Probabilistic comparison of gray and white matter coverage between depth and surface intracranial electrodes in epilepsy

In this study, we quantified the coverage of gray and white matter during intracranial electroencephalography in a cohort of epilepsy patients with surface and depth electrodes. We included 65 patients with strip electrodes (n = 12), strip and grid electrodes (n = 24), strip, grid, and depth electrodes (n = 7), or depth electrodes only (n = 22). Patient-specific imaging was used to generate probabilistic gray and white matter maps and atlas segmentations. Gray and white matter coverage was quantified using spherical volumes centered on electrode centroids, with radii ranging from 1 to 15 mm, along with detailed finite element models of local electric fields. Gray matter coverage was highly dependent on the chosen radius of influence (RoI). Using a 2.5 mm RoI, depth electrodes covered more gray matter than surface electrodes; however, surface electrodes covered more gray matter at RoI larger than 4 mm. White matter coverage and amygdala and hippocampal coverage was greatest for depth electrodes at all RoIs. This study provides the first probabilistic analysis to quantify coverage for different intracranial recording configurations. Depth electrodes offer increased coverage of gray matter over other recording strategies if the desired signals are local, while subdural grids and strips sample more gray matter if the desired signals are diffuse.

New interinstitutional, multimodal presurgical evaluation protocol associated with improved seizure freedom for poorly defined cases of focal epilepsy in children

OBJECTIVE In an attempt to improve postsurgical seizure outcomes for poorly defined cases (PDCs) of pediatric focal epilepsy (i.e., those that are not visible or well defined on 3T MRI), the authors modified their presurgical evaluation strategy. Instead of relying on concordance between video-electroencephalography and 3T MRI and using functional imaging and intracranial recording in select cases, the authors systematically used a multimodal, 3-tiered investigation protocol that also involved new collaborations between their hospital, the Montreal Children’s Hospital, and the Montreal Neurological Institute. In this study, the authors examined how their new strategy has impacted postsurgical outcomes. They hypothesized that it would improve postsurgical seizure outcomes, with the added benefit of identifying a subset of tests contributing the most. METHODS Chart review was performed for children with PDCs who underwent resection following the new strategy (i.e., new protocol [NP]), and for the same number who underwent treatment previously (i.e., preprotocol [PP]); ≥ 1-year follow-up was required for inclusion. Well-defined, multifocal, and diffuse hemispheric cases were excluded. Preoperative demographics and clinical characteristics, resection volumes, and pathology, as well as seizure outcomes (Engel class Ia vs > Ia) at 1 year postsurgery and last follow-up were reviewed. RESULTS Twenty-two consecutive NP patients were compared with 22 PP patients. There was no difference between the two groups for resection volumes, pathology, or preoperative characteristics, except that the NP group underwent more presurgical evaluation tests (p < 0.001). At 1 year postsurgery, 20 of 22 NP patients and 10 of 22 PP patients were seizure free (OR 11.81, 95% CI 2.00–69.68; p = 0.006). Magnetoencephalography and PET/MRI were associated with improved postsurgical seizure outcomes, but both were highly correlated with the protocol group (i.e., independent test effects could not be demonstrated). CONCLUSIONS A new presurgical evaluation strategy for children with PDCs of focal epilepsy led to improved postsurgical seizure freedom. No individual presurgical evaluation test was independently associated with improved outcome, suggesting that it may be the combined systematic protocol and new interinstitutional collaborations that makes the difference rather than any individual test.

Probabilistic comparison of gray and white matter coverage between depth and surface intracranial electrodes in epilepsy: a patient-specific modeling and empirical study

Objective. The objective of this study is to quantify the coverage of gray and white matter during intracranial electroencephalography in a cohort of epilepsy patients with surface and depth electrodes. Methods. We included 65 patients with strip electrodes (n=12), strip and grid electrodes (n=24), strip, grid, and depth electrodes (n=7), or depth electrodes only (n=22) from the University of Utah spanning 2010-2020. Patient-specific imaging was used to generate probabilistic gray and white matter maps and atlas segmentations. The gray and white matter coverage was quantified based on spherical volumes centered on electrode centroids, with radii ranging from 1-15 mm, along with detailed finite element models of local electric fields Results. Gray matter coverage was highly dependent on the chosen radius of influence (RoI). Using a 2.5 mm RoI, depth electrodes covered more gray matter than surface electrodes; however, surface electrodes covered more gray matter at RoI larger than 4 mm. White matter coverage was greatest for depth electrodes at all RoIs, which is noteworthy for studies involving stimulation mapping. Depth electrodes were able to record significantly more gray matter from the amygdala and hippocampus than subdural electrodes. Significance. This study provides the first probabilistic analysis to quantify gray and white matter coverage for multiple categories of intracranial recording configurations. Depth electrodes may offer increased per contact coverage of gray matter over other recording strategies if the desired signals are local to the contact, while subdural grids and strips can sample more gray matter if the desired signals are more diffuse.

Exploring Ripple Waves in the Human Brain

Ripples are brief (<150 ms) high-frequency oscillatory neural activities in the brain with a range of 140 to 200 Hz in rodents and 80 to 140 Hz in humans. Ripples are regarded as playing an essential role in several aspects of memory function, mainly in the hippocampus. This type of ripple generally occurs with sharp waves and is called a sharp-wave ripple (SPW-R). Extensive research of SPW-Rs in the rodent brain while actively awake has also linked the function of these SPW-Rs to navigation and decision making. Although many studies with rodents unveiled SPW-R function, research in humans on this subject is still sparse. Therefore, unveiling SPW-R function in the human hippocampus is warranted. A certain type of ripples may also be a biomarker of epilepsy. This type of ripple is called a pathological ripple (p-ripple). p-ripples have a wider range of frequency (80-500 Hz) than SPW-Rs, and the range of frequency is especially higher in brain regions that are intrinsically linked to epilepsy onset. Brain regions producing ripples are too small for scalp electrode recording, and intracranial recording is typically needed to detect ripples. In addition, SPW-Rs in the human hippocampus have been recorded from patients with epilepsy who may have p-ripples. Differentiating SPW-Rs and p-ripples is often not easy. We need to develop more sophisticated methods to record SPW-Rs to differentiate them from p-ripples. This paper reviews the general features and roles of ripple waves.

Intracranial recording in patients with aphasia using nanomaterial-based flexible electronics: promises and challenges

In recent years, researchers have studied how nanotechnology could enhance neuroimaging techniques. The application of nanomaterial-based flexible electronics has the potential to advance conventional intracranial electroencephalography (iEEG) by utilising brain-compatible soft nanomaterials. The resultant technique has significantly high spatial and temporal resolution, both of which enhance the localisation of brain functions and the mapping of dynamic language processing. This review presents findings on aphasia, an impairment in language and communication, and discusses how different brain imaging techniques, including positron emission tomography, magnetic resonance imaging, and iEEG, have advanced our understanding of the neural networks underlying language and reading processing. We then outline the strengths and weaknesses of iEEG in studying human cognition and the development of intracranial recordings that use brain-compatible flexible electrodes. We close by discussing the potential advantages and challenges of future investigations adopting nanomaterial-based flexible electronics for intracranial recording in patients with aphasia.

The utility of arterial spin labeling in the presurgical evaluation of poorly defined focal epilepsy in children

OBJECTIVEThe authors sought to assess the utility of arterial spin labeling (ASL) perfusion 3T-MRI for the presurgical evaluation of poorly defined focal epilepsy in pediatric patients.METHODSPseudocontinuous ASL perfusion 3T-MRI was performed in 25 consecutive children with poorly defined focal epilepsy. ASL perfusion abnormalities were detected qualitatively by visual inspection and quantitatively by calculating asymmetry index (AI) maps and significant z-score cluster maps based on successfully operated cases. ASL results were prospectively compared to scalp EEG, structural 3T-MRI, FDG-PET, ictal/interictal SPECT, magnetoencephalography (MEG), and intracranial recording results, as well as the final surgically proven epileptogenic zone (EZ) in operated patients who had at least 1 year of good (Engel class I/II) seizure outcome and positive histopathology results.RESULTSQualitative ASL perfusion abnormalities were found in 17/25 cases (68%), specifically in 17/20 MRI-positive cases (85.0%) and in none of the 5 MRI-negative cases. ASL was concordant with localizing scalp EEG findings in 66.7%, structural 3T-MRI in 90%, FDG-PET in 75%, ictal/interictal SPECT in 62.5%, and MEG in 75% of cases, and with intracranial recording results in 40% of cases. Eleven patients underwent surgery; in all 11 cases the EZ was surgically proven by positive histopathology results and the patient having at least 1 year of good seizure outcome. ASL results were concordant with this final surgically proven EZ in 10/11 cases (sensitivity 91%, specificity 50%). All 10 ASL-positive patients who underwent surgery had positive surgical pathology results and good long-term postsurgical seizure outcome at a mean follow-up of 39 months. Retrospective quantitative analysis based on significant z-score clusters found 1 true-positive result that was missed by qualitative analysis and 3 additional false-positive results (sensitivity 100%, specificity 23%).CONCLUSIONSASL supports the hypothesis regarding the EZ in poorly defined focal epilepsy cases in children. Due to its convenience and noninvasive nature, the authors recommend that ASL be added routinely to the presurgical MRI evaluation of epilepsy. Future optimized quantitative methods may improve the diagnostic yield of this technique.

Deep Neural Architectures for Mapping Scalp to Intracranial EEG

Data is often plagued by noise which encumbers machine learning of clinically useful biomarkers and electroencephalogram (EEG) data is no exemption. Intracranial EEG (iEEG) data enhances the training of deep learning models of the human brain, yet is often prohibitive due to the invasive recording process. A more convenient alternative is to record brain activity using scalp electrodes. However, the inherent noise associated with scalp EEG data often impedes the learning process of neural models, achieving substandard performance. Here, an ensemble deep learning architecture for nonlinearly mapping scalp to iEEG data is proposed. The proposed architecture exploits the information from a limited number of joint scalp-intracranial recording to establish a novel methodology for detecting the epileptic discharges from the sEEG of a general population of subjects. Statistical tests and qualitative analysis have revealed that the generated pseudo-intracranial data are highly correlated with the true intracranial data. This facilitated the detection of IEDs from the scalp recordings where such waveforms are not often visible. As a real-world clinical application, these pseudo-iEEGs are then used by a convolutional neural network for the automated classification of intracranial epileptic discharges (IEDs) and non-IED of trials in the context of epilepsy analysis. Although the aim of this work was to circumvent the unavailability of iEEG and the limitations of sEEG, we have achieved a classification accuracy of 68% an increase of 6% over the previously proposed linear regression mapping.

Subthalamic Nucleus Neurons Differentially Encode Early and Late Aspects of Speech Production

ABSTRACTBasal ganglia-thalamocortical loops mediate all motor behavior, yet little detail is known about the role of basal ganglia nuclei in speech production. Using intracranial recording during deep brain stimulation surgery, we tested the hypothesis that the firing rate of subthalamic nucleus neurons is modulated in response to both planning and motor execution aspects of speech. Nearly half of 79 recorded units exhibited firing rate modulation, during a syllable reading task administered in 12 subjects. Trial-to-trial timing of changes in subthalamic neuronal activity, relative to cue onset versus production onset, revealed that locking to cue presentation was associated more with units that decreased firing rate, while locking to speech onset was associated more with units that increased firing rate. These uniquely acquired data indicate that subthalamic activity is dynamic during the production of speech, reflecting temporally-dependent inhibition and excitation of separate populations of subthalamic neurons.