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Non-invasive estimation of local field potentials for neuroprosthesis control

机译：用于神经假体控制的无创估计局部场电位

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摘要

Recent experiments have shown the possibility of using the brain electrical activity to directly control the movement of robots or prosthetic devices in real time. Such neuroprostheses can be invasive or non-invasive, depending on how the brain signals are recorded. In principle, invasive approaches will provide a more natural and flexible control of neuroprostheses, but their use in humans is debatable given the inherent medical risks. Non-invasive approaches mainly use scalp electroencephalogram (EEG) signals and their main disadvantage is that these signals represent the noisy spatiotemporal overlapping of activity arising from very diverse brain regions, i.e., a single scalp electrode picks up and mixes the temporal activity of myriads of neurons at very different brain areas. In order to combine the benefits of both approaches, we propose to rely on the non-invasive estimation of local field potentials (LFP) in the whole human brain from the scalp measured EEG data using a recently developed inverse solution (ELECTRA) to the EEG inverse problem. The goal of a linear inverse procedure is to de-convolve or un-mix the scalp signals attributing to each brain area its own temporal activity. To illustrate the advantage of this approach we compare, using an identical set of spectral features, classification of rapid voluntary finger self-tapping with left and right hands based on scalp EEG and non-invasively estimated LFP on two subjects using a different number of electrodes.
机译：最近的实验表明，可以利用大脑的电活动直接实时控制机器人或假肢设备的运动。取决于神经信号的记录方式，这种神经假体可以是侵入性的或非侵入性的。原则上，侵入性方法将提供对神经假体的更自然和灵活的控制，但是鉴于固有的医疗风险，将其用于人体尚值得商bat。非侵入性方法主要使用头皮脑电图（EEG）信号，它们的主要缺点是这些信号代表了由非常多样的大脑区域引起的活动的嘈杂的时空重叠，即单个头皮电极拾取并混合了无数头皮的时间活动。不同大脑区域的神经元。为了结合这两种方法的优点，我们建议使用从头皮测量的脑电图数据，使用最近开发的脑电图逆解决方案（ELECTRA），以无创方式估计整个人脑中的局部场电势（LFP）反问题。线性逆过程的目标是使归因于每个大脑区域的自身时间活动的头皮信号去卷积或解混合。为了说明此方法的优势，我们使用一组相同的光谱特征进行比较，基于头皮脑电图和无创估计LFP对使用不同数量电极的两个受试者的左右手快速自愿手指自攻进行分类。

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