Grave de Peralta Rolando, Landis Theodor, Gonzalez Andino Sara
Electrical Neuroimaging Group, Geneva, Switzerland; Geneva University Hospital and Geneva University, Geneva, Switzerland.
J Physiol Paris. 2009 Nov;103(6):324-32. doi: 10.1016/j.jphysparis.2009.07.004. Epub 2009 Jul 22.
Thought-controlled neuroprostheses could allow paralyzed patients to interact with the external world using brain waves. Thus far, the fastest and more accurate control of neuroprostheses is achieved through direct recordings of neural activity [Nicolelis, M.A., 2001. Actions from thoughts. Nature 409, 403-407; Donoghue, J.P., 2002. Connecting cortex to machines: recent advances in brain interfaces. Nat. Neurosci. 5 (Suppl.), 1085-1088]. However, invasive recordings have inherent medical risks. Here we discuss some approaches that could enhance the speed and accuracy of non-invasive devices, namely, (1) enlarging the spectral analysis to include higher frequency oscillations, able to transmit substantial information over short analysis windows; (2) using spectral analysis procedures that minimize the variance of the estimates; and (3) transforming EEG recorded activity into local field potential estimates (eLFP). Theoretical and experimental arguments are used to explain why it is erroneous to think that scalp EEG cannot sense high frequency oscillations and how this might hinders further developments. We further illustrate how non-invasive eLFPs derived from the scalp-recorded electroencephalogram (EEG) can be combined with robust, broad band spectral analysis to accurately detect (off-line) the laterality of upcoming hand movements. Interestingly, the use of pattern recognition to select the brain voxels differentially engaged by the explored tasks leads to sound neural activation images. Consequently, our results indicate that both research lines, i.e., neuroprosthetics and electrical neuroimaging, might effectively benefit from their mutual interaction.
思维控制的神经假体可以使瘫痪患者利用脑电波与外部世界进行互动。到目前为止，通过直接记录神经活动能够实现对神经假体最快且最精确的控制[尼科莱利斯，M.A.，2001年。《思想产生行动》。《自然》409卷，第403 - 407页；多诺霍，J.P.，2002年。《连接皮层与机器：脑机接口的最新进展》。《自然神经科学》5（增刊），第1085 - 1088页]。然而，侵入性记录存在固有的医疗风险。在此，我们讨论一些能够提高非侵入性设备速度和准确性的方法，即：（1）扩大频谱分析范围，纳入更高频率的振荡，这类振荡能够在短分析窗口内传输大量信息；（2）使用能使估计方差最小化的频谱分析程序；（3）将脑电图记录的活动转换为局部场电位估计值（eLFP）。我们运用理论和实验论据来解释为何认为头皮脑电图无法感知高频振荡是错误的，以及这可能如何阻碍进一步发展。我们还进一步说明了如何将从头皮记录的脑电图（EEG）得出的非侵入性eLFP与稳健的宽带频谱分析相结合，以准确（离线）检测即将到来的手部动作的偏侧性。有趣的是，使用模式识别来选择在探索任务中差异参与的脑体素会产生合理的神经激活图像。因此，我们的结果表明，神经假体和电神经成像这两条研究路线可能会从它们的相互作用中有效受益。
