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 Aß42 . 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 2023;93:371-383.

Decreased Frontal Gamma Activity in Alzheimer Disease Patients.

OBJECTIVE: In Alzheimer disease (AD) animal models, synaptic dysfunction has recently been linked to a disorder of high-frequency neuronal activity. In patients, a clear relation between AD and oscillatory activity remains elusive. Here, we attempt to shed light on this relation by using a novel approach combining transcranial magnetic stimulation and electroencephalography (TMS-EEG) to probe oscillatory activity in specific hubs of the frontoparietal network in a sample of 60 mild-to-moderate AD patients. METHODS: Sixty mild-to-moderate AD patients and 21 age-matched healthy volunteers (HVs) underwent 3 TMS-EEG sessions to assess cortical oscillations over the left dorsolateral prefrontal cortex, the precuneus, and the left posterior parietal cortex. To investigate the relations between oscillatory activity, cortical plasticity, and cognitive decline, AD patients underwent a TMS-based neurophysiological characterization and a cognitive evaluation at baseline. The latter was repeated after 24 weeks to monitor clinical evolution. RESULTS: AD patients showed a significant reduction of frontal gamma activity as compared to age-matched HVs. In addition, AD patients with a more prominent decrease of frontal gamma activity showed a stronger impairment of long-term potentiation-like plasticity and a more pronounced cognitive decline at subsequent follow-up evaluation at 24 weeks. INTERPRETATION: Our data provide novel evidence that frontal lobe gamma activity is dampened in AD patients. The current results point to the TMS-EEG approach as a promising technique to measure individual frontal gamma activity in patients with AD. This index could represent a useful biomarker to predict disease progression and to evaluate response to novel pharmacological therapies. ANN NEUROL 2022;92:464-475.

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.

Motor cortex synchronization influences the rhythm of motor performance in premanifest huntington's disease.

BACKGROUND: In Huntington's disease there is evidence of structural damage in the motor system, but it is still unclear how to link this to the behavioral disorder of movement. One feature of choreic movement is variable timing and coordination between sequences of actions. We postulate this results from desynchronization of neural activity in cortical motor areas. OBJECTIVES: The objective of this study was to explore the ability to synchronize activity in a motor network using transcranial magnetic stimulation and to relate this to timing of motor performance. METHODS: We examined synchronization in oscillatory activity of cortical motor areas in response to an external input produced by a pulse of transcranial magnetic stimulation. We combined this with EEG to compare the response of 16 presymptomatic Huntington's disease participants with 16 age-matched healthy volunteers to test whether the strength of synchronization relates to the variability of motor performance at the following 2 tasks: a grip force task and a speeded-tapping task. RESULTS: Phase synchronization in response to M1 stimulation was lower in Huntington's disease than healthy volunteers (P < .01), resulting in a reduced cortical activity at global (P < .02) and local levels (P < .01). Participants who showed better timed motor performance also showed stronger oscillatory synchronization (r = -0.356; P < .05) and higher cortical activity (r = -0.393; P < .05). CONCLUSIONS: Our data may model the ability of the motor command to respond to more subtle, physiological inputs from other brain areas. This novel insight indicates that impairments of the timing accuracy of synchronization and desynchronization could be a physiological basis for some key clinical features of Huntington's disease. © 2018 International Parkinson and Movement Disorder Society.

Bi-directional modulation of somatosensory mismatch negativity with transcranial direct current stimulation: an event related potential study.

Appropriate orientation towards potentially salient novel environmental stimuli requires a system capable of detecting change in the sensorium. Mismatch negativity (MMN), an evoked potential calculated by subtracting the response to a standard repeated stimulus and a rare 'oddball' stimulus, is proposed as such a change detection mechanism. It is most widely studied in the auditory domain, but here we chose to explore the mechanism of somatosensory MMN, and specifically its dependence on the cerebellum. We recorded event-related potentials (ERPs) evoked in response to auditory and sensory stimuli from 10 healthy subjects before and after anodal, cathodal and sham transcranial direct current stimulation (tDCS) of the right cerebellar hemisphere. There was a significant increase in peak amplitude of somatosensory MMN after anodal tDCS (F(1,9) = 8.98, P < 0.02, mean difference anodal pre-post: -1.02 µV) and a significant reduction in peak amplitude of somatosensory MMN after cathodal tDCS (F(1,9) = 7.15, P < 0.03, mean difference cathodal pre-post: 0.65 µV). The amplitude of auditory MMN was unchanged by tDCS. These results reveal the capability of tDCS to cause bidirectional modulation of somatosensory MMN and the dependence of somatosensory MMN on the cerebellum.

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.

Reduced TMS-evoked EEG oscillatory activity in cortical motor regions in patients with post-COVID fatigue.

OBJECTIVE: Persistent fatigue is a major symptom of the so-called 'long-COVID syndrome', but the pathophysiological processes that cause it remain unclear. We hypothesized that fatigue after COVID-19 would be associated with altered cortical activity in premotor and motor regions. METHODS: We used transcranial magnetic stimulation combined with EEG (TMS-EEG) to explore the neural oscillatory activity of the left primary motor area (l-M1) and supplementary motor area (SMA) in a group of sixteen post-COVID patients complaining of lingering fatigue as compared to a sample of age-matched healthy controls. Perceived fatigue was assessed with the Fatigue Severity Scale (FSS) and Fatigue Rating Scale (FRS). RESULTS: Post-COVID patients showed a remarkable reduction of beta frequency in both areas. Correlation analysis exploring linear relation between neurophysiological and clinical measures revealed a significant inverse correlation between the individual level of beta oscillations evoked by TMS of SMA with the individual scores in the FRS (r(15) = -0.596; p = 0.012). CONCLUSIONS: Post-COVID fatigue is associated with a reduction of TMS-evoked beta oscillatory activity in SMA. SIGNIFICANCE: TMS-EEG could be used to identify early alterations of cortical oscillatory activity that could be related to the COVID impact in central fatigue.

Muscle and timing-specific functional connectivity between the dorsolateral prefrontal cortex and the primary motor cortex.

The pFC has a crucial role in cognitive control, executive function, and sensory processing. Functional imaging, neurophysiological, and animal studies provide evidence for a functional connectivity between the dorsolateral pFC (DLPFC) and the primary motor cortex (M1) during free choice but not instructed choice selection tasks. In this study, twin coil, neuronavigated TMS was used to examine the precise timing of the functional interaction between human left DLPFC and ipsilateral M1 during the execution of a free/specified choice selection task involving the digits of the right hand. In a thumb muscle that was not involved in the task, a conditioning pulse to the left DLPFC enhanced the excitability of the ipsilateral M1 during free selection more than specified selection 100 msec after presentation of the cue; the opposite effect was seen at 75 msec. However, the difference between free and externally specified conditions disappeared when a task-specific muscle was investigated. In this case, the influence from DLPFC was dominated by task involvement rather than mode of selection, suggesting that other processes related to movement execution were also operating. Finally, we show that the effects were spatially specific because they were absent when an adjacent area of DLPFC was stimulated. These results reveal temporally and spatially selective interactions between BA 46 and M1 that are both task and muscle specific.

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.

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.

TMS combined with EEG: Recommendations and open issues for data collection and analysis.

Transcranial magnetic stimulation (TMS) evokes neuronal activity in the targeted cortex and connected brain regions. The evoked brain response can be measured with electroencephalography (EEG). TMS combined with simultaneous EEG (TMS-EEG) is widely used for studying cortical reactivity and connectivity at high spatiotemporal resolution. Methodologically, the combination of TMS with EEG is challenging, and there are many open questions in the field. Different TMS-EEG equipment and approaches for data collection and analysis are used. The lack of standardization may affect reproducibility and limit the comparability of results produced in different research laboratories. In addition, there is controversy about the extent to which auditory and somatosensory inputs contribute to transcranially evoked EEG. This review provides a guide for researchers who wish to use TMS-EEG to study the reactivity of the human cortex. A worldwide panel of experts working on TMS-EEG covered all aspects that should be considered in TMS-EEG experiments, providing methodological recommendations (when possible) for effective TMS-EEG recordings and analysis. The panel identified and discussed the challenges of the technique, particularly regarding recording procedures, artifact correction, analysis, and interpretation of the transcranial evoked potentials (TEPs). Therefore, this work offers an extensive overview of TMS-EEG methodology and thus may promote standardization of experimental and computational procedures across groups.

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 ß-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.

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.