Mapping of primary somatosensory cortex of the hand area using a high-density electrocorticography grid for closed-loop brain computer interface.

Objective.The ideal modality for generating sensation in sensorimotor brain computer interfaces (BCI) has not been determined. Here we report the feasibility of using a high-density 'mini'-electrocorticography (mECoG) grid in a somatosensory BCI system.Approach.Thirteen subjects with intractable epilepsy underwent standard clinical implantation of subdural electrodes for the purpose of seizure localization. An additional high-density mECoG grid was placed (Adtech, 8 by 8, 1.2 mm exposed, 3 mm center-to-center spacing) over the hand area of primary somatosensory cortex. Following implantation, cortical mapping was performed with stimulation parameters of frequency: 50 Hz, pulse-width: 250µs, pulse duration: 4 s, polarity: alternating, and current that ranged from 0.5 mA to 12 mA at the discretion of the epileptologist. Location of the evoked sensory percepts was recorded along with a description of the sensation. The hand was partitioned into 48 distinct boxes. A box was included if sensation was felt anywhere within the box.Main results.The percentage of the hand covered was 63.9% (± 34.4%) (mean ± s.d.). Mean redundancy, measured as electrode pairs stimulating the same box, was 1.9 (± 2.2) electrodes per box; and mean resolution, measured as boxes included per electrode pair stimulation, was 11.4 (± 13.7) boxes with 8.1 (± 10.7) boxes in the digits and 3.4 (± 6.0) boxes in the palm. Functional utility of the system was assessed by quantifying usable percepts. Under the strictest classification, 'dermatomally exclusive' percepts, the mean was 2.8 usable percepts per grid. Allowing 'perceptually unique' percepts at the same anatomical location, the mean was 5.5 usable percepts per grid.Significance.Compared to the small area of coverage and redundancy of a microelectrode system, or the poor resolution of a standard ECoG grid, a mECoG is likely the best modality for a somatosensory BCI system with good coverage of the hand and minimal redundancy.

Gamma-band modulation in the human amygdala during reaching movements.

OBJECTIVE: Motor brain-computer interface (BCI) represents a new frontier in neurological surgery that could provide significant benefits for patients living with motor deficits. Both the primary motor cortex and posterior parietal cortex have successfully been used as a neural source for human motor BCI, leading to interest in exploring other brain areas involved in motor control. The amygdala is one area that has been shown to have functional connectivity to the motor system; however, its role in movement execution is not well studied. Gamma oscillations (30-200 Hz) are known to be prokinetic in the human cortex, but their role is poorly understood in subcortical structures. Here, the authors use direct electrophysiological recordings and the classic "center-out" direct-reach experiment to study amygdaloid gamma-band modulation in 8 patients with medically refractory epilepsy. METHODS: The study population consisted of 8 epilepsy patients (2 men; age range 21-62 years) who underwent implantation of micro-macro depth electrodes for seizure localization and EEG monitoring. Data from the macro contacts sampled at 2000 Hz were used for analysis. The classic center-out direct-reach experiment was used, which consists of an intertrial interval phase, a fixation phase, and a response phase. The authors assessed the statistical significance of neural modulation by inspecting for nonoverlapping areas in the 95% confidence intervals of spectral power for the response and fixation phases. RESULTS: In 5 of the 8 patients, power spectral analysis showed a statistically significant increase in power within regions of the gamma band during the response phase compared with the fixation phase. In these 5 patients, the 95% bootstrapped confidence intervals of trial-averaged power in contiguous frequencies of the gamma band during the response phase were above, and did not overlap with, the confidence intervals of trial-averaged power during the fixation phase. CONCLUSIONS: To the authors' knowledge, this is the first time that direct neural recordings have been used to show gamma-band modulation in the human amygdala during the execution of voluntary movement. This work indicates that gamma-band modulation in the amygdala could be a contributing source of neural signals for use in a motor BCI system.

Beta-band power modulation in the human hippocampus during a reaching task.

OBJECTIVE: Characterize the role of the beta-band (13-30 Hz) in the human hippocampus during the execution of voluntary movement. APPROACH: We recorded electrophysiological activity in human hippocampus during a reach task using stereotactic electroencephalography (SEEG). SEEG has previously been utilized to study the theta band (3-8 Hz) in conflict processing and spatial navigation, but most studies of hippocampal activity during movement have used noninvasive measures such as fMRI. We analyzed modulation in the beta band (13-30 Hz), which is known to play a prominent role throughout the motor system including the cerebral cortex and basal ganglia. We conducted the classic 'center-out' direct-reach experiment with nine patients undergoing surgical treatment for medically refractory epilepsy. MAIN RESULTS: In seven of the nine patients, power spectral analysis showed a statistically significant decrease in power within the beta band (13-30 Hz) during the response phase, compared to the fixation phase, of the center-out direct-reach task using the Wilcoxon signed-rank hypothesis test (p < 0.05). SIGNIFICANCE: This finding is consistent with previous literature suggesting that the hippocampus may be involved in the execution of movement, and it is the first time that changes in beta-band power have been demonstrated in the hippocampus using human electrophysiology. Our findings suggest that beta-band modulation in the human hippocampus may play a role in the execution of voluntary movement.

A Phantom Study of the Spatial Precision and Accuracy of Stereotactic Localization Using Computed Tomography Imaging with the Leksell Stereotactic System.

BACKGROUND: Stereotactic localization of neurosurgical targets traditionally relies on computed tomography (CT), which is considered the optimal imaging modality for geometric accuracy. However, in-depth investigations that characterize the precision and accuracy of CT images are lacking. We used a CT phantom to examine interscanner precision and interprotocol accuracy in coordinate localization. METHODS: A polymethylacrylate phantom was scanned with Toshiba Aquilion 64 and GE Healthcare LightSpeed 16 CT scanners, using both helical and incremental single-slice (SS) image acquisition protocols. The X, Y, and Z coordinates of 94 points across 6 surfaces of the phantom were physically measured. The CT scan-derived coordinates were compared with the phantom coordinates and with each other to determine accuracy and precision, respectively. RESULTS: Using the SS imaging protocol, the mean (SD) interscanner disparity in localization was 0.93 (0.39) mm, given by the average Euclidean distance between the coordinates of the 2 scanners. This discrepancy significantly varied by axis and surface, with the greatest discrepancy in the Z-axis of 0.30 mm (95% confidence interval, 0.25-0.35; P = 0.05) and on the superior surface of 1.30 mm (95% confidence interval, 1.15-1.45; P = 0.05). SS acquisition was significantly more accurate than the helical protocol. CONCLUSIONS: We found evidence of clinically relevant inconsistency between 2 CT scanners used for stereotactic localization. SS image acquisition was superior to helical scanning with respect to localization accuracy. Interscanner consistency cannot be assumed. Institutions would benefit from identifying the errors inherent in their CT scanners.

Utility and lower limits of frequency detection in surface electrode stimulation for somatosensory brain-computer interface in humans.

OBJECTIVE: Stimulation of the primary somatosensory cortex (S1) has been successful in evoking artificial somatosensation in both humans and animals, but much is unknown about the optimal stimulation parameters needed to generate robust percepts of somatosensation. In this study, the authors investigated frequency as an adjustable stimulation parameter for artificial somatosensation in a closed-loop brain-computer interface (BCI) system. METHODS: Three epilepsy patients with subdural mini-electrocorticography grids over the hand area of S1 were asked to compare the percepts elicited with different stimulation frequencies. Amplitude, pulse width, and duration were held constant across all trials. In each trial, subjects experienced 2 stimuli and reported which they thought was given at a higher stimulation frequency. Two paradigms were used: first, 50 versus 100 Hz to establish the utility of comparing frequencies, and then 2, 5, 10, 20, 50, or 100 Hz were pseudorandomly compared. RESULTS: As the magnitude of the stimulation frequency was increased, subjects described percepts that were "more intense" or "faster." Cumulatively, the participants achieved 98.0% accuracy when comparing stimulation at 50 and 100 Hz. In the second paradigm, the corresponding overall accuracy was 73.3%. If both tested frequencies were less than or equal to 10 Hz, accuracy was 41.7% and increased to 79.4% when one frequency was greater than 10 Hz (p = 0.01). When both stimulation frequencies were 20 Hz or less, accuracy was 40.7% compared with 91.7% when one frequency was greater than 20 Hz (p < 0.001). Accuracy was 85% in trials in which 50 Hz was the higher stimulation frequency. Therefore, the lower limit of detection occurred at 20 Hz, and accuracy decreased significantly when lower frequencies were tested. In trials testing 10 Hz versus 20 Hz, accuracy was 16.7% compared with 85.7% in trials testing 20 Hz versus 50 Hz (p < 0.05). Accuracy was greater than chance at frequency differences greater than or equal to 30 Hz. CONCLUSIONS: Frequencies greater than 20 Hz may be used as an adjustable parameter to elicit distinguishable percepts. These findings may be useful in informing the settings and the degrees of freedom achievable in future BCI systems.

Comparison of Intraoperative 3-Dimensional Fluoroscopy With Standard Computed Tomography for Stereotactic Frame Registration.

BACKGROUND: Three-dimensional fluoroscopy via the O-arm (Medtronic, Dublin, Ireland) has been validated for intraoperative confirmation of successful lead placement in stereotactic electrode implantation. However, its role in registration and targeting has not yet been studied. After frame placement, many stereotactic neurosurgeons obtain a computed tomography (CT) scan and merge it with a preoperative magnetic resonance imaging (MRI) scan to generate planning coordinates; potential disadvantages of this practice include increased procedure time and limited scanner availability. OBJECTIVE: To evaluate whether the second-generation O-arm (O2) can be used in lieu of a traditional CT scan to obtain accurate frame-registration scans. METHODS: In 7 patients, a postframe placement CT scan was merged with preoperative MRI and used to generate lead implantation coordinates. After implantation, the fiducial box was again placed on the patient to obtain an O2 confirmation scan. Vector, scalar, and Euclidean differences between analogous X, Y, and Z coordinates from fused O2/MRI and CT/MRI scans were calculated for 33 electrode target coordinates across 7 patients. RESULTS: Marginal means of difference for vector (X = -0.079 ± 0.099 mm; Y = -0.076 ± 0.134 mm; Z = -0.267 ± 0.318 mm), scalar (X = -0.146 ± 0.160 mm; Y = -0.306 ± 0.106 mm; Z = 0.339 ± 0.407 mm), and Euclidean differences (0.886 ± 0.190 mm) remained within the predefined equivalence margin differences of -2 mm and 2 mm. CONCLUSION: This study demonstrates that O2 may emerge as a viable alternative to the traditional CT scanner for generating planning coordinates. Adopting the O2 as a perioperative tool may offer reduced transport risks, decreased anesthesia time, and greater surgical efficiency.

Clinical neuroprosthetics: Today and tomorrow.

Implantable neurostimulation devices provide a direct therapeutic link to the nervous system and can be considered brain-computer interfaces (BCI). Under this definition, BCI are not simply science fiction, they are part of existing neurosurgical practice. Clinical BCI are standard of care for historically difficult to treat neurological disorders. These systems target the central and peripheral nervous system and include Vagus Nerve Stimulation, Responsive Neurostimulation, and Deep Brain Stimulation. Recent advances in clinical BCI have focused on creating "closed-loop" systems. These systems rely on biomarker feedback and promise individualized therapy with optimal stimulation delivery and minimal side effects. Success of clinical BCI has paralleled research efforts to create BCI that restore upper extremity motor and sensory function to patients. Efforts to develop closed loop motor/sensory BCI is linked to the successes of today's clinical BCI.

Directional tuning during reach planning in the supramarginal gyrus using local field potentials.

Previous work in directional tuning for brain machine interfaces has primarily relied on algorithm sorted neuronal action potentials in primary motor cortex. However, local field potential has been utilized to show directional tuning in macaque studies, and inferior parietal cortex has shown increased neuronal activity in reaching tasks that relied on MRI imaging. In this study we utilized local field potential recordings from a human subject performing a delayed reach task and show that high frequency band (76-100 Hz) spectral power is directionally tuned to different reaching target locations during an active reach. We also show that during the delay phase of the task, directional tuning is present in areas of the inferior parietal cortex, in particular, the supramarginal gyrus.

Biases in processing of mood-congruent facial expressions in depression.

Cognitive models of depression suggest that depressed individuals exhibit a tendency to attribute negative meaning to neutral stimuli, and enhanced processing of mood-congruent stimuli. However, evidence thus far has been inconsistent. In this study, we sought to identify both differential interpretation of neutral information as well as emotion processing biases associated with depression. Fifty adult participants completed standardized mood-related questionnaires, a novel immediate mood scale questionnaire (IMS-12), and a novel task, Emotion Matcher, in which they were required to indicate whether pairs of emotional faces show the same expression or not. We found that overall success rate and reaction time on the Emotion Matcher task did not differ as a function of severity of depression. However, more depressed participants had significantly worse performance when presented with sad-neutral face pairs, as well as increased reaction times to happy-happy pairs. In addition, accuracy of the sad-neutral pairs was found to be significantly associated with depression severity in a regression model. Our study provides partial support for the mood-congruent hypothesis, revealing only a potential bias in interpretation of sad and neutral expressions, but not a general deficit in processing of facial expressions. The potential of such bias in serving as a predictor for depression should be further examined in future studies.

Brain-Computer Interfaces in Quadriplegic Patients.

Brain-computer interfaces (BCI) are implantable devices that interface directly with the nervous system. BCI for quadriplegic patients restore function by reading motor intent from the brain and use the signal to control physical, virtual, and native prosthetic effectors. Future closed-loop motor BCI will incorporate sensory feedback to provide patients with an effective and intuitive experience. Development of widely available BCI for patients with neurologic injury will depend on the successes of today's clinical BCI. BCI are an exciting next step in the frontier of neuromodulation.

Dual responsive neurostimulation implants for epilepsy.

Closed-loop brain-responsive neurostimulation via the RNS System is a treatment option for adults with medically refractory focal epilepsy. Using a novel technique, 2 RNS Systems (2 neurostimulators and 4 leads) were successfully implanted in a single patient with bilateral parietal epileptogenic zones. In patients with multiple epileptogenic zones, this technique allows for additional treatment options. Implantation can be done successfully, without telemetry interference, using proper surgical planning and neurostimulator positioning.Trajectories for the depth leads were planned using neuronavigation with CT and MR imaging. Stereotactic frames were used for coordinate targeting. Each neurostimulator was positioned with maximal spacing to avoid telemetry interference while minimizing patient discomfort. A separate J-shaped incision was used for each neurostimulator to allow for compartmentalization in case of infection. In order to minimize surgical time and risk of infection, the neurostimulators were implanted in 2 separate surgeries, approximately 3 weeks apart.The neurostimulators and leads were successfully implanted without adverse surgical outcomes. The patient recovered uneventfully, and the early therapy settings over several months resulted in preliminary decreases in aura and seizure frequency. Stimulation by one of the neurostimulators did not result in stimulation artifacts detected by the contralateral neurostimulator.

Direct Electrical Stimulation of Lateral Orbitofrontal Cortex Acutely Improves Mood in Individuals with Symptoms of Depression.

Mood disorders cause significant morbidity and mortality, and existing therapies fail 20%-30% of patients. Deep brain stimulation (DBS) is an emerging treatment for refractory mood disorders, but its success depends critically on target selection. DBS focused on known targets within mood-related frontostriatal and limbic circuits has been variably efficacious. Here, we examine the effects of stimulation in orbitofrontal cortex (OFC), a key hub for mood-related circuitry that has not been well characterized as a stimulation target. We studied 25 subjects with epilepsy who were implanted with intracranial electrodes for seizure localization. Baseline depression traits ranged from mild to severe. We serially assayed mood state over several days using a validated questionnaire. Continuous electrocorticography enabled investigation of neurophysiological correlates of mood-state changes. We used implanted electrodes to stimulate OFC and other brain regions while collecting verbal mood reports and questionnaire scores. We found that unilateral stimulation of the lateral OFC produced acute, dose-dependent mood-state improvement in subjects with moderate-to-severe baseline depression. Stimulation suppressed low-frequency power in OFC, mirroring neurophysiological features that were associated with positive mood states during natural mood fluctuation. Stimulation potentiated single-pulse-evoked responses in OFC and modulated activity within distributed structures implicated in mood regulation. Behavioral responses to stimulation did not include hypomania and indicated an acute restoration to non-depressed mood state. Together, these findings indicate that lateral OFC stimulation broadly modulates mood-related circuitry to improve mood state in depressed patients, revealing lateral OFC as a promising new target for therapeutic brain stimulation in mood disorders.

An Amygdala-Hippocampus Subnetwork that Encodes Variation in Human Mood.

Human brain networks that encode variation in mood on naturalistic timescales remain largely unexplored. Here we combine multi-site, semi-chronic, intracranial electroencephalography recordings from the human limbic system with machine learning methods to discover a brain subnetwork that correlates with variation in individual subjects' self-reported mood over days. First we defined the subnetworks that influence intrinsic brain dynamics by identifying regions that showed coordinated changes in spectral coherence. The most common subnetwork, found in 13 of 21 subjects, was characterized by ß-frequency coherence (13-30 Hz) between the amygdala and hippocampus. Increased variability of this subnetwork correlated with worsening mood across these 13 subjects. Moreover, these subjects had significantly higher trait anxiety than the 8 of 21 for whom this amygdala-hippocampus subnetwork was absent. These results demonstrate an approach for extracting network-behavior relationships from complex datasets, and they reveal a conserved subnetwork associated with a psychological trait that significantly influences intrinsic brain dynamics and encodes fluctuations in mood.

Mood variations decoded from multi-site intracranial human brain activity.

The ability to decode mood state over time from neural activity could enable closed-loop systems to treat neuropsychiatric disorders. However, this decoding has not been demonstrated, partly owing to the difficulty of modeling distributed mood-relevant neural dynamics while dealing with the sparsity of mood state measurements. Here we develop a modeling framework to decode mood state variations from multi-site intracranial recordings in seven human subjects with epilepsy who self-reported their mood state intermittently over multiple days. We built dynamic neural encoding models of mood state and corresponding decoders for each individual and demonstrated that mood state variations over time can be decoded from neural activity. Across subjects, the decoders largely recruited neural signals from limbic regions, whose spectro-spatial features were tuned to mood variations. The dynamic models also provided an analytical tool to compute the timescales of the decoded mood state. These results provide an initial line of evidence indicating the feasibility of mood state decoding.

Responsive neurostimulation for treatment of pediatric drug-resistant epilepsy.

Responsive neurostimulation for epilepsy involves an implanted device that delivers direct electrical brain stimulation in response to detection of incipient seizures. Responsive neurostimulation is a safe and effective treatment for adults with drug-resistant epilepsy, but although novel treatments are critically needed for younger patients, responsive neurostimulation is currently not approved for children with drug-resistant epilepsy. Here, we report a 16-year-old patient with seizures arising from eloquent cortex, who was successfully treated with responsive neurostimulation. This case highlights the potential utility of this therapy for pediatric patients and underscores the need for larger studies.

Semi-automated Anatomical Labeling and Inter-subject Warping of High-Density Intracranial Recording Electrodes in Electrocorticography.

In this article, we introduce img_pipe, our open source python package for preprocessing of imaging data for use in intracranial electrocorticography (ECoG) and intracranial stereo-EEG analyses. The process of electrode localization, labeling, and warping for use in ECoG currently varies widely across laboratories, and it is usually performed with custom, lab-specific code. This python package aims to provide a standardized interface for these procedures, as well as code to plot and display results on 3D cortical surface meshes. It gives the user an easy interface to create anatomically labeled electrodes that can also be warped to an atlas brain, starting with only a preoperative T1 MRI scan and a postoperative CT scan. We describe the full capabilities of our imaging pipeline and present a step-by-step protocol for users.

Immediate Mood Scaler: Tracking Symptoms of Depression and Anxiety Using a Novel Mobile Mood Scale.

BACKGROUND: Mood disorders are dynamic disorders characterized by multimodal symptoms. Clinical assessment of symptoms is currently limited to relatively sparse, routine clinic visits, requiring retrospective recollection of symptoms present in the weeks preceding the visit. Novel advances in mobile tools now support ecological momentary assessment of mood, conducted frequently using mobile devices, outside the clinical setting. Such mood assessment may help circumvent problems associated with infrequent reporting and better characterize the dynamic presentation of mood symptoms, informing the delivery of novel treatment options. OBJECTIVES: The aim of our study was to validate the Immediate Mood Scaler (IMS), a newly developed, iPad-deliverable 22-item self-report tool designed to capture current mood states. METHODS: A total of 110 individuals completed standardized questionnaires (Patient Health Questionnaire, 9-item [PHQ-9]; generalized anxiety disorder, 7-Item [GAD-7]; and rumination scale) and IMS at baseline. Of the total, 56 completed at least one additional session of IMS, and 17 completed one additional administration of PHQ-9 and GAD-7. We conducted exploratory Principal Axis Factor Analysis to assess dimensionality of IMS, and computed zero-order correlations to investigate associations between IMS and standardized scales. Linear Mixed Model (LMM) was used to assess IMS stability across time and to test predictability of PHQ-9 and GAD-7 score by IMS. RESULTS: Strong correlations were found between standard mood scales and the IMS at baseline (r=.57-.59, P<.001). A factor analysis revealed a 12-item IMS ("IMS-12") with two factors: a "depression" factor and an "anxiety" factor. IMS-12 depression subscale was more strongly correlated with PHQ-9 than with GAD-7 (z=1.88, P=.03), but the reverse pattern was not found for IMS-12 anxiety subscale. IMS-12 showed less stability over time compared with PHQ-9 and GAD-7 (.65 vs .91), potentially reflecting more sensitivity to mood dynamics. In addition, IMS-12 ratings indicated that individuals with mild to moderate depression had greater mood fluctuations compared with individuals with severe depression (.42 vs .79; P=.04). Finally, IMS-12 significantly contributed to the prediction of subsequent PHQ-9 (beta=1.03, P=.02) and GAD-7 scores (beta =.93, P=.01). CONCLUSIONS: Collectively, these data suggest that the 12-item IMS (IMS-12) is a valid tool to assess momentary mood symptoms related to anxiety and depression. Although IMS-12 shows good correlation with standardized scales, it further captures mood fluctuations better and significantly adds to the prediction of the scales. Results are discussed in the context of providing continuous symptom quantification that may inform novel treatment options and support personalized treatment plans.