship between local stroke lesion load, regional brain age, and motor impairment remains unclear. Methods: We studied 501 individuals with chronic unilateral stroke (>180 days post-stroke) from the ENIGMA Stroke Recovery Working Group dataset (34 cohorts). Structural T1-weighted MRI scans were used to estimate regional brain-PAD in 18 predefined functional subregions via a graph convolutional network algorithm. Lesion load for each region was calculated based on lesion overlap. Linear mixed-effects models assessed associations between lesion size, local lesion load, and regional brain-PAD. Machine learning classifiers predicted motor outcomes using lesion loads and regional brain-PADs. Structural equation modeling examined directional relationships among corticospinal tract lesion load (CST-LL), ipsilesional brain-PAD, motor outcomes, and contralesional brain-PAD. Findings: Larger total lesion size was positively associated with higher ipsilesional regional brain-PADs (older brain age) across most regions (p < 0.05), and with lower contralesional brain-PAD, notably in the ventral attention-language network (p < 0.05). Higher local lesion loads showed similar patterns. Specifically, lesion load in the salience network significantly influenced regional brain-PADs across both hemispheres. Machine learning models identified CST-LL, salience network lesion load, and regional brain-PAD in the contralesional frontoparietal network as the top three predictors of motor outcomes. Structural equation modeling revealed that larger stroke damage was associated with poorer motor outcomes (β = -0.355, p < 0.001), which were further linked to younger contralesional brain age (β = 0.204, p < 0.001), suggesting that severe motor impairment is linked to compensatory decreases in contralesional brain age. Interpretation: Our findings reveal that larger stroke lesions are associated with accelerated aging in the ipsilesional hemisphere and paradoxically decelerated brain aging in the contralesional hemisphere, suggesting compensatory neural mechanisms. Assessing regional brain age may serve as a biomarker for neuroplasticity and inform targeted interventions to enhance motor recovery after stroke. Fundings: Micheal J Fox Foundation, National Institutes of Health, Canadian Institutes of Health Research, National Health and Medical Research Council, Australian Brain Foundation, Wicking Trust, Collie Trust, and Sidney and Fiona Myer Family Foundation, National Heart Foundation, Hospital Israelita Albert Einstein, Australian Research Council Future Fellowship, Wellcome Trust, National Institute for Health Research Imperial Biomedical Research Centre, European Research Council, Deutsche Forschungsgemeinschaft, REACT Pilot, National Resource Center, Research Council of Norway, South-Eastern Norway Regional Health Authority, Norwegian Extra Foundation for Health and Rehabilitation, Sunnaas Rehabilitation Hospital HT, University of Oslo, and VA Rehabilitation Research and Development.

TMS-induced modulation of brain networks and its associations to rTMS treatment for depression: a concurrent fMRI-EEG-TMS study

medRxiv · 2024-12-28 · 4 citations

Transcranial magnetic stimulation (TMS) over the left dorsolateral prefrontal cortex (L-DLPFC) is an established intervention for treatment-resistant depression (TRD), yet the underlying therapeutic mechanisms remain not fully understood. This study employs an integrative approach that combines TMS with concurrent functional magnetic resonance imaging (fMRI) and electroencephalography (EEG), aimed at assessing the acute/immediate effects of TMS on brain network dynamics and their correlation with clinical outcomes. Our study demonstrates that TMS acutely modulates connectivity within vital brain circuits, particularly the cognitive control and default mode networks. We found that the baseline TMS-evoked responses in the cognitive control and limbic networks significantly predicted clinical improvement in patients receiving a novel EEG-synchronized repetitive TMS treatment. Furthermore, this study explored the brain-state dependent effects of TMS, as the brain-state indexed by the phase of EEG prefrontal alpha oscillation. We found that clinical outcomes in this novel treatment are linked to state-specific TMS-modulated functional connectivity within a pivotal brain circuit of the L-DLPFC and the posterior subgenual anterior cingulate cortex within the limbic system. These findings contribute to our understanding of the therapeutic effects underlying TMS treatment in depression and support the potential of assessing state-dependent TMS effects in TMS timing target selection. This study emphasizes the importance of personalized timing of TMS for optimizing target engagement of specific clinically relevant brain circuits. Our results are crucial for future research into the development of personalized neuromodulation therapies for TRD patients.

Whole-brain analysis of concurrent TMS-EEG-fMRI reveals brain-wide state-dependent TMS effects

Brain stimulation · 2023-01-01 · 2 citations

Abstract Introduction: Concurrent TMS-fMRI studies have established the propagation of TMS-induced activity from the left dorsolateral prefrontal cortex (left-DLPFC) to various afferents. However, the state-dependent effect of TMS propagation pathways is less understood. Here, we used concurrent TMS-EEG-fMRI to investigate the dependency of TMS-induced activity on the brain-state (indexed via EEG prefrontal alpha phase). Methods: EEG-fMRI data were acquired from twenty-six major depression patients inside a Siemens 3T Prisma scanner. Single-pulse TMS was delivered to the left-DLPFC (F3 electrode), with inter-trial-intervals drawn from a uniform distribution (4-6 TRs). After preprocessing, prefrontal alpha (6-13 Hz) was extracted from the EEG signals at channels FP1, F3 and F7, and the phase (index of brain-state) at TMS onset was estimated. TMS trials were grouped into four phase bins based on the alpha phase. Then, general linear modeling (GLM) was used to model the BOLD signal at left-DLPFC (stimulation site), with the trials in each phase bin as a separate regressor. For each subject, the phase bins that generated the highest and lowest BOLD response at left-DLPFC were identified as the subject-wise preferred-phase and nonpreferred-phase, respectively. Lastly, whole-brain GLM analysis was performed to identify correlates of the preferred-vs-nonpreferred phase contrast. Results: At the group-level, TMS significantly (p<0.05,FWE-corrected) elevated BOLD signals in various brain regions including dorsal anterior cingulate, thalamus, right-DLPFC, but not left-DLPFC. The preferred-vs-nonpreferred phase contrast analysis identified regions in the lateral frontoparietal network (L-FPN) as significant clusters (p<0.001,uncorrected) including bilateral DLPFC and inferior parietal lobule. Lastly, at the subject-level, to investigate phase contrast effects at left-DLPFC, we permuted trials’ phase bin labels, and the permutation test showed that eleven subjects have significant phase contrast effects at left-DLPFC (p<0.05). Conclusion: The group-level whole-brain analysis suggests that the propagation of TMS-induced BOLD activity from the left-DLPFC to regions in the L-FPN depends on the brain-state. Research Category and Technology and Methods Basic Research: 10. Transcranial Magnetic Stimulation (TMS) Keywords; TMS, EEG, fMRI, MDD

Combined TMS-EEG-fMRI to unravel phase sensitivity of BOLD response

Brain stimulation · 2023-01-01

The timing of transcranial magnetic stimulation relative to the phase of prefrontal alpha EEG modulates downstream target engagement

Brain stimulation · 2023-05-01 · 32 citations

BACKGROUND: The communication through coherence model posits that brain rhythms are synchronized across different frequency bands and that effective connectivity strength between interacting regions depends on their phase relation. Evidence to support the model comes mostly from electrophysiological recordings in animals while evidence from human data is limited. METHODS: Here, an fMRI-EEG-TMS (fET) instrument capable of acquiring simultaneous fMRI and EEG during noninvasive single pulse TMS applied to dorsolateral prefrontal cortex (DLPFC) was used to test whether prefrontal EEG alpha phase moderates TMS-evoked top-down influences on subgenual, rostral and dorsal anterior cingulate cortex (ACC). Six runs (276 total trials) were acquired in each participant. Phase at each TMS pulse was determined post-hoc using single-trial sorting. Results were examined in two independent datasets: healthy volunteers (HV) (n = 11) and patients with major depressive disorder (MDD) (n = 17) collected as part of an ongoing clinical trial. RESULTS: In both groups, TMS-evoked functional connectivity between DLPFC and subgenual ACC (sgACC) depended on the EEG alpha phase. TMS-evoked DLPFC to sgACC fMRI-derived effective connectivity (EC) was modulated by EEG alpha phase in healthy volunteers, but not in the MDD patients. Top-down EC was inhibitory for TMS pulses during the upward slope of the alpha wave relative to TMS timed to the downward slope of the alpha wave. Prefrontal EEG alpha phase dependent effects on TMS-evoked fMRI BOLD activation of the rostral anterior cingulate cortex were detected in the MDD patient group, but not in the healthy volunteer group. DISCUSSION: Results demonstrate that TMS-evoked top-down influences vary as a function of the prefrontal alpha rhythm, and suggest potential clinical applications whereby TMS is synchronized to the brain's internal rhythms in order to more efficiently engage deep therapeutic targets.

Closed-loop phase-locked rTMS treatment decreases global cortical excitability in major depressive disorder patients

Brain stimulation · 2023-01-01 · 1 citations

Abstract Repetitive transcranial magnetic stimulation (rTMS) has been shown to be an effective treatment for major depressive disorder (MDD). Although considerable clinical data have supported its efficacy, its exact mechanism of action and optimal combination of stimulation parameters remains unclear. Recent research suggests that the delivery of rTMS causes long-term inhibition and excitation of neurons in varied brain areas. Additionally, interest has steadily grown for using neurophysiologic measures of cortical excitability as a biomarker for the outcomes of rTMS treatment of MDD. Under the hypothesis that EEG alpha phase is an index of excitation and inhibition across or within a network, our group developed a novel closed-loop system where an rTMS pulse train can be triggered at a specific phase of each patient's prefrontal EEG alpha rhythm to optimize treatment outcomes. Twenty-four MDD patients were randomly assigned to either the phase synchronized or unsynchronized treatment group at the beginning of treatment. Changes in global mean field power were used to characterize cortical excitability in response to rTMS administration. During the six-week daily rTMS treatment period, we observed that global cortical excitability changes within the quasi-alpha band (6-13 Hz) at rest are related to the treatment outcomes for both groups. Notably, the group received synchronized treatment showed higher decreases in cortical excitability after each session compared to the unsynchronized group. More importantly, within the synchronized treatment group, treatment weeks with a greater decrease in Hamilton Rating Scale for Depression showed significant paired (before vs. after daily treatment) excitability decreases. Our findings provide additional evidence for the hypothesis that changes in excitability are related to the mechanism of action of rTMS, and cortical excitability can serve as a reliable biomarker in rTMS treatment outcomes. Moreover, our closed-loop phase-locking rTMS delivery system can induce reduction in excitability, and thus might help increase treatment efficacy. Research Category and Technology and Methods Clinical Research: 10. Transcranial Magnetic Stimulation (TMS) Keywords: rTMS, MDD, EEG-synchronization, cortical excitability