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32 result(s) for "Casula, Elias"
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Transcranial magnetic stimulation of the precuneus enhances memory and neural activity in prodromal Alzheimer's disease
Memory loss is one of the first symptoms of typical Alzheimer's disease (AD), for which there are no effective therapies available. The precuneus (PC) has been recently emphasized as a key area for the memory impairment observed in early AD, likely due to disconnection mechanisms within large-scale networks such as the default mode network (DMN). Using a multimodal approach we investigated in a two-week, randomized, sham-controlled, double-blinded trial the effects of high-frequency repetitive transcranial magnetic stimulation (rTMS) of the PC on cognition, as measured by the Alzheimer Disease Cooperative Study Preclinical Alzheimer Cognitive Composite in 14 patients with early AD (7 females). TMS combined with electroencephalography (TMS-EEG) was used to detect changes in brain connectivity. We found that rTMS of the PC induced a selective improvement in episodic memory, but not in other cognitive domains. Analysis of TMS-EEG signal revealed an increase of neural activity in patients' PC, an enhancement of brain oscillations in the beta band and a modification of functional connections between the PC and medial frontal areas within the DMN. Our findings show that high-frequency rTMS of the PC is a promising, non-invasive treatment for memory dysfunction in patients at early stages of AD. This clinical improvement is accompanied by modulation of brain connectivity, consistently with the pathophysiological model of brain disconnection in AD. •The precuneus is a key area for memory impairment in Alzheimer’s disease (AD).•We investigated the effects of precuneus-rTMS on memory in patients with early AD.•Precuneus-rTMS induced a selective improvement in episodic memory.•Precuneus-rTMS enhance precuneus activity and connectivity with frontal areas.•Precuneus-rTMS is a promising treatment for memory dysfunction in early AD patients.
TMS-EEG perturbation biomarkers for Alzheimer’s disease patients classification
The combination of TMS and EEG has the potential to capture relevant features of Alzheimer’s disease (AD) pathophysiology. We used a machine learning framework to explore time-domain features characterizing AD patients compared to age-matched healthy controls (HC). More than 150 time-domain features including some related to local and distributed evoked activity were extracted from TMS-EEG data and fed into a Random Forest (RF) classifier using a leave-one-subject out validation approach. The best classification accuracy, sensitivity, specificity and F1 score were of 92.95%, 96.15%, 87.94% and 92.03% respectively when using a balanced dataset of features computed globally across the brain. The feature importance and statistical analysis revealed that the maximum amplitude of the post-TMS signal, its Hjorth complexity and the amplitude of the TEP calculated in the window 45–80 ms after the TMS-pulse were the most relevant features differentiating AD patients from HC. TMS-EEG metrics can be used as a non-invasive tool to further understand the AD pathophysiology and possibly contribute to patients’ classification as well as longitudinal disease tracking.
Low-frequency rTMS inhibitory effects in the primary motor cortex: Insights from TMS-evoked potentials
The neuromodulatory effects of repetitive transcranial magnetic stimulation (rTMS) have been mostly investigated by peripheral motor-evoked potentials (MEPs). New TMS-compatible EEG systems allow a direct investigation of the stimulation effects through the analysis of TMS-evoked potentials (TEPs). We investigated the effects of 1-Hz rTMS over the primary motor cortex (M1) of 15 healthy volunteers on TEP evoked by single pulse TMS over the same area. A second experiment in which rTMS was delivered over the primary visual cortex (V1) of 15 healthy volunteers was conducted to examine the spatial specificity of the effects. Single-pulse TMS evoked four main components: P30, N45, P60 and N100. M1-rTMS resulted in a significant decrease of MEP amplitude and in a significant increase of P60 and N100 amplitude. There was no effect after V1-rTMS. 1-Hz rTMS appears to increase the amount of inhibition following a TMS pulse, as demonstrated by the higher N100 and P60, which are thought to originate from GABAb-mediated inhibitory post-synaptic potentials. Our results confirm the reliability of the TMS-evoked N100 as a marker of cortical inhibition and provide insight into the neuromodulatory effects of 1-Hz rTMS. The present finding could be of relevance for therapeutic and diagnostic purposes. •We studied the effect of 1-Hz rTMS on EEG activity evoked by single pulse TMS.•Motor cortex rTMS increased late TEPs (P60/N100) and decreased MEPs.•The rTMS effects are compatible with an enhancement of inhibition following TMS.•Results confirmed that some TEP components may be markers of cortical inhibition.•Results provide insight in to the neuromodulatory mechanism of 1-Hz rTMS.
Variability and Predictors of Response to Continuous Theta Burst Stimulation: A TMS-EEG Study
Continuous theta-burst stimulation (cTBS) is a repetitive transcranial magnetic stimulation paradigm reported to decrease the excitability of the stimulated cortical area and which is thought to reflect a form of inhibitory synaptic plasticity. However, since its introduction, the effect of cTBS has shown a remarkable variability in its effects, which are often quantified by measuring the amplitude of motor evoked potentials (MEPs). Part of this inconsistency in experimental results might be due to an intrinsic variability of TMS effects caused by genetic or neurophysiologic factors. However, it is also possible that MEP only reflect the excitability of a sub-population of output neurons; resting EEG power and measures combining TMS and electroencephalography (TMS-EEG) might represent a more thorough reflection of cortical excitability. The aim of the present study was to verify the robustness of several predictors of cTBS response, such as I wave recruitment and baseline MEP amplitude, and to test cTBS after-effects on multiple neurophysiologic measurements such as MEP, resting EEG power, local mean field power (LMFP), TMS-related spectral perturbation (TRSP), and inter-trial phase clustering (ITPC). As a result, we were not able to confirm either the expected decrease of MEP amplitude after cTBS or the ability of I wave recruitment and MEP amplitude to predict the response to cTBS. Resting EEG power, LMFP, TRSP, and ITPC showed a more consistent trend toward a decrease after cTBS. Overall, our data suggest that the effect of cTBS on corticospinal excitability is variable and difficult to predict with common electrophysiologic markers, while its effect might be clearer when probed with combined TMS and EEG.
Machine Learning-Based Classification to Disentangle EEG Responses to TMS and Auditory Input
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) offers an unparalleled opportunity to study cortical physiology by characterizing brain electrical responses to external perturbation, called transcranial-evoked potentials (TEPs). Although these reflect cortical post-synaptic potentials, they can be contaminated by auditory evoked potentials (AEPs) due to the TMS click, which partly show a similar spatial and temporal scalp distribution. Therefore, TEPs and AEPs can be difficult to disentangle by common statistical methods, especially in conditions of suboptimal AEP suppression. In this work, we explored the ability of machine learning algorithms to distinguish TEPs recorded with masking of the TMS click, AEPs and non-masked TEPs in a sample of healthy subjects. Overall, our classifier provided reliable results at the single-subject level, even for signals where differences were not shown in previous works. Classification accuracy (CA) was lower at the group level, when different subjects were used for training and test phases, and when three stimulation conditions instead of two were compared. Lastly, CA was higher when average, rather than single-trial TEPs, were used. In conclusion, this proof-of-concept study proposes machine learning as a promising tool to separate pure TEPs from those contaminated by sensory input.
Improving visuo-motor learning with cerebellar theta burst stimulation: Behavioral and neurophysiological evidence
The cerebellum is strongly implicated in learning new motor skills. Theta burst stimulation (TBS), a form of repetitive transcranial magnetic stimulation, can be used to influence cerebellar activity. Our aim was to explore the potential of cerebellar TBS in modulating visuo-motor adaptation, a form of motor learning, in young healthy subjects. Cerebellar TBS was applied immediately before the learning phase of a visuo-motor adaptation task (VAT), in two different experiments. Firstly, we evaluated the behavioral effects of continuous (cTBS), intermittent (iTBS) or sham TBS on the learning, re-adaptation and de-adaptation phases of VAT. Subsequently, we investigated the changes induced by iTBS or sham TBS on motor cortical activity related to each phase of VAT, as measured by concomitant TMS/EEG recordings. We found that cerebellar TBS induced a robust bidirectional modulation of the VAT performance. More specifically, cerebellar iTBS accelerated visuo-motor adaptation, by speeding up error reduction in response to a novel perturbation. This gain of function was still maintained when the novel acquired motor plan was tested during a subsequent phase of re-adaptation. On the other hand, cerebellar cTBS induced the opposite effect, slowing the rate of error reduction in both learning and re-adaptation phases. Additionally, TMS/EEG recordings showed that cerebellar iTBS induced specific changes of cortical activity in the interconnected motor networks. The improved performance was accompanied by an increase of TMS-evoked cortical activity and a generalized desynchronization of TMS-evoked cortical oscillations. Taken together, our behavioral and neurophysiological findings provide the first-time multimodal evidence of the potential efficacy of cerebellar TBS in improving motor learning, by promoting successful cerebellar-cortical reorganization. ∙The cerebellum is crucial in visuo-motor adaptation.∙Neural activity of the cerebellum can be modulated by means of theta burst stimulation (TBS).∙Cerebellar iTBS speeds up motor learning, modulating motor cortical activity.
The effect of coil orientation on the stimulation of the pre-supplementary motor area: a combined TMS and EEG study
Studies using transcranial magnetic stimulation (TMS) have demonstrated the importance of direction and intensity of the applied current when the primary motor cortex (M1) is targeted. By varying these, it is possible to stimulate different subsets of neural elements, as demonstrated by modulation of motor evoked potentials (MEPs) and motor behaviour. The latter involves premotor areas as well, and among them, the presupplementary motor area (pre–SMA) has recently received significant attention in the study of motor inhibition. It is possible that, similar to M1, different neuronal populations can be activated by varying the direction and intensity of TMS; however, the absence of a direct electrophysiological outcome has limited this investigation. The problem can be solved by quantifying direct cortical responses by means of combined TMS and electroencephalography (TMS–EEG). We investigated the effect of variable coil orientations (0°, 90°, 180° and 270°) and stimulation intensities (100%, 120% and 140% of resting motor threshold) on local mean field potential (LMFP), transcranial evoked potential (TEP) peaks and TMS–related spectral perturbation (TRSP) from pre–SMA stimulation. As a result, early and late LMFP and peaks were larger, with the coil handle pointing posteriorly (0°) and laterally (90°). This was true also for TRSP in the β–γ range, but, surprisingly, θ–α TRSP was larger with the coil pointing at 180°. A 90° orientation activated the right M1, as shown by MEPs elicitation, thus limiting the spatial specificity of the stimulation. These results suggest that coil orientation and stimulation intensity are critical when stimulating the pre–SMA.
Cerebellar theta burst stimulation modulates the neural activity of interconnected parietal and motor areas
Voluntary movement control and execution are regulated by the influence of the cerebellar output over different interconnected cortical areas, through dentato-thalamo connections. In the present study we applied transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to directly assess the effects of cerebellar theta-burst stimulation (TBS) over the controlateral primary motor cortex (M1) and posterior parietal cortex (PPC) in a group of healthy volunteers. We found a TBS-dependent bidirectional modulation over TMS-evoked activity; specifically, cTBS increased whereas iTBS decreased activity between 100 and 200 ms after TMS, in a similar manner over both M1 and PPC areas. On the oscillatory domain, TBS induced specific changes over M1 natural frequencies of oscillation: TMS-evoked alpha activity was decreased by cTBS whereas beta activity was enhanced by iTBS. No effects were observed after sham stimulation. Our data provide novel evidence showing that the cerebellum exerts its control on the cortex likely by impinging on specific set of interneurons dependent on GABA-ergic activity. We show that cerebellar TBS modulates cortical excitability of distant interconnected cortical areas by acting through common temporal, spatial and frequency domains.
Real-time cortical dynamics during motor inhibition
The inhibition of action is a fundamental executive mechanism of human behaviour that involve a complex neural network. In spite of the progresses made so far, many questions regarding the brain dynamics occurring during action inhibition are still unsolved. Here, we used a novel approach optimized to investigate real-time effective brain dynamics, which combines transcranial magnetic stimulation (TMS) with simultaneous electroencephalographic (EEG) recordings. 22 healthy volunteers performed a motor Go/NoGo task during TMS of the hand-hotspot of the primary motor cortex (M1) and whole-scalp EEG recordings. We reconstructed source-based real-time spatiotemporal dynamics of cortical activity and cortico-cortical connectivity throughout the task. Our results showed a task-dependent bi-directional change in theta/gamma supplementary motor cortex (SMA) and M1 connectivity that, when participants were instructed to inhibit their response, resulted in an increase of a specific TMS-evoked EEG potential (N100), likely due to a GABA-mediated inhibition. Interestingly, these changes were linearly related to reaction times, when participants were asked to produce a motor response. In addition, TMS perturbation revealed a task-dependent long-lasting modulation of SMA–M1 natural frequencies, i.e. alpha/beta activity. Some of these results are shared by animal models and shed new light on the physiological mechanisms of motor inhibition in humans.
Simultaneous transcranial electrical and magnetic stimulation boost gamma oscillations in the dorsolateral prefrontal cortex
Neural oscillations in the gamma frequency band have been identified as a fundament for synaptic plasticity dynamics and their alterations are central in various psychiatric and neurological conditions. Transcranial magnetic stimulation (TMS) and alternating electrical stimulation (tACS) may have a strong therapeutic potential by promoting gamma oscillations expression and plasticity. Here we applied intermittent theta-burst stimulation (iTBS), an established TMS protocol known to induce LTP-like cortical plasticity, simultaneously with transcranial alternating current stimulation (tACS) at either theta (θtACS) or gamma (γtACS) frequency on the dorsolateral prefrontal cortex (DLPFC). We used TMS in combination with electroencephalography (EEG) to evaluate changes in cortical activity on both left/right DLPFC and over the vertex. We found that simultaneous iTBS with γtACS but not with θtACS resulted in an enhancement of spectral gamma power, a trend in shift of individual peak frequency towards faster oscillations and an increase of local connectivity in the gamma band. Furthermore, the response to the neuromodulatory protocol, in terms of gamma oscillations and connectivity, were directly correlated with the initial level of cortical excitability. These results were specific to the DLPFC and confined locally to the site of stimulation, not being detectable in the contralateral DLPFC. We argue that the results described here could promote a new and effective method able to induce long-lasting changes in brain plasticity useful to be clinically applied to several psychiatric and neurological conditions.