Anatomo-functional approach to multimodal motor mapping in diffuse glioma surgery: hierarchical networks.

IF 2.7 3区 医学 Q1 ANATOMY & MORPHOLOGY
José Pedro Lavrador, Víctor García-Milán, Francesco Marchi, Kapil Rajwani, Nida Kalyal, Andrea Perera, Sankhya Prakashvel, Yasir A Chowdhury, Ali Elhag, Laura Ferrari, Alba Diaz-Baamonde, Richard Gullan, Keyoumars Ashkan, Ranjeev Bhangoo, Ana Mirallave Pescador, Francesco Vergani
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引用次数: 0

Abstract

Onco-functional balance during motor-eloquent diffuse glioma resection is challenging. This balance is personal according to individual background, treatment expectations and surgical experience. Nevertheless, preservation of muscle contraction in isolation is no longer an accepted outcome. Motor planning and accurate purposeful execution are essential for useful motor function after surgery. Multiple brain networks work together to achieve this result: local networks focused on motor output, modular networks dedicated to sensorimotor integration and integrative networks responsible for the incorporation of motor function within the overall brain cognition. Intraoperatively, local networks are better probed by asleep techniques whereas integrative networks can only be assessed with awake techniques (modular networks is a crossroad for both techniques). Here, we propose a schematic hierarchical model to address these networks according to an orthogonal plane organization. Local networks are always pivotal given the common final output of motor function. Modular sensorimotor networks achieve their higher specialization within the central lobe given the subcortical connection via specialized U-fiber system underneath central sulcus. Integrative networks are fundamental anterior and posterior to the central lobe within the corona radiata and capsules where the main association fibers that subserve the large brain networks and cognitive hubs are located.

弥漫性胶质瘤手术中多模态运动定位的解剖功能方法:分层网络。
在弥漫性神经胶质瘤切除术中,单功能平衡是一个挑战。这种平衡是根据个人背景、治疗期望和手术经验而定的。然而,孤立地保持肌肉收缩不再是一种可接受的结果。运动计划和精确的目标执行对于术后有用的运动功能至关重要。多个大脑网络协同工作以实现这一结果:局部网络专注于运动输出,模块化网络致力于感觉运动整合,整合网络负责将运动功能整合到整体大脑认知中。术中,局部网络可以通过睡眠技术更好地探测,而综合网络只能通过清醒技术进行评估(模块化网络是两种技术的交叉路口)。在这里,我们提出了一个示意图层次模型来解决这些网络根据一个正交平面组织。考虑到运动功能的共同最终输出,局部网络总是至关重要的。模块化感觉运动网络通过中央沟下的特殊u -纤维系统在皮层下连接,从而在中央叶内实现更高的专门化。综合神经网络是辐射冠和脑囊内中央叶前后的基础神经网络,其中主要的关联纤维为大的大脑网络和认知中枢提供服务。
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来源期刊
Brain Structure & Function
Brain Structure & Function 医学-解剖学与形态学
CiteScore
6.00
自引率
6.50%
发文量
168
审稿时长
8 months
期刊介绍: Brain Structure & Function publishes research that provides insight into brain structure−function relationships. Studies published here integrate data spanning from molecular, cellular, developmental, and systems architecture to the neuroanatomy of behavior and cognitive functions. Manuscripts with focus on the spinal cord or the peripheral nervous system are not accepted for publication. Manuscripts with focus on diseases, animal models of diseases, or disease-related mechanisms are only considered for publication, if the findings provide novel insight into the organization and mechanisms of normal brain structure and function.
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