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Vakilna, Y. S.

Publications and source records attributed to Vakilna, Y. S..

2 recordsLinked to original sources

Microelectrode arrays enable directional stereo-EEG during kainate-mediated seizures

Surgical planning for drug-resistant epilepsy often relies on stereo-EEG (sEEG) recordings obtained with cylindrical ring electrodes. Prior modeling studies, including lead-field analysis, suggest that microelectrodes distributed around an sEEG-sized insulating body offer superior source amplification and directional sensitivity that are not available with either a ring design or microelectrodes on micro-structures, e.g. Neuropixel. However, these advantages have not been demonstrated in seizure models. This study evaluated high-density sEEG recordings using directional microelectrode arrays in a kainate-mediated rat model (n=6). Two 64-channel microelectrode arrays were implanted near the hippocampus, and the signals were spatially averaged to emulate virtual ring electrodes for comparison. Device locations were reconstructed and placed in copies of the Waxholm Space Rat Brain Atlas registered to subject-specific MRI scans. In subjects exhibiting seizures (n=4), automated line length detection showed that microelectrode signals identified epileptiform activity sooner and with greater specificity than ring electrodes. In subjects that only seized post-kainate injection (n=3), manual review by a board-certified epileptologist confirmed that microelectrodes provided the earliest onset detection times. Furthermore, the microelectrode arrays high resolution revealed distinct instances of hyperactivity occurring at similar depths but from different directions -- a feature indistinguishable to standard ring electrodes. These results demonstrate that microelectrodes on a large insulating body significantly enhance signal quality and spatial localization. This technology offers a potential advancement over current clinical standards for identifying seizure foci during surgical planning. SIGNIFICANCESurgical treatment for drug-resistant epilepsy depends on accurately identifying the brain regions where seizures begin. Current stereo-EEG electrodes sample activity with ring contacts that average signals around the probe shaft, potentially obscuring directional differences in nearby neural activity. This study shows that microelectrodes distributed around an sEEG-sized insulating body can improve seizure-related signal detection and spatial localization compared with ring-like recordings from the same implant locations. By resolving activity that conventional ring electrodes cannot distinguish, high-density directional sEEG may provide more informative recordings for seizure mapping. These findings support the development of next-generation intracranial electrodes for improving epilepsy surgical planning.

neuroscience↗

sEEG-Suite: An Interactive Pipeline for Semi-Automated Contact Localization and Anatomical Labeling with Brainstorm

Stereoelectroencephalography (sEEG) is a critical tool for mapping epileptic networks in patients with drug-resistant epilepsy. Accurate localization and labeling of sEEG contacts are essential for identifying the seizure onset zone (SOZ) and ensuring optimal resective surgery. Traditional methods for localizing and labeling sEEG contacts rely on manual processing, which is prone to human error and variability. To address these challenges, we developed and integrated a semi-automatic sEEG contact localization and labeling pipeline within Brainstorm1, an open-source software platform for multimodal brain imaging analysis2-8, widely adopted in the neuroscience community with over 50,000 registered users and an active online user forum. The software has been supported by the National Institute of Health (NIH) for over two decades. The pipeline presented in this paper performs three key steps: (1) import and apply rigid co-registration of post-implantation Computed Tomography (CT) or post-CT with pre-implantation Magnetic Resonance Imaging (pre-MRI), (2) post-CT image segmentation and semi-automatic detection of sEEG contacts using GARDEL9, which has been integrated as a Brainstorm plugin, and (3) automatic anatomical labeling of contacts using standard and commonly used brain anatomy templates and atlases. Integrating this pipeline into Brainstorm brings the best of both worlds: GARDELs automation and Brainstorms multimodal data compatibility, and rich library of visualization and advanced analysis tools at both sensor and source level6. This sEEG-Suite tool facilitates reproducible research, supports clinical workflows, and accelerates sEEG-based investigations of invasive brain recordings.

neuroscience↗