Single-Pulse Transcranial Magnetic Stimulation-Evoked Potential Amplitudes and Latencies in the Motor and Dorsolateral Prefrontal Cortex among Young, Older Healthy Participants, and Schizophrenia Patients

Agreement and Consistency of Absolute and Relative Corticospinal Stimulus-Response Curves for Upper, Lower, and Axial Musculature in Healthy Adults

PURPOSE

To assess the agreement and consistency of absolute and relative stimulus-response curve (SRC) parameter estimates for upper extremity, lower extremity, and axial muscles.

METHODS

Thirty (15 W, age: 27.0 ± 6.3 y, height: 171.9 ± 8.9 cm, weight: 80.2 ± 19.3 kg) healthy adults completed absolute (5% to 100% stimulator output) and relative (65% to 160% motor threshold) SRCs of the first dorsal interosseous, vastus lateralis, and rectus abdominis during submaximal isometric contractions. Mean motor-evoked potential amplitudes were fit with nonlinear regression to derive MEPmax, V50, and slope. Absolute agreement and consistency were assessed with ICCs, Cronbachs alphas, and Bland-Altman plots. Independent t-tests were used to examine differences in motor threshold, physical activity, strength, and muscle activity among participants with valid and invalid SRC parameters.

RESULTS

Absolute and relative SRCs displayed good agreement and consistency for MEPmax and V50 but not slope. Motor thresholds were lower among participants with valid absolute SRCs for the rectus abdominis and vastus lateralis. Motor threshold, physical activity, strength, and muscle activity did not differ among those with valid and invalid parameters for all relative SRCs and absolute SRCs for the first dorsal interosseous.

CONCLUSIONS

Absolute and relative SRCs produce similar MEPmax and V50 estimates in the first dorsal interosseous, vastus lateralis, and rectus abdominis. The validity of absolute and relative SRC results may differ depending on individual characteristics and tested muscles.

Individualized time windows enhance TMS-EEG signal characterization and improve assessment of cortical function in schizophrenia

Transcranial magnetic stimulation and electroencephalography (TMS-EEG) recordings are crucial to directly assess cortical excitability and inhibition in a non-invasive and task-free manner. TMS-EEG signals are characterized by TMS-evoked potentials (TEPs), which are employed to evaluate cortical function. Nonetheless, different time windows (TW) have been used to compute them over the years. Moreover, these TWs tend to be the same for all participants omitting the intersubject variability. Therefore, the objective of this study is to assess the effect of using different TWs to compute the TEPs, moving from a common fixed TW to more adaptive individualized TWs. Twenty-nine healthy (HC) controls and twenty schizophrenia patients (SCZ) underwent single-pulse (SP) TMS-EEG protocol. Firstly, only the HC were considered to evaluate the TEPs for three different TWs in terms of amplitude and topographical distribution. Secondly, the SCZ patients were included to determine which TW is better to characterize the brain alterations of SCZ. The results indicate that a more individualized TW provides a better characterization of the SP TMS-EEG signals, although all of them show the same tendency. Regarding the comparison between groups, the individualized TW is the one that provides a better differentiation between populations. They also provide further support to the possible imbalance of cortical excitability/inhibition in the SCZ population due to its reduced activity in the N45 TEP and greater amplitude values in the N100. Results also suggest that the SCZ brain has a baseline hyperactive state since the TEPs of the SCZ appear earlier than those of the HC.

Modern neurophysiological techniques indexing normal or abnormal brain aging

Brain aging is associated with a decline in cognitive performance, motor function and sensory perception, even in the absence of neurodegeneration. The underlying pathophysiological mechanisms remain incompletely understood, though alterations in neurogenesis, neuronal senescence and synaptic plasticity are implicated. Recent years have seen advancements in neurophysiological techniques such as electroencephalography (EEG), magnetoencephalography (MEG), event-related potentials (ERP) and transcranial magnetic stimulation (TMS), offering insights into physiological and pathological brain aging. These methods provide real-time information on brain activity, connectivity and network dynamics. Integration of Artificial Intelligence (AI) techniques promise as a tool enhancing the diagnosis and prognosis of age-related cognitive decline. Our review highlights recent advances in these electrophysiological techniques (focusing on EEG, ERP, TMS and TMS-EEG methodologies) and their application in physiological and pathological brain aging. Physiological aging is characterized by changes in EEG spectral power and connectivity, ERP and TMS parameters, indicating alterations in neural activity and network function. Pathological aging, such as in Alzheimer's disease, is associated with further disruptions in EEG rhythms, ERP components and TMS measures, reflecting underlying neurodegenerative processes. Machine learning approaches show promise in classifying cognitive impairment and predicting disease progression. Standardization of neurophysiological methods and integration with other modalities are crucial for a comprehensive understanding of brain aging and neurodegenerative disorders. Advanced network analysis techniques and AI methods hold potential for enhancing diagnostic accuracy and deepening insights into age-related brain changes.

Investigating cortical excitability and inhibition in patients with schizophrenia: A TMS-EEG study

BACKGROUND

Transcranial magnetic stimulation (TMS) combined with electromyography (EMG) has widely been used as a non-invasive brain stimulation tool to assess excitation/inhibition (E/I) balance. E/I imbalance is a putative mechanism underlying symptoms in patients with schizophrenia. Combined TMS-electroencephalography (TMS-EEG) provides a detailed examination of cortical excitability to assess the pathophysiology of schizophrenia. This study aimed to investigate differences in TMS-evoked potentials (TEPs), TMS-related spectral perturbations (TRSP) and intertrial coherence (ITC) between patients with schizophrenia and healthy controls.

MATERIALS AND METHODS

TMS was applied over the motor cortex during EEG recording. Differences in TEPs, TRSP and ITC between the patient and healthy subjects were analysed for all electrodes at each time point, by applying multiple independent sample t-tests with a cluster-based permutation analysis to correct for multiple comparisons.

RESULTS

Patients demonstrated significantly reduced amplitudes of early and late TEP components compared to healthy controls. Patients also showed a significant reduction of early delta (50-160 ms) and theta TRSP (30-250ms),followed by a reduction in alpha and beta suppression (220-560 ms; 190-420 ms). Patients showed a reduction of both early (50-110 ms) gamma increase and later (180-230 ms) gamma suppression. Finally, the ITC was significantly lower in patients in the alpha band, from 30 to 260 ms.

CONCLUSION

Our findings support the putative role of impaired GABA-receptor mediated inhibition in schizophrenia impacting excitatory neurotransmission. Further studies can usefully elucidate mechanisms underlying specific symptoms clusters using TMS-EEG biometrics.

Considerable effects of lateralization and aging in intracortical excitation and inhibition

Introduction

Findings based on the use of transcranial magnetic stimulation and electromyography (TMS-EMG) to determine the effects of motor lateralization and aging on intracortical excitation and inhibition in the primary motor cortex (M1) are inconsistent in the literature. TMS and electroencephalography (TMS-EEG) measures the excitability of excitatory and inhibitory circuits in the brain cortex without contamination from the spine and muscles. This study aimed to investigate the effects of motor lateralization (dominant and non-dominant hemispheres) and aging (young and older) and their interaction effects on intracortical excitation and inhibition within the M1 in healthy adults, measured using TMS-EMG and TMS-EEG.

Methods

This study included 21 young (mean age = 28.1 ± 3.2 years) and 21 older healthy adults (mean age = 62.8 ± 4.2 years). A battery of TMS-EMG measurements and single-pulse TMS-EEG were recorded for the bilateral M1.

Results

Two-way repeated-measures analysis of variance was used to investigate lateralization and aging and the lateralization-by-aging interaction effect on neurophysiological outcomes. The non-dominant M1 presented a longer cortical silent period and larger amplitudes of P60, N100, and P180. Corticospinal excitability in older participants was significantly reduced, as supported by a larger resting motor threshold and lower motor-evoked potential amplitudes. N100 amplitudes were significantly reduced in older participants, and the N100 and P180 latencies were significantly later than those in young participants. There was no significant lateralization-by-aging interaction effect in any outcome.

Conclusion

Lateralization and aging have independent and significant effects on intracortical excitation and inhibition in healthy adults. The functional decline of excitatory and inhibitory circuits in the M1 is associated with aging.

A dose-response characterization of transcranial magnetic stimulation intensity and evoked potential amplitude in the dorsolateral prefrontal cortex

By combining transcranial magnetic stimulation (TMS) with electroencephalography, human cortical circuits can be directly interrogated. The resulting electrical trace contains TMS-evoked potential (TEP) components, and it is not known whether the amplitudes of these components are stimulus intensity dependent. We examined this in the left dorsolateral prefrontal cortex in nineteen healthy adult participants and extracted TEP amplitudes for the N40, P60, N120, and P200 components at 110%, 120%, and 130% of resting motor threshold (RMT). To probe plasticity of putative stimulus intensity dose-response relationships, this was repeated after participants received intermittent theta burst stimulation (iTBS; 600 pulses, 80% RMT). The amplitude of the N120 and P200 components exhibited a stimulus intensity dose-response relationship, however the N40 and P60 components did not. After iTBS, the N40 and P60 components continued to exhibit a lack of stimulus intensity dose-dependency, and the P200 dose-response was unchanged. In the N120 component, however, we saw evidence of change within the stimulus intensity dose-dependent relationship characterized by a decrease in absolute peak amplitudes at lower stimulus intensities. These data suggest that TEP components have heterogeneous dose-response relationships, with implications for standardizing and harmonizing methods across experiments. Moreover, the selective modification of the N120 dose-response relationship may provide a novel marker for iTBS plasticity in health and disease.

Three novel methods for determining motor threshold with transcranial magnetic stimulation outperform conventional procedures

Objective. Thresholding of neural responses is central to many applications of transcranial magnetic stimulation (TMS), but the stochastic aspect of neuronal activity and motor evoked potentials (MEPs) challenges thresholding techniques. We analyzed existing methods for obtaining TMS motor threshold and their variations, introduced new methods from other fields, and compared their accuracy and speed.Approach. In addition to existing relative-frequency methods, such as the five-out-of-ten method, we examined adaptive methods based on a probabilistic motor threshold model using maximum-likelihood (ML) or maximuma-posteriori(MAP) estimation. To improve the performance of these adaptive estimation methods, we explored variations in the estimation procedure and inclusion of population-level prior information. We adapted a Bayesian estimation method which iteratively incorporated information of the TMS responses into the probability density function. A family of non-parametric stochastic root-finding methods with different convergence criteria and stepping rules were explored as well. The performance of the thresholding methods was evaluated with an independent stochastic MEP model.Main Results. The conventional relative-frequency methods required a large number of stimuli, were inherently biased on the population level, and had wide error distributions for individual subjects. The parametric estimation methods obtained the thresholds much faster and their accuracy depended on the estimation method, with performance significantly improved when population-level prior information was included. Stochastic root-finding methods were comparable to adaptive estimation methods but were much simpler to implement and did not rely on a potentially inaccurate underlying estimation model.Significance. Two-parameter MAP estimation, Bayesian estimation, and stochastic root-finding methods have better error convergence compared to conventional single-parameter ML estimation, and all these methods require significantly fewer TMS pulses for accurate estimation than conventional relative-frequency methods. Stochastic root-finding appears particularly attractive due to the low computational requirements, simplicity of the algorithmic implementation, and independence from potential model flaws in the parametric estimators.

Auditory white noise exposure results in intrinsic cortical excitability changes

Cortical excitability is commonly measured by applying magnetic stimulation in combination with measuring behavioral response. This measure has, however, some shortcomings including spatial limitation to the primary motor cortex and not accounting for intrinsic excitability fluctuations. Here, we use a measure for intrinsic excitability based on phase synchronization previously validated for epilepsy. We apply this measure in 30 healthy participants' magnetoencephalography (MEG) recordings during the exposure of auditory white noise, a stimulus that has been suggested to modify cortical excitability. Using cortical parcellation of the MEG source data, we could find a specific pattern of increased and decreased excitability while participants are exposed to white noise vs. silence. Specifically, excitability during white noise exposure decreases in the frontal lobe and increases in the temporal lobe. This study thus adds to the understanding of cortical excitability changes due to specific environmental stimuli as well as the spatial extent of these effects.

Assessing Consciousness through Neurofeedback and Neuromodulation: Possibilities and Challenges

Neurofeedback is a non-invasive therapeutic approach that has gained traction in recent years, showing promising results for various neurological and psychiatric conditions. It involves real-time monitoring of brain activity, allowing individuals to gain control over their own brainwaves and improve cognitive performance or alleviate symptoms. The use of electroencephalography (EEG), such as brain-computer interface (BCI), transcranial direct current stimulation (tDCS), and transcranial magnetic stimulation (TMS), has been instrumental in developing neurofeedback techniques. However, the application of these tools in patients with disorders of consciousness (DoC) presents unique challenges. In this narrative review, we explore the use of neurofeedback in treating patients with DoC. More specifically, we discuss the advantages and challenges of using tools such as EEG neurofeedback, tDCS, TMS, and BCI for these conditions. Ultimately, we hope to provide the neuroscientific community with a comprehensive overview of neurofeedback and emphasize its potential therapeutic applications in severe cases of impaired consciousness levels.

TMS-EEG signatures of facilitated cognitive reappraisal in emotion regulation by left ventrolateral prefrontal cortex stimulation

OBJECTIVE

Left ventrolateral prefrontal cortex (VLPFC) has been demonstrated to be a crucial region involved in the down-regulation of negative affect by cognitive reappraisal. However, the neural evidence of causality is still lacking. The current study was to investigate the contribution of left VLPFC in cognitive reappraisal by using single-pulse transcranial magnetic stimulation (spTMS) and electroencephalogram (EEG).

METHODS

Fifteen participants repeated the cognitive reappraisal task at different TMS settings: no stimulation, spTMS applied at 300 ms after image onset to the left VLPFC, and to the vertex as a control site. EEG and behavioral data were concurrently recorded. TMS-evoked potential (TEP) and late positive potential (LPP) were investigated.

RESULTS

In cognitive reappraisal, left VLPFC stimulation elicited stronger TEPs than vertex stimulation at 180 ms after TMS onset. Increased source activation of TEPs was identified in the precentral gyrus. Emotion regulation by reappraisal enlarged the trough of TEP at stimulation site. The left VLPFC stimulation led to enhanced LPP in cognitive reappraisal, which was negatively correlated with self-reported arousal.

CONCLUSIONS

The TMS stimulation over left VLPFC influences the cognitive reappraisal process by potentiating the neural responses. Accordingly, the cortical region responsible for the execution of cognitive reappraisal is activated. The modulated neural activity is related to the behavioral response. The present study provided neural signatures for the facilitated execution of emotion regulation by left VLPFC stimulation, potentially contributing to the therapeutic protocols for mood disorders.

Correlation of White Blood Cell, Neutrophils, and Hemoglobin with Metabolic Syndrome and Its Components

Background

Metabolic syndrome (MetS) is a global health problem. White blood cell (WBC), neutrophils and neutrophil-to-lymphocyte ratio (NLR) are valid indicators involved in acute and chronic inflammation. The aims of our study were to analyze the correlation and severity of these indicators with MetS and its components, and explore the diagnostic value of their combined tests for MetS.

Methods

A total of 7726 subjects were recruited, and laboratory biomarkers were collected. The differences of indicators between MetS group and non-MetS group were analyzed. The linear trend between each indicator and the increasing number of metabolic disorders was analyzed using trend variance test. The correlation between each indicator and MetS with its components was analyzed by logistic regression.

Results

The levels of WBC, neutrophil, and hemoglobin grew significantly in the MetS group compared to non-MetS group, and gradually increased with the increased number of MetS disorders. Logistic regression analysis indicated significant correlations between WBC, neutrophils, and hemoglobin with MetS and its components. ROC curve analysis showed WBC, neutrophils, and hemoglobin served as good predictors for MetS, especially in adults aged under 40.

Conclusion

Our study indicated that WBC, neutrophils, and hemoglobin are efficient indicators for predicting MetS and evaluate its severity.

EEG, ERPs, and EROs in patients with neurodegenerative dementing disorders: A window into the cortical neurophysiology of cognition and behavior

In the human brain, physiological aging is characterized by progressive neuronal loss, leading to disruption of synapses and to a degree of failure in neurotransmission and information flow. However, there is increasing evidence to support the notion that the aged brain has a remarkable level of resilience (i.s. ability to reorganize itself), with the aim of preserving its physiological activity. It is therefore of paramount interest to develop objective markers able to characterize the biological processes underlying brain aging in the intact human, and to distinguish them from brain degeneration associated to age-related neurological progressive diseases like Alzheimer's disease. EEG, alone and combined with transcranial magnetic stimulation (TMS-EEG), is particularly suited to this aim, due to the functional nature of the information provided, and thanks to the ease with which it can be integrated in ecological scenarios including behavioral tasks. In this review, we aimed to provide the reader with updated information about the role of modern methods of EEG and TMS-EEG analysis in the investigation of physiological brain aging and Alzheimer's disease. In particular, we focused on data about cortical connectivity obtained by using readouts such graph theory network brain organization and architecture, and transcranial evoked potentials (TEPs) during TMS-EEG. Overall, findings in the literature support an important potential contribution of such neurophysiological techniques to the understanding of the mechanisms underlying normal brain aging and the early (prodromal/pre-symptomatic) stages of dementia.

Changes in the TMS-evoked potential N100 in the dorsolateral prefrontal cortex as a function of depression severity in adolescents

Studies using transcranial magnetic stimulation with simultaneous electroencephalography (TMS-EEG) revealed an imbalance between cortical excitation and inhibition (E/I) in the dorsolateral prefrontal cortex (DLPFC) in depression. As adolescence is a developmental period with an increase in depression prevalence and profound neural changes, it is crucial to study the relationship between depression and cortical excitability in adolescence. We aimed to investigate the cortical excitability of the DLPFC in adolescents with depression and a dependency of the TMS-evoked potential N100 on the depression severity. 36 clinical patients (12–18 years of age; 21 females) with a major depressive episode were assessed twice in a longitudinal design: shortly after admission (T0) and after six weeks of intervention (T1). GABA-B-mediated cortical inhibition in the left and right DLPFC, as assessed by the N100, was recorded with EEG. Significantly higher depression scores were reported at T0 compared to T1 (p < 0.001). N100 amplitudes were significantly increased (i.e., more negative) at T0 compared to T1 (p = 0.03). No significant hemispheric difference was found in the N100 component. The correlation between the difference in depression severity and the difference in N100 amplitudes (T0–T1) obtained during stimulation of the left DLPFC did not remain significant after correction for testing in both hemispheres. Higher N100 amplitudes during a state of greater depression severity are suggestive of an E/I imbalance in the DLPFC in adolescents with an acute depressive episode. The N100 reduction potentially reflects a normalization of DLPFC over inhibition in association with decreased depressive symptomatology, indicating severity dependency.

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.

TMS-EEG responses across the lifespan: Measurement, methods for characterisation and identified responses

The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) allows probing of the neurophysiology of any neocortical brain area in vivo with millisecond accuracy. TMS-EEG is particularly unique compared with other available neurophysiological methods, as it can measure the state and dynamics of excitatory and inhibitory systems separately. Because of these capabilities, TMS-EEG responses are sensitive to the brain state, and the responses are influenced by brain maturation and ageing, making TMS-EEG a suitable method to study age-specific pathophysiology. In this review, we outline the TMS-EEG measurement procedure, the existing methods used for characterising TMS-EEG responses and the challenges associated with identifying the responses. We also summarise the findings thus far on how TMS-EEG responses change across the lifespan and the TMS-EEG features that separate typical and atypical brain maturation and ageing. Finally, we give an overview of the gaps in current knowledge to provide directions for future studies.

Human Body Rhythms in the Development of Non-Invasive Methods of Closed-Loop Adaptive Neurostimulation

The creation and improvement of non-invasive closed-loop brain stimulation technologies represent an exciting and rapidly expanding field of neuroscience. To identify the appropriate way to close the feedback loop in adaptive neurostimulation procedures, it was previously proposed to use on-line automatic sensory stimulation with the parameters modulated by the patient's own rhythmical processes, such as respiratory rate, heart rate, and electroencephalogram (EEG) rhythms. The current paper aims to analyze several recent studies demonstrating further development in this line of research. The advantages of using automatic closed-loop feedback from human endogenous rhythms in non-invasive adaptive neurostimulation procedures have been demonstrated for relaxation assistance, for the correction of stress-induced functional disturbances, for anxiety management, and for the cognitive rehabilitation of an individual. Several distinctive features of the approach are noted to delineate its further development.