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术中人体微电极记录的参数化:将动作电位形态与脑解剖结构相联系。

Parameterization of intraoperative human microelectrode recordings: Linking action potential morphology to brain anatomy.

作者信息

Baker Matthew R, Klassen Bryan T, Jensen Michael A, Valencia Gabriela Ojeda, Heydari Hossein, Ince Nuri F, Müller Klaus-Robert, Miller Kai J

机构信息

Department of Neurosurgery, Mayo Clinic, Rochester, MN, USA.

Department of Neurology, Mayo Clinic, Rochester, MN, USA.

出版信息

bioRxiv. 2025 Jan 22:2025.01.20.633934. doi: 10.1101/2025.01.20.633934.

Abstract

Deep brain stimulation (DBS) is a targeted manipulation of brain circuitry to treat neurological and neuropsychiatric conditions. Optimal DBS lead placement is essential for treatment efficacy. Current targeting practice is based on preoperative and intraoperative brain imaging, intraoperative electrophysiology, and stimulation mapping. Electrophysiological mapping using extracellular microelectrode recordings aids in identifying functional subdomains, anatomical boundaries, and disease-correlated physiology. The shape of single-unit action potentials may differ due to different biophysical properties between cell-types and brain regions. Here, we describe a technique to parameterize the structure and duration of sorted spike units using a novel algorithmic approach based on canonical response parameterization, and illustrate how it may be used on DBS microelectrode recordings. Isolated spike shapes are parameterized then compared using a spike similarity metric and grouped by hierarchical clustering. When spike morphology is associated with anatomy, we find regional clustering in the human globus pallidus. This method is widely applicable for spike removal and single-unit characterization and could be integrated into intraoperative array-based technologies to enhance targeting and clinical outcomes in DBS lead placement.

摘要

深部脑刺激(DBS)是一种针对脑回路的操作,用于治疗神经和神经精神疾病。最佳的DBS电极植入位置对于治疗效果至关重要。当前的靶向操作基于术前和术中脑成像、术中电生理学以及刺激图谱。使用细胞外微电极记录进行电生理图谱分析有助于识别功能亚域、解剖边界以及与疾病相关的生理学特征。由于细胞类型和脑区之间生物物理特性不同,单个单元动作电位的形状可能会有所差异。在此,我们描述一种使用基于典型反应参数化的新型算法方法对分类的尖峰单元的结构和持续时间进行参数化的技术,并说明如何将其用于DBS微电极记录。对分离的尖峰形状进行参数化,然后使用尖峰相似性度量进行比较,并通过层次聚类进行分组。当尖峰形态与解剖结构相关时,我们在人类苍白球中发现区域聚类。该方法广泛适用于尖峰去除和单个单元表征,并且可以集成到基于术中阵列的技术中,以提高DBS电极植入的靶向性和临床效果。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/778c/11785027/fd696227d475/nihpp-2025.01.20.633934v1-f0001.jpg

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