Single pulse TMS-induced modulations of resting brain neurodynamics encoded in EEG phase

Fast acquisition of resting motor threshold with a stimulus-response curve - Possibility or hazard for transcranial magnetic stimulation applications?

Objective

Previous research has suggested that transcranial magnetic stimulation (TMS) related cortical excitability measures could be estimated quickly using stimulus-response curves with short interstimulus intervals (ISIs). Here we evaluated the resting motor threshold (rMT) estimated with these curves.

Methods

Stimulus-response curves were measured with three ISIs: 1.2-2 s, 2-3 s, and 3-4 s. Each curve was formed with 108 stimuli using stimulation intensities ranging from 0.75 to 1.25 times the rMT_guess, which was estimated based on motor evoked potential (MEP) amplitudes of three scout responses.

Results

The ISI did not affect the rMT estimated from the curves (F = 0.235, p = 0.683) or single-trial MEP amplitudes at the group level (F = 0.90, p = 0.405), but a significant subject by ISI interaction (F = 3.64; p < 0.001) was detected in MEP amplitudes. No trend was observed which ISI was most excitable, as it varied between subjects.

Conclusions

At the group level, the stimulus-response curves are unaffected by the short ISI. At the individual level, these curves are highly affected by the ISI.

Significance

Estimating rMT using stimulus-response curves with short ISIs impacts the rMT estimate and should be avoided in clinical and research TMS applications.

Bihemispheric sensorimotor oscillatory network states determine cortical responses to transcranial magnetic stimulation

BACKGROUND

Brain responses to external stimuli vary with fluctuating states of neuronal activity. Previous work has demonstrated effects of phase and power of the ongoing local sensorimotor μ-alpha-oscillation on responses to transcranial magnetic stimulation (TMS) of motor cortex (M1). However, M1 is part of a distributed network, and the effects of oscillatory activity in this network on TMS-evoked EEG responses (TEPs) have not been explored.

OBJECTIVES

To determine the effects of oscillatory activity in the bihemispheric sensorimotor network on TEPs.

METHODS

31 healthy subjects received single-pulse TMS of the left M1 hand area during EEG recording. Ongoing bihemispheric sensorimotor cortex oscillatory states were reconstructed from the EEG directly preceding TMS, and inferred by a data-driven method combining a multivariate autoregressive model and a Hidden Markov model. TEP amplitudes (P25, N45, P70, N100 and P180) were then compared between different bihemispheric sensorimotor cortex oscillatory states.

RESULTS

Four bihemispheric sensorimotor cortex oscillatory states were identified, with different interhemispheric expressions of theta and alpha oscillations. High alpha-power states in the stimulated sensorimotor cortex increased P25 amplitude. Alpha power in the alpha-alpha state (stimulated - non-stimulated hemisphere) correlated in both hemispheres with N45 amplitude. Theta power in the alpha-theta state correlated in the non-stimulated hemisphere with P70 amplitude.

CONCLUSIONS

Bihemispheric sensorimotor cortex oscillatory states contribute to TEPs, with a relevance shift from stimulated to non-stimulated M1 from P25 over N45 to P70. This significantly extends previous findings: not only ongoing local oscillations but distributed network oscillatory states determine cortical responsiveness to external stimuli.

Longer Transcranial Magnetic Stimulation Intertrial Interval Increases Size, Reduces Variability, and Improves the Reliability of Motor Evoked Potentials

High rates of variability in the amplitude of transcranial magnetic stimulation (TMS)-induced motor evoked potentials (MEPs), a popular method for assessing corticospinal excitability (CSE), make it essential to examine inherent reliability of the MEP amplitude. We aimed to investigate the effects of different intertrial intervals (ITIs) of single-pulse TMS on the amplitude, variability, and test-retest reliability of MEPs. Twenty-five TMS single pulses were recorded at four different ITIs of 5, 10, 15, and 20 sec from 15 healthy participants who attended two experimental sessions. Repeated measures analysis of variance (rmANOVA) and standardized z-value standard deviations (SDs) were used to investigate the effects of ITIs on MEP amplitudes and variability. Test-retest reliability of MEP amplitudes was also assessed using rmANOVA and intraclass correlation (ICC). rmANOVA revealed significantly larger MEP amplitudes following ITIs of 10, 15, and 20 sec compared with ITI 5, with no significant increases between ITIs of 15 and 20 sec. Standardized z-value SDs revealed variability rate reduction following longer ITIs with significant reductions occurring following ITIs of 10, 15, and 20 sec compared with ITI 5 with no significant difference between ITIs of 15 and 20 sec. rmANOVA showed no significant Time main effect on the MEP changes confirming within- and between-session agreement. ICCs reported significant within- and between-session reliability in all selected ITIs. The findings of the current study indicate that longer ITIs up to 15 sec can significantly induce larger MEPs with lower variability and higher reliability. The increase in ITIs not only reduces the chance of TMS-induced changes in CSE but also helps us to use this assessment tool in studies with smaller sample sizes.

The effects of transcranial alternating current stimulation (tACS) at individual alpha peak frequency (iAPF) on motor cortex excitability in young and elderly adults

Transcranial alternating current stimulation (tACS) can modulate brain oscillations, cortical excitability and behaviour. In aging, the decrease in EEG alpha activity (8–12 Hz) in the parieto-occipital and mu rhythm in the motor cortex are correlated with the decline in cognitive and motor functions, respectively. Increasing alpha activity using tACS might therefore improve cognitive and motor function in the elderly. The present study explored the influence of tACS on cortical excitability in young and old healthy adults. We applied tACS at individual alpha peak frequency for 10 min (1.5 mA) to the left motor cortex. Transcranial magnetic stimulation was used to assess the changes in cortical excitability as measured by motor-evoked potentials at rest, before and after stimulation. TACS increased cortical excitability in both groups. However, our results also suggest that the mechanism behind the effects was different, as we observed an increase and decrease in intracortical inhibition in the old group and young group, respectively. Our results indicate that both groups profited similarly from the stimulation. There was no indication that tACS was more effective in conditions of low alpha power, that is, in the elderly.

Exploring Cortical Plasticity and Oscillatory Brain Dynamics via Transcranial Magnetic Stimulation and Resting-State Electroencephalogram

Transcranial magnetic stimulation (TMS) is a non-invasive, non-pharmacological technique that is able to modulate cortical activity beyond the stimulation period. The residual aftereffects are akin to the plasticity mechanism of the brain and suggest the potential use of TMS for therapy. For years, TMS has been shown to transiently improve symptoms of neuropsychiatric disorders, but the underlying neural correlates remain elusive. Recently, there is evidence that altered connectivity of brain network dynamics is the mechanism underlying symptoms of various neuropsychiatric illnesses. By combining TMS and electroencephalography (EEG), the functional connectivity patterns among brain regions, and the causal link between function or behaviour and a specific brain region can be determined. Nonetheless, the brain network connectivity are highly complex and involve the dynamics interplay among multitude of brain regions. In this review article, we present previous TMS-EEG co-registration studies, which explore the functional connectivity patterns of human cerebral cortex. We argue the possibilities of neural correlates of long-term potentiation/depression (LTP-/LTD)-like mechanisms of synaptic plasticity that drive the TMS aftereffects as shown by the dissociation between EEG and motor evoked potentials (MEP) cortical output. Here, we also explore alternative explanations that drive the EEG oscillatory modulations post TMS. The precise knowledge of the neurophysiological mechanisms underlying TMS will help characterise disturbances in oscillatory patterns, and the altered functional connectivity in neuropsychiatric illnesses.

Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography

The concurrent combination of transcranial magnetic stimulation (TMS) with electroencephalography (TMS-EEG) is a powerful technology for characterizing and modulating brain networks across developmental, behavioral, and disease states. Given the global initiatives in mapping the human brain, recognition of the utility of this technique is growing across neuroscience disciplines. Importantly, TMS-EEG offers translational biomarkers that can be applied in health and disease, across the lifespan, and in humans and animals, bridging the gap between animal models and human studies. However, to utilize the full potential of TMS-EEG methodology, standardization of TMS-EEG study protocols is needed. In this article, we review the principles of TMS-EEG methodology, factors impacting TMS-EEG outcome measures, and the techniques for preventing and correcting artifacts in TMS-EEG data. To promote the standardization of this technique, we provide comprehensive guides for designing TMS-EEG studies and conducting TMS-EEG experiments. We conclude by reviewing the application of TMS-EEG in basic, cognitive and clinical neurosciences, and evaluate the potential of this emerging technology in brain research.

Resting state brain dynamics and its transients: a combined TMS-EEG study

The brain at rest exhibits a spatio-temporally rich dynamics which adheres to systematic behaviours that persist in task paradigms but appear altered in disease. Despite this hypothesis, many rest state paradigms do not act directly upon the rest state and therefore cannot confirm hypotheses about its mechanisms. To address this challenge, we combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG) to study brain's relaxation toward rest following a transient perturbation. Specifically, TMS targeted either the medial prefrontal cortex (MPFC), i.e. part of the Default Mode Network (DMN) or the superior parietal lobule (SPL), involved in the Dorsal Attention Network. TMS was triggered by a given brain state, namely an increase in occipital alpha rhythm power. Following the initial TMS-Evoked Potential, TMS at MPFC enhances the induced occipital alpha rhythm, called Event Related Synchronisation, with a longer transient lifetime than TMS at SPL, and a higher amplitude. Our findings show a strong coupling between MPFC and the occipital alpha power. Although the rest state is organized around a core of resting state networks, the DMN functionally takes a special role among these resting state networks.

Transcranial focused ultrasound modulates intrinsic and evoked EEG dynamics

BACKGROUND

The integration of EEG recordings and transcranial neuromodulation has provided a useful construct for noninvasively investigating the modification of human brain circuit activity. Recent evidence has demonstrated that focused ultrasound can be targeted through the human skull to affect the amplitude of somatosensory evoked potentials and its associated spectral content.

OBJECTIVE/HYPOTHESIS

The present study tests whether focused ultrasound transmitted through the human skull and targeted to somatosensory cortex can affect the phase and phase rate of cortical oscillatory dynamics.

METHODS

A computational model was developed to gain insight regarding the insertion behavior of ultrasound induced pressure waves in the human head. The instantaneous phase and phase rate of EEG recordings before, during, and after transmission of transcranial focused ultrasound (tFUS) to human somatosensory cortex were examined to explore its effects on phase dynamics.

RESULTS

Computational modeling results show the skull effectively reinforces the focusing of tFUS due to curvature of material interfaces. Neurophysiological recordings show that tFUS alters the phase distribution of intrinsic brain activity for beta frequencies, but not gamma. This modulation was accompanied by a change in phase rate of both beta and gamma frequencies. Additionally, tFUS modulated phase distributions in the beta band of early sensory-evoked activity but did not affect late sensory-evoked activity, lending support to the spatial specificity of tFUS for neuromodulation. This spatial specificity was confirmed through an additional experiment where the ultrasound transducer was moved 1 cm laterally from the original cortical target.

CONCLUSIONS

Focused ultrasonic energy can alter EEG oscillatory dynamics through local mechanical perturbation of discrete cortical circuits.

Outline of a general theory of behavior and brain coordination

Much evidence suggests that dynamic laws of neurobehavioral coordination are sui generis: they deal with collective properties that are repeatable from one system to another and emerge from microscopic dynamics but may not (even in principle) be deducible from them. Nevertheless, it is useful to try to understand the relationship between different levels while all the time respecting the autonomy of each. We report a program of research that uses the theoretical concepts of coordination dynamics and quantitative measurements of simple, well-defined experimental model systems to explicitly relate neural and behavioral levels of description in human beings. Our approach is both top-down and bottom-up and aims at ending up in the same place: top-down to derive behavioral patterns from neural fields, and bottom-up to generate neural field patterns from bidirectional coupling between astrocytes and neurons. Much progress can be made by recognizing that the two approaches--reductionism and emergentism--are complementary. A key to understanding is to couch the coordination of very different things--from molecules to thoughts--in the common language of coordination dynamics.

High-frequency neuronal network modulations encoded in scalp EEG precede the onset of focal seizures

Modulations of neuronal network interactions by seizure precursors are only partially understood and difficult to measure, in part due to inherent intra- and inter-patient seizure heterogeneities and EEG variability. This study investigated preictal neuromodulations associated with seizures originating in the temporal and/or frontal lobes, using information theoretic parameters estimated from awake scalp EEGs in two frequency ranges, ≤100 Hz and >100 Hz, respectively. Seizure-related activity at high frequencies has not been extensively estimated in awake scalp EEGs. Based on the statistical similarity of preictal and ictal information parameters, preictal network interactions appeared to be specifically modulated at frequencies >100 Hz, but not at lower frequencies. The dynamics of these parameters varied distinctly according to the origin of seizure onset (temporal versus frontal). Although preliminary, and based on a small patient sample for which the potential heterogeneity of multiple anticonvulsive medications was difficult to control, these results suggest that preictal modulations may be estimated from high-frequency scalp EEGs using directional information measures with high specificity to ictal events, and may thus be promising for improving seizure prediction.