Trough-phase coupling of 40 Hz oscillatory transcranial direct current stimulation with iTBS enhances corticospinal excitability and brain connectivity in healthy individuals

Trough-phase coupling of 40 Hz oscillatory transcranial direct current stimulation with iTBS enhances corticospinal excitability and brain connectivity in healthy individuals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Trough-phase coupling of 40 Hz oscillatory transcranial direct current stimulation with iTBS enhances corticospinal excitability and brain connectivity in healthy individuals Xiaowei Ma, Shuaixiang Wang, Fangyuan Yan, Li Liu, Jiayi Liang, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9418222/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Intermittent theta-burst stimulation (iTBS) and oscillatory transcranial direct current stimulation (otDCS) can both induce neuroplastic changes, yet the neurophysiological effects of their combination and the role of phase alignment remain unclear. This study examined whether coupling iTBS to the peak versus trough phase of 40 Hz otDCS differentially modulates corticospinal excitability and brain network connectivity. Eighteen healthy adults participated in a randomized crossover study involving five stimulation conditions: peak-phase otDCS + iTBS, trough-phase otDCS + iTBS, otDCS, iTBS, and sham. Motor-evoked potentials (MEPs) and TMS-EEG directed connectivity were assessed. All active stimulation conditions induced early increases in corticospinal excitability. At 30 min, the trough-phase otDCS + iTBS condition produced greater facilitation than the peak-phase otDCS + iTBS condition and the single-modality conditions. TMS-EEG analyses further showed enhanced late-stage directed information flow following trough-phase coupling. These findings indicate that phase alignment influences the after-effects of combined otDCS and iTBS. Trough-phase coupling may contribute to more sustained corticospinal excitability changes and altered directed brain connectivity. corticospinal excitability motor-evoked potentials non-invasive brain stimulation oscillatory transcranial direct current stimulation intermittent theta-burst stimulation TMS-EEG Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) are two widely used forms of non-invasive brain stimulation (NIBS) that enable controlled modulation of cortical excitability through externally applied magnetic or electric fields (Valero-Cabré et al., 2017 ; Polanía et al., 2018 ; Jannati et al., 2023 ). Their effects are not confined to the local stimulation site. Previous studies have shown that TMS can also influence distributed brain networks beyond the stimulated region, thereby altering functional connectivity and patterns of information integration across brain areas (Valero-Cabré et al., 2017 ; Castrillon et al., 2020 ). Because NIBS can modulate both cortical excitability and network-level activity, it has become an important tool in motor and cognitive neuroscience as well as in related clinical interventions (Jannati et al., 2023 ; Fregni et al., 2021 ). However, stimulation-induced effects remain highly variable in magnitude, duration, and reproducibility across paradigms. Developing stimulation strategies that induce more stable and longer-lasting plastic changes therefore remains a major challenge in the field. Intermittent theta-burst stimulation (iTBS), a patterned form of repetitive TMS (rTMS), can induce after-effects on corticospinal excitability that outlast the stimulation period. However, these effects are often variable across individuals and may be influenced by baseline inhibitory state, stimulation timing, and inter-session interval (Huang et al., 2005 ; Diao et al., 2022 ; Yu et al., 2020 ). In parallel, oscillatory transcranial direct current stimulation (otDCS) has been proposed as a modified form of tDCS that superimposes rhythmic modulation on a direct-current background, with the aim of interacting more directly with endogenous neural oscillations. For example, theta-frequency otDCS over the posterior parietal cortex has been reported to improve associative memory in humans (Vulić et al., 2021 ), and waveform-modulated electrical stimulation has shown preliminary benefit in a randomized trial of upper-limb motor recovery after chronic stroke (Chen et al., 2021 ). Animal studies further suggest that prolonged iTBS can enhance hippocampus-dependent memory and may be accompanied by changes in hippocampal theta activity, neurotransmitter balance, and synaptic plasticity mechanisms related to long-term potentiation (LTP) and long-term depression (LTD) (Wu et al., 2024 ; Lee et al., 2023 ). Our previous work also suggested that anodal gamma-frequency otDCS may produce greater excitability-enhancing effects than conventional tDCS or tACS (Guo et al., 2025 ). Together, these findings raise the possibility that a more precise interaction between iTBS-induced plastic processes and the rhythmic or state-dependent modulation provided by otDCS may improve the stability and persistence of neuromodulatory effects. Although both tDCS and iTBS can modulate corticospinal excitability, the after-effects of a single tDCS session are often relatively short-lived, suggesting that brief interventions may be insufficient to maintain robust plastic changes (Nitsche & Paulus, 2000 ). Moreover, the interaction between tDCS and iTBS does not appear to reflect simple linear summation, but rather depends on stimulation timing and ongoing brain state (Dai et al., 2025 ). Thus, the plastic effects ultimately induced by iTBS may be shaped, to a considerable extent, by the temporal characteristics of stimulation delivery and the neurophysiological context at the time of intervention. Against this background, combined electromagnetic stimulation has attracted increasing attention in both experimental and translational settings. For example, combined rTMS and tDCS has shown potential clinical benefit in patients with subacute stroke (Fisk et al., 2026 ). However, evidence regarding optimal coupling strategies and parameter settings remains limited. Mechanistic studies and computational models suggest that phase alignment may influence synaptic plasticity processes and thereby shape subsequent network reorganization, including changes in synchrony and connectivity patterns (Chauhan et al., 2022 ; Manos et al., 2021 ). Consistent with this view, rhythmic stimulation or phase-locked external inputs may couple with endogenous neural oscillations and produce frequency- or phase-dependent neurophysiological and behavioral effects (Thut et al., 2011 ; Zaehle et al., 2010 ; Helfrich et al., 2014 ). For example, Maiella et al. ( 2022 ) reported enhanced gamma power and gamma-band functional connectivity following the simultaneous application of gamma-frequency tACS and iTBS over the dorsolateral prefrontal cortex (DLPFC) (Maiella et al., 2022 ). More recent studies have further shown that synchronized tACS-iTBS protocols can induce frequency-specific changes in oscillatory power accompanied by measurable neural and behavioral effects (Briley et al., 2024 ). However, the after-effects of tACS are often modest and not always consistent, and may vary according to stimulation parameters and outcome measures, indicating that current coupling strategies still require refinement (Antal et al., 2008 ). In the motor system, recent evidence suggests that gamma-frequency tACS applied over the human motor cortex can modulate iTBS-induced plasticity in a frequency-dependent manner, highlighting the strong parameter dependence of cross-modal neuromodulation (Liao et al., 2025 ). In addition, phase-locked gamma-frequency tACS-iTBS protocols have begun to compare peak-phase and trough-phase stimulation (Glinski et al., 2025 ). Nevertheless, direct evidence for phase-specific coupling between gamma-frequency otDCS and iTBS remains limited. It therefore remains unclear whether coupling iTBS to the peak versus trough phase of 40 Hz otDCS produces differential effects on corticospinal excitability and directed brain network connectivity. Motor-evoked potentials (MEPs) and TMS combined with electroencephalography (TMS-EEG) provide complementary outcome measures for characterizing neuromodulatory effects at different levels. MEPs primarily reflect changes in corticospinal excitability (Rossini et al., 2015 ), whereas TMS-EEG can be used to assess stimulation-related changes in directed brain network connectivity and their temporal evolution (Tremblay et al., 2019 ). Combining these two approaches may provide a more integrated characterization of neuromodulatory effects from both corticospinal and network-level perspectives, while also offering broader insight into the underlying plasticity mechanisms and interindividual variability (Rogasch & Fitzgerald, 2013 ). In the present study, 40 Hz anodal otDCS was applied as an oscillatory background in healthy participants, and iTBS was precisely coupled to either the peak or trough phase of the otDCS waveform, with otDCS, iTBS, and sham included as control conditions. We aimed to determine whether phase-specific coupling differentially affects the magnitude and persistence of corticospinal excitability changes, as well as the pattern of TMS-evoked directed network reorganization. We hypothesized that phase-coupled cross-modal stimulation would modulate corticospinal excitability and network-level responses, and that peak-phase alignment and trough-phase alignment would be associated with different neurophysiological effects. 2. Materials and Methods 2.1 Participants This study recruited 18 healthy participants (9 men and 9 women; age range, 20-30 years; mean age, 24.7 ± 0.6 years). Before enrollment, all participants completed a standardized TMS safety screening questionnaire to exclude neurological, psychiatric, or major medical disorders, as well as any TMS-related contraindications or precautions, in accordance with established safety guidelines (Rossi et al., 2021). Female participants were confirmed to be non-pregnant at the time of enrollment. None of the participants were taking medications known to affect central nervous system excitability, and none had taken part in other interventional studies within the previous 12 weeks. Written informed consent was obtained from all participants after a full explanation of the study aims, procedures, and potential risks. The study protocol was approved by the Ethics Committee of the First Hospital of Hebei Medical University (Approval No. [2024] Research Review No. 121) and was conducted in accordance with the latest revision of the Declaration of Helsinki (World Medical Association, 2013). 2.2 Experimental Design This study used a randomized, within-subject crossover design in which participants and outcome assessors were blinded, whereas the operators were not blinded. To reduce potential bias, all operators followed standardized procedures throughout the experiment. Each participant completed five stimulation conditions in a counterbalanced order, with a washout interval of at least 3 days between sessions: (1) peak-phase otDCS + iTBS, (2) trough-phase otDCS + iTBS, (3) otDCS, (4) iTBS, and (5) sham. To minimize the potential influence of circadian variation, each participant was scheduled at approximately the same time of day across sessions whenever possible. At the beginning of each session, baseline assessments were performed, including resting motor threshold (RMT), motor-evoked potentials (MEPs), and transcranial magnetic stimulation combined with electroencephalography (TMS-EEG). The overall experimental timeline and stimulation-condition matrix are illustrated in Fig. 1A and C. The assigned stimulation intervention was then delivered. MEPs were recorded immediately after stimulation (0 min) and again at 10, 20, and 30 min post-stimulation. TMS-EEG was recorded before and after stimulation. MEP and TMS-EEG measurements were performed by trained researchers who were blinded to the stimulation condition. Throughout each session, participants were monitored for subjective discomfort and adverse events, including tingling, itching, headache, dizziness, and fatigue. The skin at the electrode contact sites was also inspected for local reactions, such as erythema or burning sensations. Sample size was estimated a priori using G*Power 3.1.9.7 (Heinrich Heine University Düsseldorf, Germany) based on a repeated-measures analysis of variance framework. The design included two within-subject factors, stimulation condition (five levels) and time (four levels: 0, 10, 20, and 30 min), with the condition × time interaction specified as the primary effect of interest. The interaction effect size was estimated as Cohen’s f = 0.33 based on pilot data. With a significance level of α = 0.05, statistical power of 0.90, an assumed correlation among repeated measures of 0.5, and a nonsphericity correction of ε = 0.70, the minimum required sample size was estimated to be 9 participants. Allowing for an anticipated dropout rate of 20%, at least 12 participants were required. A total of 18 healthy participants were ultimately included. 2.3 Interventions The stimulation montage, including electrode placement and coil positioning, is illustrated in Fig. 1B. otDCS Stimulation was delivered using a battery-powered constant-current stimulator (Tymes Healthcare Technology (Tianjin) Co., Ltd., Tianjin, China) with saline-soaked sponge electrodes (5 × 7 cm). The anode was positioned over the left primary motor cortex (C3, according to the international 10/20 system), and the cathode over the right mastoid area. The current oscillated sinusoidally at 40 Hz between 0 and 2 mA for 10 min. iTBS Repetitive TMS was delivered using a Magelle-10 stimulator (Tymes Healthcare Technology (Tianjin) Co., Ltd., Tianjin, China) with a figure-of-eight coil (70 mm in diameter). The iTBS protocol consisted of 2-s trains of 40-Hz triplets repeated at 5 Hz for 192 s (600 pulses in total) at 70% RMT. Phase-Coupled otDCS + iTBS In the peak-phase otDCS + iTBS condition, iTBS trains were synchronized with the peak of the otDCS sinusoidal waveform. In the trough-phase otDCS + iTBS condition, iTBS trains were synchronized with the trough of the otDCS waveform. In both conditions, otDCS was delivered continuously for 10 min, while iTBS was applied during the initial 192 s (Fig. 1D). A phase-synchronization module was used to align TMS pulses precisely with predefined phases of the otDCS sinusoidal waveform. The module detected phase-specific points of the otDCS signal and generated trigger pulses to control the TMS unit, ensuring precise temporal alignment (<5 ms jitter). Temporal isolation and interference-suppression circuits were implemented to maintain trigger stability, enabling reliable phase-coupled magnetic-electrical stimulation. Sham A unified sham condition was used to simulate both the sensory features of otDCS and the auditory and somatosensory features of TMS within a single control session, without producing effective neuromodulation. The electrode montage was identical to that used in the active otDCS conditions. For the electrical sham component, the current was ramped up to 2 mA over 15 s and then ramped down to 0 mA over the next 15 s, with no current delivered thereafter. For the magnetic sham component, the TMS coil was held approximately perpendicular to the scalp over M1 to reproduce the acoustic click and part of the somatosensory sensation without producing effective cortical stimulation. Session duration, procedures, and assessments were matched across conditions to minimize expectancy effects. 2.4 Motor Evoked Potentials (MEPs) Single-pulse TMS was delivered over the left primary motor cortex (M1) hotspot, defined as the scalp location that elicited the largest and most consistent MEPs in the right abductor pollicis brevis (APB) muscle. Resting motor threshold (RMT) was defined as the lowest stimulation intensity capable of eliciting MEPs ≥50 μV in at least 5 of 10 consecutive trials. MEPs were recorded at 120% RMT with inter-pulse intervals of 5 ± 1 s. At each time point (baseline and 0, 10, 20, and 30 min after stimulation), 15 MEPs were recorded and averaged for analysis. MEP modulation was quantified as the normalized percentage change from baseline (ΔMEP%), calculated as follows: where A represents the mean post-stimulation MEP amplitude and B represents the mean baseline MEP amplitude. 2.5 TMS-EEG Acquisition TMS-EEG was recorded using a magnetic-field-compatible 128-channel amplifier (Yunshen Ltd., Beijing, China) at a sampling rate of 1024 Hz. A TMS-compatible EEG cap (Greentek Ltd., Wuhan, China) was positioned according to the extended international 10-05 system. Electrode impedance was continuously monitored and efforts were made to keep it below 5 kΩ. The reference and ground electrodes were placed at Ref and Gnd, respectively, and the data were re-referenced offline to the common average. Single-pulse TMS was delivered over the left primary motor cortex (M1; C3) at 110% of the resting motor threshold (RMT) using a 70-mm figure-of-eight coil. A total of 120 pulses were delivered with an interstimulus interval of 4 s to minimize interactions between consecutive stimuli. Participants were seated comfortably with their eyes closed and wore earplugs to reduce auditory artifacts during recording. 2.6 TMS-EEG Data Processing and Network Analysis EEG data were preprocessed and analyzed using MATLAB (R2023a, MathWorks, USA), custom MATLAB scripts, and the EEGLAB toolbox to characterize time-varying directed brain network connectivity. Preprocessing included band-pass filtering (3-30 Hz), downsampling to 128 Hz, and epoching from −1000 ms to +2000 ms relative to the TMS pulse. The onset of each single-pulse TMS (sTMS) event was identified from the trigger channel, and the peak of the trigger signal was defined as time zero (0 ms). Artifact rejection was performed using amplitude-based screening and visual inspection to remove contaminated trials. After preprocessing, 80-100 artifact-free trials per participant were retained for further analysis. Time-varying directed connectivity was estimated using a time-varying multivariate autoregressive model, and causal interactions between EEG channels were quantified with the adaptive directed transfer function (ADTF) (Song et al., 2021; Song et al., 2019). Directed networks reconstructed from pre-stimulation and post-stimulation EEG data were compared, and connectivity changes were visualized as directed brain network graphs (Song et al., 2020; Song et al., 2019). To quantify whole-brain outward information flow, out-strength was calculated from the directed ADTF matrices as the weighted out-degree of each node and then averaged across nodes to obtain a whole-brain mean out-strength time series. Before graph construction, self-connections (diagonal elements) were removed and connectivity weights were constrained to non-negative values. To reduce between-session scale variability, each pre-stimulation ADTF matrix was normalized by the 95th percentile of its positive edge weights, and the same scaling factor was applied to the paired post-stimulation matrix at the corresponding time point. Proportional thresholding was then performed by retaining the top 30% of positive edges in the pre-stimulation matrix, and the same cutoff was applied to the paired post-stimulation matrix to ensure consistent thresholding within each paired comparison. Changes in network outflow were quantified using an out-strength log-ratio index (OSLI), defined as: to avoid numerical instability near zero. Based on the temporal patterns observed in the time-varying ADTF graphs, two analysis windows (60-500 ms and 500-2000 ms) were selected for OSLI quantification. OSLI values within each window were summarized using the median across time points. Group-level effects were evaluated using two-tailed one-sample t-tests against zero, and raw p-values were adjusted using the Benjamini-Hochberg false discovery rate procedure across the two predefined windows within each stimulation condition. 2.7 Statistical analysis Statistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA), MATLAB, and R. For MEP outcomes, amplitudes were normalized to baseline within each participant and expressed as percentage change from baseline (ΔMEP%) for inferential analyses. For descriptive visualization, MEP amplitudes were additionally presented as baseline-normalized ratios (post/baseline). MEP data were analyzed using a two-way repeated-measures ANOVA with two within-subject factors: stimulation condition (five levels: peak-phase otDCS + iTBS, trough-phase otDCS + iTBS, otDCS, iTBS, and sham) and time (four levels: 0, 10, 20, and 30 min). Mauchly’s test was used to assess sphericity. When the sphericity assumption was violated, Greenhouse-Geisser correction was applied, and corrected degrees of freedom were reported. Partial eta squared (ηp²) was used as the measure of effect size. Where significant main effects or interactions were observed (p < 0.05), Bonferroni-corrected post hoc comparisons were performed, with mean differences (MDs), 95% confidence intervals (CIs), and adjusted p-values reported. For EEG-derived connectivity measures, the out-strength log-ratio index (OSLI) was calculated for each participant under each stimulation condition. Within each predefined post-stimulation time window (60-500 ms and 500-2000 ms), two-tailed one-sample t-tests were used to determine whether OSLI differed from zero. To control for multiple testing across the two time windows within each stimulation condition, p-values were adjusted using the Benjamini-Hochberg false discovery rate (FDR) procedure. Statistical significance for connectivity analyses was defined as q < 0.05. 3. Results All 18 healthy participants completed all five experimental sessions. Overall, the stimulation protocols were well tolerated. No serious adverse events were observed during the study, and no participant reported headache, dizziness, marked skin discomfort, or seizures. 3.1 Changes of RMT before and after stimulation Resting motor threshold (RMT) did not change significantly from before to after stimulation (F(1,17) = 0.58, p = 0.449), indicating that overall RMT remained stable across the experimental sessions. The results are presented in Table 1. Table 1. RMT before and immediately after stimulation in five conditions. Data are presented as mean ± standard deviation. 3.2 MEP alterations under five stimulation types Repeated-measures ANOVA revealed significant main effects of stimulation condition (F(2.84, 48.22) = 14.56, p < 0.001, ηp² = 0.461) and a significant main effect of time (F(3, 51) = 31.29, p < 0.001, ηp² = 0.648), as well as a significant stimulation condition × time interaction (F(12, 204) = 4.09, p < 0.001, ηp² = 0.194). When Mauchly’s test indicated a violation of sphericity, Greenhouse-Geisser correction was applied and corrected degrees of freedom were reported. Group-averaged baseline-normalized MEP ratios are shown in Fig. 2, whereas individual trajectories of baseline-normalized MEPs (Post/Pre, baseline = 1.0) are shown in Fig. 3. Post hoc comparisons showed that during the early post-stimulation period (0-20 min), all active stimulation conditions (trough-phase otDCS + iTBS, peak-phase otDCS + iTBS, otDCS, and iTBS) produced significantly greater MEP enhancement than sham (all Bonferroni-adjusted p < 0.05), whereas no significant pairwise differences were observed among the active conditions after correction. At 30 min after stimulation, the trough-phase otDCS + iTBS condition showed significantly greater MEP enhancement than the peak-phase otDCS + iTBS, otDCS, iTBS, and sham conditions (all Bonferroni-adjusted p < 0.05). The peak-phase otDCS + iTBS condition also remained significantly different from sham at 30 min (adjusted p = 0.011), whereas otDCS and iTBS no longer differed significantly from sham at this time point (adjusted p = 0.057 and 0.078, respectively). Mean ± SEM normalized MEPs are shown at baseline and at 0, 10, 20, and 30 min after stimulation for Peak-otDCS+iTBS, Trough-otDCS+iTBS, otDCS, iTBS, and sham. MEP amplitudes were normalized to baseline (baseline = 1.0; dotted line). Symbols denote significant between-condition differences at the corresponding time point (P < 0.05): * vs Sham; # vs Peak-otDCS+iTBS; Δ vs otDCS; + vs iTBS. 3.3 Time-varying EEG network patterns and whole-brain out-strength (OSLI) As shown in Fig. 4, the five stimulation conditions produced distinct time-varying patterns of directed brain network reorganization in healthy participants. Overall, the sham condition showed fluctuating and spatially scattered connectivity changes without a sustained or coherent pattern of network reorganization. The peak-phase otDCS + iTBS condition was characterized predominantly by reduced connectivity across most of the observation period. The iTBS and otDCS conditions both showed enhanced connectivity at later stages, although their temporal profiles and spatial extent differed. By contrast, the trough-phase otDCS + iTBS condition showed an early emergence of enhanced directed connectivity, which gradually evolved into a more widespread and sustained pattern over time. Representative dynamic networks at selected post-sTMS time points (208-1849 ms) are shown for Peak, Trough, otDCS, iTBS, and Sham. Red lines denote increased directed connections, and green lines denote decreased directed connections. Peak, peak-phase otDCS+iTBS; Trough, trough-phase otDCS+iTBS; otDCS, oscillatory transcranial direct current stimulation; iTBS, intermittent theta-burst stimulation; sTMS, single-pulse transcranial magnetic stimulation. Under the sham condition, some scattered enhanced connections could be observed, mainly involving left frontotemporal regions projecting toward frontal, midline frontal, and centro-parietal areas. However, these changes did not show sustained expansion or stable maintenance over time, and no clear large-scale reorganization pattern emerged across the observation period. The peak-phase otDCS + iTBS condition remained dominated by reduced connectivity throughout most of the post-sTMS period. Although a small number of enhanced connections could be identified, they were spatially restricted and did not develop into a sustained large-scale pattern of increased integration. In the iTBS condition, reduced information flow predominated during the initial and early stages (208 ms and 208-458 ms), and reduced connectivity remained dominant during the intermediate stage (458-701 ms), with only a small number of enhanced connections emerging. In the late period (701-1849 ms), a more evident delayed enhancement was observed, particularly as increased bidirectional coupling between the left frontal node F7 and right parietal nodes P4 and P8, together with the involvement of parietal and centro-parietal pathways. However, the spatial coverage and consistency of these enhanced connections remained limited. In the otDCS condition, enhanced connectivity at 208 ms was mainly distributed over right frontal and fronto-central regions, with FC6 acting as a prominent outward-driving node and F8 also participating in the emerging pattern. During 208-458 ms and 458-701 ms, enhanced connections became more clearly organized into directed pathways from temporo-parietal and temporal regions toward right frontal hubs, particularly FC6 and F8. This enhancement pattern remained relatively stable into the late period, although its overall spatial extent and consistency were still less pronounced than those observed under trough-phase otDCS + iTBS. By contrast, in the trough-phase otDCS + iTBS condition, reduced connections were still predominant at the initial stage (208 ms), but local enhanced connections had already emerged, mainly around FC5, which showed both outward-directed interactions and local convergence with neighboring motor- and frontal-related nodes. During the subsequent 208-458 ms interval, the network pattern gradually shifted from predominantly reduced connectivity to predominantly enhanced connectivity, with increasingly apparent directed interactions from temporo-parietal and temporal regions toward frontal and central areas. During 458-701 ms, this enhancement pattern further expanded to include frontal hubs and central-parietal regions. In the late period (701-1849 ms), enhanced directed connectivity became more widespread across the network, indicating a relatively extensive and sustained increase in effective connectivity. To further quantify global changes in outward information flow reflected by these time-varying network patterns, the out-strength log-ratio index (OSLI) was used to summarize stimulation-induced changes in global directed outflow. Based on visual inspection of whole-brain outflow trajectories across the five stimulation conditions, two post-stimulation windows were selected for analysis: an early window (60-500 ms) and a late window (500-2000 ms). As shown in Fig. 5, the trough-phase otDCS + iTBS condition showed a significant positive shift in OSLI during the late window (q < 0.05), whereas the early-window effect did not survive correction. In contrast, no significant deviation of OSLI from zero was observed in either the early or late window for the sham, peak-phase otDCS + iTBS, iTBS, or otDCS conditions after FDR correction. Taken together, these results indicate that the trough-phase otDCS + iTBS condition showed a significant late-window increase in global directed outflow, consistent with the broader and more sustained enhancement of directed connectivity observed in the time-varying network graphs. 4. Discussion The present study examined the effects of 40 Hz anodal otDCS combined with iTBS at different phase alignments on corticospinal excitability and time-varying brain networks. Several main findings emerged. First, all active stimulation conditions increased MEP amplitudes relative to sham during the early post-stimulation period (0–20 min). At 30 min, both peak-phase and trough-phase coupling remained significantly above sham, whereas only trough-phase otDCS + iTBS showed a statistical advantage over some of the other stimulation conditions in direct between-condition comparisons. These findings suggest that phase alignment may influence not only the immediate modulation of cortical excitability but also the persistence of after-effects. Under the present stimulation parameters, trough-phase coupling was associated with more persistent corticospinal excitability changes. Second, among the network changes from before to after stimulation observed across conditions, trough-phase coupling was associated with more evident changes in time-varying directed connectivity. In the late window (500–2000 ms), graph-based visualization suggested more widespread and sustained directed connectivity changes under trough-phase coupling, accompanied by a positive shift in OSLI. Other stimulation conditions also showed network changes, but their spatial extent and temporal profile differed from those observed under trough-phase coupling. The late increase in directed information flow was broadly consistent with the sustained MEP enhancement observed at later post-stimulation time points. Taken together, these findings suggest that the effects of phase coupling may extend beyond local excitability changes and may also involve coordinated reorganization of network-level information transfer. Compared with peak-phase coupling and the single-modality conditions, the effect of trough-phase otDCS + iTBS on MEP amplitudes was more consistent with a delayed consolidation process than with a simple immediate amplification. Previous studies have shown that the induction and maintenance of LTP-like plasticity in the primary motor cortex depend strongly on the physiological state of the target region at the time of stimulation (Abraham, 2008 ; Zrenner et al., 2018 ). According to the BCM (Bienenstock-Cooper-Munro) metaplasticity framework, the threshold for synaptic modification is not fixed but shifts dynamically as a function of prior activity (Cooper & Bear, 2012 ; Murakami et al., 2012 ). At the synaptic level, this state dependence may be related to the nonlinear channel dynamics of N-methyl-D-aspartate receptors (NMDARs). Under moderate depolarization, plasticity-related changes are associated with NMDAR-mediated Ca²⁺ influx and may contribute to the development of LTP-like effects (Huang et al., 2007 ; Wischnewski et al., 2019 ). By contrast, excessive depolarization or prolonged excitatory drive may alter the direction of plasticity and may also recruit local GABAergic interneurons more strongly, thereby enhancing feedback inhibition (Hamada et al., 2013 ). In the present study, the more evident late facilitatory effect under trough-phase stimulation may be related to the transient electrophysiological background at the time of stimulation. Compared with the peak phase, the trough phase corresponds to a moment at which the instantaneous current of the 40 Hz oscillatory waveform approaches zero. A plausible interpretation is that, although this state remains subthreshold, stimulation delivered at the trough phase may occur under a relatively less excitable physiological background. Under such conditions, synaptic plasticity may be less likely to reach saturation prematurely, and compensatory inhibitory recruitment may be less pronounced. As a result, the physiological context during trough-phase stimulation may be more favorable for the induction of LTP-like effects. This interpretation may help explain why trough-phase coupling was associated with a more evident late facilitatory effect in the present study, although the underlying mechanism remains uncertain. By contrast, peak-phase coupling may correspond to a relatively stronger depolarizing background, which could leave less physiological margin for further synaptic strengthening and may be less favorable for the broader network-level expression of plasticity-related effects. Whether phase-specific stimulation also selectively recruits late I-waves that are more sensitive to plasticity remains unclear and warrants further study (Di Lazzaro et al., 2012 ). Another noteworthy observation is that although both peak-phase and trough-phase coupling remained significantly above sham at 30 min, only trough-phase coupling showed a statistical advantage in direct between-condition comparisons. This suggests that the late effect observed under trough-phase coupling cannot be explained solely by simple summation of electrical and magnetic stimulation, and that their temporal relationship may represent a more important factor. Unlike constant direct current stimulation, otDCS not only biases membrane potential but may also influence ongoing neural oscillations. Its 40 Hz oscillatory component may rhythmically modulate cortical population activity through a fluctuating electric field. In the present study, both phase-coupled conditions were combined with iTBS, which itself facilitates corticospinal excitability, and this likely explains why both conditions remained above sham at later time points. However, the relative advantage observed under trough-phase coupling is unlikely to be attributable simply to a greater total stimulation effect. According to the framework of spike-timing-dependent plasticity (STDP), the relative timing between presynaptic and postsynaptic activity is a key determinant of the direction and magnitude of synaptic modification (Vogeti et al., 2022 ). From this perspective, the continuous oscillatory background generated by otDCS may provide a phase-dependent temporal reference for incoming magnetic pulses. When iTBS bursts arrive at the trough phase, the timing of stimulation may more closely match a window in which cortical neuronal populations are more susceptible to facilitatory input. Such temporal alignment may be more favorable for STDP-related facilitatory plasticity and may contribute to the retention of early plastic changes and their subsequent network-level expression (Raco et al., 2016 ; Guerra et al., 2018 ). By contrast, although peak-phase stimulation also occurs under the same 40 Hz oscillatory background, the timing of pulse arrival may not coincide with the most favorable facilitatory window. As a result, support for further strengthening of synaptic connectivity may be relatively limited, and the stabilization of early plastic changes during consolidation may be less efficient (Huang et al., 2010 ). Taken together, these findings suggest that the more persistent effect observed under trough-phase coupling may depend less on stimulation intensity per se than on a more favorable temporal configuration between electrical and magnetic stimulation. The TMS-EEG findings provide complementary network-level evidence for these effects. Time-varying effective connectivity analysis based on the adaptive directed transfer function (ADTF) suggested a biphasic pattern of network change following stimulation. During the early phase (60–500 ms), directed information flow was generally reduced across the brain. During the late phase (500–2000 ms), network changes became progressively more condition dependent and followed different trajectories. The widespread decoupling observed during the early phase across active conditions suggests that the original communication pattern may first undergo a brief period of weakening and adjustment following stimulation-induced perturbation. The subsequent divergence of network trajectories during the late phase further suggests that the evolution of information flow at this stage is strongly condition dependent rather than reflecting a uniform recovery process. From a topological perspective, late-stage connectivity patterns differed across stimulation conditions. The sham condition mainly showed spatially dispersed fluctuations and did not exhibit a sustained or clearly organized reconfiguration pattern. Single-modality stimulation also induced enhanced connectivity, but these effects appeared relatively limited and showed marked spatiotemporal selectivity. At the descriptive level, iTBS was mainly characterized by relatively focal bidirectional coupling between the left frontal node F7 and the right parietal nodes P4 and P8 at later stages. In contrast, otDCS initially drove outward pathways centered on the right frontal hubs FC6 and F8 and subsequently evolved toward a more stable right temporo-frontal input pattern. Neither single-modality condition developed into a broadly integrated configuration involving multiple hubs. By contrast, trough-phase otDCS + iTBS showed a more evident trend toward enhanced connectivity during the late phase. In the graph-based visualization, this condition appeared to show local outward-directed connectivity centered on FC5 at an early stage (approximately 208 ms), followed by gradual expansion toward frontal, motor, and posterior regions during 458–1849 ms. Overall, trough-phase coupling was associated with more widespread connectivity enhancement at multiple late time points. In comparison, peak-phase coupling also showed some enhanced connections during later stages, but their distribution and density were less pronounced than those observed under trough-phase coupling. The enhanced connections under peak-phase coupling remained relatively local rather than developing into a broader pattern of network expansion. In light of the MEP findings, these results suggest that local connectivity enhancement alone may be insufficient to support more persistent excitability changes. As a global measure of directed information outflow, the OSLI results were broadly consistent with the network patterns described above. During the early time window (60–500 ms), OSLI did not significantly deviate from zero under any condition, suggesting that no global increase in outward information flow was evident at this stage. During the late time window (500–2000 ms), a significant positive OSLI shift relative to baseline was observed under trough-phase otDCS + iTBS, whereas peak-phase coupling, single-modality stimulation, and sham did not show reliable increases in global outward drive. The agreement between the ADTF topology and the global OSLI results suggests that trough-phase coupling may be more closely associated with sustained late-stage reorganization of directed network activity. The mechanisms underlying these network-level changes may also be related to the temporal configuration imposed by phase coupling. When iTBS is coupled to the trough phase of the 40 Hz otDCS waveform, the resulting subthreshold bias state may reduce the likelihood of premature saturation of synaptic plasticity while also attenuating compensatory recruitment of local inhibitory circuits. It may further favor spatiotemporal integration processes related to cross-frequency coupling, such as theta-gamma phase-amplitude interactions, thereby increasing the probability that stimulation pulses fall within temporal windows characterized by greater neuronal responsiveness and temporal coordination (Canolty & Knight, 2010 ). Under such conditions, locally induced activity may be more likely to propagate to distant cortical regions and give rise to broader network responses. By contrast, peak-phase alignment may correspond to a relatively higher background depolarization level and a greater likelihood of engaging local inhibitory circuits. As a result, even when local activation is evident, its propagation to broader networks may remain constrained. The correspondence observed here between network reorganization and the persistence of MEP effects further suggests that long-lasting cortical plasticity may depend not only on transient changes in local synaptic efficacy but also on whether these micro-scale changes can be incorporated into larger-scale cortical network dynamics and support subsequent network-level reorganization. Finally, RMT remained stable before and after stimulation across conditions. This finding is broadly consistent with previous non-invasive neuromodulation studies showing that subthreshold anodal stimulation or iTBS alone does not typically induce systematic changes in RMT (Hallett, 2007 ). From a neurophysiological perspective, RMT is mainly related to the conductance properties of voltage-gated ion channels in corticospinal axons and may, to some extent, reflect baseline membrane excitability (Ziemann et al., 1996 ). The absence of significant RMT changes in the present study therefore suggests that the sustained increase in MEP amplitude observed under trough-phase coupling was more likely related to changes in intracortical synaptic transmission, as well as to alterations in local microcircuits and network connectivity, rather than to a generalized shift in corticospinal threshold. Limitations Several limitations should be acknowledged. Although a randomized crossover design with a washout interval of at least 3 days was used, the sample size remained relatively small, and all participants were healthy young adults. Caution is therefore needed when extending these findings to older individuals or clinical populations. In addition, only peak- and trough-phase alignment at 40 Hz was examined. Other parameters, including phase offset, stimulation frequency, stimulation intensity, and burst structure, were not systematically compared. Accordingly, the present findings are better interpreted as proof-of-concept evidence rather than as identification of an optimal dose-timing combination. The observation period was limited to 30 min, and the present study therefore mainly reflects short-term electrophysiological plasticity; direct evidence for behavioral effects or longer-term outcomes remains lacking. Other issues that may also affect interpretation include hotspot-based targeting rather than real-time neuronavigation, sensor-level TMS-EEG analysis, residual sensory artifacts, and possible impedance drift or vigilance fluctuations during prolonged recordings (Biabani et al., 2019 ; Conde et al., 2019 ). Future studies should further optimize combinations of phase and dose parameters and incorporate individualized electric field modeling together with source-space analyses (Thielscher et al., 2015 ) to improve mechanistic inference. It will also be important to conduct studies in patient populations with larger sample sizes, longer follow-up periods, and functional outcome measures, in order to better evaluate the durability, generalizability, and translational potential of phase-optimized stimulation protocols. Conclusion In summary, the present findings suggest that phase alignment may be a relevant temporal factor in cross-modal electromagnetic neuromodulation. Under the present stimulation parameters, coupling iTBS bursts to the trough phase of 40 Hz otDCS was associated with more persistent enhancement of corticospinal excitability and more evident late-stage changes in directed brain connectivity than peak-phase coupling and the single-modality conditions. These findings support the concept of phase-dependent plasticity in cross-modal stimulation and suggest that temporally coordinated stimulation may help improve the stability of neuromodulatory effects. Future studies are needed to further refine phase-optimized stimulation protocols and to evaluate their potential relevance for neurological disorders characterized by altered brain connectivity, such as stroke and Parkinson’s disease. Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of the First Hospital of Hebei Medical University. All procedures were conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available due to participant privacy and institutional restrictions but are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by the Medical Science Research Project of the Health Commission of Hebei Province (Grant No. 20250010). Authors’ contributions S.W. contributed to investigation, formal analysis, and writing the original draft. F.Y. contributed to methodology, validation, and writing—review and editing. L.L. contributed to investigation. J.L. contributed to investigation. M.Y. contributed to validation. S.Q. contributed to investigation. H.Q. contributed to validation. D.W. contributed to investigation. Y.G. contributed to supervision and writing—review and editing. 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Neurology, Cangzhou Central Hospital","correspondingAuthor":false,"prefix":"","firstName":"Shuaixiang","middleName":"","lastName":"Wang","suffix":""},{"id":633362998,"identity":"7bc01fde-e9f9-4935-bf94-b8993fdbbf03","order_by":2,"name":"Fangyuan Yan","email":"","orcid":"","institution":"Department of Graduate School, Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Fangyuan","middleName":"","lastName":"Yan","suffix":""},{"id":633363003,"identity":"4b24e809-fa72-45a5-bf9a-37a2b900c078","order_by":3,"name":"Li Liu","email":"","orcid":"","institution":"Department of Graduate School, Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Li","middleName":"","lastName":"Liu","suffix":""},{"id":633363005,"identity":"a27727cf-d34e-496c-9a33-908d43e9df87","order_by":4,"name":"Jiayi Liang","email":"","orcid":"","institution":"Department of Graduate School, Hebei Medical 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University","correspondingAuthor":false,"prefix":"","firstName":"Huiqing","middleName":"","lastName":"Qiu","suffix":""},{"id":633363018,"identity":"240f15a6-e98a-48d4-9af7-5f354de72bd9","order_by":8,"name":"Danning Wang","email":"","orcid":"","institution":"Department of Neurology, The First Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Danning","middleName":"","lastName":"Wang","suffix":""},{"id":633363023,"identity":"c4f13eab-91df-4702-97bf-48c111c7853f","order_by":9,"name":"Yan Gao","email":"","orcid":"","institution":"Department of Neurology, The First Hospital of Hebei Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Gao","suffix":""},{"id":633363034,"identity":"16408a0e-59d1-4add-be0b-b5b24df7d5b1","order_by":10,"name":"Yuping Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYDCCAyg8AwYGfmbmww8IaGFsQNEi2c6WZkCCFpCu8zwKEvh08B1vfv7g457D8ub8a8ykCwru2G0+zAO0rMYmGpcWyTPHDBtnPDtsuHPGGzPpGQbPkrcd5j3wgOFYWm4DDi0GN3IYm3kO3GbccOOMmTSPweFks8N8CQaMDYcJarGHazFu5jGQIEZL4obzPWAtdgbMBLSA/DJzxoH/yRtusBVbzzA4nCBxGBjICXj8AgyxBx8+HEiz3XD+8MbbBX8O2/P3Hz784EONDU4tCCCRYcAMpBLBKhMIKgcB/uMPQFrsiVI8CkbBKBgFIwoAAIRoZZm5OSr0AAAAAElFTkSuQmCC","orcid":"","institution":"Department of Neurology, The First Hospital of Hebei Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yuping","middleName":"","lastName":"Wang","suffix":""}],"badges":[],"createdAt":"2026-04-14 17:08:02","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9418222/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9418222/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108820741,"identity":"52669eb5-d56a-4004-a527-602e037e805a","added_by":"auto","created_at":"2026-05-08 16:42:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":725399,"visible":true,"origin":"","legend":"\u003cp\u003eExperimental design and phase-coupled stimulation paradigm.\u003c/p\u003e\n\u003cp\u003e(A) Experimental timeline. Each session comprised pre-stimulation TMS-EEG, baseline MEPs, and RMT, followed by one of five stimulation conditions and post-stimulation assessments. Single-pulse TMS at 120% RMT (15 trials) was delivered at 0, 10, 20, and 30 min to assess corticospinal excitability. TMS-EEG was recorded after the 30-min MEP assessment.\u003c/p\u003e\n\u003cp\u003e(B) Stimulation montage. The otDCS anode was placed over C3 (left M1) and the cathode over the contralateral mastoid. A figure-of-eight TMS coil was positioned over the motor hotspot.\u003c/p\u003e\n\u003cp\u003e(C) Protocol matrix. Five conditions were tested: Peak-otDCS+iTBS, Trough-otDCS+iTBS, otDCS, iTBS, and sham.\u003c/p\u003e\n\u003cp\u003e(D) Phase-coupling schematic. iTBS bursts were synchronized to the peak or trough of 40-Hz otDCS (0-2 mA) during the initial 192 s, followed by otDCS alone to complete the 10-min stimulation period.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9418222/v1/800f7274316f097138920dc1.png"},{"id":108820557,"identity":"0691b009-1006-4430-b2e2-e22692060648","added_by":"auto","created_at":"2026-05-08 16:42:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":168869,"visible":true,"origin":"","legend":"\u003cp\u003eMEP at each time point in five stimulation conditions. \u0026nbsp;\u0026nbsp;\u003cbr\u003e\n Mean ± SEM normalized MEPs are shown at baseline and at 0, 10, 20, and 30 min after stimulation for Peak-otDCS+iTBS, Trough-otDCS+iTBS, otDCS, iTBS, and sham. MEP amplitudes were normalized to baseline (baseline = 1.0; dotted line). Symbols denote significant between-condition differences at the corresponding time point (P \u0026lt; 0.05): * vs Sham; # vs Peak-otDCS+iTBS; Δ vs otDCS; + vs iTBS.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9418222/v1/902e5880ae1aa746e7077f21.png"},{"id":108820692,"identity":"7c1d7557-5d85-42a9-a691-89c44ac6a5e2","added_by":"auto","created_at":"2026-05-08 16:42:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":686392,"visible":true,"origin":"","legend":"\u003cp\u003eIndividual corticospinal excitability across five stimulation sessions.\u003c/p\u003e\n\u003cp\u003ePanels A-E show normalized MEP amplitudes for Peak-otDCS+iTBS, Trough-otDCS+iTBS, otDCS, iTBS, and sham, respectively. Thin lines represent individual participants (P1-P18), and the thick line indicates the group mean. MEP amplitudes were normalized to each participant’s baseline (dotted line = 1.0) and are shown at baseline and at 0, 10, 20, and 30 min after stimulation.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-9418222/v1/61d122ae5d46f045c8293666.png"},{"id":108820190,"identity":"81a75002-3d5c-4815-880d-717258d47537","added_by":"auto","created_at":"2026-05-08 16:40:23","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5299336,"visible":true,"origin":"","legend":"\u003cp\u003eThe time-varying EEG network connections after sTMS of participants under five different stimulation conditions.\u003c/p\u003e\n\u003cp\u003eRepresentative dynamic networks at selected post-sTMS time points (208-1849 ms) are shown for Peak, Trough, otDCS, iTBS, and Sham. Red lines denote increased directed connections, and green lines denote decreased directed connections. Peak, peak-phase otDCS+iTBS; Trough, trough-phase otDCS+iTBS; otDCS, oscillatory transcranial direct current stimulation; iTBS, intermittent theta-burst stimulation; sTMS, single-pulse transcranial magnetic stimulation.\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-9418222/v1/205cb846cdbe676920ae8668.png"},{"id":108820691,"identity":"88d431dc-b818-4ba6-b6ad-44b399ebd8f1","added_by":"auto","created_at":"2026-05-08 16:42:22","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":176952,"visible":true,"origin":"","legend":"\u003cp\u003eModulation of whole-brain outward network drive across stimulation conditions.\u003c/p\u003e\n\u003cp\u003eWhole-brain out-strength was derived from directed ADTF networks and summarized using the out-strength log-ratio index (OSLI) for two post-stimulation windows (60-500 ms and 500-2000 ms). Dots represent individual participants, and horizontal bars indicate the group mean and 95% confidence intervals (CIs). The dashed line indicates no change relative to baseline. Group-level effects were assessed using two-tailed one-sample t-tests against zero, with Benjamini-Hochberg false discovery rate (FDR) correction applied across time windows within each stimulation condition. A significant increase in the late window was observed only in the Trough condition (q \u0026lt; 0.05, FDR-corrected).\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-9418222/v1/ac8693b741a97a78c46f0461.png"},{"id":108822479,"identity":"9411c5e7-dac1-485c-8297-afa7f54795e8","added_by":"auto","created_at":"2026-05-08 16:49:01","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7370844,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9418222/v1/34a16f70-be66-4586-a413-bcae911ec64f.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Trough-phase coupling of 40 Hz oscillatory transcranial direct current stimulation with iTBS enhances corticospinal excitability and brain connectivity in healthy individuals","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eTranscranial magnetic stimulation (TMS) and transcranial electrical stimulation (tES) are two widely used forms of non-invasive brain stimulation (NIBS) that enable controlled modulation of cortical excitability through externally applied magnetic or electric fields (Valero-Cabr\u0026eacute; et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Polan\u0026iacute;a et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Jannati et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Their effects are not confined to the local stimulation site. Previous studies have shown that TMS can also influence distributed brain networks beyond the stimulated region, thereby altering functional connectivity and patterns of information integration across brain areas (Valero-Cabr\u0026eacute; et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Castrillon et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Because NIBS can modulate both cortical excitability and network-level activity, it has become an important tool in motor and cognitive neuroscience as well as in related clinical interventions (Jannati et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Fregni et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, stimulation-induced effects remain highly variable in magnitude, duration, and reproducibility across paradigms. Developing stimulation strategies that induce more stable and longer-lasting plastic changes therefore remains a major challenge in the field.\u003c/p\u003e \u003cp\u003eIntermittent theta-burst stimulation (iTBS), a patterned form of repetitive TMS (rTMS), can induce after-effects on corticospinal excitability that outlast the stimulation period. However, these effects are often variable across individuals and may be influenced by baseline inhibitory state, stimulation timing, and inter-session interval (Huang et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Diao et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In parallel, oscillatory transcranial direct current stimulation (otDCS) has been proposed as a modified form of tDCS that superimposes rhythmic modulation on a direct-current background, with the aim of interacting more directly with endogenous neural oscillations. For example, theta-frequency otDCS over the posterior parietal cortex has been reported to improve associative memory in humans (Vulić et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and waveform-modulated electrical stimulation has shown preliminary benefit in a randomized trial of upper-limb motor recovery after chronic stroke (Chen et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Animal studies further suggest that prolonged iTBS can enhance hippocampus-dependent memory and may be accompanied by changes in hippocampal theta activity, neurotransmitter balance, and synaptic plasticity mechanisms related to long-term potentiation (LTP) and long-term depression (LTD) (Wu et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Lee et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Our previous work also suggested that anodal gamma-frequency otDCS may produce greater excitability-enhancing effects than conventional tDCS or tACS (Guo et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Together, these findings raise the possibility that a more precise interaction between iTBS-induced plastic processes and the rhythmic or state-dependent modulation provided by otDCS may improve the stability and persistence of neuromodulatory effects.\u003c/p\u003e \u003cp\u003eAlthough both tDCS and iTBS can modulate corticospinal excitability, the after-effects of a single tDCS session are often relatively short-lived, suggesting that brief interventions may be insufficient to maintain robust plastic changes (Nitsche \u0026amp; Paulus, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Moreover, the interaction between tDCS and iTBS does not appear to reflect simple linear summation, but rather depends on stimulation timing and ongoing brain state (Dai et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Thus, the plastic effects ultimately induced by iTBS may be shaped, to a considerable extent, by the temporal characteristics of stimulation delivery and the neurophysiological context at the time of intervention. Against this background, combined electromagnetic stimulation has attracted increasing attention in both experimental and translational settings. For example, combined rTMS and tDCS has shown potential clinical benefit in patients with subacute stroke (Fisk et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2026\u003c/span\u003e). However, evidence regarding optimal coupling strategies and parameter settings remains limited. Mechanistic studies and computational models suggest that phase alignment may influence synaptic plasticity processes and thereby shape subsequent network reorganization, including changes in synchrony and connectivity patterns (Chauhan et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Manos et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Consistent with this view, rhythmic stimulation or phase-locked external inputs may couple with endogenous neural oscillations and produce frequency- or phase-dependent neurophysiological and behavioral effects (Thut et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Zaehle et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Helfrich et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For example, Maiella et al. (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) reported enhanced gamma power and gamma-band functional connectivity following the simultaneous application of gamma-frequency tACS and iTBS over the dorsolateral prefrontal cortex (DLPFC) (Maiella et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). More recent studies have further shown that synchronized tACS-iTBS protocols can induce frequency-specific changes in oscillatory power accompanied by measurable neural and behavioral effects (Briley et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). However, the after-effects of tACS are often modest and not always consistent, and may vary according to stimulation parameters and outcome measures, indicating that current coupling strategies still require refinement (Antal et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). In the motor system, recent evidence suggests that gamma-frequency tACS applied over the human motor cortex can modulate iTBS-induced plasticity in a frequency-dependent manner, highlighting the strong parameter dependence of cross-modal neuromodulation (Liao et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). In addition, phase-locked gamma-frequency tACS-iTBS protocols have begun to compare peak-phase and trough-phase stimulation (Glinski et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Nevertheless, direct evidence for phase-specific coupling between gamma-frequency otDCS and iTBS remains limited. It therefore remains unclear whether coupling iTBS to the peak versus trough phase of 40 Hz otDCS produces differential effects on corticospinal excitability and directed brain network connectivity.\u003c/p\u003e \u003cp\u003eMotor-evoked potentials (MEPs) and TMS combined with electroencephalography (TMS-EEG) provide complementary outcome measures for characterizing neuromodulatory effects at different levels. MEPs primarily reflect changes in corticospinal excitability (Rossini et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), whereas TMS-EEG can be used to assess stimulation-related changes in directed brain network connectivity and their temporal evolution (Tremblay et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Combining these two approaches may provide a more integrated characterization of neuromodulatory effects from both corticospinal and network-level perspectives, while also offering broader insight into the underlying plasticity mechanisms and interindividual variability (Rogasch \u0026amp; Fitzgerald, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In the present study, 40 Hz anodal otDCS was applied as an oscillatory background in healthy participants, and iTBS was precisely coupled to either the peak or trough phase of the otDCS waveform, with otDCS, iTBS, and sham included as control conditions. We aimed to determine whether phase-specific coupling differentially affects the magnitude and persistence of corticospinal excitability changes, as well as the pattern of TMS-evoked directed network reorganization. We hypothesized that phase-coupled cross-modal stimulation would modulate corticospinal excitability and network-level responses, and that peak-phase alignment and trough-phase alignment would be associated with different neurophysiological effects.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003e2.1 Participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study recruited 18 healthy participants (9 men and 9 women; age range, 20-30 years; mean age, 24.7 \u0026plusmn; 0.6 years). Before enrollment, all participants completed a standardized TMS safety screening questionnaire to exclude neurological, psychiatric, or major medical disorders, as well as any TMS-related contraindications or precautions, in accordance with established safety guidelines (Rossi et al., 2021). Female participants were confirmed to be non-pregnant at the time of enrollment. None of the participants were taking medications known to affect central nervous system excitability, and none had taken part in other interventional studies within the previous 12 weeks. Written informed consent was obtained from all participants after a full explanation of the study aims, procedures, and potential risks. The study protocol was approved by the Ethics Committee of the First Hospital of Hebei Medical University (Approval No. [2024] Research Review No. 121) and was conducted in accordance with the latest revision of the Declaration of Helsinki (World Medical Association, 2013).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Experimental Design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study used a randomized, within-subject crossover design in which participants and outcome assessors were blinded, whereas the operators were not blinded. To reduce potential bias, all operators followed standardized procedures throughout the experiment. Each participant completed five stimulation conditions in a counterbalanced order, with a washout interval of at least 3 days between sessions: (1) peak-phase otDCS + iTBS, (2) trough-phase otDCS + iTBS, (3) otDCS, (4) iTBS, and (5) sham. To minimize the potential influence of circadian variation, each participant was scheduled at approximately the same time of day across sessions whenever possible.\u0026nbsp;At the beginning of each session, baseline assessments were performed, including resting motor threshold (RMT), motor-evoked potentials (MEPs), and transcranial magnetic stimulation combined with electroencephalography (TMS-EEG). The overall experimental timeline and stimulation-condition matrix are illustrated in Fig. 1A and C. The assigned stimulation intervention was then delivered. MEPs were recorded immediately after stimulation (0 min) and again at 10, 20, and 30 min post-stimulation. TMS-EEG was recorded before and after stimulation. MEP and TMS-EEG measurements were performed by trained researchers who were blinded to the stimulation condition. Throughout each session, participants were monitored for subjective discomfort and adverse events, including tingling, itching, headache, dizziness, and fatigue. The skin at the electrode contact sites was also inspected for local reactions, such as erythema or burning sensations.\u003c/p\u003e\n\u003cp\u003eSample size was estimated a priori using G*Power 3.1.9.7 (Heinrich Heine University D\u0026uuml;sseldorf, Germany) based on a repeated-measures analysis of variance framework. The design included two within-subject factors, stimulation condition (five levels) and time (four levels: 0, 10, 20, and 30 min), with the condition \u0026times; time interaction specified as the primary effect of interest. The interaction effect size was estimated as Cohen\u0026rsquo;s f = 0.33 based on pilot data. With a significance level of \u0026alpha; = 0.05, statistical power of 0.90, an assumed correlation among repeated measures of 0.5, and a nonsphericity correction of \u0026epsilon; = 0.70, the minimum required sample size was estimated to be 9 participants. Allowing for an anticipated dropout rate of 20%, at least 12 participants were required. A total of 18 healthy participants were ultimately included.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Interventions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe stimulation montage, including electrode placement and coil positioning, is illustrated in Fig. 1B.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eotDCS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStimulation was delivered using a battery-powered constant-current stimulator (Tymes Healthcare Technology (Tianjin) Co., Ltd., Tianjin, China) with saline-soaked sponge electrodes (5 \u0026times; 7 cm). The anode was positioned over the left primary motor cortex (C3, according to the international 10/20 system), and the cathode over the right mastoid area. The current oscillated sinusoidally at 40 Hz between 0 and 2 mA for 10 min.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eiTBS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRepetitive TMS was delivered using a Magelle-10 stimulator (Tymes Healthcare Technology (Tianjin) Co., Ltd., Tianjin, China) with a figure-of-eight coil (70 mm in diameter). The iTBS protocol consisted of 2-s trains of 40-Hz triplets repeated at 5 Hz for 192 s (600 pulses in total) at 70% RMT.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePhase-Coupled otDCS + iTBS\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the peak-phase otDCS + iTBS condition, iTBS trains were synchronized with the peak of the otDCS sinusoidal waveform. In the trough-phase otDCS + iTBS condition, iTBS trains were synchronized with the trough of the otDCS waveform. In both conditions, otDCS was delivered continuously for 10 min, while iTBS was applied during the initial 192 s (Fig. 1D).\u003c/p\u003e\n\u003cp\u003eA phase-synchronization module was used to align TMS pulses precisely with predefined phases of the otDCS sinusoidal waveform. The module detected phase-specific points of the otDCS signal and generated trigger pulses to control the TMS unit, ensuring precise temporal alignment (\u0026lt;5 ms jitter). Temporal isolation and interference-suppression circuits were implemented to maintain trigger stability, enabling reliable phase-coupled magnetic-electrical stimulation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSham\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA unified sham condition was used to simulate both the sensory features of otDCS and the auditory and somatosensory features of TMS within a single control session, without producing effective neuromodulation. The electrode montage was identical to that used in the active otDCS conditions. For the electrical sham component, the current was ramped up to 2 mA over 15 s and then ramped down to 0 mA over the next 15 s, with no current delivered thereafter. For the magnetic sham component, the TMS coil was held approximately perpendicular to the scalp over M1 to reproduce the acoustic click and part of the somatosensory sensation without producing effective cortical stimulation. Session duration, procedures, and assessments were matched across conditions to minimize expectancy effects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.4 Motor Evoked Potentials (MEPs)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSingle-pulse TMS was delivered over the left primary motor cortex (M1) hotspot, defined as the scalp location that elicited the largest and most consistent MEPs in the right abductor pollicis brevis (APB) muscle. Resting motor threshold (RMT) was defined as the lowest stimulation intensity capable of eliciting MEPs\u0026nbsp;\u0026ge;50\u0026nbsp;\u0026mu;V in at least 5 of 10 consecutive trials.\u0026nbsp;MEPs were recorded at 120% RMT with inter-pulse intervals of 5 \u0026plusmn; 1 s. At each time point (baseline and 0, 10, 20, and 30 min after stimulation), 15 MEPs were recorded and averaged for analysis.\u003c/p\u003e\n\u003cp\u003eMEP modulation was quantified as the normalized percentage change from baseline (\u0026Delta;MEP%), calculated as follows:\u003c/p\u003e\n\u003cp\u003e\u003cimg width=\"374\" height=\"35\" src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1778256082.gif\" v:shapes=\"_x0000_i1025\" alt=\"image\"\u003e\u003c/p\u003e\n\u003cp\u003ewhere A represents the mean post-stimulation MEP amplitude and B represents the mean baseline MEP amplitude.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.5 TMS-EEG Acquisition\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTMS-EEG was recorded using a magnetic-field-compatible 128-channel amplifier (Yunshen Ltd., Beijing, China) at a sampling rate of 1024 Hz. A TMS-compatible EEG cap (Greentek Ltd., Wuhan, China) was positioned according to the extended international 10-05 system. Electrode impedance was continuously monitored and efforts were made to keep it below 5 k\u0026Omega;. The reference and ground electrodes were placed at Ref and Gnd, respectively, and the data were re-referenced offline to the common average. Single-pulse TMS was delivered over the left primary motor cortex (M1; C3) at 110% of the resting motor threshold (RMT) using a 70-mm figure-of-eight coil. A total of 120 pulses were delivered with an interstimulus interval of 4 s to minimize interactions between consecutive stimuli. Participants were seated comfortably with their eyes closed and wore earplugs to reduce auditory artifacts during recording.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.6 TMS-EEG Data Processing and Network Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEEG data were preprocessed and analyzed using MATLAB (R2023a, MathWorks, USA), custom MATLAB scripts, and the EEGLAB toolbox to characterize time-varying directed brain network connectivity. Preprocessing included band-pass filtering (3-30 Hz), downsampling to 128 Hz, and epoching from \u0026minus;1000 ms to +2000 ms relative to the TMS pulse. The onset of each single-pulse TMS (sTMS) event was identified from the trigger channel, and the peak of the trigger signal was defined as time zero (0 ms). Artifact rejection was performed using amplitude-based screening and visual inspection to remove contaminated trials. After preprocessing, 80-100 artifact-free trials per participant were retained for further analysis.\u003c/p\u003e\n\u003cp\u003eTime-varying directed connectivity was estimated using a time-varying multivariate autoregressive model, and causal interactions between EEG channels were quantified with the adaptive directed transfer function (ADTF) (Song et al., 2021; Song et al., 2019). Directed networks reconstructed from pre-stimulation and post-stimulation EEG data were compared, and connectivity changes were visualized as directed brain network graphs (Song et al., 2020; Song et al., 2019).\u003c/p\u003e\n\u003cp\u003eTo quantify whole-brain outward information flow, out-strength was calculated from the directed ADTF matrices as the weighted out-degree of each node and then averaged across nodes to obtain a whole-brain mean out-strength time series. Before graph construction, self-connections (diagonal elements) were removed and connectivity weights were constrained to non-negative values. To reduce between-session scale variability, each pre-stimulation ADTF matrix was normalized by the 95th percentile of its positive edge weights, and the same scaling factor was applied to the paired post-stimulation matrix at the corresponding time point. Proportional thresholding was then performed by retaining the top 30% of positive edges in the pre-stimulation matrix, and the same cutoff was applied to the paired post-stimulation matrix to ensure consistent thresholding within each paired comparison.\u003c/p\u003e\n\u003cp\u003eChanges in network outflow were quantified using an out-strength log-ratio index (OSLI), defined as:\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1778256161.png\" width=\"873\" height=\"193\"\u003e\u003c/p\u003e\n\u003cp\u003eto avoid numerical instability near zero. Based on the temporal patterns observed in the time-varying ADTF graphs, two analysis windows (60-500 ms and 500-2000 ms) were selected for OSLI quantification. OSLI values within each window were summarized using the median across time points. Group-level effects were evaluated using two-tailed one-sample t-tests against zero, and raw p-values were adjusted using the Benjamini-Hochberg false discovery rate procedure across the two predefined windows within each stimulation condition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.7 Statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS version 26.0 (IBM, Armonk, NY, USA), MATLAB, and R. For MEP outcomes, amplitudes were normalized to baseline within each participant and expressed as percentage change from baseline (\u0026Delta;MEP%) for inferential analyses. For descriptive visualization, MEP amplitudes were additionally presented as baseline-normalized ratios (post/baseline). MEP data were analyzed using a two-way repeated-measures ANOVA with two within-subject factors: stimulation condition (five levels: peak-phase otDCS + iTBS, trough-phase otDCS + iTBS, otDCS, iTBS, and sham) and time (four levels: 0, 10, 20, and 30 min). Mauchly\u0026rsquo;s test was used to assess sphericity. When the sphericity assumption was violated, Greenhouse-Geisser correction was applied, and corrected degrees of freedom were reported. Partial eta squared (\u0026eta;p\u0026sup2;) was used as the measure of effect size. Where significant main effects or interactions were observed (p \u0026lt; 0.05), Bonferroni-corrected post hoc comparisons were performed, with mean differences (MDs), 95% confidence intervals (CIs), and adjusted p-values reported. For EEG-derived connectivity measures, the out-strength log-ratio index (OSLI) was calculated for each participant under each stimulation condition. Within each predefined post-stimulation time window (60-500 ms and 500-2000 ms), two-tailed one-sample t-tests were used to determine whether OSLI differed from zero. To control for multiple testing across the two time windows within each stimulation condition, p-values were adjusted using the Benjamini-Hochberg false discovery rate (FDR) procedure. Statistical significance for connectivity analyses was defined as q \u0026lt; 0.05.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003eAll 18 healthy participants completed all five experimental sessions. Overall, the stimulation protocols were well tolerated. No serious adverse events were observed during the study, and no participant reported headache, dizziness, marked skin discomfort, or seizures.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1 Changes of RMT before and after stimulation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResting motor threshold (RMT) did not change significantly from before to after stimulation (F(1,17) = 0.58, p = 0.449), indicating that overall RMT remained stable across the experimental sessions. The results are presented in Table 1.\u003c/p\u003e\n\u003cp\u003eTable 1. RMT before and immediately after stimulation in five conditions.\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1778256337.png\" width=\"953\" height=\"159\"\u003e\u003c/p\u003e\n\u003cp\u003eData are presented as mean \u0026plusmn; standard deviation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 MEP alterations under five stimulation types\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRepeated-measures ANOVA revealed significant main effects of stimulation condition (F(2.84, 48.22) = 14.56, p \u0026lt; 0.001, \u0026eta;p\u0026sup2; = 0.461) and a significant main effect of time (F(3, 51) = 31.29, p \u0026lt; 0.001, \u0026eta;p\u0026sup2; = 0.648), as well as a significant stimulation condition \u0026times; time interaction (F(12, 204) = 4.09, p \u0026lt; 0.001, \u0026eta;p\u0026sup2; = 0.194). When Mauchly\u0026rsquo;s test indicated a violation of sphericity, Greenhouse-Geisser correction was applied and corrected degrees of freedom were reported.\u003c/p\u003e\n\u003cp\u003eGroup-averaged baseline-normalized MEP ratios are shown in Fig. 2, whereas individual trajectories of baseline-normalized MEPs (Post/Pre, baseline = 1.0) are shown in Fig. 3. Post hoc comparisons showed that during the early post-stimulation period (0-20 min), all active stimulation conditions (trough-phase otDCS + iTBS, peak-phase otDCS + iTBS, otDCS, and iTBS) produced significantly greater MEP enhancement than sham (all Bonferroni-adjusted p \u0026lt; 0.05), whereas no significant pairwise differences were observed among the active conditions after correction. At 30 min after stimulation, the trough-phase otDCS + iTBS condition showed significantly greater MEP enhancement than the peak-phase otDCS + iTBS, otDCS, iTBS, and sham conditions (all Bonferroni-adjusted p \u0026lt; 0.05). The peak-phase otDCS + iTBS condition also remained significantly different from sham at 30 min (adjusted p = 0.011), whereas otDCS and iTBS no longer differed significantly from sham at this time point (adjusted p = 0.057 and 0.078, respectively).\u003c/p\u003e\n\u003cp\u003eMean \u0026plusmn; SEM normalized MEPs are shown at baseline and at 0, 10, 20, and 30 min after stimulation for Peak-otDCS+iTBS, Trough-otDCS+iTBS, otDCS, iTBS, and sham. MEP amplitudes were normalized to baseline (baseline = 1.0; dotted line). Symbols denote significant between-condition differences at the corresponding time point (P \u0026lt; 0.05): * vs Sham; # vs Peak-otDCS+iTBS; \u0026Delta; vs otDCS; + vs iTBS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Time-varying EEG network patterns and whole-brain out-strength (OSLI)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAs shown in Fig. 4, the five stimulation conditions produced distinct time-varying patterns of directed brain network reorganization in healthy participants. Overall, the sham condition showed fluctuating and spatially scattered connectivity changes without a sustained or coherent pattern of network reorganization. The peak-phase otDCS + iTBS condition was characterized predominantly by reduced connectivity across most of the observation period. The iTBS and otDCS conditions both showed enhanced connectivity at later stages, although their temporal profiles and spatial extent differed. By contrast, the trough-phase otDCS + iTBS condition showed an early emergence of enhanced directed connectivity, which gradually evolved into a more widespread and sustained pattern over time.\u003c/p\u003e\n\u003cp\u003eRepresentative dynamic networks at selected post-sTMS time points (208-1849 ms) are shown for Peak, Trough, otDCS, iTBS, and Sham. Red lines denote increased directed connections, and green lines denote decreased directed connections. Peak, peak-phase otDCS+iTBS; Trough, trough-phase otDCS+iTBS; otDCS, oscillatory transcranial direct current stimulation; iTBS, intermittent theta-burst stimulation; sTMS, single-pulse transcranial magnetic stimulation.\u003c/p\u003e\n\u003cp\u003eUnder the sham condition, some scattered enhanced connections could be observed, mainly involving left frontotemporal regions projecting toward frontal, midline frontal, and centro-parietal areas. However, these changes did not show sustained expansion or stable maintenance over time, and no clear large-scale reorganization pattern emerged across the observation period.\u003c/p\u003e\n\u003cp\u003eThe peak-phase otDCS + iTBS condition remained dominated by reduced connectivity throughout most of the post-sTMS period. Although a small number of enhanced connections could be identified, they were spatially restricted and did not develop into a sustained large-scale pattern of increased integration.\u003c/p\u003e\n\u003cp\u003eIn the iTBS condition, reduced information flow predominated during the initial and early stages (208 ms and 208-458 ms), and reduced connectivity remained dominant during the intermediate stage (458-701 ms), with only a small number of enhanced connections emerging. In the late period (701-1849 ms), a more evident delayed enhancement was observed, particularly as increased bidirectional coupling between the left frontal node F7 and right parietal nodes P4 and P8, together with the involvement of parietal and centro-parietal pathways. However, the spatial coverage and consistency of these enhanced connections remained limited.\u003c/p\u003e\n\u003cp\u003eIn the otDCS condition, enhanced connectivity at 208 ms was mainly distributed over right frontal and fronto-central regions, with FC6 acting as a prominent outward-driving node and F8 also participating in the emerging pattern. During 208-458 ms and 458-701 ms, enhanced connections became more clearly organized into directed pathways from temporo-parietal and temporal regions toward right frontal hubs, particularly FC6 and F8. This enhancement pattern remained relatively stable into the late period, although its overall spatial extent and consistency were still less pronounced than those observed under trough-phase otDCS + iTBS.\u003c/p\u003e\n\u003cp\u003eBy contrast, in the trough-phase otDCS + iTBS condition, reduced connections were still predominant at the initial stage (208 ms), but local enhanced connections had already emerged, mainly around FC5, which showed both outward-directed interactions and local convergence with neighboring motor- and frontal-related nodes. During the subsequent 208-458 ms interval, the network pattern gradually shifted from predominantly reduced connectivity to predominantly enhanced connectivity, with increasingly apparent directed interactions from temporo-parietal and temporal regions toward frontal and central areas. During 458-701 ms, this enhancement pattern further expanded to include frontal hubs and central-parietal regions. In the late period (701-1849 ms), enhanced directed connectivity became more widespread across the network, indicating a relatively extensive and sustained increase in effective connectivity.\u003c/p\u003e\n\u003cp\u003eTo further quantify global changes in outward information flow reflected by these time-varying network patterns, the out-strength log-ratio index (OSLI) was used to summarize stimulation-induced changes in global directed outflow. Based on visual inspection of whole-brain outflow trajectories across the five stimulation conditions, two post-stimulation windows were selected for analysis: an early window (60-500 ms) and a late window (500-2000 ms). As shown in Fig. 5, the trough-phase otDCS + iTBS condition showed a significant positive shift in OSLI during the late window (q \u0026lt; 0.05), whereas the early-window effect did not survive correction. In contrast, no significant deviation of OSLI from zero was observed in either the early or late window for the sham, peak-phase otDCS + iTBS, iTBS, or otDCS conditions after FDR correction. Taken together, these results indicate that the trough-phase otDCS + iTBS condition showed a significant late-window increase in global directed outflow, consistent with the broader and more sustained enhancement of directed connectivity observed in the time-varying network graphs.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThe present study examined the effects of 40 Hz anodal otDCS combined with iTBS at different phase alignments on corticospinal excitability and time-varying brain networks. Several main findings emerged. First, all active stimulation conditions increased MEP amplitudes relative to sham during the early post-stimulation period (0\u0026ndash;20 min). At 30 min, both peak-phase and trough-phase coupling remained significantly above sham, whereas only trough-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS showed a statistical advantage over some of the other stimulation conditions in direct between-condition comparisons. These findings suggest that phase alignment may influence not only the immediate modulation of cortical excitability but also the persistence of after-effects. Under the present stimulation parameters, trough-phase coupling was associated with more persistent corticospinal excitability changes. Second, among the network changes from before to after stimulation observed across conditions, trough-phase coupling was associated with more evident changes in time-varying directed connectivity. In the late window (500\u0026ndash;2000 ms), graph-based visualization suggested more widespread and sustained directed connectivity changes under trough-phase coupling, accompanied by a positive shift in OSLI. Other stimulation conditions also showed network changes, but their spatial extent and temporal profile differed from those observed under trough-phase coupling. The late increase in directed information flow was broadly consistent with the sustained MEP enhancement observed at later post-stimulation time points. Taken together, these findings suggest that the effects of phase coupling may extend beyond local excitability changes and may also involve coordinated reorganization of network-level information transfer.\u003c/p\u003e \u003cp\u003eCompared with peak-phase coupling and the single-modality conditions, the effect of trough-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS on MEP amplitudes was more consistent with a delayed consolidation process than with a simple immediate amplification. Previous studies have shown that the induction and maintenance of LTP-like plasticity in the primary motor cortex depend strongly on the physiological state of the target region at the time of stimulation (Abraham, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Zrenner et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). According to the BCM (Bienenstock-Cooper-Munro) metaplasticity framework, the threshold for synaptic modification is not fixed but shifts dynamically as a function of prior activity (Cooper \u0026amp; Bear, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Murakami et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). At the synaptic level, this state dependence may be related to the nonlinear channel dynamics of N-methyl-D-aspartate receptors (NMDARs). Under moderate depolarization, plasticity-related changes are associated with NMDAR-mediated Ca\u0026sup2;⁺ influx and may contribute to the development of LTP-like effects (Huang et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Wischnewski et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). By contrast, excessive depolarization or prolonged excitatory drive may alter the direction of plasticity and may also recruit local GABAergic interneurons more strongly, thereby enhancing feedback inhibition (Hamada et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). In the present study, the more evident late facilitatory effect under trough-phase stimulation may be related to the transient electrophysiological background at the time of stimulation. Compared with the peak phase, the trough phase corresponds to a moment at which the instantaneous current of the 40 Hz oscillatory waveform approaches zero. A plausible interpretation is that, although this state remains subthreshold, stimulation delivered at the trough phase may occur under a relatively less excitable physiological background. Under such conditions, synaptic plasticity may be less likely to reach saturation prematurely, and compensatory inhibitory recruitment may be less pronounced. As a result, the physiological context during trough-phase stimulation may be more favorable for the induction of LTP-like effects. This interpretation may help explain why trough-phase coupling was associated with a more evident late facilitatory effect in the present study, although the underlying mechanism remains uncertain. By contrast, peak-phase coupling may correspond to a relatively stronger depolarizing background, which could leave less physiological margin for further synaptic strengthening and may be less favorable for the broader network-level expression of plasticity-related effects. Whether phase-specific stimulation also selectively recruits late I-waves that are more sensitive to plasticity remains unclear and warrants further study (Di Lazzaro et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother noteworthy observation is that although both peak-phase and trough-phase coupling remained significantly above sham at 30 min, only trough-phase coupling showed a statistical advantage in direct between-condition comparisons. This suggests that the late effect observed under trough-phase coupling cannot be explained solely by simple summation of electrical and magnetic stimulation, and that their temporal relationship may represent a more important factor. Unlike constant direct current stimulation, otDCS not only biases membrane potential but may also influence ongoing neural oscillations. Its 40 Hz oscillatory component may rhythmically modulate cortical population activity through a fluctuating electric field. In the present study, both phase-coupled conditions were combined with iTBS, which itself facilitates corticospinal excitability, and this likely explains why both conditions remained above sham at later time points. However, the relative advantage observed under trough-phase coupling is unlikely to be attributable simply to a greater total stimulation effect. According to the framework of spike-timing-dependent plasticity (STDP), the relative timing between presynaptic and postsynaptic activity is a key determinant of the direction and magnitude of synaptic modification (Vogeti et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). From this perspective, the continuous oscillatory background generated by otDCS may provide a phase-dependent temporal reference for incoming magnetic pulses. When iTBS bursts arrive at the trough phase, the timing of stimulation may more closely match a window in which cortical neuronal populations are more susceptible to facilitatory input. Such temporal alignment may be more favorable for STDP-related facilitatory plasticity and may contribute to the retention of early plastic changes and their subsequent network-level expression (Raco et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Guerra et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). By contrast, although peak-phase stimulation also occurs under the same 40 Hz oscillatory background, the timing of pulse arrival may not coincide with the most favorable facilitatory window. As a result, support for further strengthening of synaptic connectivity may be relatively limited, and the stabilization of early plastic changes during consolidation may be less efficient (Huang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Taken together, these findings suggest that the more persistent effect observed under trough-phase coupling may depend less on stimulation intensity per se than on a more favorable temporal configuration between electrical and magnetic stimulation.\u003c/p\u003e \u003cp\u003eThe TMS-EEG findings provide complementary network-level evidence for these effects. Time-varying effective connectivity analysis based on the adaptive directed transfer function (ADTF) suggested a biphasic pattern of network change following stimulation. During the early phase (60\u0026ndash;500 ms), directed information flow was generally reduced across the brain. During the late phase (500\u0026ndash;2000 ms), network changes became progressively more condition dependent and followed different trajectories. The widespread decoupling observed during the early phase across active conditions suggests that the original communication pattern may first undergo a brief period of weakening and adjustment following stimulation-induced perturbation. The subsequent divergence of network trajectories during the late phase further suggests that the evolution of information flow at this stage is strongly condition dependent rather than reflecting a uniform recovery process.\u003c/p\u003e \u003cp\u003eFrom a topological perspective, late-stage connectivity patterns differed across stimulation conditions. The sham condition mainly showed spatially dispersed fluctuations and did not exhibit a sustained or clearly organized reconfiguration pattern. Single-modality stimulation also induced enhanced connectivity, but these effects appeared relatively limited and showed marked spatiotemporal selectivity. At the descriptive level, iTBS was mainly characterized by relatively focal bidirectional coupling between the left frontal node F7 and the right parietal nodes P4 and P8 at later stages. In contrast, otDCS initially drove outward pathways centered on the right frontal hubs FC6 and F8 and subsequently evolved toward a more stable right temporo-frontal input pattern. Neither single-modality condition developed into a broadly integrated configuration involving multiple hubs. By contrast, trough-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS showed a more evident trend toward enhanced connectivity during the late phase. In the graph-based visualization, this condition appeared to show local outward-directed connectivity centered on FC5 at an early stage (approximately 208 ms), followed by gradual expansion toward frontal, motor, and posterior regions during 458\u0026ndash;1849 ms. Overall, trough-phase coupling was associated with more widespread connectivity enhancement at multiple late time points. In comparison, peak-phase coupling also showed some enhanced connections during later stages, but their distribution and density were less pronounced than those observed under trough-phase coupling. The enhanced connections under peak-phase coupling remained relatively local rather than developing into a broader pattern of network expansion. In light of the MEP findings, these results suggest that local connectivity enhancement alone may be insufficient to support more persistent excitability changes.\u003c/p\u003e \u003cp\u003eAs a global measure of directed information outflow, the OSLI results were broadly consistent with the network patterns described above. During the early time window (60\u0026ndash;500 ms), OSLI did not significantly deviate from zero under any condition, suggesting that no global increase in outward information flow was evident at this stage. During the late time window (500\u0026ndash;2000 ms), a significant positive OSLI shift relative to baseline was observed under trough-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS, whereas peak-phase coupling, single-modality stimulation, and sham did not show reliable increases in global outward drive. The agreement between the ADTF topology and the global OSLI results suggests that trough-phase coupling may be more closely associated with sustained late-stage reorganization of directed network activity.\u003c/p\u003e \u003cp\u003eThe mechanisms underlying these network-level changes may also be related to the temporal configuration imposed by phase coupling. When iTBS is coupled to the trough phase of the 40 Hz otDCS waveform, the resulting subthreshold bias state may reduce the likelihood of premature saturation of synaptic plasticity while also attenuating compensatory recruitment of local inhibitory circuits. It may further favor spatiotemporal integration processes related to cross-frequency coupling, such as theta-gamma phase-amplitude interactions, thereby increasing the probability that stimulation pulses fall within temporal windows characterized by greater neuronal responsiveness and temporal coordination (Canolty \u0026amp; Knight, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Under such conditions, locally induced activity may be more likely to propagate to distant cortical regions and give rise to broader network responses. By contrast, peak-phase alignment may correspond to a relatively higher background depolarization level and a greater likelihood of engaging local inhibitory circuits. As a result, even when local activation is evident, its propagation to broader networks may remain constrained. The correspondence observed here between network reorganization and the persistence of MEP effects further suggests that long-lasting cortical plasticity may depend not only on transient changes in local synaptic efficacy but also on whether these micro-scale changes can be incorporated into larger-scale cortical network dynamics and support subsequent network-level reorganization.\u003c/p\u003e \u003cp\u003eFinally, RMT remained stable before and after stimulation across conditions. This finding is broadly consistent with previous non-invasive neuromodulation studies showing that subthreshold anodal stimulation or iTBS alone does not typically induce systematic changes in RMT (Hallett, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). From a neurophysiological perspective, RMT is mainly related to the conductance properties of voltage-gated ion channels in corticospinal axons and may, to some extent, reflect baseline membrane excitability (Ziemann et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). The absence of significant RMT changes in the present study therefore suggests that the sustained increase in MEP amplitude observed under trough-phase coupling was more likely related to changes in intracortical synaptic transmission, as well as to alterations in local microcircuits and network connectivity, rather than to a generalized shift in corticospinal threshold.\u003c/p\u003e \u003cp\u003e \u003cb\u003eLimitations\u003c/b\u003e \u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. Although a randomized crossover design with a washout interval of at least 3 days was used, the sample size remained relatively small, and all participants were healthy young adults. Caution is therefore needed when extending these findings to older individuals or clinical populations. In addition, only peak- and trough-phase alignment at 40 Hz was examined. Other parameters, including phase offset, stimulation frequency, stimulation intensity, and burst structure, were not systematically compared. Accordingly, the present findings are better interpreted as proof-of-concept evidence rather than as identification of an optimal dose-timing combination. The observation period was limited to 30 min, and the present study therefore mainly reflects short-term electrophysiological plasticity; direct evidence for behavioral effects or longer-term outcomes remains lacking. Other issues that may also affect interpretation include hotspot-based targeting rather than real-time neuronavigation, sensor-level TMS-EEG analysis, residual sensory artifacts, and possible impedance drift or vigilance fluctuations during prolonged recordings (Biabani et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Conde et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFuture studies should further optimize combinations of phase and dose parameters and incorporate individualized electric field modeling together with source-space analyses (Thielscher et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) to improve mechanistic inference. It will also be important to conduct studies in patient populations with larger sample sizes, longer follow-up periods, and functional outcome measures, in order to better evaluate the durability, generalizability, and translational potential of phase-optimized stimulation protocols.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, the present findings suggest that phase alignment may be a relevant temporal factor in cross-modal electromagnetic neuromodulation. Under the present stimulation parameters, coupling iTBS bursts to the trough phase of 40 Hz otDCS was associated with more persistent enhancement of corticospinal excitability and more evident late-stage changes in directed brain connectivity than peak-phase coupling and the single-modality conditions. These findings support the concept of phase-dependent plasticity in cross-modal stimulation and suggest that temporally coordinated stimulation may help improve the stability of neuromodulatory effects. Future studies are needed to further refine phase-optimized stimulation protocols and to evaluate their potential relevance for neurological disorders characterized by altered brain connectivity, such as stroke and Parkinson\u0026rsquo;s disease.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of the First Hospital of Hebei Medical University. All procedures were conducted in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants prior to enrollment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available due to participant privacy and institutional restrictions but are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Medical Science Research Project of the Health Commission of Hebei Province (Grant No. 20250010).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eS.W. contributed to investigation, formal analysis, and writing the original draft.\u003c/p\u003e\n\u003cp\u003eF.Y. contributed to methodology, validation, and writing\u0026mdash;review and editing.\u003c/p\u003e\n\u003cp\u003eL.L. contributed to investigation.\u003c/p\u003e\n\u003cp\u003eJ.L. contributed to investigation.\u003c/p\u003e\n\u003cp\u003eM.Y. contributed to validation.\u003c/p\u003e\n\u003cp\u003eS.Q. contributed to investigation.\u003c/p\u003e\n\u003cp\u003eH.Q. contributed to validation.\u003c/p\u003e\n\u003cp\u003eD.W. contributed to investigation.\u003c/p\u003e\n\u003cp\u003eY.G. contributed to supervision and writing\u0026mdash;review and editing.\u003c/p\u003e\n\u003cp\u003eY.W. contributed to conceptualization, supervision, and writing\u0026mdash;review and editing.\u003c/p\u003e\n\u003cp\u003eX.M. contributed to supervision and writing\u0026mdash;review and editing.\u003c/p\u003e\n\u003cp\u003eAll authors read and approved the final manuscript.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all participants for their time and cooperation.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbraham, W. 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Brain Stimul, 11(2), 374-389. https://doi.org/10.1016/j.brs.2017.11.016\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"corticospinal excitability, motor-evoked potentials, non-invasive brain stimulation, oscillatory transcranial direct current stimulation, intermittent theta-burst stimulation, TMS-EEG","lastPublishedDoi":"10.21203/rs.3.rs-9418222/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9418222/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntermittent theta-burst stimulation (iTBS) and oscillatory transcranial direct current stimulation (otDCS) can both induce neuroplastic changes, yet the neurophysiological effects of their combination and the role of phase alignment remain unclear. This study examined whether coupling iTBS to the peak versus trough phase of 40 Hz otDCS differentially modulates corticospinal excitability and brain network connectivity. Eighteen healthy adults participated in a randomized crossover study involving five stimulation conditions: peak-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS, trough-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS, otDCS, iTBS, and sham. Motor-evoked potentials (MEPs) and TMS-EEG directed connectivity were assessed. All active stimulation conditions induced early increases in corticospinal excitability. At 30 min, the trough-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS condition produced greater facilitation than the peak-phase otDCS\u0026thinsp;+\u0026thinsp;iTBS condition and the single-modality conditions. TMS-EEG analyses further showed enhanced late-stage directed information flow following trough-phase coupling. These findings indicate that phase alignment influences the after-effects of combined otDCS and iTBS. Trough-phase coupling may contribute to more sustained corticospinal excitability changes and altered directed brain connectivity.\u003c/p\u003e","manuscriptTitle":"Trough-phase coupling of 40 Hz oscillatory transcranial direct current stimulation with iTBS enhances corticospinal excitability and brain connectivity in healthy individuals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-08 16:22:32","doi":"10.21203/rs.3.rs-9418222/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"51523322217915794002293965510378602593","date":"2026-05-19T02:44:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-29T15:22:44+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-20T09:53:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-20T09:16:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of NeuroEngineering and Rehabilitation","date":"2026-04-14T16:51:32+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-neuroengineering-and-rehabilitation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jner","sideBox":"Learn more about [Journal of NeuroEngineering and Rehabilitation](http://jneuroengrehab.biomedcentral.com/)","snPcode":"12984","submissionUrl":"https://submission.nature.com/new-submission/12984/3","title":"Journal of NeuroEngineering and Rehabilitation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1551ef84-86c6-4baa-94e5-99cbb6e53ed2","owner":[],"postedDate":"May 8th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"51523322217915794002293965510378602593","date":"2026-05-19T02:44:02+00:00","index":25,"fulltext":""},{"type":"reviewersInvited","content":"16","date":"2026-04-29T15:22:44+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-08T16:22:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-08 16:22:32","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9418222","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9418222","identity":"rs-9418222","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}