Network-level macroscale structural connectivity predicts propagation of transcranial magnetic stimulation

Debunking the Myth of Excitatory and Inhibitory Repetitive Transcranial Magnetic Stimulation in Cognitive Neuroscience Research

Repetitive TMS (rTMS) is a powerful neuroscientific tool with the potential to noninvasively identify brain-behavior relationships in humans. Early work suggested that certain rTMS protocols (e.g., continuous theta-burst stimulation, intermittent theta-burst stimulation, high-frequency rTMS, low-frequency rTMS) predictably alter the probability that cortical neurons will fire action potentials (i.e., change cortical excitability). However, despite significant methodological, conceptual, and technical advances in rTMS research over the past few decades, overgeneralization of early rTMS findings has led to a stubbornly persistent assumption that rTMS protocols by their nature induce behavioral and/or physiological inhibition or facilitation, even when they are applied to nonmotor cortical sites or under untested circumstances. In this Perspectives article, we offer a "public service announcement" that summarizes the origins of this problematic assumption, highlighting limitations of seminal studies that inspired them and results of contemporary studies that violate them. Next, we discuss problems associated with holding this assumption, including making brain-behavior inferences without confirming the locality and directionality of neurophysiological changes. Finally, we provide recommendations for researchers to eliminate this misguided assumption when designing and interpreting their own work, emphasizing results of recent studies showing that the effects of rTMS on neurophysiological metrics and their associated behaviors can be caused by mechanisms other than binary changes in excitability of the stimulated brain region or network. Collectively, we contend that no rTMS protocol is by its nature either excitatory or inhibitory, and that researchers must use caution with these terms when forming experimental hypotheses and testing brain-behavior relationships.

Exploring the causal involvement of the rIPL and white matter interindividual variability in spatial orienting and consciousness

BACKGROUND

Spatial attention enables the selection of relevant over irrelevant stimuli through dorsal and ventral fronto-parietal networks. These networks are connected through long white matter tracts, such as the superior longitudinal fasciculus (SLF) and the Inferior Fronto-Occipital fasciculus (IFOF).

OBJECTIVE/HYPOTHESIS

The main purpose of this study was to explore, in healthy participants, the causal role of the right Inferior Parietal Lobe (rIPL) in spatial orienting and conscious perception. We also explored how interindividual differences in the microstructural properties of white matter were related to the effects of transcranial magnetic stimulation (TMS) and, secondarily, to attentional orienting effects in the control stimulation condition.

METHODS

Participants (n=51) performed a behavioural task involving the detection of a visual stimulus at the threshold of consciousness, preceded by either central (endogenous) or peripheral (exogenous) cues. After cue onset, a burst of TMS pulses was applied over the rIPL or a control active region (vertex). White matter properties were explored through diffusion-weighted imaging tractography and whole-brain NODDI analysis.

RESULTS

TMS over the rIPL (compared to the control condition) did not modulate spatial attention nor conscious perception, but it decreased accuracy when attention was endogenously oriented (compared to the exogenous condition) and speeded up reaction times when targets were presented in the attended right hemifield (compared to the left hemifield). Part of the variability in the TMS and attentional orienting effects were explained by the integrity of the SLF and the IFOF.

CONCLUSIONS

Individual variability in attentional orienting effects was associated with the anatomical links between attentional networks. Negative correlations between TMS effects and relevant white matter tracts were interpreted as compensatory mechanisms, while positive correlations with tracts innervating the stimulated area could reflect a TMS signal propagation effect. These results will contribute to the understanding of the role of white matter variability in the susceptibility to neuromodulation, with potential implications for research and clinical treatment.

Stimulation mapping and whole-brain modeling reveal gradients of excitability and recurrence in cortical networks

The human brain exhibits a modular and hierarchical structure, spanning low-order sensorimotor to high-order cognitive/affective systems. What is the mechanistic significance of this organization for brain dynamics and information processing properties? We investigated this question using rare simultaneous multimodal electrophysiology (stereotactic and scalp electroencephalography - EEG) recordings in 36 patients with drug-resistant focal epilepsy during presurgical intracerebral electrical stimulation (iES) (323 stimulation sessions). Our analyses revealed an anatomical gradient of excitability across the cortex, with stronger iES-evoked EEG responses in high-order compared to low-order regions. Mathematical modeling further showed that this variation in excitability levels results from a differential dependence on recurrent feedback from non-stimulated regions across the anatomical hierarchy, and could be extinguished by suppressing those connections in-silico. High-order brain regions/networks thus show an activity pattern characterized by more inter-network functional integration than low-order ones, which manifests as a spatial gradient of excitability that is emergent from, and causally dependent on, the underlying hierarchical network structure. These findings offer new insights into how hierarchical brain organization influences cognitive functions and could inform strategies for targeted neuromodulation therapies.

Investigating the predictive models of efficacy of accelerated neuronavigation-guided rTMS for suicidal depression based on multimodal large-scale brain networks

Background

Accelerated neuronavigation-guided high-dose repetitive transcranial magnetic stimulation (NH-rTMS) can rapidly reduce suicidal ideation and alleviate depressive symptoms in one week. Exploring accelerated NH-rTMS-related biomarkers will enhance the precision of treatment decisions for patients with major depressive disorder (MDD). This study aimed to establish predictive models of treatment response to accelerated NH-rTMS in MDD based on multimodal large-scale brain networks.

Method

In this study, morphological, structural, and functional brain networks were constructed for untreated MDD patients with suicidal ideation before accelerated NH-rTMS treatment. Linear support vector regression methods were utilized to examine the ability of multimodal brain networks in predicting antidepressant and anti-suicidal effects of accelerated NH-rTMS.

Results

We found that both the morphological and structural networks predicted the percentage changes of total Beck Scale of Suicidal Ideation and 24-item Hamilton Depression Rating Scale (HAMD-24) scores. Additionally, the functional networks predicted the percentage changes of total HAMD-24 scores. Further analyses revealed that the structural networks outperformed the morphological and functional networks and the somatomotor module outperformed other subnetworks in the prediction.

Conclusions

In summary, our study provides brain connectome-based predictive models of treatment response to accelerated NH-rTMS in MDD patients with suicidal ideation.

Investigating visuo-tactile mirror properties in borderline personality disorder: A TMS-EEG study

OBJECTIVES

Patients with borderline personality disorder (pw-BPD) have decreased levels of cognitive empathy, which may be subtended by mirror-like mechanisms in the somatosensory cortices, i.e., the Tactile Mirror System (TaMS). Here, we aimed to shed light on the TaMS and empathic deficits in pw-BPD focusing on connectivity, using transcranial magnetic stimulation and electroencephalography (TMS-EEG).

METHODS

After study preregistration, we collected self-report measures of empathic abilities, behavioral performance in a visuo-tactile spatial congruency task investigating TaMS activity, and TMS-evoked potentials (TEPs) from 20 pw-BPD and 20 healthy controls. TMS was delivered over the right primary somatosensory cortex (S1) during touch observation and real touch delivery.

RESULTS

Pw-BPD reported significantly lower levels of cognitive empathy than controls and made significantly more errors in reporting the side of real touches during touch observation. Moreover, pw-BPD presented an altered connectivity pattern from S1-TEPs during touch perception and touch observation, in the last case without differences between human- and object-directed touches.

CONCLUSIONS

The results do not support a specific impairment of TaMS in pw-BPD, but reveal significant behavioral and connectivity alterations within the somatosensory network during touch processing.

SIGNIFICANCE

The present findings temper the proposed role of the TaMS in BPD, while still highlighting the involvement of somatosensory network alterations.

Reproducible routes: reliably navigating the connectome to enrich personalized brain stimulation strategies

Non-invasive brain stimulation (NIBS) technologies, such as repetitive transcranial magnetic stimulation (rTMS), offer significant therapeutic potential for a growing number of neuropsychiatric conditions. Concurrent with the expansion of this field is the swift evolution of rTMS methodologies, including approaches to optimize stimulation site planning. Traditional targeting methods, foundational to early successes in the field and still widely employed today, include using scalp-based heuristics or integrating structural MRI co-registration to align the transcranial magnetic stimulation (TMS) coil with anatomical landmarks. Recent evidence, however, supports refining and personalizing stimulation sites based on the target's structural and/or functional connectivity profile. These connectomic approaches harness the network-wide neuromodulatory effects of rTMS to reach deeper brain structures while also enabling a greater degree of personalization by accounting for heterogenous network topology. In this study, we acquired baseline multimodal magnetic resonance (MRI) at two time points to evaluate the reliability and reproducibility of distinct connectome-based strategies for stimulation site planning. Specifically, we compared the intra-individual difference between the optimal stimulation sites generated at each time point for (1) functional connectivity (FC) guided targets derived from resting-state functional MRI and (2) structural connectivity (SC) guided targets derived from diffusion tensor imaging. Our findings suggest superior reproducibility of SC-guided targets. We emphasize the necessity for further research to validate these findings across diverse patient populations, thereby advancing the personalization of rTMS treatments.

The role of white matter variability in TMS neuromodulatory effects

BACKGROUND

Transcranial Magnetic Stimulation (TMS) is a widely used tool to explore the causal role of focal brain regions in cognitive processing. TMS effects over attentional processes are consistent and replicable, while at the same time subjected to individual variability. This individual variability needs to be understood to better comprehend TMS effects, and most importantly, its clinical applications.

OBJECTIVE

This study aimed to explore the role of white matter variability in TMS neuromodulatory effects on behavior in healthy participants (N = 50).

METHODS

Participants completed an attentional task in which orienting and alerting cues preceded near-threshold targets. Continuous Theta Burst Stimulation (cTBS) was applied over the left frontal eye field (FEF) or an active vertex condition. White matter was explored with diffusion-weighted imaging tractography and Tract-Based Spatial Statistics (TBSS).

RESULTS

Behaviorally, TMS over the left FEF slowed down reaction times (especially in the alerting task), impaired accuracy in the objective task, and reduced the proportion of seen targets (as compared to the vertex condition). Attentional effects increased, overall, when TMS was applied to the left FEF as compared to the vertex condition. Correlations between white matter and TMS effects showed i) reduced TMS effects associated with the microstructural properties of long-range white matter pathways such as the superior longitudinal fasciculus (SLF), and interhemispheric fibers of the corpus callosum (CC), and ii) increased TMS effects in participants with high integrity of the CC connecting the stimulated region with the opposite hemisphere. Additionally, variability in attentional effects was also related to white matter, showing iii) increased alerting effects in participants with low integrity of association, commissural, and projection fibers, and iv) increased orienting effects in participants with high integrity of the right SLF III.

CONCLUSION

All these observations highlight the importance of taking into account individual variability in white matter for the understanding of cognitive processing and brain neuromodulation effects.

The alterations of repetitive transcranial magnetic stimulation on the energy landscape of resting-state networks differ across the human cortex

Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention tool for the noninvasive modulation of brain activity and behavior in neuroscience research and clinical settings. However, the resting-state dynamic evolution of large-scale functional brain networks following rTMS has rarely been investigated. Here, using resting-state fMRI images collected from 23 healthy individuals before (baseline) and after 1 Hz rTMS of the left frontal (FRO) and occipital (OCC) lobes, we examined the different effects of rTMS on brain dynamics across the human cortex. By fitting a pairwise maximum entropy model (pMEM), we constructed an energy landscape for the baseline and poststimulus conditions by fitting a pMEM. We defined dominant brain states (local minima) in the energy landscape with synergistic activation and deactivation patterns of large-scale functional networks. We calculated state dynamics including appearance probability, transitions and duration. The results showed that 1 Hz rTMS induced increased and decreased state probability, transitions and duration when delivered to the FRO and OCC targets, respectively. Most importantly, the shortest path and minimum cost between dominant brain states were altered after stimulation. The absolute sum of the costs from the source states to the destinations was lower after OCC stimulation than after FRO stimulation. In conclusion, our study characterized the dynamic trajectory of state transitions in the energy landscape and suggested that local rTMS can induce significant dynamic perturbation involving stimulated and distant functional networks, which aligns with the modern view of the dynamic and complex brain. Our results suggest low-dimensional mapping of rTMS-induced brain adaption, which will contribute to a broader and more effective application of rTMS in clinical settings.

Insight into motor fatigue mechanisms in natalizumab treated multiple sclerosis patients with wearing off

Motor fatigue in Multiple Sclerosis (MS) is due to reduced motor cortex (M1) output and altered sensorimotor network (SMN) modulation. Natalizumab, a disease-modifying therapy, reduces neuroinflammation and improves fatigue. However, some patients treated with natalizumab experience fatigue recurrence ('wearing-off') before subsequent infusions. Wearing-off provides a valuable window into MS-related motor fatigue mechanisms in a controlled, clinically stable, setting. This study investigates whether wearing-off is associated with worsening motor fatigue and its neurophysiological mechanisms and assesses natalizumab's effect on MS-related fatigue. Forty-five relapsing-remitting MS patients with wearing-off symptoms were evaluated pre- and post-natalizumab infusion. Assessments included evaluating disability levels, depressive symptoms, and the impact of fatigue symptoms on cognitive, physical, and psychosocial functioning. The motor fatigue index was computed through the number of blocks completed during a fatiguing task and peripheral, central, and supraspinal fatigue (M1 output) were evaluated by measuring the superimposed twitches evoked by peripheral nerve and transcranial magnetic stimulation of M1. Transcranial magnetic stimulation-electroencephalography assessed M1 effective connectivity by measuring TMS-evoked potentials (TEPs) within the SMN before- and after the task. We found that wearing-off was associated with increased motor fatigue index, increased central and supraspinal fatigue, and diminished task-related modulation of TEPs compared to post-natalizumab infusion. Wearing-off was also associated with worsened fatigue impact and depression symptom scores. We conclude that the wearing-off phenomenon is associated with worsening motor fatigue due to altered M1 output and modulation of the SMN. Motor fatigue in MS may reflect reversible, inflammation-related changes in the SMN that natalizumab can modulate. Our findings apply primarily to MS patients receiving natalizumab, emphasizing the need for further research on other treatments with wearing-off.

Unraveling the mesoscale organization induced by network-driven processes

Complex systems are characterized by emergent patterns created by the nontrivial interplay between dynamical processes and the networks of interactions on which these processes unfold. Topological or dynamical descriptors alone are not enough to fully embrace this interplay in all its complexity, and many times one has to resort to dynamics-specific approaches that limit a comprehension of general principles. To address this challenge, we employ a metric-that we name Jacobian distance-which captures the spatiotemporal spreading of perturbations, enabling us to uncover the latent geometry inherent in network-driven processes. We compute the Jacobian distance for a broad set of nonlinear dynamical models on synthetic and real-world networks of high interest for applications from biological to ecological and social contexts. We show, analytically and computationally, that the process-driven latent geometry of a complex network is sensitive to both the specific features of the dynamics and the topological properties of the network. This translates into potential mismatches between the functional and the topological mesoscale organization, which we explain by means of the spectrum of the Jacobian matrix. Finally, we demonstrate that the Jacobian distance offers a clear advantage with respect to traditional methods when studying human brain networks. In particular, we show that it outperforms classical network communication models in explaining functional communities from structural data, therefore highlighting its potential in linking structure and function in the brain.

Exploring Motor Network Connectivity in State-Dependent Transcranial Magnetic Stimulation: A Proof-of-Concept Study

State-dependent non-invasive brain stimulation (NIBS) informed by electroencephalography (EEG) has contributed to the understanding of NIBS inter-subject and inter-session variability. While these approaches focus on local EEG characteristics, it is acknowledged that the brain exhibits an intrinsic long-range dynamic organization in networks. This proof-of-concept study explores whether EEG connectivity of the primary motor cortex (M1) in the pre-stimulation period aligns with the Motor Network (MN) and how the MN state affects responses to the transcranial magnetic stimulation (TMS) of M1. One thousand suprathreshold TMS pulses were delivered to the left M1 in eight subjects at rest, with simultaneous EEG. Motor-evoked potentials (MEPs) were measured from the right hand. The source space functional connectivity of the left M1 to the whole brain was assessed using the imaginary part of the phase locking value at the frequency of the sensorimotor μ-rhythm in a 1 s window before the pulse. Group-level connectivity revealed functional links between the left M1, left supplementary motor area, and right M1. Also, pulses delivered at high MN connectivity states result in a greater MEP amplitude compared to low connectivity states. At the single-subject level, this relation is more highly expressed in subjects that feature an overall high cortico-spinal excitability. In conclusion, this study paves the way for MN connectivity-based NIBS.

No Object-Location Memory Improvement through Focal Transcranial Direct Current Stimulation over the Right Temporoparietal Cortex

Remembering objects and their associated location (object-location memory; OLM), is a fundamental cognitive function, mediated by cortical and subcortical brain regions. Previously, the combination of OLM training and transcranial direct current stimulation (tDCS) suggested beneficial effects, but the evidence remains heterogeneous. Here, we applied focal tDCS over the right temporoparietal cortex in 52 participants during a two-day OLM training, with anodal tDCS (2 mA, 20 min) or sham (40 s) on the first day. The focal stimulation did not enhance OLM performance on either training day (stimulation effect: -0.09, 95%CI: [-0.19; 0.02], p = 0.08). Higher electric field magnitudes in the target region were not associated with individual performance benefits. Participants with content-related learning strategies showed slightly superior performance compared to participants with position-related strategies. Additionally, training gains were associated with individual verbal learning skills. Consequently, the lack of behavioral benefits through focal tDCS might be due to the involvement of different cognitive processes and brain regions, reflected by participant's learning strategies. Future studies should evaluate whether other brain regions or memory-relevant networks may be involved in the modulation of object-location associations, investigating other target regions, and further exploring individualized stimulation parameters.

Individualized brain mapping for navigated neuromodulation

ABSTRACT

The brain is a complex organ that requires precise mapping to understand its structure and function. Brain atlases provide a powerful tool for studying brain circuits, discovering biological markers for early diagnosis, and developing personalized treatments for neuropsychiatric disorders. Neuromodulation techniques, such as transcranial magnetic stimulation and deep brain stimulation, have revolutionized clinical therapies for neuropsychiatric disorders. However, the lack of fine-scale brain atlases limits the precision and effectiveness of these techniques. Advances in neuroimaging and machine learning techniques have led to the emergence of stereotactic-assisted neurosurgery and navigation systems. Still, the individual variability among patients and the diversity of brain diseases make it necessary to develop personalized solutions. The article provides an overview of recent advances in individualized brain mapping and navigated neuromodulation and discusses the methodological profiles, advantages, disadvantages, and future trends of these techniques. The article concludes by posing open questions about the future development of individualized brain mapping and navigated neuromodulation.

Controlling target brain regions by optimal selection of input nodes

The network control theory framework holds great potential to inform neurostimulation experiments aimed at inducing desired activity states in the brain. However, the current applicability of the framework is limited by inappropriate modeling of brain dynamics, and an overly ambitious focus on whole-brain activity control. In this work, we leverage recent progress in linear modeling of brain dynamics (effective connectivity) and we exploit the concept of target controllability to focus on the control of a single region or a small subnetwork of nodes. We discuss when control may be possible with a reasonably low energy cost and few stimulation loci, and give general predictions on where to stimulate depending on the subset of regions one wishes to control. Importantly, using the robustly asymmetric effective connectome instead of the symmetric structural connectome (as in previous research), we highlight the fundamentally different roles in- and out-hubs have in the control problem, and the relevance of inhibitory connections. The large degree of inter-individual variation in the effective connectome implies that the control problem is best formulated at the individual level, but we discuss to what extent group results may still prove useful.

Effective connectivity abnormalities in Lewy body disease with visual hallucinations

OBJECTIVE

To assess the changes in effective connectivity of important regions of the visual network (VIS) and dorsal attention network (DAN) underlying visual hallucinations (VHs) in Dementia with Lewy Bodies (DLB), Parkinson's Disease (PD) and Parkinson's Disease Dementia (PDD), as measured by a transcranial magnetic stimulation-electroencephalographic technique (TMS-EEG).

METHODS

We stimulated the right visual cortex (V1/V2), the right intraparietal sulcus and the right frontal eye fields, two key regions of the DAN, and measured TMS-evoked cortical activation within the VIS and the DAN. We compared 11 patients with VHs and 15 patients without VHs.

RESULTS

Patients with VHs showed lower TMS-evoked cortical activation within the DAN following intraparietal sulcus and frontal eye fields stimulation than patients without VHs. No difference was found between patients with and without cognitive impairment. Also, when considering only patients with cognitive impairment, VHs were associated with lower TMS-evoked cortical activation following intraparietal sulcus stimulation.

CONCLUSIONS

DLB, PD, and PDD patients with VHs had less effective connectivity of the right intraparietal sulcus within the DAN than patients without VHs.

SIGNIFICANCE

We provided the first evidence that VHs are associated with specific intraparietal sulcus dysfunction within the DAN in patients with PDD, PD, and DLB.

Network-level dynamics underlying a combined rTMS and psychotherapy treatment for major depressive disorder: An exploratory network analysis

Background

Despite the growing use of repetitive transcranial magnetic stimulation (rTMS) as a treatment for depression, there is a limited understanding of the mechanisms of action and how potential treatment-related brain changes help to characterize treatment response. To address this gap in understanding we investigated the effects of an approach combining rTMS with simultaneous psychotherapy on global functional connectivity.

Method

We compared task-related functional connectomes based on an idiographic goal priming task tied to emotional regulation acquired before and after simultaneous rTMS/psychotherapy treatment for patients with major depressive disorders and compared these changes to normative connectivity patterns from a set of healthy volunteers (HV) performing the same task.

Results

At baseline, compared to HVs, patients demonstrated hyperconnectivity of the DMN, cerebellum and limbic system, and hypoconnectivity of the fronto-parietal dorsal-attention network and visual cortex. Simultaneous rTMS/psychotherapy helped to normalize these differences, which were reduced after treatment. This finding suggests that the rTMS/therapy treatment regularizes connectivity patterns in both hyperactive and hypoactive brain networks.

Conclusions

These results help to link treatment to a comprehensive model of the neurocircuitry underlying depression and pave the way for future studies using network-guided principles to significantly improve rTMS efficacy for depression.

Effects of transcranial magnetic stimulation (TMS) current direction and pulse waveform on cortico-cortical connectivity: A registered report TMS-EEG study

Transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) are a promising proxy for measuring effective connectivity, that is, the directed transmission of physiological signals along cortico-cortical tracts, and for developing connectivity-based biomarkers. A crucial point is how stimulation parameters may affect TEPs, as they may contribute to the general variability of findings across studies. Here, we manipulated two TMS parameters (i.e. current direction and pulse waveform) while measuring (a) an early TEP component reflecting contralateral inhibition of motor areas, namely, M1-P15, as an operative model of interhemispheric cortico-cortical connectivity, and (b) motor-evoked potentials (MEP) for the corticospinal pathway. Our results showed that these two TMS parameters are crucial to evoke the M1-P15, influencing its amplitude, latency, and replicability. Specifically, (a) M1-P15 amplitude was strongly affected by current direction in monophasic stimulation; (b) M1-P15 latency was significantly modulated by current direction for monophasic and biphasic pulses. The replicability of M1-P15 was substantial for the same stimulation condition. At the same time, it was poor when stimulation parameters were changed, suggesting that these factors must be controlled to obtain stable single-subject measures. Finally, MEP latency was modulated by current direction, whereas non-statistically significant changes were evident for amplitude. Overall, our study highlights the importance of TMS parameters for early TEP responses recording and suggests controlling their impact in developing connectivity biomarkers from TEPs. Moreover, these results point out that the excitability of the corticospinal tract, which is commonly used as a reference to set TMS intensity, may not correspond to the excitability of cortico-cortical pathways.

Noise improves the association between effects of local stimulation and structural degree of brain networks

Stimulation to local areas remarkably affects brain activity patterns, which can be exploited to investigate neural bases of cognitive function and modify pathological brain statuses. There has been growing interest in exploring the fundamental action mechanisms of local stimulation. Nevertheless, how noise amplitude, an essential element in neural dynamics, influences stimulation-induced brain states remains unknown. Here, we systematically examine the effects of local stimulation by using a large-scale biophysical model under different combinations of noise amplitudes and stimulation sites. We demonstrate that noise amplitude nonlinearly and heterogeneously tunes the stimulation effects from both regional and network perspectives. Furthermore, by incorporating the role of the anatomical network, we show that the peak frequencies of unstimulated areas at different stimulation sites averaged across noise amplitudes are highly positively related to structural connectivity. Crucially, the association between the overall changes in functional connectivity as well as the alterations in the constraints imposed by structural connectivity with the structural degree of stimulation sites is nonmonotonically influenced by the noise amplitude, with the association increasing in specific noise amplitude ranges. Moreover, the impacts of local stimulation of cognitive systems depend on the complex interplay between the noise amplitude and average structural degree. Overall, this work provides theoretical insights into how noise amplitude and network structure jointly modulate brain dynamics during stimulation and introduces possibilities for better predicting and controlling stimulation outcomes.

TMS-evoked responses are driven by recurrent large-scale network dynamics

A compelling way to disentangle the complexity of the brain is to measure the effects of spatially and temporally synchronized systematic perturbations. In humans, this can be non-invasively achieved by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Spatiotemporally complex and long-lasting TMS-EEG evoked potential (TEP) waveforms are believed to result from recurrent, re-entrant activity that propagates broadly across multiple cortical and subcortical regions, dispersing from and later re-converging on, the primary stimulation site. However, if we loosely understand the TEP of a TMS-stimulated region as the impulse response function of a noisy underdamped harmonic oscillator, then multiple later activity components (waveform peaks) should be expected even for an isolated network node in the complete absence of recurrent inputs. Thus emerges a critically important question for basic and clinical research on human brain dynamics: what parts of the TEP are due to purely local dynamics, what parts are due to reverberant, re-entrant network activity, and how can we distinguish between the two? To disentangle this, we used source-localized TMS-EEG analyses and whole-brain connectome-based computational modelling. Results indicated that recurrent network feedback begins to drive TEP responses from 100 ms post-stimulation, with earlier TEP components being attributable to local reverberatory activity within the stimulated region. Subject-specific estimation of neurophysiological parameters additionally indicated an important role for inhibitory GABAergic neural populations in scaling cortical excitability levels, as reflected in TEP waveform characteristics. The novel discoveries and new software technologies introduced here should be of broad utility in basic and clinical neuroscience research.

The effects of age and biological sex on the association between I-wave recruitment and the response to cTBS: an exploratory study

The neuroplastic response to continuous theta burst stimulation (cTBS) is inherently variable. The measurement of I-wave latencies has been shown to strongly predict the magnitude and direction of the response to cTBS, whereby longer latencies are associated with stronger long-term depression-like responses. However, potential differences in this association relating to age and sex have not been explored. We performed cTBS and measured I-wave recruitment (via MEP latencies) in 66 participants (31 female) ranging in age from 11 to 78 years. The influence of age and sex on the association between I-wave recruitment and the response to cTBS was tested using linear regression models. In contrast to previous studies, there was not a significant association between I-wave latencies and cTBS response at the group level (p = 0.142, R² = 0.033). However, there were interactions between I-waves and both age and sex when predicting cTBS response. Subgroup analysis revealed that preferential late I-wave recruitment predicted cTBS response in adolescent females, but not in adolescent or adult males or adult females. These data suggest that the generalisability of I-wave measurement in predicting the response to cTBS may be lower than initially believed. Prediction models should include age and sex, rather than I-wave latencies alone, as our findings suggest that, while each factor alone is not a strong predictor, these factors interact to influence the response to cTBS.

Neural bases of motor fatigue in multiple sclerosis: A multimodal approach using neuromuscular assessment and TMS-EEG

Motor fatigue is one of the most common symptoms in multiple sclerosis (MS) patients. Previous studies suggested that increased motor fatigue in MS may arise at the central nervous system level. However, the mechanisms underlying central motor fatigue in MS are still unclear. This paper investigated whether central motor fatigue in MS reflects impaired corticospinal transmission or suboptimal primary motor cortex (M1) output (supraspinal fatigue). Furthermore, we sought to identify whether central motor fatigue is associated with abnormal M1 excitability and connectivity within the sensorimotor network. Twenty-two patients affected by relapsing-remitting MS and 15 healthy controls (HCs) performed repeated blocks of contraction at different percentages of maximal voluntary contraction with the right first dorsal interosseus muscle until exhaustion. Peripheral, central, and supraspinal components of motor fatigue were quantified by a neuromuscular assessment based on the superimposed twitch evoked by peripheral nerve and transcranial magnetic stimulation (TMS). Corticospinal transmission, excitability and inhibition during the task were tested by measurement of motor evoked potential (MEP) latency, amplitude, and cortical silent period (CSP). M1 excitability and connectivity was measured by TMS-evoked electroencephalography (EEG) potentials (TEPs) elicited by M1 stimulation before and after the task. Patients completed fewer blocks of contraction and showed higher values of central and supraspinal fatigue than HCs. We found no MEP or CSP differences between MS patients and HCs. Patients showed a post-fatigue increase in TEPs propagation from M1 to the rest of the cortex and in source-reconstructed activity within the sensorimotor network, in contrast to the reduction observed in HCs. Post-fatigue increase in source-reconstructed TEPs correlated with supraspinal fatigue values. To conclude, MS-related motor fatigue is caused by central mechanisms related explicitly to suboptimal M1 output rather than impaired corticospinal transmission. Furthermore, by adopting a TMS-EEG approach, we proved that suboptimal M1 output in MS patients is associated with abnormal task-related modulation of M1 connectivity within the sensorimotor network. Our findings shed new light on the central mechanisms of motor fatigue in MS by highlighting a possible role of abnormal sensorimotor network dynamics. These novel results may point to new therapeutical targets for fatigue in MS.

Causally mapping human threat extinction relevant circuits with depolarizing brain stimulation methods

Laboratory threat extinction paradigms and exposure-based therapy both involve repeated, safe confrontation with stimuli previously experienced as threatening. This fundamental procedural overlap supports laboratory threat extinction as a compelling analogue of exposure-based therapy. Threat extinction impairments have been detected in clinical anxiety and may contribute to exposure-based therapy non-response and relapse. However, efforts to improve exposure outcomes using techniques that boost extinction - primarily rodent extinction - have largely failed to date, potentially due to fundamental differences between rodent and human neurobiology. In this review, we articulate a comprehensive pre-clinical human research agenda designed to overcome these failures. We describe how connectivity guided depolarizing brain stimulation methods (i.e., TMS and DBS) can be applied concurrently with threat extinction and dual threat reconsolidation-extinction paradigms to causally map human extinction relevant circuits and inform the optimal integration of these methods with exposure-based therapy. We highlight candidate targets including the amygdala, hippocampus, ventromedial prefrontal cortex, dorsal anterior cingulate cortex, and mesolimbic structures, and propose hypotheses about how stimulation delivered at specific learning phases could strengthen threat extinction.

Assessing the mechanisms of brain plasticity by transcranial magnetic stimulation

Transcranial magnetic stimulation (TMS) is a non-invasive technique for focal brain stimulation based on electromagnetic induction where a fluctuating magnetic field induces a small intracranial electric current in the brain. For more than 35 years, TMS has shown promise in the diagnosis and treatment of neurological and psychiatric disorders in adults. In this review, we provide a brief introduction to the TMS technique with a focus on repetitive TMS (rTMS) protocols, particularly theta-burst stimulation (TBS), and relevant rTMS-derived metrics of brain plasticity. We then discuss the TMS-EEG technique, the use of neuronavigation in TMS, the neural substrate of TBS measures of plasticity, the inter- and intraindividual variability of those measures, effects of age and genetic factors on TBS aftereffects, and then summarize alterations of TMS-TBS measures of plasticity in major neurological and psychiatric disorders including autism spectrum disorder, schizophrenia, depression, traumatic brain injury, Alzheimer's disease, and diabetes. Finally, we discuss the translational studies of TMS-TBS measures of plasticity and their therapeutic implications.

Neurophysiologic predictors of individual risk for post-operative delirium after elective surgery

BACKGROUND

Post-surgical delirium is associated with increased morbidity, lasting cognitive decline, and loss of functional independence. Within a conceptual framework that delirium is triggered by stressors when vulnerabilities exist in cerebral connectivity and plasticity, we previously suggested that neurophysiologic measures might identify individuals at risk for post-surgical delirium. Here we demonstrate the feasibility of the approach and provide preliminary experimental evidence of the predictive value of such neurophysiologic measures for the risk of delirium in older persons undergoing elective surgery.

METHODS

Electroencephalography (EEG) and transcranial magnetic stimulation (TMS) were collected from 23 patients prior to elective surgery. Resting-state EEG spectral power ratio (SPR) served as a measure of integrity of neural circuits. TMS-EEG metrics of plasticity (TMS-plasticity) were used as indicators of brain capacity to respond to stressors. Presence or absence of delirium was assessed using the confusion assessment method (CAM). We included individuals with no baseline clinically relevant cognitive impairment (MoCA scores ≥21) in order to focus on subclinical neurophysiological measures.

RESULTS

In patients with no baseline cognitive impairment (N = 20, age = 72 ± 6), 3 developed post-surgical delirium (MoCA = 24 ± 2.6) and 17 did not (controls; MoCA = 25 ± 2.4). Patients who developed delirium had pre-surgical resting-state EEG power ratios outside the 95% confidence interval of controls, and 2/3 had TMS-plasticity measures outside the 95% CI of controls.

CONCLUSIONS

Consistent with our proposed conceptual framework, this pilot study suggests that non-invasive and scalable neurophysiologic measures can identify individuals at risk of post-operative delirium. Specifically, abnormalities in resting-state EEG spectral power or TMS-plasticity may indicate sub-clinical risk for post-surgery delirium. Extension and confirmation of these findings in a larger sample is needed to assess the clinical utility of the proposed neurophysiologic markers, and to identify specific connectivity and plasticity targets for therapeutic interventions that might minimize the risk of delirium.

Effect of group-based vs individualized stimulation site selection on reliability of network-targeted TMS

BACKGROUND

Transcranial magnetic stimulation (TMS) is a widely used technique for the noninvasive assessment and manipulation of brain activity and behavior. Although extensively used for research and clinical purposes, recent studies have questioned the reliability of TMS findings because of the high inter-individual variability that has been observed.

OBJECTIVE

In this study, we compared the efficacy and reliability of different targeting scenarios on the TMS-evoked response.

METHODS

24 subjects underwent a single pulse stimulation protocol over two parietal nodes belonging to the Dorsal Attention (DAN) and Default Mode (DMN) Networks respectively. Across visits, the stimulated target for both networks was chosen either based on group-derived networks' maps or personalized network topography based on individual anatomy and functional profile. All stimulation visits were conducted twice, one month apart, during concomitant electroencephalography recording.

RESULTS

At the network level, we did not observe significant differences in the TMS-evoked response between targeting conditions. However, reliable patterns of activity were observed- for both networks tested- following the individualized targeting approach. When the same analyses were carried out at the electrode space level, evidence of reliable patterns was observed following the individualized stimulation of the DAN, but not of the DMN.

CONCLUSIONS

Our findings suggest that individualization of stimulation sites might ensure reliability of the evoked TMS-response across visits. Furthermore, individualized stimulation sites appear to be of foremost importance in highly variable, high order task-positive networks, such as the DAN.

Transcranial magnetic stimulation treatment in Alzheimer's disease: a meta-analysis of its efficacy as a function of protocol characteristics and degree of personalization

Alzheimer's disease (AD) represents the most common type of neurodegenerative disorder. Although our knowledge on the causes of AD remains limited and no curative treatments are available, several interventions have been proposed in trying to improve patients' symptomatology. Among those, transcranial magnetic stimulation (TMS) has been shown a promising, safe and noninvasive intervention to improve global cognitive functioning. Nevertheless, we currently lack agreement between research studies on the optimal stimulation protocol yielding the highest efficacy in these patients. To answer this query, we conducted a systematic literature search in PubMed, PsycINFO and Scopus databases and meta-analysis of studies published in the last 10 years (2010-2021) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Differently from prior published meta-analytic work, we investigated whether protocols that considered participants-specific neuroimaging scans for the selection of individualized stimulation targets held more successful outcomes compared to those relying on a generalized targeting selection criteria. We then compared the effect sizes of subsets of studies based on additional protocol characteristics (frequency, duration of intervention, number of stimulation sites, use of concomitant cognitive training and patients' educational level). Our results confirm TMS efficacy in improving global cognitive functioning in mild-to-moderate AD patients, but also highlight the flaws of current protocols characteristics, including a possible lack of sufficient personalization in stimulation protocols.

M1-P15 as a cortical marker for transcallosal inhibition: A preregistered TMS-EEG study

In a recently published study combining transcranial magnetic stimulation and electroencephalography (TMS-EEG), an early component of TMS-evoked potentials (TEPs), i.e., M1-P15, was proposed as a measure of transcallosal inhibition between motor cortices. Given that early TEPs are known to be highly variable, further evidence is needed before M1-P15 can be considered a reliable index of effective connectivity. Here, we conceived a new preregistered TMS-EEG study with two aims. The first aim was validating the M1-P15 as a cortical index of transcallosal inhibition by replicating previous findings on its relationship with the ipsilateral silent period (iSP) and with performance in bimanual coordination. The second aim was inducing a task-dependent modulation of transcallosal inhibition. A new sample of 32 healthy right-handed participants underwent behavioral motor tasks and TMS-EEG recording, in which left and right M1 were stimulated both during bimanual tasks and during an iSP paradigm. Hypotheses and methods were preregistered before data collection. Results show a replication of our previous findings on the positive relationship between M1-P15 amplitude and the iSP normalized area. Differently, the relationship between M1-P15 latency and bimanual coordination was not confirmed. Finally, M1-P15 amplitude was modulated by the characteristics of the bimanual task the participants were performing, and not by the contralateral hand activity during the iSP paradigm. In sum, the present results corroborate our previous findings in validating the M1-P15 as a cortical marker of transcallosal inhibition and provide novel evidence of its task-dependent modulation. Importantly, we demonstrate the feasibility of preregistration in the TMS-EEG field to increase methodological rigor and transparency.

The optimum parameters and neuroimaging mechanism of repetitive transcranial magnetic stimulation to post-stroke cognitive impairment, a protocol of an orthogonally-designed randomized controlled trial

Objective

Repetitive Transcranial Magnetic Stimulation (rTMS) has been used in cognition impairment due to various neuropsychiatric disorders. However, its optimum parameters and the neuroimaging mechanism are still of uncertainty. In order to simulate a study setting as close to real world as possible, the present study introduces a new orthogonally-designed protocol, consisting of the rTMS intervention with four key parameters (stimulating site, frequency, intensity and pulse number) and three different levels in each one, and aims to investigate the optimum parameters and the brain activity and connectivity in default mode network (DMN), dorsal attention network (DAN), central executive network (CEN) following rTMS intervention to post-stroke cognition impairment (PSCI).

Methods

A single-center, orthogonally-designed, triple-blind randomized controlled trial will be conducted and forty-five PSCI patients will be recruited and randomly assigned to one of nine active rTMS groups based on four rTMS paraments: stimulating site, frequency, intensity and pulse number. Neuropsychological, activities of daily living, quality of life and functional magnetic resonance imaging (fMRI) evaluations were be performed pre-, post- and 3 months after rTMS.

Discussion

This study evaluates the optimum parameters of rTMS for patients with post-stroke cognition impairment and explores the alteration of neural function in DMN, DAN, CEN brain network. These results would facilitate the standardized application of rTMS in cognition impairment rehabilitation.

Cortical-subcortical structural connections support transcranial magnetic stimulation engagement of the amygdala

The amygdala processes valenced stimuli, influences emotion, and exhibits aberrant activity across anxiety disorders, depression, and PTSD. Interventions modulating amygdala activity hold promise as transdiagnostic psychiatric treatments. In 45 healthy participants, we investigated whether transcranial magnetic stimulation (TMS) elicits indirect changes in amygdala activity when applied to ventrolateral prefrontal cortex (vlPFC), a region important for emotion regulation. Harnessing in-scanner interleaved TMS/functional MRI (fMRI), we reveal that vlPFC neurostimulation evoked acute and focal modulations of amygdala fMRI BOLD signal. Larger TMS-evoked changes in the amygdala were associated with higher fiber density in a vlPFC-amygdala white matter pathway when stimulating vlPFC but not an anatomical control, suggesting this pathway facilitated stimulation-induced communication between cortex and subcortex. This work provides evidence of amygdala engagement by TMS, highlighting stimulation of vlPFC-amygdala circuits as a candidate treatment for transdiagnostic psychopathology. More broadly, it indicates that targeting cortical-subcortical structural connections may enhance the impact of TMS on subcortical neural activity and, by extension, subcortex-subserved behaviors.

Identification and verification of a 'true' TMS evoked potential in TMS-EEG

The concurrent combination of transcranial magnetic stimulation and electroencephalography (TMS-EEG) can unveil functional neural mechanisms with applications in basic and clinical research. In particular, TMS-evoked potentials (TEPs) potentially allow studying excitability and connectivity of the cortex in a causal manner that is not easily or non-invasively attainable with other neuroimaging techniques. The TEP waveform is obtained by isolating the EEG responses phase-locked to the time of TMS application. The intended component in a TEP waveform is the cortical activation by the TMS-induced electric current, free of instrumental and physiological artifact sources. This artifact-free cortical activation can be referred to as 'true' TEP. However, due to many unwanted auxiliary effects of TMS, the interpretation of 'true' TEPs has not been free of controversy. This paper reviews the most recent understandings of 'true' TEPs and their application. In the first part of the paper, TEP components are defined according to recommended methodologies. In the second part, the verification of 'true' TEP is discussed along with its sensitivity to brain-state, age, and disease. The various proposed origins of TEP components are then presented in the context of existing literature. Throughout the paper, lessons learned from the past TMS-EEG studies are highlighted to guide the identification and interpretation of 'true' TEPs in future studies.

Personalizing Repetitive Transcranial Magnetic Stimulation Parameters for Depression Treatment Using Multimodal Neuroimaging

Repetitive transcranial magnetic stimulation (rTMS) is a tool that can be used to administer treatment for neuropsychiatric disorders such as major depressive disorder, although the clinical efficacy is still rather modest. Overly general stimulation protocols that consider neither patient-specific depression symptomology nor individualized brain characteristics, such as anatomy or structural and functional connections, may be the cause of the high inter- and intraindividual variability in rTMS clinical responses. Multimodal neuroimaging can provide the necessary insights into individual brain characteristics and can therefore be used to personalize rTMS parameters. Optimal coil positioning should include a three-step process: 1) identify the optimal (indirect) target area based on the exact symptom pattern of the patient; 2) derive the cortical (direct) target location based on functional and/or structural connectomes derived from functional and diffusion magnetic resonance imaging data; and 3) determine the ideal coil position by computational modeling, such that the electric field distribution overlaps with the cortical target. These TMS-induced electric field simulations, derived from anatomical and diffusion magnetic resonance imaging data, can be further applied to compute optimal stimulation intensities. In addition to magnetic resonance imaging, electroencephalography can provide complementary information regarding the ongoing brain oscillations. This information can be used to determine the optimal timing and frequency of the stimuli. The heightened benefits of these personalized stimulation approaches are logically reasoned, but speculative. Randomized clinical trials will be required to compare clinical responses from standard rTMS protocols to personalized protocols. Ultimately, an optimized clinical response may result from precision protocols derived from combinations of personalized stimulation parameters.

Identifying novel biomarkers with TMS-EEG - Methodological possibilities and challenges

Biomarkers are essential for understanding the underlying pathologies in brain disorders and for developing effective treatments. Combined transcranial magnetic stimulation and electroencephalography (TMS-EEG) is an emerging neurophysiological tool that can be used for biomarker development. This method can identify biomarkers associated with the function and dynamics of the inhibitory and excitatory neurotransmitter systems and effective connectivity between brain areas. In this review, we outline the current state of the TMS-EEG biomarker field by summarizing the existing protocols and the possibilities and challenges associated with this methodology.

Network structure mediates functional reorganization induced by optogenetic stimulation of non-human primate sensorimotor cortex

Because aberrant network-level functional connectivity underlies a variety of neural disorders, the ability to induce targeted functional reorganization would be a profound development toward therapies for neural disorders. Brain stimulation has been shown to induce large-scale network-wide functional connectivity changes (FCC), but the mapping from stimulation to the induced changes is unclear. Here, we develop a model which jointly considers the stimulation protocol and the cortical network structure to accurately predict network-wide FCC in response to optogenetic stimulation of non-human primate primary sensorimotor cortex. We observe that the network structure has a much stronger effect than the stimulation protocol on the resulting FCC. We also observe that the mappings from these input features to the FCC diverge over frequency bands and successive stimulations. Our framework represents a paradigm shift for targeted neural stimulation and can be used to interrogate, improve, and develop stimulation-based interventions for neural disorders.

Network Diffusion Embedding Reveals Transdiagnostic Subnetwork Disruption and Potential Treatment Targets in Internalizing Psychopathologies

Network diffusion models are a common and powerful way to study the propagation of information through a complex system and they offer straightforward approaches for studying multimodal brain network data. We developed an analytic framework to identify brain subnetworks with perturbed information diffusion capacity using the structural basis that best maps to resting state functional connectivity and applied it towards a heterogeneous dataset of internalizing psychopathologies (IPs), a set of psychiatric conditions in which similar brain network deficits are found across the swath of the disorders, but a unifying neuropathological substrate for transdiagnostic symptom expression is currently unknown. This research provides preliminary evidence of a transdiagnostic brain subnetwork deficit characterized by information diffusion impairment of the right area 8BM, a key brain region involved in organizing a broad spectrum of cognitive tasks, which may underlie previously reported dysfunction of multiple brain circuits in the IPs. We also demonstrate that models of neuromodulation involving targeting this brain region normalize IP diffusion dynamics towards those of healthy controls. These analyses provide a framework for multimodal methods that identify both brain subnetworks with disrupted information diffusion and potential targets of these subnetworks for therapeutic neuromodulatory intervention based on previously well-characterized methodology.

Functional Connectivity States of Alpha Rhythm Sources in the Human Cortex at Rest: Implications for Real-Time Brain State Dependent EEG-TMS

Alpha is the predominant rhythm of the human electroencephalogram, but its function, multiple generators and functional coupling patterns are still relatively unknown. In this regard, alpha connectivity patterns can change between different cortical generators depending on the status of the brain. Therefore, in the light of the communication through coherence framework, an alpha functional network depends on the functional coupling patterns in a determined state. This notion has a relevance for brain-state dependent EEG-TMS because, beyond the local state, a network connectivity overview at rest could provide further and more comprehensive information for the definition of 'instantaneous state' at the stimulation moment, rather than just the local state around the stimulation site. For this reason, we studied functional coupling at rest in 203 healthy subjects with MEG data. Sensor signals were source localized and connectivity was studied at the Individual Alpha Frequency (IAF) between three different cortical areas (occipital, parietal and prefrontal). Two different and complementary phase-coherence metrices were used. Our results show a consistent connectivity between parietal and prefrontal regions whereas occipito-prefrontal connectivity is less marked and occipito-parietal connectivity is extremely low, despite physical closeness. We consider our results a relevant add-on for informed, individualized real-time brain state dependent stimulation, with possible contributions to novel, personalized non-invasive therapeutic approaches.

Phase-dependent local brain states determine the impact of image-guided transcranial magnetic stimulation on motor network electroencephalographic synchronization

Recent studies have synchronized transcranial magnetic stimulation (TMS) application with pre-defined brain oscillatory phases showing how brain response to perturbation depends on the brain state. However, none have investigated whether phase-dependent TMS can possibly modulate connectivity with homologous distant brain regions belonging to the same network. In the framework of network-targeted TMS, we investigated whether stimulation delivered at a specific phase of ongoing brain oscillations might favour stronger cortico-cortical (c-c) synchronization of distant network nodes connected to the stimulation target. Neuronavigated TMS pulses were delivered over the primary motor cortex (M1) during ongoing electroencephalography recording in 24 healthy individuals over two repeated sessions 1 month apart. Stimulation effects were analysed considering whether the TMS pulse was delivered at the time of a positive (peak) or negative (trough) phase of μ-frequency oscillation, which determines c-c synchrony within homologous areas of the sensorimotor network. Diffusion weighted imaging was used to study c-c connectivity within the sensorimotor network and identify contralateral regions connected with the stimulation spot. Depending on when during the μ-activity the TMS-pulse was applied (peak or trough), its impact on inter-hemispheric network synchrony varied significantly. Higher M1-M1 phase-lock synchronization after the TMS-pulse (0-200 ms) in the μ-frequency band was found for trough compared to peak stimulation trials in both study visits. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of the response to the external perturbation, with implications for interventions aimed at engaging more distributed functional brain networks. KEY POINTS: Synchronized transcranial magnetic stimulation (TMS) pulses with pre-defined brain oscillatory phases allow evaluation of the impact of brain states on TMS effects. TMS pulses over M1 at the negative peak of the μ-frequency band induce higher phase-lock synchronization with interconnected contralateral homologous regions. Cortico-cortical synchronization changes are linearly predicted by the fibre density and cross-section of the white matter tract that connects the two brain regions. Phase-dependent TMS delivery might be crucial not only to amplify local effects but also to increase the magnitude and reliability of within-network synchronization.

An integrated TMS-EEG and MRI approach to explore the interregional connectivity of the default mode network

Explorations of the relation between brain anatomy and functional connections in the brain are crucial for shedding more light on network connectivity that sustains brain communication. In this study, by means of an integrative approach, we examined both the structural and functional connections of the default mode network (DMN) in a group of sixteen healthy subjects. For each subject, the DMN was extracted from the structural and functional resonance imaging data; the areas that were part of the DMN were defined as the regions of interest. Then, the target network was structurally explored by diffusion-weighted imaging, tested by neurophysiological means, and retested by means of concurrent transcranial magnetic stimulation and electroencephalography (TMS-EEG). A series of correlational analyses were performed to explore the relationship between the amplitude of early-latency TMS-evoked potentials and the indexes of structural connectivity (weighted number of fibres and fractional anisotropy). Stimulation of the left or right parietal nodes of the DMN-induced activation in the contralateral parietal and frontocentral electrodes within 60 ms; this activation correlated with fractional anisotropy measures of the corpus callosum. These results showed that distant secondary activations after target stimulation can be predicted based on the target’s anatomical connections. Interestingly, structural features of the corpus callosum predicted the activation of the directly connected nodes, i.e., parietal-parietal nodes, and of the broader DMN network, i.e., parietal-frontal nodes, as identified with functional magnetic resonance imaging. Our results suggested that the proposed integrated approach would allow us to describe the contributory causal relationship between structural connectivity and functional connectivity of the DMN.

Cognitive Improvement via Left Angular Gyrus-Navigated Repetitive Transcranial Magnetic Stimulation Inducing the Neuroplasticity of Thalamic System in Amnesic Mild Cognitive Impairment Patients

Background: Stimulating superficial brain regions highly associated with the hippocampus by repetitive transcranial magnetic stimulation (rTMS) may improve memory of Alzheimer’s disease (AD) spectrum patients. Objective: We recruited 16 amnesic mild cognitive impairment (aMCI) and 6 AD patients in the study. All the patients were stimulated to the left angular gyrus, which was confirmed a strong link to the hippocampus through neuroimaging studies, by the neuro-navigated rTMS for four weeks. Methods: Automated fiber quantification using diffusion tensor imaging metrics and graph theory analysis on functional network were employed to detect the neuroplasticity of brain networks. Results: After neuro-navigated rTMS intervention, the episodic memory of aMCI patients and Montreal Cognitive Assessment score of two groups were significantly improved. Increased FA values of right anterior thalamic radiation among aMCI patients, while decreased functional network properties of thalamus subregions were observed, whereas similar changes not found in AD patients. It is worth noting that the improvement of cognition was associated with the neuroplasticity of thalamic system. Conclusion: We speculated that the rTMS intervention targeting left angular gyrus may be served as a strategy to improve cognitive impairment at the early stage of AD patients, supporting by the neuroplasticity of thalamic system.

Personalized Repetitive Transcranial Magnetic Stimulation for Primary Progressive Aphasia

BACKGROUND

Primary progressive aphasia (PPA) is a neurodegenerative syndrome for which no effective treatment is available.

OBJECTIVE

We aimed to assess the effect of repetitive transcranial magnetic stimulation (rTMS), using personalized targeting.

METHODS

We conducted a randomized, double-blind, pilot study of patients with PPA receiving rTMS, with a subgroup of patients receiving active- versus control-site rTMS in a cross-over design. Target for active TMS varied among the cases and was determined during a pre-treatment phase from a list of potential regions. The primary outcome was changes in spontaneous speech (word count). Secondary outcomes included changes in other language tasks, global cognition, global impression of change, neuropsychiatric symptoms, and brain metabolism using FDG-PET.

RESULTS

Twenty patients with PPA were enrolled (14 with nonfluent and 6 with semantic variant PPA). For statistical analyses, data for the two variants were combined. Compared to the control group (n = 7), the group receiving active-site rTMS (n = 20) showed improvements in spontaneous speech, other language tasks, patient and caregiver global impression of change, apathy, and depression. This group also showed improvement or stabilization of results obtained in the baseline examination. Increased metabolism was observed in several brain regions after the therapy, particularly in the left frontal and parieto-temporal lobes and in the precuneus and posterior cingulate bilaterally.

CONCLUSION

We found an improvement in language, patient and caregiver perception of change, apathy, and depression using high frequency rTMS. The increase of regional brain metabolism suggests enhancement of synaptic activity with the treatment.

TRIAL REGISTRATION

NCT03580954 (https://clinicaltrials.gov/ct2/show/NCT03580954).

Targeting Default Mode Network Dysfunction in Persons at Risk of Alzheimer's Disease with Transcranial Magnetic Stimulation (NEST4AD): Rationale and Study Design

BACKGROUND

Default mode network (DMN) dysfunction is well established in Alzheimer's disease (AD) and documented in both preclinical stages and at-risk subjects, thus representing a potential disease target. Multi-sessions of repetitive transcranial magnetic stimulation (rTMS) seem capable of modulating DMN dynamics and memory in healthy individuals and AD patients; however, the potential of this approach in at-risk subjects has yet to be tested.

OBJECTIVE

This study will test the effect of rTMS on the DMN in healthy older individuals carrying the strongest genetic risk factor for AD, the Apolipoprotein E (APOE) ɛ4 allele.

METHODS

We will recruit 64 older participants without cognitive deficits, 32 APOE ɛ4 allele carriers and 32 non-carriers as a reference group. Participants will undergo four rTMS sessions of active (high frequency) or sham DMN stimulation. Multimodal imaging exam (including structural, resting-state, and task functional MRI, and diffusion tensor imaging), TMS with concurrent electroencephalography (TMS-EEG), and cognitive assessment will be performed at baseline and after the stimulation sessions.

RESULTS

We will assess changes in DMN connectivity with resting-state functional MRI and TMS-EEG, as well as changes in memory performance in APOE ɛ4 carriers. We will also investigate the mechanisms underlying DMN modulation through the assessment of correlations with measures of neuronal activity, excitability, and structural connectivity with multimodal imaging.

CONCLUSION

The results of this study will inform on the physiological and cognitive outcomes of DMN stimulation in subjects at risk for AD and on the possible mechanisms. These results may outline the design of future non-pharmacological preventive interventions for AD.

Alpha-band cortico-cortical phase synchronization is associated with effective connectivity in the motor network

OBJECTIVE

Communication-through-coherence proposes that the phase synchronization (PS) of neural oscillations between cortical areas supports neural communication. In this study, we exploited transcranial magnetic stimulation (TMS)-evoked potentials (TEPs) to test this hypothesis at the macroscale level, i.e., whether PS between cortical areas supports interarea communication. TEPs are electroencephalographic (EEG) responses time-locked to TMS pulses reflecting interarea communication, as they are generated by the transmission of neural activity from the stimulated area to connected regions. If interarea PS is important for communication, it should be associated with the TEP amplitude in the connected areas.

METHODS

TMS was delivered over the left primary motor cortex (M1) of fourteen healthy volunteers, and 70-channel EEG was recorded. Early TEP components were source-localized to identify their generators, i.e., distant brain regions activated by M1 through effective connections. Next, linear regressions were used to test the relationship between the TEP amplitude and the pre-stimulus PS between the M1 and the connected regions in four frequency bands (range 4-45 Hz).

RESULTS

Pre-stimulus interarea PS in the alpha-band was positively associated with the amplitude of early TEP components, namely, the N15 (ipsilateral supplementary motor area), P25 (contralateral M1) and P60 (ipsilateral parietal cortex).

CONCLUSIONS

Alpha-band PS predicts the response amplitude of the distant brain regions effectively connected to M1.

SIGNIFICANCE

Our study supports the role of EEG-PS in interarea communication, as theorized by communication-through-coherence.

Perturbation of resting-state network nodes preferentially propagates to structurally rather than functionally connected regions

Combining Transcranial Magnetic Stimulation (TMS) with electroencephalography (EEG) offers the opportunity to study signal propagation dynamics at high temporal resolution in the human brain. TMS pulse induces a local effect which propagates across cortical networks engaging distant cortical and subcortical sites. However, the degree of propagation supported by the structural compared to functional connectome remains unclear. Clarifying this issue would help tailor TMS interventions to maximize target engagement. The goal of this study was to establish the contribution of functional and structural connectivity in predicting TMSinduced signal propagation after perturbation of two distinct brain networks. For this purpose, 24 healthy individuals underwent two identical TMS-EEG visits where neuronavigated TMS pulses were delivered to nodes of the default mode network (DMN) and the dorsal attention network (DAN). The functional and structural connectivity derived from each individual stimulation spot were characterized via functional magnetic resonance imaging (fMRI) and Diffusion Weighted Imaging (DWI), and signal propagation across these two metrics was compared. Direct comparison between the signal extracted from brain regions either functionally or structurally connected to the stimulation sites, shows a stronger activation over cortical areas connected via white matter pathways, with a minor contribution of functional projections. This pattern was not observed when analyzing spontaneous resting state EEG activity. Overall, results suggest that structural links can predict network-level response to perturbation more accurately than functional connectivity. Additionally, DWI-based estimation of propagation patterns can be used to estimate off-target engagement of other networks and possibly guide target selection to maximize specificity.

Tinnitus and Brain Stimulation

The pathophysiological mechanisms that underlie the generation and maintenance of tinnitus are being unraveled progressively. Based on this knowledge, a large variety of different neuromodulatory interventions have been developed and are still being designed, adapting to the progressive mechanistic insights in the pathophysiology of tinnitus. rTMS targeting the temporal, temporoparietal, and the frontal cortex has been the mainstay of non-invasive neuromodulation. Yet, the evidence is still unclear, and therefore systematic meta-analyses are needed for drawing conclusions on the effectiveness of rTMS in chronic tinnitus. Different forms of transcranial electrical stimulation (tDCS, tACS, tRNS), applied over the frontal and temporal cortex, have been investigated in tinnitus patients, also without robust evidence for universal efficacy. Cortex and deep brain stimulation with implanted electrodes have shown benefit, yet there is insufficient data to support their routine clinical use. Recently, bimodal stimulation approaches have revealed promising results and it appears that targeting different sensory modalities in temporally combined manners may be more promising than single target approaches.While most neuromodulatory approaches seem promising, further research is required to help translating the scientific outcomes into routine clinical practice.