EEG/ECoG/EMG publications

Rapid detection and diagnosis of a traumatic brain injury (TBI) can significantly improve the prognosis for recovery. Helmet-mounted sensors that detect impact severity based on measurements of acceleration or pressure show promise for aiding triage and transport decisions in active, field environments such as professional sports or military combat. The detected signals, however, report on the mechanics of an impact rather than directly indicating the presence and severity of an injury. We explored the use of cortical somatosensory evoked electroencephalographic potentials (SSEPs) to detect and track, in real-time, neural electrophysiological abnormalities within the first hour following head injury in an animal model. To study the immediate electrophysiological effects of injury in vivo, we developed an experimental paradigm involving focused ultrasound that permits continuous, real-time measurements and minimizes mechanical artifact. Injury was associated with a dramatic reduction of amplitude over the damaged hemisphere directly after the injury. The amplitude systematically improved over time but remained significantly decreased at one hour, compared with baseline. In contrast, at one hour there was a concomitant enhancement of the cortical SSEP amplitude evoked from the uninjured hemisphere. Analysis of the inter-trial electroencephalogram (EEG) also revealed significant changes in low-frequency components and an increase in EEG entropy up to 30 minutes after injury, likely reflecting altered EEG reactivity to somatosensory stimuli. Injury-induced alterations in SSEPs were also observed using noninvasive epidermal electrodes, demonstrating viability of practical implementation. These results suggest cortical SSEPs recorded at just a few locations by head-mounted sensors and associated multiparametric analyses could potentially be used to rapidly detect and monitor brain injury in settings that normally present significant levels of mechanical and electrical noise.

Objective . Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram. Approach . Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient. Main results . The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30–150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies. Significance. Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.

Objective. The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. In this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. Approach. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n -gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. Main results. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. Significance. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

Nervous systems distinguish between self- and other-generated movements by monitoring discrepancies between planned and performed actions. To do so, corollary discharges are conveyed to sensory areas and gate expected reafference. Such gating is observed in neonatal rats during wake-related movements. In contrast, twitches, which are self-generated movements produced during active (or REM) sleep, differ from wake movements in that they reliably trigger robust neural activity. Accordingly, we hypothesized that the gating actions of corollary discharge are absent during twitching. Here, we identify the external cuneate nucleus (ECN), which processes sensory input from the forelimbs, as a site of movement-dependent sensory gating during wake. Whereas pharmacological disinhibition of the ECN unmasked wake-related reafference, twitch-related reafference was unaffected. This is the first demonstration of a neural comparator that is differentially engaged depending on the kind of movement produced. This mechanism explains how twitches, although self-generated, trigger abundant reafferent activation of sensorimotor circuits in the developing brain.

Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals. We also find direction-distinguishing information up to 400ms before force onset in the pre-movement signals, captured by electrodes placed over the limb-ipsilateral dorsal premotor regions. This approach can contribute to more accurate decoding of higher-level movement goals, at earlier timescales, and inform sensor placement. Our results also contribute to further understanding of the spatiotemporal features of human motor planning.

High-density electrocorticography (ECoG) arrays are promising interfaces for high-resolution neural recording from the cortical surface. Commercial options for high-density arrays are limited, and historically tradeoffs must be made between spatial coverage and electrode density. However, thin-film technology is a promising alternative for generating electrode arrays capable of large area coverage and high channel count, with resolution on the order of cortical columns in the functional surface unit of a human gyrus. Here, we evaluate the sensing performance of a high-density thin-film 128-electrode array designed specifically for recording the distributed neural activity of a single human cortical gyrus. We found robust field potential responses throughout the superior temporal gyrus evoked by speech sounds, and clear phonetic feature selectivity at the resolution of 2 mm inter-electrode distance. Decoding accuracy improved with increasing density of electrodes over all three patients tested. Thin-film ECoG has significant potential for high-density neural interface applications at the scale of a human gyrus.

Cardiac arrest (CA) is one of the most prominent causes of morbidity and mortality in adults. Therapeutic hypothermia (TH) is a recommended treatment to improve survival and functional outcome following CA, however, it is unclear what degree of TH is most beneficial. It has been suggested that TH of 33°C provides no survival or outcome benefits over TH of 36°C. Additionally, there is a lack of verified objective quantitative prognostic tools for comatose CA patients under TH. In this study, we calculated three quantitative markers of somatosensory evoked potentials (SSEP) to examine their potential to track recovery in the early period following CA under graded TH. A total of 16 rats were randomly divided among 4 temperature groups (n=4/group): normothermia (N0, 36.5-37.5°C), hypothermia 1 (H1, 30-32°C), hypothermia 2 (H2, 32-34°C) and hypothermia 3 (H3, 34-36°C). All rats underwent a 15min baseline SSEP recording followed by 9min asphyxial-CA, resulting in severe cerebral injury, and immediate temperature management following resuscitation for 6 hours. SSEP recordings were maintained in 15 min intervals from 30min-4hrs after resuscitation. The N10 amplitude, N10 latency and quantitative SSEP phase space area (qSSEP-PSA) were calculated for the early recovery period and normalized to their respective baselines. Functional recovery was determined by the neurological deficit scale (NDS). N10 amplitude was significantly larger in H1, H2 and H3 compared to N0. N10 latency was significantly longer in H1 than all temperature groups and all hypothermia groups had significantly longer latencies than N0. qSSEP-PSA had significantly better recovery in H1 and H2 than N0. Animals with good outcome (72hr NDS>50) had better recovery of all markers. N10 amplitude was significantly correlated with N10 latency and qSSEP-PSA. The results importantly demonstrate that quantified SSEPs have the potential to objectively track recovery following CA with graded TH.

The ventral premotor cortex (PMv) is a key node in the neural network involved in grasping. One way PMv can carry out this function is by modulating the outputs of the primary motor cortex (M1) to intrinsic hand and forearm muscles. As many PMv neurons discharge when grasping with either arm, both PMv within the same hemisphere (ipsilateral; iPMv) and in the opposite hemisphere (contralateral; cPMv) could modulate M1 outputs. Our objective was to compare modulatory effects of iPMv and cPMv on M1 outputs to intrinsic hand and forearm muscles. We used paired-pulse protocols with intracortical microstimulations in capuchin monkeys. A conditioning stimulus was applied in either iPMv or cPMv simultaneously or prior to a test stimulus in M1 and the effects quantified in electromyographic signals. Modulatory effects from iPMv were predominantly facilitatory, and facilitation was much more common and powerful on intrinsic hand than forearm muscles. In contrast, while the conditioning of cPMv could elicit facilitatory effects, in particular to intrinsic hand muscles, it was much more likely to inhibit M1 outputs. These data show that iPMv and cPMv have very different modulatory effects on the outputs of M1 to intrinsic hand and forearm muscles.

Target speaker identification is essential for speech enhancement algorithms in assistive devices aimed toward helping the hearing impaired. Several recent studies have reported that target speaker identification is possible through electroencephalography (EEG) recordings. If the EEG system could be reduced to acceptable size while retaining the signal quality, hearing aids could benefit from the integration with concealed EEG. To compare the performance of a multichannel around-the-ear EEG system with high-density cap EEG recordings an envelope tracking algorithm was applied in a competitive speaker paradigm. The data from 20 normal hearing listeners were concurrently collected from the traditional state-of-the-art laboratory wired EEG system and a wireless mobile EEG system with two bilaterally-placed around-the-ear electrode arrays (cEEGrids). The results show that the cEEGrid ear-EEG technology captured neural signals that allowed the identification of the attended speaker above chance-level, with 69.3% accuracy, while cap-EEG signals resulted in the accuracy of 84.8%. Further analyses investigated the influence of ear-EEG signal quality and revealed that the envelope tracking procedure was unaffected by variability in channel impedances. We conclude that the quality of concealed ear-EEG recordings as acquired with the cEEGrid array has potential to be used in the brain-computer interface steering of hearing aids.

Unlabelled: Accurate sensory discrimination is commonly believed to require precise representations in the nervous system; however, neural stimulus responses can be highly variable, even to identical stimuli. Recent studies suggest that cortical response variability decreases during stimulus processing, but the implications of such effects on stimulus discrimination are unclear. To address this, we examined electrocorticographic cortical field potential recordings from the human nonprimary auditory cortex (superior temporal gyrus) while subjects listened to speech syllables. Compared with a prestimulus baseline, activation variability decreased upon stimulus onset, similar to findings from microelectrode recordings in animal studies. We found that this decrease was simultaneous with encoding and spatially specific for those electrodes that most strongly discriminated speech sounds. We also found that variability was predominantly reduced in a correlated subspace across electrodes. We then compared signal and variability (noise) correlations and found that noise correlations reduce more for electrodes with strong signal correlations. Furthermore, we found that this decrease in variability is strongest in the high gamma band, which correlates with firing rate response. Together, these findings indicate that the structure of single-trial response variability is shaped to enhance discriminability despite non-stimulus-related noise. Significance statement: Cortical responses can be highly variable to auditory speech sounds. Despite this, sensory perception can be remarkably stable. Here, we recorded from the human superior temporal gyrus, a high-order auditory cortex, and studied the changes in the cortical representation of speech stimuli across multiple repetitions. We found that neural variability is reduced upon stimulus onset across electrodes that encode speech sounds.

The analysis of cross-frequency coupling (CFC) has become popular in studies involving intracranial and scalp EEG recordings in humans. It has been argued that some cases where CFC is mathematically present may not reflect an interaction of two distinct yet functionally coupled neural sources with different frequencies. Here we provide two empirical examples from intracranial recordings where CFC can be shown to be driven by the shape of a periodic waveform rather than by a functional interaction between distinct sources. Using simulations, we also present a generalized and realistic scenario where such coupling may arise. This scenario, which we term waveform-dependent CFC, arises when sharp waveforms (e.g., cortical potentials) occur in a periodic manner throughout parts of the data. Since the waveforms are repeated periodically, they constitute a slow wave that is inherently phase-aligned with the high-frequency component carried by the same waveforms. We submit that such behavior of the data, which seems to be present in various cortical signals, cannot be interpreted as reflecting functional modulation between distinct neural sources without additional evidence. In addition, we show that even low amplitude periodic potentials that cannot be readily observed or controlled for, are sufficient for significant CFC to occur.

Language tasks require the coordinated activation of multiple subnetworks-groups of related cortical interactions involved in specific components of task processing. Although electrocorticography (ECoG) has sufficient temporal and spatial resolution to capture the dynamics of event-related interactions between cortical sites, it is difficult to decompose these complex spatiotemporal patterns into functionally discrete subnetworks without explicit knowledge of each subnetwork's timing. We hypothesized that subnetworks corresponding to distinct components of task-related processing could be identified as groups of interactions with co-varying strengths. In this study, five subjects implanted with ECoG grids over language areas performed word repetition and picture naming. We estimated the interaction strength between each pair of electrodes during each task using a time-varying dynamic Bayesian network (tvDBN) model constructed from the power of high gamma (70-110Hz) activity, a surrogate for population firing rates. We then reduced the dimensionality of this model using principal component analysis (PCA) to identify groups of interactions with co-varying strengths, which we term functional network components (FNCs). This data-driven technique estimates both the weight of each interaction's contribution to a particular subnetwork, and the temporal profile of each subnetwork's activation during the task. We found FNCs with temporal and anatomical features consistent with articulatory preparation in both tasks, and with auditory and visual processing in the word repetition and picture naming tasks, respectively. These FNCs were highly consistent between subjects with similar electrode placement, and were robust enough to be characterized in single trials. Furthermore, the interaction patterns uncovered by FNC analysis correlated well with recent literature suggesting important functional-anatomical distinctions between processing external and self-produced speech. Our results demonstrate that subnetwork decomposition of event-related cortical interactions is a powerful paradigm for interpreting the rich dynamics of large-scale, distributed cortical networks during human cognitive tasks.

Spinal cord injury usually occurs at the level of the cervical spine and results in profound impairment of forelimb function. In this study, we recorded awake behaving intramuscular electromyography (EMG) from the biceps and triceps muscles of the impaired forelimb during volitional and reflexive forelimb movements before and after unilateral cervical spinal cord injury (cSCI) in rats. C5/C6 hemicontusion reduced volitional forelimb strength by more than 50% despite weekly rehabilitation for one month post-injury. Triceps EMG during volitional strength assessment was reduced by more than 60% following injury, indicating reduced descending drive. Biceps EMG during reflexive withdrawal from a thermal stimulus was increased by 500% following injury, indicating flexor withdrawal hyperreflexia. The reduction in volitional forelimb strength was significantly correlated with volitional and reflexive biceps EMG activity. Our results support the hypothesis that biceps hyperreflexia and descending volitional drive both significantly contribute to forelimb strength deficits after cSCI and provide new insight into dynamic muscular dysfunction after cSCI. The use of multiple automated quantitative measures of forelimb dysfunction in the rodent cSCI model will likely aid the search for effective regenerative, pharmacological, and neuroprosthetic treatments for spinal cord injury.

Many postnatal onset neurological disorders such as autism spectrum disorders (ASDs) and intellectual disability are thought to arise largely from disruption of excitatory/inhibitory homeostasis. Although mouse models of Rett syndrome (RTT), a postnatal neurological disorder caused by loss-of-function mutations in MECP2, display impaired excitatory neurotransmission, the RTT phenotype can be largely reproduced in mice simply by removing MeCP2 from inhibitory GABAergic neurons. To determine what role excitatory signaling impairment might play in RTT pathogenesis, we generated conditional mouse models with Mecp2 either removed from or expressed solely in glutamatergic neurons. MeCP2 deficiency in glutamatergic neurons leads to early lethality, obesity, tremor, altered anxiety-like behaviors, and impaired acoustic startle response, which is distinct from the phenotype of mice lacking MeCP2 only in inhibitory neurons. These findings reveal a role for excitatory signaling impairment in specific neurobehavioral abnormalities shared by RTT and other postnatal neurological disorders.

Objectives/Hypothesis Permanent facial nerve injury is a difficult challenge for both patients and physicians given its potential for debilitating functional, cosmetic, and psychological sequelae. Although current surgical interventions have provided considerable advancements in facial nerve rehabilitation, they often fail to fully address all impairments. We aim to introduce an alternative approach to facial nerve rehabilitation. Study Design Acute experiments in animals with normal facial function. Methods The study included three anesthetized cats. Four facial muscles ( levator auris longus, orbicularis oculi, nasalis, and orbicularis oris ) were monitored with a standard electromyographic (EMG) facial nerve monitoring system with needle electrodes. The main trunk of the facial nerve was exposed, and a 16‐channel penetrating electrode array was placed into the nerve. Electrical current pulses were delivered to each stimulating electrode individually. Elicited EMG voltage outputs were recorded for each muscle. Results Stimulation through individual channels selectively activated restricted nerve populations, resulting in selective contraction of individual muscles. Increasing stimulation current levels resulted in increasing EMG voltage responses. Typically, selective activation of two or more distinct muscles was successfully achieved via a single placement of the multi‐channel electrode array by selection of appropriate stimulation channels. Conclusion We have established in the animal model the ability of a penetrating electrode array to selectively stimulate restricted fiber populations within the facial nerve and to selectively elicit contractions in specific muscles and regions of the face. These results show promise for the development of a facial nerve implant system. Level of Evidence N/A. Laryngoscope , 2016 127:460–465, 2017

Implantable biomedical microdevices enable the restoration of body function and improvement of health condition. As the interface between artificial machines and natural tissue, various kinds of microelectrodes with high density and tiny size were developed to undertake precise and complex medical tasks through electrical stimulation and electrophysiological recording. However, if only the electrical interaction existed between electrodes and muscle or nerve tissue without nutrition factor delivery, it would eventually lead to a significant symptom of denervation-induced skeletal muscle atrophy. In this paper, we developed a novel flexible tubular microelectrode integrated with fluidic drug delivery channel for dynamic tissue implant. First, the whole microelectrode was made of biocompatible polymers, which could avoid the drawbacks of the stiff microelectrodes that are easy to be broken and damage tissue. Moreover, the microelectrode sites were circumferentially distributed on the surface of polymer microtube in three dimensions, which would be beneficial to the spatial selectivity. Finally, the in vivo results confirmed that our implantable tubular microelectrodes were suitable for dynamic electrophysiological recording and simultaneous fluidic drug delivery, and the electrode performance was further enhanced by the conducting polymer modification.

Current models of cortical speech and language processing include multiple regions within the temporal lobe of both hemispheres. Human communication, by necessity, involves complex interactions between regions subserving speech and language processing with those involved in more general cognitive functions. To assess these interactions, we utilized an ecologically salient conversation-based approach. This approach mandates that we first clarify activity patterns at the earliest stages of cortical speech processing. Therefore, we examined high gamma (70-150 Hz) responses within the electrocorticogram (ECoG) recorded simultaneously from Heschl's gyrus (HG) and lateral surface of the superior temporal gyrus (STG). Subjects were neurosurgical patients undergoing evaluation for treatment of medically intractable epilepsy. They performed an expanded version of the Mini-mental state examination (MMSE), which included additional spelling, naming, and memory-based tasks. ECoG was recorded from HG and the STG using multicontact depth and subdural electrode arrays, respectively. Differences in high gamma activity during listening to the interviewer and the subject's self-generated verbal responses were quantified for each recording site and across sites within HG and STG. The expanded MMSE produced widespread activation in auditory cortex of both hemispheres. No significant difference was found between activity during listening to the interviewer's questions and the subject's answers in posteromedial HG (auditory core cortex). A different pattern was observed throughout anterolateral HG and posterior and middle portions of lateral STG (non-core auditory cortical areas), where activity was significantly greater during listening compared to speaking. No systematic task-specific differences in the degree of suppression during speaking relative to listening were found in posterior and middle STG. Individual sites could, however, exhibit task-related variability in the degree of suppression during speaking compared to listening. The current study demonstrates that ECoG recordings can be acquired in time-efficient dialog-based paradigms, permitting examination of language and cognition in an ecologically salient manner. The results obtained from auditory cortex serve as a foundation for future studies addressing patterns of activity beyond auditory cortex that subserve human communication.

Unlabelled: Sensory processing deficits are common in autism spectrum disorders, but the underlying mechanisms are unclear. Fragile X Syndrome (FXS) is a leading genetic cause of intellectual disability and autism. Electrophysiological responses in humans with FXS show reduced habituation with sound repetition and this deficit may underlie auditory hypersensitivity in FXS. Our previous study in Fmr1 knockout (KO) mice revealed an unusually long state of increased sound-driven excitability in auditory cortical neurons suggesting that cortical responses to repeated sounds may exhibit abnormal habituation as in humans with FXS. Here, we tested this prediction by comparing cortical event related potentials (ERP) recorded from wildtype (WT) and Fmr1 KO mice. We report a repetition-rate dependent reduction in habituation of N1 amplitude in Fmr1 KO mice and show that matrix metalloproteinase-9 (MMP-9), one of the known FMRP targets, contributes to the reduced ERP habituation. Our studies demonstrate a significant up-regulation of MMP-9 levels in the auditory cortex of adult Fmr1 KO mice, whereas a genetic deletion of Mmp-9 reverses ERP habituation deficits in Fmr1 KO mice. Although the N1 amplitude of Mmp-9/Fmr1 DKO recordings was larger than WT and KO recordings, the habituation of ERPs in Mmp-9/Fmr1 DKO mice is similar to WT mice implicating MMP-9 as a potential target for reversing sensory processing deficits in FXS. Together these data establish ERP habituation as a translation relevant, physiological pre-clinical marker of auditory processing deficits in FXS and suggest that abnormal MMP-9 regulation is a mechanism underlying auditory hypersensitivity in FXS. Significance: Fragile X Syndrome (FXS) is the leading known genetic cause of autism spectrum disorders. Individuals with FXS show symptoms of auditory hypersensitivity. These symptoms may arise due to sustained neural responses to repeated sounds, but the underlying mechanisms remain unclear. For the first time, this study shows deficits in habituation of neural responses to repeated sounds in the Fmr1 KO mice as seen in humans with FXS. We also report an abnormally high level of matrix metalloprotease-9 (MMP-9) in the auditory cortex of Fmr1 KO mice and that deletion of Mmp-9 from Fmr1 KO mice reverses habituation deficits. These data provide a translation relevant electrophysiological biomarker for sensory deficits in FXS and implicate MMP-9 as a target for drug discovery.

The auditory cortex is well-known to be critical for music perception, including the perception of consonance and dissonance. Studies on the neural correlates of consonance and dissonance perception have largely employed non-invasive electrophysiological and functional imaging techniques in humans as well as neurophysiological recordings in animals, but the fine-grained spatiotemporal dynamics within the human auditory cortex remain unknown. We recorded electrocorticographic (ECoG) signals directly from the lateral surface of either the left or right temporal lobe of eight patients undergoing neurosurgical treatment as they passively listened to highly consonant and highly dissonant musical chords. We assessed ECoG activity in the high gamma (γhigh, 70-150 Hz) frequency range within the superior temporal gyrus (STG) and observed two types of cortical sites of interest in both hemispheres: one type showed no significant difference in γhigh activity between consonant and dissonant chords, and another type showed increased γhigh responses to dissonant chords between 75 and 200 ms post-stimulus onset. Furthermore, a subset of these sites exhibited additional sensitivity towards different types of dissonant chords, and a positive correlation between changes in γhigh power and the degree of stimulus roughness was observed in both hemispheres. We also observed a distinct spatial organization of cortical sites in the right STG, with dissonant-sensitive sites located anterior to non-sensitive sites. In sum, these findings demonstrate differential processing of consonance and dissonance in bilateral STG with the right hemisphere exhibiting robust and spatially organized sensitivity toward dissonance.

Changes in the environment require rapid modification or inhibition of ongoing behavior. We used the stop-signal paradigm and intracranial recordings to investigate response preparation, inhibition, and monitoring of task-relevant information. Electrocorticographic data were recorded in eight patients with electrodes covering frontal, temporal, and parietal cortex, and time-frequency analysis was used to examine power differences in the beta (13–30 Hz) and high-gamma bands (60–180 Hz). Over motor cortex, beta power decreased, and high-gamma power increased during motor preparation for both go trials (Go) and unsuccessful stops (US). For successful stops (SS), beta increased, and high-gamma was reduced, indexing the cancellation of the prepared response. In the middle frontal gyrus (MFG), stop signals elicited a transient high-gamma increase. The MFG response occurred before the estimated stop-signal reaction time but did not distinguish between SS and US trials, likely signaling attention to the salient stop stimulus. A postresponse high-gamma increase in MFG was stronger for US compared with SS and absent in Go, supporting a role in behavior monitoring. These results provide evidence for differential contributions of frontal subregions to response inhibition, including motor preparation and inhibitory control in motor cortex and cognitive control and action evaluation in lateral prefrontal cortex.