TMS-evoked long-lasting artefacts: A new adaptive algorithm for EEG signal correction

OBJECTIVE: During EEG the discharge of TMS generates a long-lasting decay artefact (DA) that makes the analysis of TMS-evoked potentials (TEPs) difficult. Our aim was twofold: (1) to describe how the DA affects the recorded EEG and (2) to develop a new adaptive detrend algorithm (ADA) able to correct the DA. METHODS: We performed two experiments testing 50 healthy volunteers. In experiment 1, we tested the efficacy of ADA by comparing it with two commonly-used independent component analysis (ICA) algorithms. In experiment 2, we further investigated the efficiency of ADA and the impact of the DA evoked from TMS over frontal, motor and parietal areas. RESULTS: Our results demonstrated that (1) the DA affected the EEG signal in the spatiotemporal domain; (2) ADA was able to completely remove the DA without affecting the TEP waveforms; (3). ICA corrections produced significant changes in peak-to-peak TEP amplitude. CONCLUSIONS: ADA is a reliable solution for the DA correction, especially considering that (1) it does not affect physiological responses; (2) it is completely data-driven and (3) its effectiveness does not depend on the characteristics of the artefact and on the number of recording electrodes. SIGNIFICANCE: We proposed a new reliable algorithm of correction for long-lasting TMS-EEG artifacts

Feeling of ownership over an embodied avatar's hand brings about fast changes of fronto-parietal cortical dynamics

When we look at our body parts, we are immediately aware that they belong to us and we rarely doubt about the integrity, continuity, and sense of ownership of our body. Despite this certainty, immersive virtual reality (IVR) may lead to a strong feeling of embodiment over an artificial body part seen from a first-person perspective (1PP). Although such feeling of ownership (FO) has been described in different situations, it is not yet understood how this phenomenon is generated at neural level. To track the real-time brain dynamics associated with FO, we delivered transcranial magnetic stimuli over the hand region in the primary motor cortex (M1) and simultaneously recorded electroencephalography (EEG) in 19 healthy volunteers (11 male/8 female) watching IVR renderings of anatomically plausible (full-limb) versus implausible (hand disconnected from the forearm) virtual limbs. Our data show that embodying a virtual hand is temporally associated with a rapid drop of cortical activity of the onlookers' hand region in the M1 contralateral to the observed hand. Spatiotemporal analysis shows that embodying the avatar's hand is also associated with fast changes of activity within an interconnected fronto-parietal circuit ipsilateral to the brain stimulation. Specifically, an immediate reduction of connectivity with the premotor area is paralleled by an enhancement in the connectivity with the posterior parietal cortex (PPC) which is related to the strength of ownership illusion ratings and thus likely reflects conscious feelings of embodiment. Our results suggest that changes of bodily representations are underpinned by a dynamic cross talk within a highly-plastic, fronto-parietal network

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 (theta tACS) or gamma (gamma tACS) 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 gamma tACS but not with theta tACS 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

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

Novel TMS-EEG indexes to investigate interhemispheric dynamics in humans

To validate two indexes of interhemispheric signal propagation (ISP) and balance (IHB) by combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG)

2019 Dataset of Participatory Budgeting in Italy

The dataset provides data on Italian Municipalities’ policies pertaining to participatory budgeting (PB). The dataset comprises information on municipalities with a population of over 2,000 inhabitants, and is composed as follows: Municipality ISTAT Code (ID), Municipality Name (MN) Province, Region, Population (2011 Census), Researcher (IR), Mapping randomized process (MR), Mapping Method (MM), twenty dummy variables identifying Municipalities running PB in a given year (y1994, y2002 to y2020), Number of years with PB (TOT). Overall, the dataset comprises 4517 units (with 467 missing), for a total of 4050 mapped municipalities

Effect of Cerebellar Stimulation on Gait and Balance Recovery in Patients With Hemiparetic Stroke: A Randomized Clinical Trial

Gait and balance impairment is associated with poorer functional recovery after stroke. The cerebellum is known to be strongly implicated in the functional reorganization of motor networks in patients with stroke, especially for gait and balance functions

Cortico-cortical stimulation and robot-assisted therapy (CCS and RAT) for upper limb recovery after stroke: study protocol for a randomised controlled trial

Abstract Background Since birth, during the exploration of the environment to interact with objects, we exploit both the motor and sensory components of the upper limb (UL). This ability to integrate sensory and motor information is often compromised following a stroke. However, to date, rehabilitation protocols are focused primarily on recovery of motor function through physical therapies. Therefore, we have planned a clinical trial to investigate the effect on functionality of UL after a sensorimotor transcranial stimulation (real vs sham) in add-on to robot-assisted therapy in the stroke population. Methods A randomised double-blind controlled trial design involving 32 patients with a single chronic stroke (onset > 180 days) was planned. Each patient will undergo 15 consecutive sessions (5 days for 3 weeks) of paired associative stimulation (PAS) coupled with UL robot-assisted therapy. PAS stimulation will be administered using a bifocal transcranial magnetic stimulator (TMS) on the posterior-parietal cortex and the primary motor area (real or sham) of the lesioned hemisphere. Clinical, kinematics and neurophysiological changes will be evaluated at the end of protocol and at 1-month follow-up and compared with baseline. The Fugl-Meyer assessment scale will be the primary outcome. Secondly, kinematic variables will be recorded during the box-and-block test and reaching tasks using video analysis and inertial sensors. Single pulse TMS and electroencephalography will be used to investigate the changes in local cortical reactivity and in the interconnected areas. Discussion The presented trial shall evaluate with a multimodal approach the effects of sensorimotor network stimulation applied before a robot-assisted therapy training on functional recovery of the upper extremity after stroke. The combination of neuromodulation and robot-assisted therapy can promote an increase of cortical plasticity of sensorimotor areas followed by a clinical benefit in the motor function of the upper limb. Trial registration ClinicalTrials.gov NCT05478434. Registered on 28 Jul 2022

Regional Precuneus Cortical Hyperexcitability in Alzheimer's Disease Patients

Objective Neuronal excitation/inhibition (E/I) imbalance is a potential cause of neuronal network malfunctioning in Alzheimer's disease (AD), contributing to cognitive dysfunction. Here, we used a novel approach combining transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to probe cortical excitability in different brain areas known to be directly involved in AD pathology. Methods We performed TMS-EEG recordings targeting the left dorsolateral prefrontal cortex (l-DLPFC), the left posterior parietal cortex (l-PPC), and the precuneus (PC) in a large sample of patients with mild-to-moderate AD (n = 65) that were compared with a group of age-matched healthy controls (n = 21). Results We found that patients with AD are characterized by a regional cortical hyperexcitability in the PC and, to some extent, in the frontal lobe, as measured by TMS-evoked potentials. Notably, cortical excitability assessed over the l-PPC was comparable between the 2 groups. Furthermore, we found that the individual level of PC excitability was associated with the level of cognitive impairment, as measured with Mini-Mental State Examination, and with corticospinal fluid levels of A beta(42). Interpretation Our data provide novel evidence that precuneus cortical hyperexcitability is a key feature of synaptic dysfunction in patients with AD. The current results point to the combined approach of TMS and EEG as a novel promising technique to measure hyperexcitability in patients with AD. This index could represent a useful biomarker to stage disease severity and evaluate response to novel therapies. ANN NEUROL 202

TMS-EEG perturbation biomarkers for Alzheimer’s disease patients classification

Abstract 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