Rapid and minimum invasive functional brain mapping by real-time visualization of high gamma activity during awake craniotomy

Speech and Language Errors during Awake Brain Surgery and Postoperative Language Outcome in Glioma Patients: A Systematic Review

Awake craniotomy with direct electrical stimulation (DES) is the standard treatment for patients with gliomas in eloquent areas. Even though language is monitored carefully during surgery, many patients suffer from postoperative aphasia, with negative effects on their quality of life. Some perioperative factors are reported to influence postoperative language outcome. However, the influence of different intraoperative speech and language errors on language outcome is not clear. Therefore, we investigate this relation. A systematic search was performed in which 81 studies were included, reporting speech and language errors during awake craniotomy with DES and postoperative language outcomes in adult glioma patients up until 6 July 2020. The frequencies of intraoperative errors and language status were calculated. Binary logistic regressions were performed. Preoperative language deficits were a significant predictor for postoperative acute (OR = 3.42, p < 0.001) and short-term (OR = 1.95, p = 0.007) language deficits. Intraoperative anomia (OR = 2.09, p = 0.015) and intraoperative production errors (e.g., dysarthria or stuttering; OR = 2.06, p = 0.016) were significant predictors for postoperative acute language deficits. Postoperatively, the language deficits that occurred most often were production deficits and spontaneous speech deficits. To conclude, during surgery, intraoperative anomia and production errors should carry particular weight during decision-making concerning the optimal onco-functional balance for a given patient, and spontaneous speech should be monitored. Further prognostic research could facilitate intraoperative decision-making, leading to fewer or less severe postoperative language deficits and improvement of quality of life.

Workshops of the Eighth International Brain-Computer Interface Meeting: BCIs: The Next Frontier

The Eighth International Brain-Computer Interface (BCI) Meeting was held June 7-9th, 2021 in a virtual format. The conference continued the BCI Meeting series' interactive nature with 21 workshops covering topics in BCI (also called brain-machine interface) research. As in the past, workshops covered the breadth of topics in BCI. Some workshops provided detailed examinations of specific methods, hardware, or processes. Others focused on specific BCI applications or user groups. Several workshops continued consensus building efforts designed to create BCI standards and increase the ease of comparisons between studies and the potential for meta-analysis and large multi-site clinical trials. Ethical and translational considerations were both the primary topic for some workshops or an important secondary consideration for others. The range of BCI applications continues to expand, with more workshops focusing on approaches that can extend beyond the needs of those with physical impairments. This paper summarizes each workshop, provides background information and references for further study, presents an overview of the discussion topics, and describes the conclusion, challenges, or initiatives that resulted from the interactions and discussion at the workshop.

Novel intraoperative online functional mapping of somatosensory finger representations for targeted stimulating electrode placement: technical note

Defining eloquent cortex intraoperatively, traditionally performed by neurosurgeons to preserve patient function, can now help target electrode implantation for restoring function. Brain-machine interfaces (BMIs) have the potential to restore upper-limb motor control to paralyzed patients but require accurate placement of recording and stimulating electrodes to enable functional control of a prosthetic limb. Beyond motor decoding from recording arrays, precise placement of stimulating electrodes in cortical areas associated with finger and fingertip sensations allows for the delivery of sensory feedback that could improve dexterous control of prosthetic hands. In this study, the authors demonstrated the use of a novel intraoperative online functional mapping (OFM) technique with high-density electrocorticography to localize finger representations in human primary somatosensory cortex. In conjunction with traditional pre- and intraoperative targeting approaches, this technique enabled accurate implantation of stimulating microelectrodes, which was confirmed by postimplantation intracortical stimulation of finger and fingertip sensations. This work demonstrates the utility of intraoperative OFM and will inform future studies of closed-loop BMIs in humans.

Deep Learning Provides Exceptional Accuracy to ECoG-Based Functional Language Mapping for Epilepsy Surgery

The success of surgical resection in epilepsy patients depends on preserving functionally critical brain regions, while removing pathological tissues. Being the gold standard, electro-cortical stimulation mapping (ESM) helps surgeons in localizing the function of eloquent cortex through electrical stimulation of electrodes placed directly on the cortical brain surface. Due to the potential hazards of ESM, including increased risk of provoked seizures, electrocorticography based functional mapping (ECoG-FM) was introduced as a safer alternative approach. However, ECoG-FM has a low success rate when compared to the ESM. In this study, we address this critical limitation by developing a new algorithm based on deep learning for ECoG-FM and thereby we achieve an accuracy comparable to ESM in identifying eloquent language cortex. In our experiments, with 11 epilepsy patients who underwent presurgical evaluation (through deep learning-based signal analysis on 637 electrodes), our proposed algorithm obtained an accuracy of 83.05% in identifying language regions, an exceptional 23% improvement with respect to the conventional ECoG-FM analysis (∼60%). Our findings have demonstrated, for the first time, that deep learning powered ECoG-FM can serve as a stand-alone modality and avoid likely hazards of the ESM in epilepsy surgery. Hence, reducing the potential for developing post-surgical morbidity in the language function.

Disconnection of the pathological connectome for multifocal epilepsy surgery

OBJECTIVERecent neuroimaging studies suggest that intractable epilepsy involves pathological functional networks as well as strong epileptogenic foci. Combining cortico-cortical evoked potential (CCEP) recording and tractography is a useful strategy for mapping functional connectivity in normal and pathological networks. In this study, the authors sought to demonstrate the efficacy of preoperative combined CCEP recording, high gamma activity (HGA) mapping, and tractography for surgical planning, and of intraoperative CCEP measures for confirmation of selective pathological network disconnection.METHODSThe authors treated 4 cases of intractable epilepsy. Diffusion tensor imaging-based tractography data were acquired before the first surgery for subdural grid implantation. HGA and CCEP investigations were done after the first surgery, before the second surgery was performed to resect epileptogenic foci, with continuous CCEP monitoring during resection.RESULTSAll 4 patients in this report had measurable pathological CCEPs. The mean negative peak-1 latency of normal CCEPs related to language functions was 22.2 ± 3.5 msec, whereas pathological CCEP latencies varied between 18.1 and 22.4 msec. Pathological CCEPs diminished after complete disconnection in all cases. At last follow-up, all of the patients were in long-term postoperative seizure-free status, although 1 patient still suffered from visual aura every other month.CONCLUSIONSCombined CCEP measurement, HGA mapping, and tractography greatly facilitated targeted disconnection of pathological networks in this study. Although CCEP recording requires technical expertise, it allows for assessment of pathological network involvement in intractable epilepsy and may improve seizure outcome.

Time-Variant Linear Discriminant Analysis Improves Hand Gesture and Finger Movement Decoding for Invasive Brain-Computer Interfaces

Invasive brain-computer interfaces yield remarkable performance in a multitude of applications. For classification experiments, high-gamma bandpower features and linear discriminant analysis (LDA) are commonly used due to simplicity and robustness. However, LDA is inherently static and not suited to account for transient information that is typically present in high-gamma features. To resolve this issue, we here present an extension of LDA to the time-variant feature space. We call this method time-variant linear discriminant analysis (TVLDA). It intrinsically provides a feature reduction stage, which makes external approaches thereto obsolete, such as feature selection techniques or common spatial patterns (CSPs). As well, we propose a time-domain whitening stage which equalizes the pronounced 1/f-shape of the typical brain-wave spectrum. We evaluated our proposed architecture based on recordings from 15 epilepsy patients with temporarily implanted subdural grids, who participated in additional research experiments besides clinical treatment. The experiments featured two different motor tasks involving three high-level gestures and individual finger movement. We used log-transformed bandpower features from the high-gamma band (50-300 Hz, excluding power-line harmonics) for classification. On average, whitening improved the classification performance by about 11%. On whitened data, TVLDA outperformed LDA with feature selection by 11.8%, LDA with CSPs by 13.9%, and regularized LDA with vectorized features by 16.4%. At the same time, TVLDA only required one or two internal features to achieve this. TVLDA provides stable results even if very few trials are available. It is easy to implement, fully automatic and deterministic. Due to its low complexity, TVLDA is suited for real-time brain-computer interfaces. Training is done in less than a second. TVLDA performed particularly well in experiments with data from high-density electrode arrays. For example, the three high-level gestures were correctly identified at a rate of 99% over all subjects. Similarly, the decoding accuracy of individual fingers was 96% on average over all subjects. To our knowledge, these mean accuracies are the highest ever reported for three-class and five-class motor-control BCIs.

Awake Microvascular Decompression for Trigeminal Neuralgia: Concept and Initial Results

BACKGROUND

In this initial series, we evaluated the use of microvascular decompression (MVD) under an awake anesthesia protocol ("awake" MVD) to assess whether intraoperative pain evaluation can identify and mitigate insufficient decompression of the trigeminal nerve, improving surgical outcomes, and possibly expand the indications of MVD in patients with comorbidities that would preclude the use of general endotracheal anesthesia (GEA).

METHODS

An Institutional Review Board-approved prospective study of 10 consecutive adults who underwent MVD for trigeminal neuralgia (TN) was conducted. The primary outcome measure was postoperative TN pain quantified on the Barrow Neurological Institute (BNI) Pain Severity Scale.

RESULTS

The median patient age was 65.5 years, with a female:male ratio of 6:4. All 10 patients tolerated the procedure well and did not require GEA intraoperatively or postoperatively. Nine patients had a successful surgical outcome (BNI score I, n = 5; BNI score II, n = 4). One patient did not have pain relief (BNI score IV). This same patient also developed a pseudomeningocele, which was the sole surgical complication observed in this series. One patient experienced recurrence of pain at 11 months, with BNI score increasing from I to II. The median duration of follow-up was 16.5 months. Two patients did not experienced resolution of evoked pain during intraoperative awake testing following decompression. Further intraoperative exploration revealed secondary offending vessels that were subsequently decompressed, leading to resolution of pain.

CONCLUSIONS

Intraoperative awake testing for treatment efficacy may increase the success rate of MVD by rapidly identifying and mitigating insufficient cranial nerve V decompression.

Awake High-Flow Extracranial to Intracranial Bypass for Complex Cerebral Aneurysms: Institutional Clinical Trial Results

OBJECTIVE

Assess the potential added benefit to patient outcomes of "awake" neurological testing when compared with standard neurophysiologic testing performed under general endotracheal anesthesia.

METHODS

Prospective study of 30 consecutive adult patients who underwent awake high flow extracranial to intracranial (HFEC-IC) bypass. Clinical neurological and neurophysiologic findings were recorded. Primary outcome measures were the incidence of stroke/cerebrovascular accident (CVA), length of stay, discharge to rehabilitation, 30-day modified Rankin scale score, and death. An analysis was also performed of a retrospective control cohort (n = 110 patients who underwent HFEC-IC for internal carotid artery (ICA) aneurysms under standard general endotracheal anesthesia).

RESULTS

Five patients (16.6%) developed clinical awake neurological changes (4, contralateral hemiparesis; 1, ipsilateral visual changes) during the 10-minute ICA occlusion test. These patients had 2 kinks in the graft, 1 vasospasm, 1 requiring reconstruction of the distal anastomosis, and 1 developed blurring of vision that reversed after the removal of the distal permanent clip on the ICA. Three of these 5 patients had asynchronous clinical "awake" neurological and neurophysiologic changes. Two patients (7%) developed CVA. Median length of stay was 4 days. Twenty-eight of 30 patients were discharged to home. Median modified Rankin scale score was 1. There were no deaths in this series. Absolute risk reduction in the awake craniotomy group (n = 30) relative to control retrospective group (n = 110) was 7% for CVA, 9% for discharge to rehabilitation, and 10% for graft patency.

CONCLUSIONS

Temporary ICA occlusion during HFEC-IC bypass for ICA aneurysms in conjunction with awake intraoperative clinical testing was effective in detecting a subset of patients (n = 3, 10%) in whom neurological deficit was not detected by neurophysiologic monitoring alone.

Passive language mapping combining real-time oscillation analysis with cortico-cortical evoked potentials for awake craniotomy

OBJECTIVE

Electrocortical stimulation (ECS) is the gold standard for functional brain mapping; however, precise functional mapping is still difficult in patients with language deficits. High gamma activity (HGA) between 80 and 140 Hz on electrocorticography is assumed to reflect localized cortical processing, whereas the cortico-cortical evoked potential (CCEP) can reflect bidirectional responses evoked by monophasic pulse stimuli to the language cortices when there is no patient cooperation. The authors propose the use of “passive” mapping by combining HGA mapping and CCEP recording without active tasks during conscious resections of brain tumors.

METHODS

Five patients, each with an intraaxial tumor in their dominant hemisphere, underwent conscious resection of their lesion with passive mapping. The authors performed functional localization for the receptive language area, using real-time HGA mapping, by listening passively to linguistic sounds. Furthermore, single electrical pulses were delivered to the identified receptive temporal language area to detect CCEPs in the frontal lobe. All mapping results were validated by ECS, and the sensitivity and specificity were evaluated.

RESULTS

Linguistic HGA mapping quickly identified the language area in the temporal lobe. Electrical stimulation by linguistic HGA mapping to the identified temporal receptive language area evoked CCEPs on the frontal lobe. The combination of linguistic HGA and frontal CCEPs needed no patient cooperation or effort. In this small case series, the sensitivity and specificity were 93.8% and 89%, respectively.

CONCLUSIONS

The described technique allows for simple and quick functional brain mapping with higher sensitivity and specificity than ECS mapping. The authors believe that this could improve the reliability of functional brain mapping and facilitate rational and objective operations. Passive mapping also sheds light on the underlying physiological mechanisms of language in the human brain.

"Awake" clipping of cerebral aneurysms: report of initial series

OBJECTIVE Risk of ischemia during aneurysm surgery is significantly related to temporary clipping time and final clipping that might incorporate a perforator. In this study, the authors attempted to assess the potential added benefit to patient outcomes of "awake" neurological testing when compared with standard neurophysiological testing performed under general anesthesia. The procedure is performed after the induction of conscious sedation, and for the neurological testing, the patient is fully awake. METHODS The authors conducted an institutional review board-approved prospective study of clipping unruptured intracranial aneurysms (UIAs) in 30 consecutive adult patients who underwent awake clipping. The end points were the incidence of stroke/cerebrovascular accident (CVA), death, discharge to a long-term facility, length of stay, and 30-day modified Rankin Scale score. All clinical and neurophysiological intraoperative monitoring data were recorded. RESULTS The median patient age was 52 years (range 27-63 years); 19 (63%) female and 11 (37%) male patients were included. Twenty-seven (90%) aneurysms were anterior, and 3 (10%) were posterior circulation aneurysms. Five (17%) had been coiled previously, 3 (10%) had been clipped previously, 2 (7%) were partially calcified, and 2 (7%) were fusiform aneurysms. Three patients developed synchronous clinical neurological and neurophysiological changes during temporary clipping with consequent removal of the temporary clip and reversal of those clinical and neurophysiological changes. Three patients developed asynchronous clinical neurological and neurophysiological changes. These 3 patients developed hemiparesis without changes in neurophysiological monitoring results. One patient developed linked clinical neurological and neurophysiological changes during final clipping that were not reversed by reapplication of the clip, and the patient had a CVA. Four patients with internal carotid artery ophthalmic segment aneurysms underwent visual testing with final clipping, and 1 of these patients required repositioning of the clip. Three patients who required permanent occlusion of a vessel as part of their aneurysm treatment underwent a 10-minute intraoperative clinical respective-vessel test occlusion. The median length of stay was 3 days (range 1-5 days). The median modified Rankin Scale score was 1 (range 0-3). All of the patients were discharged to home from the hospital except for 1 who developed a CVA and was discharged to a rehabilitation facility. There were no deaths in this series. CONCLUSIONS The 3 patients who developed neurological deterioration without a concomitant neurophysiological finding during temporary clipping revealed a potential advantage of awake aneurysm surgery (i.e., in decreasing the risk of ischemic injury).

Clinical Impact and Implication of Real-Time Oscillation Analysis for Language Mapping

BACKGROUND

We developed a functional brain analysis system that enabled us to perform real-time task-related electrocorticography (ECoG) and evaluated its potential in clinical practice. We hypothesized that high gamma activity (HGA) mapping would provide better spatial and temporal resolution with high signal-to-noise ratios.

METHODS

Seven awake craniotomy patients were evaluated. ECoG was recorded during language tasks using subdural grids, and HGA (60-170 Hz) maps were obtained in real time. The patients also underwent electrocortical stimulation (ECS) mapping to validate the suspected functional locations on HGA mapping. The results were compared and calculated to assess the sensitivity and specificity of HGA mapping. For reference, bedside HGA-ECS mapping was performed in 5 epilepsy patients.

RESULTS

HGA mapping demonstrated functional brain areas in real time and was comparable with ECS mapping. Sensitivity and specificity for the language area were 90.1% ± 11.2% and 90.0% ± 4.2%, respectively. Most HGA-positive areas were consistent with ECS-positive regions in both groups, and there were no statistical between-group differences.

CONCLUSIONS

Although this study included a small number of subjects, it showed real-time HGA mapping with the same setting and tasks under different conditions. This study demonstrates the clinical feasibility of real-time HGA mapping. Real-time HGA mapping enabled simple and rapid detection of language functional areas in awake craniotomy. The mapping results were highly accurate, although the mapping environment was noisy. Further studies of HGA mapping may provide the potential to elaborate complex brain functions and networks.

Online visualization of brain connectivity

BACKGROUND

While visualization of brain activity has well established practical applications such as real-time functional mapping or neurofeedback, visual representation of brain connectivity is not widely used. In addition, technically challenging single-trial connectivity estimation may have hindered practical usage of connectivity in online applications.

NEW METHOD

In this work, we developed algorithms that are capable of estimating and visualizing (effective) connectivity between independent cortical sources during online EEG recordings.

RESULTS

The core routines of our procedure, such as CSPVARICA source extraction and regularized connectivity estimation, are available in our open source Python-based toolbox SCoT. We demonstrate for the first time that online connectivity visualization is feasible. We show this in a feasibility study with twelve participants performing two different tasks, namely motor execution and resting with eyes open or closed. Connectivity patterns were significantly different between two motor tasks in four participants, whereas significant differences between resting task patterns were found in seven participants.

COMPARISON WITH EXISTING METHODS

Existing connectivity studies have focused on offline methods. In contrast, there are only a small number of examples in the literature that explored online connectivity estimation. For example, a system based on wearable EEG has been demonstrated to work for one subject, and the Glass Brain project has received considerable attention in popular sciences last year. However, none of these attempts validate their methods on multiple subjects.

CONCLUSIONS

Our results show that causal connectivity patterns can be observed online during EEG measurements, which is a first step towards real-time connectivity analysis.