Muller Leah, Hamilton Liberty S, Edwards Erik, Bouchard Kristofer E, Chang Edward F
Department of Neurological Surgery and Department of Physiology, University of California, San Francisco, 675 Nelson Rising Lane, Room 511, San Francisco, CA 94158, USA. Joint Program in Bioengineering, UC Berkeley/UC San Francisco, USA. Medical Scientist Training Program, UC San Francisco, USA.
J Neural Eng. 2016 Oct;13(5):056013. doi: 10.1088/1741-2560/13/5/056013. Epub 2016 Aug 31.
Electrocorticography (ECoG) has become an important tool in human neuroscience and has tremendous potential for emerging applications in neural interface technology. Electrode array design parameters are outstanding issues for both research and clinical applications, and these parameters depend critically on the nature of the neural signals to be recorded. Here, we investigate the functional spatial resolution of neural signals recorded at the human cortical surface. We empirically derive spatial spread functions to quantify the shared neural activity for each frequency band of the electrocorticogram.
Five subjects with high-density (4 mm center-to-center spacing) ECoG grid implants participated in speech perception and production tasks while neural activity was recorded from the speech cortex, including superior temporal gyrus, precentral gyrus, and postcentral gyrus. The cortical surface field potential was decomposed into traditional EEG frequency bands. Signal similarity between electrode pairs for each frequency band was quantified using a Pearson correlation coefficient.
The correlation of neural activity between electrode pairs was inversely related to the distance between the electrodes; this relationship was used to quantify spatial falloff functions for cortical subdomains. As expected, lower frequencies remained correlated over larger distances than higher frequencies. However, both the envelope and phase of gamma and high gamma frequencies (30-150 Hz) are largely uncorrelated (<90%) at 4 mm, the smallest spacing of the high-density arrays. Thus, ECoG arrays smaller than 4 mm have significant promise for increasing signal resolution at high frequencies, whereas less additional gain is achieved for lower frequencies.
Our findings quantitatively demonstrate the dependence of ECoG spatial resolution on the neural frequency of interest. We demonstrate that this relationship is consistent across patients and across cortical areas during activity.
皮层脑电图(ECoG)已成为人类神经科学中的一项重要工具,在神经接口技术的新兴应用中具有巨大潜力。电极阵列设计参数是研究和临床应用中的突出问题,这些参数严重依赖于要记录的神经信号的性质。在此,我们研究在人类皮层表面记录的神经信号的功能空间分辨率。我们通过实验推导空间扩散函数,以量化皮层脑电图各频段的共享神经活动。
五名植入高密度(中心距4毫米)ECoG网格的受试者参与言语感知和产生任务,同时从包括颞上回、中央前回和中央后回在内的言语皮层记录神经活动。皮层表面场电位被分解为传统的脑电图频段。使用皮尔逊相关系数量化每个频段电极对之间的信号相似性。
电极对之间神经活动的相关性与电极之间的距离呈负相关;这种关系被用于量化皮层子区域的空间衰减函数。正如预期的那样,低频在比高频更大的距离上仍保持相关性。然而,在高密度阵列最小间距4毫米处,伽马和高伽马频率(30 - 150赫兹)的包络和相位在很大程度上不相关(<90%)。因此,小于4毫米的ECoG阵列在提高高频信号分辨率方面有很大前景,而在低频方面获得的额外增益较少。
我们的研究结果定量地证明了ECoG空间分辨率对感兴趣神经频率的依赖性。我们证明这种关系在患者之间以及活动期间的不同皮层区域是一致的。