Carbon-Based Fiber Materials as Implantable Depth Neural Electrodes

Implantable brain electrophysiology electrodes are valuable tools in both fundamental and applied neuroscience due to their ability to record neural activity with high spatiotemporal resolution from shallow and deep brain regions. Their use has been hindered, however, by the challenges in achieving chronically stable operations. Furthermore, implantable depth neural electrodes can only carry out limited data sampling within predefined anatomical regions, making it challenging to perform large-area brain mapping. Minimizing inflammatory responses and associated gliosis formation, and improving the durability and stability of the electrode insulation layers are critical to achieve long-term stable neural recording and stimulation. Combining electrophysiological measurements with simultaneous whole-brain imaging techniques, such as magnetic resonance imaging (MRI), provides a useful solution to alleviate the challenge in scalability of implantable depth electrodes. In recent years, various carbon-based materials have been used to fabricate flexible neural depth electrodes with reduced inflammatory responses and MRI-compatible electrodes, which allows structural and functional MRI mapping of the whole brain without obstructing any brain regions around the electrodes. Here, we conducted a systematic comparative evaluation on the electrochemical properties, mechanical properties, and MRI compatibility of different kinds of carbon-based fiber materials, including carbon nanotube fibers, graphene fibers, and carbon fibers. We also developed a strategy to improve the stability of the electrode insulation without sacrificing the flexibility of the implantable depth electrodes by sandwiching an inorganic barrier layer inside the polymer insulation film. These studies provide us with important insights into choosing the most suitable materials for next-generation implantable depth electrodes with unique capabilities for applications in both fundamental and translational neuroscience research.

LeGUI: A Fast and Accurate Graphical User Interface for Automated Detection and Anatomical Localization of Intracranial Electrodes

Accurate anatomical localization of intracranial electrodes is important for identifying the seizure foci in patients with epilepsy and for interpreting effects from cognitive studies employing intracranial electroencephalography. Localization is typically performed by coregistering postimplant computed tomography (CT) with preoperative magnetic resonance imaging (MRI). Electrodes are then detected in the CT, and the corresponding brain region is identified using the MRI. Many existing software packages for electrode localization chain together separate preexisting programs or rely on command line instructions to perform the various localization steps, making them difficult to install and operate for a typical user. Further, many packages provide solutions for some, but not all, of the steps needed for confident localization. We have developed software, Locate electrodes Graphical User Interface (LeGUI), that consists of a single interface to perform all steps needed to localize both surface and depth/penetrating intracranial electrodes, including coregistration of the CT to MRI, normalization of the MRI to the Montreal Neurological Institute template, automated electrode detection for multiple types of electrodes, electrode spacing correction and projection to the brain surface, electrode labeling, and anatomical targeting. The software is written in MATLAB, core image processing is performed using the Statistical Parametric Mapping toolbox, and standalone executable binaries are available for Windows, Mac, and Linux platforms. LeGUI was tested and validated on 51 datasets from two universities. The total user and computational time required to process a single dataset was approximately 1 h. Automatic electrode detection correctly identified 4362 of 4695 surface and depth electrodes with only 71 false positives. Anatomical targeting was verified by comparing electrode locations from LeGUI to locations that were assigned by an experienced neuroanatomist. LeGUI showed a 94% match with the 482 neuroanatomist-assigned locations. LeGUI combines all the features needed for fast and accurate anatomical localization of intracranial electrodes into a single interface, making it a valuable tool for intracranial electrophysiology research.

Microdialysis and microperfusion electrodes in neurologic disease monitoring

Contemporary biomarker collection techniques in blood and cerebrospinal fluid have to date offered only modest clinical insights into neurologic diseases such as epilepsy and glioma. Conversely, the collection of human electroencephalography (EEG) data has long been the standard of care in these patients, enabling individualized insights for therapy and revealing fundamental principles of human neurophysiology. Increasing interest exists in simultaneously measuring neurochemical biomarkers and electrophysiological data to enhance our understanding of human disease mechanisms. This review compares microdialysis, microperfusion, and implanted EEG probe architectures and performance parameters. Invasive consequences of probe implantation are also investigated along with the functional impact of biofouling. Finally, previously developed microdialysis electrodes and microperfusion electrodes are reviewed in preclinical and clinical settings. Critically, current and precedent microdialysis and microperfusion probes lack the ability to collect neurochemical data that is spatially and temporally coincident with EEG data derived from depth electrodes. This ultimately limits diagnostic and therapeutic progress in epilepsy and glioma research. However, this gap also provides a unique opportunity to create a dual-sensing technology that will provide unprecedented insights into the pathogenic mechanisms of human neurologic disease.

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.

Future of Neurology & Technology: Stereo-electroencephalography in Presurgical Epilepsy Evaluation

Stereo-electroencephalography (SEEG) is not only a sophisticated and highly technological investigation but a new and better way to conceptualize the spatial and temporal dynamics of epileptic activity. The first intracranial investigations with SEEG were carried out in France in the mid-twentieth century; however, its use in North America is much more recent. Given its significantly lower risk of complications and its ability to sample both superficial and deep structures as well as both hemispheres simultaneously, SEEG has become the preferred method to conduct intracranial EEG monitoring in most comprehensive epilepsy centers in North America. SEEG is an invasive neurophysiological methodology used for advanced pre-surgical work-up in the 20% of drug-resistant patients with more complex focal epilepsy in whom non-invasive investigations do not allow to decide on surgical candidacy. SEEG uses stereotactically-implanted depth electrodes to map the origin and propagation of epileptic seizures by creating a three-dimensional representation of the abnormal electrical activity in the brain. SEEG analysis takes into account the background, interictal, and ictal activity, as well as the results of cortical electrical stimulation procedures, to reliably delineate the epileptogenic network. By means of a clinical vignette, this article will walk general neurologists, but especially neurology trainees through the immense potential of this methodology. In summary, SEEG enables to accurately identify the epileptogenic zone in patients with drug-resistant focal epilepsy who otherwise would be not amenable to surgical treatment, the best way to improve seizure control and achieve seizure-freedom in this patient population.

Case Report: PAFAH1B1 Mutation and Posterior Band Heterotopia With Focal Temporal Lobe Epilepsy Treated by Responsive Neurostimulation

Subcortical band heterotopia (SBH), also known as double cortex syndrome, is a malformation of cortical development caused by inherited or somatic gene variants. We present a case of a young adult with posterior SBH and electroclinical features of focal neocortical temporal lobe epilepsy. Genomic blood analysis identified a pathogenic somatic mosaicism duplication variant of the PAFAH1B1 gene. Despite bilateral cortical MRI abnormalities, the interictal and ictal EEG findings indicated a focal epileptogenic region in the left posterior temporal region. Chronic responsive cortical neurostimulation across two four-contact depth electrodes placed 5 mm on either side of the maximal interictal spiking identified during intraoperative electrocorticography resulted in a consistent 28% reduction in duration of electrographic seizures and as well as constricted propagation. Although electrographic seizures continued, the family reported no clinical seizures and a marked improvement in resistant behaviors. This observation supports that focal neocortical neuromodulation can control clinical seizures of consistently localized origin despite genetic etiology, bilateral structural brain abnormalities, and continuation of non-propagating electrographic seizures. We propose that a secondary somatic mutation may be the cause of the focal neocortical temporal lobe epilepsy.

The comparative study of invasive electroencephalography modalities in temporal lobe epilepsy

Introduction. Invasive video-EEG monitoring (invasive EEG) is indicated in patients with refractory focal epilepsy while localization of the epileptogenic zone is unclear. Methods of invasive EEG in different groups of patients demonstrate variable results.Objective: to analyse the results of invasive EEG via subdural and depth electrodes in patients with refractory temporal lobe epilepsy with mesial temporal lobe seizures.Materials and methods. The series of 37 patients who underwent invasive EEG from 2013 to 2020 was retrospectively analysed. The study includes primary adult patients with structural refractory focal epilepsy with mesial temporal lobe seizures without tumor and vascular pathology. Patients were divided onto 3 groups: 1) with foramen ovale electrodes 2) subdural strip electrodes and 3) combination of subdural strips and depths electrodes. The results of anteromedial temporal lobectomy after 6 months were classified according to Engel scale.Results. A group with foramen ovale electrodes included 7 patients, subdural strips – 23, combination – 7. The seizure onset zone was detected in 36 (97 %) cases. Serious complications were observed in 2 (29 %) cases in the group with foramen ovale electrodes. The mean follow-up in 23 (76 %) patients after resective surgery was 28.3 months. Favourable results (Engel I, II) were observed in 4 (80 %) patients with foramen ovale electrodes, in 8 (67 %) patients with subdural electrodes, in 6 (100 %) with combination. Unfavourable results (Engel III, IV) were noted in 1 (20 %) patient with foramen ovale electrode, in 4 (33 %) patients with subdural strips.Conclusion. All the presented modalities of invasive EEG are effective for localizing of seizure onset zone in this category of patients. Foramen ovale electrode using may be limited due to increased risk of complications.

Decoding of human identity by computer vision and neuronal vision

SummaryExtracting meaning from a dynamic and variable flow of incoming information is a major goal of both natural and artificial intelligence. Computer vision (CV) guided by deep learning (DL) has made significant strides in recognizing a specific identity despite highly variable attributes1,2. This is the same challenge faced by the nervous system and partially addressed by the concept cells—neurons exhibiting selective firing in response to specific persons/places, described in the human medial temporal lobe (MTL)3–6. Yet, access to neurons representing a particular concept is limited due to these neurons’ sparse coding. It is conceivable, however, that the information required for such decoding is present in relatively small neuronal populations. To evaluate how well neuronal populations encode identity information in natural settings, we recorded neuronal activity from multiple brain regions of nine neurosurgical epilepsy patients implanted with depth electrodes, while the subjects watched an episode of the TV series “24”. We implemented DL models that used the time-varying population neural data as inputs and decoded the visual presence of the main characters in each frame. Before training and testing the DL models, we devised a minimally supervised CV algorithm (with comparable performance against manually-labelled data7) to detect and label all the important characters in each frame. This methodology allowed us to compare “computer vision” with “neuronal vision”—footprints associated with each character present in the activity of a subset of neurons—and identify the brain regions that contributed to this decoding process. We then tested the DL models during a recognition memory task following movie viewing where subjects were asked to recognize clip segments from the presented episode. DL model activations were not only modulated by the presence of the corresponding characters but also by participants’ subjective memory of whether they had seen the clip segment, and by the associative strengths of the characters in the narrative plot. The described approach can offer novel ways to probe the representation of concepts in time-evolving dynamic behavioral tasks. Further, the results suggest that the information required to robustly decode concepts is present in the population activity of only tens of neurons even in brain regions beyond MTL.