Collaborative robot (cobot) controlled system for transcranial magnetic stimulation

经颅磁刺激(TMS)是一种使用强磁刺激进行无创神经调节的方法 电流传递到放置在头皮旁边的线圈，在大脑中感应电场和电流。事实是 由时变磁场感应的电场使刺激能够穿透颅骨 高效、安全、无痛。因此，TMS在基础科学研究中变得非常受欢迎 并用于诊断和治疗应用，如治疗抗药性抑郁症。这是众所周知的 TMS诱导的大脑激活的影响从主要靶区传播到次要靶区 在解剖上与之相连的区域，产生网络级别的反应。这一观察结果已经 对于理解刺激效果的重要后果。首先，主要目标位置必须 根据个体解剖结构进行定义，并保持一致的刺激位置。第二, 需要神经成像方法来记录大脑网络对刺激的反应。 TMS神经导航系统在科学界迅速流行起来，因为 基于特定受试者磁共振的精确无框架立体定向系统的研制 成像(MRI)数据以定义刺激目标。虽然有可能获得准确的手动线圈定位 在核磁共振引导的神经导航下，对于更复杂的实验，这可能会导致严重的操作员疲劳 由于长时间将笨重的TMS线圈保持在固定位置导致不想要的 刺激的空间目标的可变性。可以使用机械线圈夹持器来缓解 操作者疲劳，但受试者头部的任何移动都需要耗时地重新定位 托架装置。机器人定位TMS线圈可以说是最准确和最有效的方法 解决这些问题，但仪器相当昂贵，并且系统的移动性/便携性有限 因为它的体积很大。近年来，协作式机器人(Cobot)技术被引入，以降低成本和 提高TMS线圈自动定位的机动性。该系统也可以手动和之后进行试验 由操作员将TMS线圈初始引导至所需目标，TMS合作机器人将保持 线圈定位一致，精度高，磁头自动检测/校正 动议。在这项提案中，目标是获得一种用于神经导航TMS的仪器系统，该系统由 协作机器人。由于其可运输的特性，该系统可以与神经成像一起使用 方法如功能磁共振成像(FMRI)、脑电(EEG)、脑磁图(MEG)、 和正电子发射断层扫描(PET)。经颅磁共振仪与神经影像的联合观察能力 并量化神经调节效应，使潜在新疗法的平行翻译研究成为可能 TMS的应用和对基本激活机制的更详细的研究。这台仪器 该系统将成为当地一大批用户的独特资源。

Transcranial Magnetic Stimulation (TMS) is a method for non-invasive neuromodulation that uses strong currents passed to a coil placed next to the scalp to induce electric fields and currents in the brain. The fact that the electric field is induced by a time-varying magnetic field enables the stimulation to penetrate the skull efficiently, safely, and painlessly. Therefore, TMS has become highly popular for both basic scientific research and for diagnostic and therapeutic applications such as treatment of drug-resistant depression. It is well known that the effects of the TMS-induced brain activations propagate from the primary target area to the secondary areas that are anatomically connected to it, generating a network-level response. This observation has important consequences for understanding the effects of the stimulation. First, the primary target location must be defined with respect to individual anatomy and the stimulation location maintained consistently. Second, neuroimaging methods are needed to record how the brain networks respond to the stimulation. TMS neuronavigation systems have rapidly gained popularity in the scientific community due to the development of the accurate frameless stereotactic systems utilizing subject-specific Magnetic Resonance Imaging (MRI) data to define stimulation targets. While it is possible to obtain accurate manual coil positioning under MRI guided neuronavigation, for more complex experiments this may cause significant operator fatigue due to holding the bulky TMS coil in a fixed position for extended periods of time resulting in unwanted variability in the spatial targeting of the stimulation. Mechanical coil holders can be employed to mitigate the operator fatigue, but any movement of the subject’s head will require a time-consuming repositioning of the holder device. Robotic positioning of the TMS coil is arguably the most accurate and efficient method for resolving these issues, but the instrumentation is rather costly, and the system has limited mobility/portability due to its large size. Recently, collaborative robot (cobot) technology was introduced to lower the cost and increase the mobility of automatic TMS coil positioning. The system can be piloted also manually and after initial guidance of the TMS coil to the desired target by a human operator, the TMS cobot will maintain consistent positioning of the coil with a high degree of accuracy and automatic detection/correction for head motion. In this proposal, the goal is to acquire an instrument system for neuronavigated TMS controlled with a collaborative robot. Due to its transportable nature, the system can be used in conjunction with neuroimaging methods such as functional MRI (fMRI), electroencephalography (EEG), magnetoencephalography (MEG), and Positron Emission Tomography (PET). The capability of and combining TMS with neuroimaging to observe and quantify the neuromodulation effects enable parallel translational studies on potential new therapeutic TMS applications and more detailed investigations of the fundamental activation mechanisms. The instrument system will be a unique resource for a large group of users in the local area.