Removal of physiological artifacts from simultaneous EEG and fMRI recordings.

OBJECTIVE: Simultaneous recording of the electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) allows a combination of eletrophysiological and haemodynamic information to be used to form a more complete picture of cerebral dynamics. However, EEG recorded within the MRI scanner is contaminated by both imaging artifacts and physiological artifacts. The majority of the techniques used to pre-process such EEG focus on removal of the imaging and balistocardiogram artifacts, with some success, but don't remove all other physiological artifacts. METHODS: We propose a new offline EEG artifact removal method based upon a combination of independent component analysis and fMRI-based head movement estimation to aid the removal of physiological artifacts from EEG recorded during EEG-fMRI recordings. Our method makes novel use of head movement trajectories estimated from the fMRI recording in order to assist with identifying physiological artifacts in the EEG and is designed to be used after removal of the fMRI imaging artifact from the EEG. RESULTS: We evaluate our method on EEG recorded during a joint EEG-fMRI session from healthy adult participants. Our method significantly reduces the influence of all types of physiological artifacts on the EEG. We also compare our method with a state-of-the-art physiological artifact removal method and demonstrate superior performance removing physiological artifacts. CONCLUSIONS: Our proposed method is able to remove significantly more physiological artifact components from the EEG, recorded during a joint EEG-fMRI session, than other state-of-the-art methods. SIGNIFICANCE: Our proposed method represents a marked improvement over current processing pipelines for removing physiological noise from EEG recorded during a joint EEG-fMRI session.

Distributed source modeling of intracranial stereoelectro-encephalographic measurements.

Intracranial stereoelectroencephalography (sEEG) provides unsurpassed sensitivity and specificity for human neurophysiology. However, functional mapping of brain functions has been limited because the implantations have sparse coverage and differ greatly across individuals. Here, we developed a distributed, anatomically realistic sEEG source-modeling approach for within- and between-subject analyses. In addition to intracranial event-related potentials (iERP), we estimated the sources of high broadband gamma activity (HBBG), a putative correlate of local neural firing. Our novel approach accounted for a significant portion of the variance of the sEEG measurements in leave-one-out cross-validation. After logarithmic transformations, the sensitivity and signal-to-noise ratio were linearly inversely related to the minimal distance between the brain location and electrode contacts (slope≈-3.6). The signa-to-noise ratio and sensitivity in the thalamus and brain stem were comparable to those locations at the vicinity of electrode contact implantation. The HGGB source estimates were remarkably consistent with analyses of intracranial-contact data. In conclusion, distributed sEEG source modeling provides a powerful neuroimaging tool, which facilitates anatomically-normalized functional mapping of human brain using both iERP and HBBG data.

A comprehensive study on electroencephalography and magnetoencephalography sensitivity to cortical and subcortical sources.

Signal-to-noise ratio (SNR) maps are a good way to visualize electroencephalography (EEG) and magnetoencephalography (MEG) sensitivity. SNR maps extend the knowledge about the modulation of EEG and MEG signals by source locations and orientations and can therefore help to better understand and interpret measured signals as well as source reconstruction results thereof. Our work has two main objectives. First, we investigated the accuracy and reliability of EEG and MEG finite element method (FEM)-based sensitivity maps for three different head models, namely an isotropic three and four-compartment and an anisotropic six-compartment head model. As a result, we found that ignoring the cerebrospinal fluid leads to an overestimation of EEG SNR values. Second, we examined and compared EEG and MEG SNR mappings for both cortical and subcortical sources and their modulation by source location and orientation. Our results for cortical sources show that EEG sensitivity is higher for radial and deep sources and MEG for tangential ones, which are the majority of sources. As to the subcortical sources, we found that deep sources with sufficient tangential source orientation are recordable by the MEG. Our work, which represents the first comprehensive study where cortical and subcortical sources are considered in highly detailed FEM-based EEG and MEG SNR mappings, sheds a new light on the sensitivity of EEG and MEG and might influence the decision of brain researchers or clinicians in their choice of the best modality for their experiment or diagnostics, respectively.

Reliability of mismatch negativity event-related potentials in a multisite, traveling subjects study.

OBJECTIVE: To determine the optimal methods for measuring mismatch negativity (MMN), an auditory event-related potential (ERP), and quantify sources of MMN variance in a multisite setting. METHODS: Reliability of frequency, duration, and double (frequency + duration) MMN was determined from eight traveling subjects, tested on two occasions at eight laboratory sites. Deviant-specific variance components were estimated for MMN peak amplitude and latency measures using different ERP processing methods. Generalizability (G) coefficients were calculated using two-facet (site and occasion), fully-crossed models and single-facet (occasion) models within each laboratory to assess MMN reliability. RESULTS: G-coefficients calculated from two-facet models indicated fair (0.4 < G<=0.6) duration MMN reliability at electrode Fz, but poor (G < 0.4) double and frequency MMN reliability. Single-facet G-coefficients averaged across laboratory resulted in improved reliability (G > 0.5). MMN amplitude reliability was greater than latency reliability, and reliability with mastoid referencing significantly outperformed nose-referencing. CONCLUSIONS: EEG preprocessing methods have an impact on the reliability of MMN amplitude. Within site MMN reliability can be excellent, consistent with prior single site studies. SIGNIFICANCE: With standardized data collection and ERP processing, MMN can be reliably obtained in multisite studies, providing larger samples sizeswithin rare patient groups.

A TrAdaBoost Method for Detecting Multiple Subjects' N200 and P300 Potentials Based on Cross-Validation and an Adaptive Threshold.

Traditional training methods need to collect a large amount of data for every subject to train a subject-specific classifier, which causes subjects fatigue and training burden. This study proposes a novel training method, TrAdaBoost based on cross-validation and an adaptive threshold (CV-T-TAB), to reduce the amount of data required for training by selecting and combining multiple subjects' classifiers that perform well on a new subject to train a classifier. This method adopts cross-validation to extend the amount of the new subject's training data and sets an adaptive threshold to select the optimal combination of the classifiers. Twenty-five subjects participated in the N200- and P300-based brain-computer interface. The study compares CV-T-TAB to five traditional training methods by testing them on the training of a support vector machine. The accuracy, information transfer rate, area under the curve, recall and precision are used to evaluate the performances under nine conditions with different amounts of data. CV-T-TAB outperforms the other methods and retains a high accuracy even when the amount of data is reduced to one-third of the original amount. The results imply that CV-T-TAB is effective in improving the performance of a subject-specific classifier with a small amount of data by adopting multiple subjects' classifiers, which reduces the training cost.

Temporal and spatial characteristics of meditation EEG.

OBJECTIVE: This article discusses the importance of decisions made about the temporal and spatial characteristics of EEG during recording and analysis of meditation practices. ISSUE: A recent meta-analysis averaged EEG in the alpha1 and alpha2 bands to characterize mindfulness practices. This ignored known differences in cognitive processing associated with these two bands, and so confounded their conclusion about brain patterns during mindfulness. Another paper averaged EEG from central electrodes, which reflect activity of motor cortices, and frontal electrodes, which reflect activity of the frontal association cortices, to characterize Transcendental Meditation practice. This averaged the signals from motor and frontal cortices, which respond to different behaviors, and so confounded any conclusion about the nature of brain patterns during Transcendental Meditation practice. Also, both of these papers reported power-derived measures. This misses the connectivity information that is captured in coherence analysis. CONCLUSION: Meditation researchers should (a) investigate narrow frequency bands, especially theta1, theta2, alpha1 and alpha2, which are known to reflect different cognitive processes, (b) average EEG over theoretically known spatial areas, and (c) employ power as well as coherence analysis to more accurately define different categories of meditation practices and more reliably apply meditation practices to specific subject populations. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Addressing measurement issues in electroencephalography studies of meditations as alternative interventions of posttraumatic stress disorder.

Posttraumatic stress disorder (PTSD) is a debilitating mental disorder affecting numerous U.S. citizens, but conventional interventions have shown limited success in treating PTSD symptoms (e.g., high dropout rates). Various meditative techniques have been used as alternative interventions to treat PTSD, demonstrating that these interventions have strong potential to improve symptoms and quality of life in people with PTSD. Despite the initial promise, our limited understanding of the mechanisms of meditation has hindered the establishment of meditation as an evidence-based clinical intervention optimized for trauma survivors. Therefore, it is imperative to determine the neurobiological mechanism of meditation using rigorous functional outcome measures of the central nervous system. Electroencephalography (EEG) has been widely used as an ideal tool for mechanistic studies of meditation because it provides a sensitive functional neural measurement of synchronized brain networks that may reflect meditation-related trait and state changes in brain dynamics. However, recent meta-analyses of EEG meditation studies have provided mixed findings, with some consistencies across (e.g., enhanced theta and alpha frequency neural oscillations) as well as a number of inconsistent findings across studies. The present commentary addresses critical measurement issues in meditation EEG studies that are often disregarded and thus underlie the replication problems, which represent one of the major obstacles in mechanistic studies of meditation using EEG. In particular, the physiological artifact-related issues in time, frequency, and time-frequency measures and spatial-domain measurement problems inherent to EEG are reviewed, and standard methods of EEG processing and analysis are recommended to resolve the problems. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Detecting silent seizures by their sound.

OBJECTIVE: The traditional approach to interpreting electroencephalograms (EEGs) requires physicians with formal training to visually assess the waveforms. This approach can be less practical in critical settings where a trained EEG specialist is not readily available to review the EEG and diagnose ongoing subclinical seizures, such as nonconvulsive status epilepticus. METHODS: We have developed a novel method by which EEG data are converted to sound in real time by letting the underlying electrophysiological signal modulate a voice tone that is in the audible range. Here, we explored whether individuals without any prior EEG training could listen to 15-second sonified EEG and determine whether the EEG represents seizures or nonseizure conditions. We selected 84 EEG samples to represent seizures (n = 7), seizure-like activity (n = 25), or nonperiodic, nonrhythmic activity (normal or focal/generalized slowing, n = 52). EEGs from single channels in the left and right hemispheres were then converted to sound files. After a 4-minute training video, medical students (n = 34) and nurses (n = 30) were asked to designate each audio sample as "seizure" or "nonseizure." We then compared their performance with that of EEG-trained neurologists (n = 12) and medical students (n = 29) who also diagnosed the same EEGs on visual display. RESULTS: Nonexperts listening to single-channel sonified EEGs detected seizures with remarkable sensitivity (students, 98% ± 5%; nurses, 95% ± 14%) compared to experts or nonexperts reviewing the same EEGs on visual display (neurologists, 88% ± 11%; students, 76% ± 19%). If the EEGs contained seizures or seizure-like activity, nonexperts listening to sonified EEGs rated them as seizures with high specificity (students, 85% ± 9%; nurses, 82% ± 12%) compared to experts or nonexperts viewing the EEGs visually (neurologists, 90% ± 7%; students, 65% ± 20%). SIGNIFICANCE: Our study confirms that individuals without EEG training can detect ongoing seizures or seizure-like rhythmic periodic patterns by listening to sonified EEG. Although sonification of EEG cannot replace the traditional approaches to EEG interpretation, it provides a meaningful triage tool for fast assessment of patients with suspected subclinical seizures.

ERP correlates of error processing during performance on the Halstead Category Test.

The Halstead Category Test (HCT) is a neuropsychological test that measures a person's ability to formulate and apply abstract principles. Performance must be adjusted based on feedback after each trial and errors are common until the underlying rules are discovered. Event-related potential (ERP) studies associated with the HCT are lacking. This paper demonstrates the use of a methodology inspired on Singular Spectrum Analysis (SSA) applied to EEG signals, to remove high amplitude ocular and movement artifacts during performance on the test. This filtering technique introduces no phase or latency distortions, with minimum loss of relevant EEG information. Importantly, the test was applied in its original clinical format, without introducing adaptations to ERP recordings. After signal treatment, the feedback-related negativity (FRN) wave, which is related to error-processing, was identified. This component peaked around 250ms, after feedback, in fronto-central electrodes. As expected, errors elicited more negative amplitudes than correct responses. Results are discussed in terms of the increased clinical potential that coupling ERP information with behavioral performance data can bring to the specificity of the HCT in diagnosing different types of impairment in frontal brain function.

Investigating the Effects of Peripheral Electrical Stimulation on Corticomuscular Functional Connectivity Stroke Survivors.

BACKGROUND: Electrical stimulation (ES) in the periphery can induce brain plasticity and has been used clinically to promote motor recovery in patients with central nervous system lesion. Electroencephalogram (EEG) and electromyogram (EMG) are readily applicable in clinical settings and can detect real-time functional connectivity between motor cortex and muscles with EEG-EMG (corticomuscular) coherence. OBJECTIVE: The purpose of this study was to determine whether EEG-EMG coherence can detect changes in corticomuscular control induced by peripheral ES. METHODS: Fifteen healthy young adults and 15 stroke survivors received 40-min electrical stimulation session on median nerve. The stimulation (1-ms rectangular pulse, 100 Hz) was delivered with a 20-s on-20-s off cycle, and the intensity was set at the subjects' highest tolerable level without muscle contraction or pain. Both before and after the stimulation session, subjects performed a 20-s steady-hold thumb flexion at 50% maximal voluntary contraction (MVC) while EEG and EMG were collected. RESULTS: Our results demonstrated that after ES, EEG-EMG coherence in gamma band increased significantly for 22.1 and 48.6% in healthy adults and stroke survivors, respectively. In addition, after ES, force steadiness was also improved in both groups, as indicated by the decrease in force fluctuation during steady-hold contraction (-1.7% MVC and -3.9%MVC for healthy and stroke individuals, respectively). CONCLUSIONS: Our results demonstrated that EEG-EMG coherence can detect ES-induced changes in the neuromuscular system. Also, because gamma coherence is linked to afferent inputs encoding, improvement in motor performance is likely related to ES-elicited strong sensory input and enhanced sensorimotor integration.

Early evaluation of the therapeutic effectiveness in children with epilepsy by quantitative EEG: a model of Mozart K.448 listening--a preliminary study.

PURPOSE: There are many treatments being developed for patients with epilepsy, including anti-epileptic drugs, ketogenic diet and vagus nerve stimulation. To date, there is a lack of valid methods to predict at an early stage the therapeutic effects on patients with epilepsy who receive one of these treatments. Our previous studies revealed that epileptiform discharges which were observed in patients with epilepsy were significantly decreased while listening to Mozart K.448. In this study, we attempted to develop a useful marker by utilizing a quantitative electroencephalogram (qEEG) method in analyzing the features of EEG to early evaluate the effect of the music on children with epilepsy, even without epileptiform discharges. METHODS: EEG segments from 19 Taiwanese children who were selected from a large screen study of music effect (eight boys and 11 girls) diagnosed with epilepsy were analyzed. EEG examinations were performed in two parallel periods in each patient; before, and while listening to Mozart K.448's first movement (8 min 22s) and EEG data were compared by qEEG. EEG segments were classified into music effective/ineffective group. The term "effective" was defined as patient exposure to music resulting in over a 25% reduction in epileptiform discharges. On the contrary, the term "ineffective" was defined as patient exposure to music resulting in less than a 5% reduction in epileptiform discharges. RESULTS: There were four global feature descriptors selected for the music effective/ineffective classification. Two descriptors, DecorrTime_avg_AVG and DecorrTime_std_AVG, were related to the EEG feature "decorrelation" whereas the other two descriptors, RelPowGamma_avg_SNR and RelPowGamma_std_SNR, were related to "relative power of gamma." There were significantly higher RelPowGamma_std_SNR (0.190±0.133 vs. -0.026±0.119, p=0.0029), DecorrTime_std_AVG (0.005±0.004 vs. 0.0003±0.0016, p=0.0055), DecorrTime_avg_AVG (0.005±0.005 vs. -0.002±0.008, p=0.0179), and RelPowGamma_avg_SNR (0.176±0.219 vs. -0.078±0.244, p=0.0222) in the effective group than in the ineffective group. The precision rate of classification was 0.953. CONCLUSIONS: Using qEEG, we have developed a useful model for predicting therapeutic effectiveness of music in patients with epilepsy. Among the limited number of patients, the tool is of potential to predict the effectiveness in patients even without epileptiform discharges. It is worthwhile in the application of other therapeutic model.

Performance measurement for brain-computer or brain-machine interfaces: a tutorial.

OBJECTIVE: Brain-computer interfaces (BCIs) have the potential to be valuable clinical tools. However, the varied nature of BCIs, combined with the large number of laboratories participating in BCI research, makes uniform performance reporting difficult. To address this situation, we present a tutorial on performance measurement in BCI research. APPROACH: A workshop on this topic was held at the 2013 International BCI Meeting at Asilomar Conference Center in Pacific Grove, California. This paper contains the consensus opinion of the workshop members, refined through discussion in the following months and the input of authors who were unable to attend the workshop. MAIN RESULTS: Checklists for methods reporting were developed for both discrete and continuous BCIs. Relevant metrics are reviewed for different types of BCI research, with notes on their use to encourage uniform application between laboratories. SIGNIFICANCE: Graduate students and other researchers new to BCI research may find this tutorial a helpful introduction to performance measurement in the field.

Monotic versus dichotic multiple-stimulus auditory steady state responses in young children.

In their recent study on infant multiple auditory steady state responses (ASSR), the authors found that ASSR amplitudes unexpectedly decreased when switching from 1-ear stimulation to 2-ear stimulation, a result not present in adults. In addition, residual EEG noise levels increased in the 2-ear condition. In the present study, to determine whether to use 1-ear or 2-ear multiple ASSR Protocols clinically, the authors tested a new group of 19 young children to determine whether these unexpected findings could be replicated. ASSR amplitude and EEG noise were compared for 1-ear (4 stimuli) versus 2-ear (8 stimuli) multiple stimuli presented at 60 dBHL. Results indicated a small but significant decrease in amplitudes going from 1-ear (40.1 nV) to 2-ear (37.9 nV) multiple stimuli. EEG noise was not significantly different between the 2 conditions. Despite small amplitude decreases, the 2-ear stimulus condition was more efficient for infants and young children with normal hearing.

Methods to eliminate stimulus transduction artifact from insert earphones during electroencephalography.

OBJECTIVE: To reduce stimulus transduction artifacts in EEG while using insert earphones. DESIGN: Reference Equivalent Threshold SPLs were assessed for Etymotic ER-4B earphones in 15 volunteers. Auditory brainstem responses (ABRs) and middle latency responses (MLRs)-as well as long-duration complex ABRs-to click and /dα/ speech stimuli were recorded in a single-case design. RESULTS: Transduction artifacts occurred in raw EEG responses, but they were eliminated by shielding, counter-phasing (averaging across stimuli 180° out of phase), or rereferencing. CONCLUSIONS: Clinical grade ABRs, MLRs, and cABRs can be recorded with a standard digital EEG system and high-fidelity insert earphones, provided one or more techniques are used to remove the stimulus transduction artifact.

Electrophysiological measurement of binaural beats: effects of primary tone frequency and observer age.

OBJECTIVE: The purpose of this study was to determine the reliability of the electrophysiological binaural beat steady state response as a gauge of temporal fine structure coding, particularly as it relates to the aging auditory system. The hypothesis was that the response would be more robust in a lower, than in a higher, frequency region and in younger, than in older, adults. DESIGN: Two experiments were undertaken. The first measured the 40 Hz binaural beat steady state response elicited by tone pairs in two frequency regions: lower (390 and 430 Hz tone pair) and higher (810 and 850 Hz tone pair). Frequency following responses (FFRs) evoked by the tones were also recorded. Ten young adults with normal hearing participated. The second experiment measured the binaural beat and FFRs in older adults but only in the lower frequency region. Fourteen older adults with relatively normal hearing participated. Response metrics in both experiments included response component signal-to-noise ratio (F statistic) and magnitude-squared coherence. RESULTS: Experiment 1 showed that FFRs were elicited in both frequency regions but were more robust in the lower frequency region. Binaural beat responses elicited by the lower frequency pair of tones showed greater amplitude fluctuation within a participant than the respective FFRs. Experiment 2 showed that older adults exhibited similar FFRs to younger adults, but proportionally fewer older participants showed binaural beat responses. Age differences in onset responses were also observed. CONCLUSIONS: The lower prevalence of the binaural beat response in older adults, despite the presence of FFRs, provides tentative support for the sensitivity of this measure to age-related deficits in temporal processing. However, the lability of the binaural beat response advocates caution in its use as an objective measure of fine structure coding.

Using the auditory steady state response to record response amplitude curves. A possible fast objective method for diagnosing dead regions.

OBJECTIVES: To assess a novel objective method of measuring response amplitude curves (RACs) using auditory steady state responses in adults. DESIGN: RACs were recorded in 20 normal-hearing adults. The RACs were measured by recording the changes in the amplitude of the auditory steady state response in the presence of (1) swept frequency narrowband masking noise and (2) fixed narrowband masking noise. RESULTS: The mean recorded RAC tip frequency for a 2-kHz signal was 2250 Hz for the swept masker method and 2239 Hz for the fixed masker method. The estimated repeatability coefficients, calculated using an assumed mean difference of zero, were 389 Hz for the swept method and 342 Hz for the fixed method. CONCLUSIONS: These initial results indicate that the swept- and fixed-masking methods appear to be viable and fast ways to record RACs in normal-hearing adults. Further work is needed to further optimize the accuracy of the tip frequency estimation and to establish the normative range of tip frequencies over a wide range of test frequencies in normal-hearing and hearing-impaired subjects.

Intractable epilepsy: management and therapeutic alternatives.

More than half of patients with newly diagnosed epilepsy achieve complete seizure control without major side-effects. Patients who continue to have seizures after initial medical therapy should have an early and detailed assessment to confirm the diagnosis, to determine the underlying cause and epilepsy syndrome, and to choose an adequate treatment strategy. The risks and potential benefits of surgical procedures or experimental therapy have to be weighed against the chance of improvement and the potential side-effects of additional medical therapy. Surgery for temporal lobe epilepsy, the most common cause of focal epilepsy, can control seizures and improve quality of life in appropriately selected patients. However, around 20-30% of patients do not respond to medical or surgical treatment. The management of chronic intractable epilepsy requires comprehensive care to address the adverse events of medical treatment, quality of life issues, and comorbid disorders. Much research focuses on the experimental treatment options that offer hope of seizure reduction or cure.

Recent developments in the diagnosis and treatment of status epilepticus.

Despite increased understanding of its potential complications, status epilepticus (SE) frequently remains difficult to diagnose and treat. Advances in continuous electroencephalogram (EEG) monitoring facilitate more rapid identification of SE, even without visible clinical signs of seizures. EEG monitoring assists in modifying SE treatment and in making a prognosis. Despite the improved recognition of SE, some patients continue to seize after treatment with intravenous benzodiazepines and other medications. There are new uses for valproic acid, levetiracetam, and topiramate, and they have evidence of efficacy in treating different forms of SE. If medical treatments do not terminate SE, other interventions, such as surgery and stimulation procedures, may promote seizure cessation. This article reviews recent studies evaluating the use of continuous EEG monitoring in the setting of SE, new uses of anticonvulsants, and nonpharmacologic interventions for SE.

Sensitivity of EEG and MEG to the N1 and P2 auditory evoked responses modulated by spectral complexity of sounds.

Acoustic complexity of a stimulus has been shown to modulate the electromagnetic N1 (latency approximately 110 ms) and P2 (latency 190 ms) auditory evoked responses. We compared the relative sensitivity of electroencephalography (EEG) and magnetoencephalography (MEG) to these neural correlates of sensation. Simultaneous EEG and MEG were recorded while participants listened to three variants of a piano tone. The piano stimuli differed in their number of harmonics: the fundamental frequency (f ( 0 )), only, or f ( 0 ) and the first two or eight harmonics. The root mean square (RMS) of the amplitude of P2 but not N1 increased with spectral complexity of the piano tones in EEG and MEG. The RMS increase for P2 was more prominent in EEG than MEG, suggesting important radial sources contributing to the P2 only in EEG. Source analysis revealing contributions from radial and tangential sources was conducted to test this hypothesis. Source waveforms revealed a significant increase in the P2 radial source amplitude in EEG with increased spectral complexity of piano tones. The P2 of the tangential source waveforms also increased in amplitude with increased spectral complexity in EEG and MEG. The P2 auditory evoked response is thus represented by both tangential (gyri) and radial (sulci) activities. The radial contribution is expressed preferentially in EEG, highlighting the importance of combining EEG with MEG where complex source configurations are suspected.

[Changes in cortical interhemispheric coherence produced by functional electrical stimulation (FES)]. / Alterações na coerência cortical inter-hemisférica produzidas pela estimulação elétrica funcional (FES).

The aim of the present study was to observe cortical alterations produced by functional electrical stimulation (FES), through quantitative electroencephalography (qEEG). Electrostimulation was performed on the right forearm to stimulate the extension of the index finger. EEG activity was recorded simultaneously. The sample consisted of 45 subjects randomly divided into 3 groups of 15 subjects each. The control group was submitted to 24 blocks of stimulation at a current intensity of zero. Group 1 was submitted to 24 blocks and group 2 to 36 blocks. Interhemispheric coherence between F3-F4, C3-C4 and P3-P4 was assessed through a statistical analysis. Results pointed out to increased coherence values after stimulation.