Scherer Reinhold, Zanos Stavros P, Miller Kai J, Rao Rajesh P N, Ojemann Jeffrey G
Department of Computer Science and Engineering, University of Washington, Seattle, Washington 98105, USA.
Neurosurg Focus. 2009 Jul;27(1):E12. doi: 10.3171/2009.4.FOCUS0981.
Electrocorticography (ECoG) offers a powerful and versatile platform for developing brain-computer interfaces; it avoids the risks of brain-invasive methods such as intracortical implants while providing significantly higher signal-to-noise ratio than noninvasive techniques such as electroencephalography. The authors demonstrate that both contra- and ipsilateral finger movements can be discriminated from ECoG signals recorded from a single brain hemisphere. The ECoG activation patterns over sensorimotor areas for contra- and ipsilateral movements were found to overlap to a large degree in the recorded hemisphere. Ipsilateral movements, however, produced less pronounced activity compared with contralateral movements. The authors also found that single-trial classification of movements could be improved by selecting patient-specific frequency components in high-frequency bands (> 50 Hz). Their discovery that ipsilateral hand movements can be discriminated from ECoG signals from a single hemisphere has important implications for neurorehabilitation, suggesting in particular the possibility of regaining ipsilateral movement control using signals from an intact hemisphere after damage to the other hemisphere.
皮层脑电图(ECoG)为开发脑机接口提供了一个强大且通用的平台;它避免了诸如皮层内植入等脑侵入性方法的风险,同时提供了比脑电图等非侵入性技术显著更高的信噪比。作者证明,从单个脑半球记录的ECoG信号可以区分对侧和同侧手指运动。在记录的半球中,发现对侧和同侧运动的感觉运动区域上的ECoG激活模式在很大程度上重叠。然而,与对侧运动相比,同侧运动产生的活动不太明显。作者还发现,通过选择高频带(>50Hz)中患者特定的频率成分,可以改善运动的单次试验分类。他们发现同侧手部运动可以从单个半球的ECoG信号中区分出来,这对神经康复具有重要意义,特别表明在一个半球受损后,利用来自完整半球的信号恢复同侧运动控制的可能性。