Reproducibility of TMS-Evoked EEG responses

Application of wavelet based denoising techniques to rTMS evoked potentials

This paper presents a new method of removing noise from the EEG response signal recorded during repetitive transcranial magnetic stimulation (rTMS). This noise is principally composed of the residual stimulus artifact and mV amplitude compound muscle action potentials recorded from the scalp muscles and precludes analysis of the cortical evoked potentials, especially during the first 15 ms post stimulus. The method uses the wavelet transform with a fourth order Daubechies mother wavelet and a novel coefficient reduction algorithm based on cortical amplitude thresholds. The approach has been tested and two methods of coefficient reduction compared using data recorded during a study of cortical sensitivity to rTMS at different scalp locations.

Brain responses evoked by high-frequency repetitive transcranial magnetic stimulation: an event-related potential study

BACKGROUND

Many recent studies have used repetitive transcranial magnetic stimulation (rTMS) to study brain-behavior relationships. However, the pulse-to-pulse neural effects of rapid delivery of multiple TMS pulses are unknown largely because of TMS-evoked electrical artifacts limiting recording of brain activity.ObjectiveIn this study, TMS-related artifacts were removed with independent component analysis (ICA), which allowed for the investigation of the neurophysiologic effects of rTMS with simultaneous electroencephalographic (EEG) recordings.

METHODS

Repetitive TMS trains of 10 Hz, 3 seconds (110% of motor threshold) were delivered to the postcentral gyrus and superior parietal lobule in 16 young adults. Simultaneous EEG recordings were made with a TMS-compatible system. The stereotypical pattern of TMS-related electrical artifacts was identified by ICA.

RESULTS

Removal of artifacts allowed for identification of a series of five evoked brain potentials occurring within 100 milliseconds of each TMS pulse. With the exception of the first potential, for both areas targeted, there was a quadratic relationship between potential peak amplitude and pulse number within the TMS train. This was characterized by a decrease, followed by a rise in amplitude.

CONCLUSIONS

ICA is an effective method for removal of TMS-evoked electrical artifacts in EEG data. With the use of this procedure we found that the physiologic responses to TMS pulses delivered in a high-frequency train of pulses are not independent. The sensitivity of the magnitude of these responses to recent stimulation history suggests a complex recruitment of multiple neuronal events with different temporal dynamics.

Potentiation of Short-Latency Cortical Responses by High-Frequency Repetitive Transcranial Magnetic Stimulation

It is generally accepted that low- and high-frequency repetitive transcranial magnetic stimulation (rTMS) induces changes in cortical excitability, but there is only indirect evidence of its effects despite a large number of studies employing different stimulation parameters. Typically the cortical modulations are inferred through indirect measurements, such as recording the change in electromyographic responses. Recently it has become possible to directly evaluate rTMS-induced changes at the cortical level using electronencephalography (EEG). The present study investigates the modulation induced by high-frequency rTMS via EEG by evaluating changes in the latency and amplitude of TMS-evoked responses. In this study, rTMS was applied to the left primary motor cortex (MI) in 16 participants while an EEG was simultaneously acquired from 29 scalp electrodes. The rTMS consisted of 40 trains at 20 Hz with 10 stimuli each (a total of 400 stimuli) that were delivered at the individual resting motor threshold. The on-line modulation induced by the high-frequency TMS was characterized by a sequence of EEG responses. Two of the rTMS-induced responses, P5 and N8, were specifically modulated according to the protocol. Their latency decreased from the first to the last TMS stimuli, while the amplitude values increased. These results provide the first direct, on-line evaluation of the effects of high-frequency TMS on EEG activity. In addition, the results provide a direct demonstration of cortical potentiation induced by rTMS in humans.

Transcranial magnetic stimulation and connectivity mapping: tools for studying the neural bases of brain disorders

There has been an increasing emphasis on characterizing pathophysiology underlying psychiatric and neurological disorders in terms of altered neural connectivity and network dynamics. Transcranial magnetic stimulation (TMS) provides a unique opportunity for investigating connectivity in the human brain. TMS allows researchers and clinicians to directly stimulate cortical regions accessible to electromagnetic coils positioned on the scalp. The induced activation can then propagate through long-range connections to other brain areas. Thus, by identifying distal regions activated during TMS, researchers can infer connectivity patterns in the healthy human brain and can examine how those patterns may be disrupted in patients with different brain disorders. Conversely, connectivity maps derived using neuroimaging methods can identify components of a dysfunctional network. Nodes in this dysfunctional network accessible as targets for TMS by virtue of their proximity to the scalp may then permit TMS-induced alterations of components of the network not directly accessible to TMS via propagated effects. Thus TMS can provide a portal for accessing and altering neural dynamics in networks that are widely distributed anatomically. Finally, when long-term modulation of network dynamics is induced by trains of repetitive TMS, changes in functional connectivity patterns can be studied in parallel with changes in patient symptoms. These correlational data can elucidate neural mechanisms underlying illness and recovery. In this review, we focus on the application of these approaches to the study of psychiatric and neurological illnesses.

Reliability of long-interval cortical inhibition in healthy human subjects: a TMS-EEG study

Cortical inhibition (CI) is measured by transcranial magnetic stimulation (TMS) combined with electromyography (EMG) through long-interval CI (LICI) and cortical silent period (CSP) paradigms. Recently, we illustrated that LICI can be measured from the dorsolateral prefrontal cortex (DLPFC) through combined TMS with electroencephalography (EEG). We further demonstrated that LICI had different effects on cortical oscillations in the DLPFC compared with motor cortex. The purpose of this study was to establish the validity and reliability of TMS-EEG indices of CI and to replicate our previous findings in an extended sample. The validity of TMS-EEG was examined by evaluating its relationship to standard EMG measures of LICI and the CSP in the left motor cortex in 36 and 16 subjects, respectively. Test-retest reliability was examined in 14 subjects who returned for a repeat session within 7 days of the first session. LICI was applied to the left DLPFC in 30 subjects to compare LICI in the DLPFC with that in the motor cortex. In the motor cortex, EEG measures of LICI correlated with EMG measures of LICI and CSP. All indices of LICI showed high test-retest reliability in motor cortex and DLPFC. Gamma and beta oscillations were significantly inhibited in the DLPFC but not in the motor cortex, confirming previous findings in an extended sample. These findings demonstrate that indexing LICI through TMS combined with EEG is a valid and reliable method to evaluate inhibition from motor and prefrontal regions.

EEG responses to TMS are sensitive to changes in the perturbation parameters and repeatable over time

BACKGROUND

High-density electroencephalography (hd-EEG) combined with transcranial magnetic stimulation (TMS) provides a direct and non-invasive measure of cortical excitability and connectivity in humans and may be employed to track over time pathological alterations, plastic changes and therapy-induced modifications in cortical circuits. However, the diagnostic/monitoring applications of this technique would be limited to the extent that TMS-evoked potentials are either stereotypical (non-sensitive) or random (non-repeatable) responses. Here, we used controlled changes in the stimulation parameters (site, intensity, and angle of stimulation) and repeated longitudinal measurements (same day and one week apart) to evaluate the sensitivity and repeatability of TMS/hd-EEG potentials.

METHODOLOGY/PRINCIPAL FINDINGS

In 10 volunteers, we performed 92 single-subject comparisons to evaluate the similarities/differences between pairs of TMS-evoked potentials recorded in the same/different stimulation conditions. For each pairwise comparison, we used non-parametric statistics to calculate a Divergence Index (DI), i.e., the percentage of samples that differed significantly, considering all scalp locations and the entire post-stimulus period. A receiver operating characteristic analysis showed that it was possible to find an optimal DI threshold of 1.67%, yielding 96.7% overall accuracy of TMS/hd-EEG in detecting whether a change in the perturbation parameters occurred or not.

CONCLUSIONS/SIGNIFICANCE

These results demonstrate that the EEG responses to TMS essentially reflect deterministic properties of the stimulated neuronal circuits as opposed to stereotypical responses or uncontrolled variability. To the extent that TMS-evoked potentials are sensitive to changes and repeatable over time, they may be employed to detect longitudinal changes in the state of cortical circuits.

Methodology for combined TMS and EEG

The combination of transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) provides us the possibility to non-invasively probe the brain's excitability, time-resolved connectivity and instantaneous state. Early attempts to combine TMS and EEG suffered from the huge electromagnetic artifacts seen in EEG as a result of the electric field induced by the stimulus pulses. To deal with this problem, TMS-compatible EEG systems have been developed. However, even with amplifiers that are either immune to or recover quickly from the pulse, great challenges remain. Artifacts may arise from the movement of electrodes, from muscles activated by the pulse, from eye movements, from electrode polarization, or from brain responses evoked by the coil click. With careful precautions, many of these problems can be avoided. The remaining artifacts can be usually reduced by filtering, but control experiments are often needed to make sure that the measured signals actually originate in the brain. Several studies have shown the power of TMS-EEG by giving us valuable information about the excitability or connectivity of the brain.