通孔的大小影响微ecog阵列中神经信号的振幅和选择性。

Manan Sethia, Mesut Sahin
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摘要

背景:皮质电图(ECoG)阵列通常用于记录动物和人类受试者的大脑活动。关于阵列几何形状,特别是基板上的通孔如何影响记录的信号,文献中缺乏指导方针。建立有限元模型,模拟位于大鼠大脑皮层不同深度的神经元产生的电场,并在大鼠大脑皮层表面放置微ECoG阵列(μECoG)记录神经信号。所选阵列设计为典型的8 × 8圆形(直径100 μm)触点阵列,间距500 μm。通过改变记录触点之间的通孔大小来观察效果。结果:结果表明,如果基底小于灰质中神经元深度的约4倍,则记录的信号幅度减小。信号幅值分布在通孔周围呈下降趋势,接触部位的幅值也低于无孔设计;这种效应随着孔的大小而增加。另一个值得注意的结果是,通过孔尺寸的选择可以提高或降低多接触记录的空间选择性,其效果取决于选择性记录的目标神经元对与其深度之间的距离。结论:孔尺寸对记录的神经信号幅值有明显影响,可以作为降低通道间相关性的参数,从而最大限度地提高μECoG阵列神经信号的信息量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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The size of via holes influence the amplitude and selectivity of neural signals in Micro-ECoG arrays.

Background: Electrocorticography (ECoG) arrays are commonly used to record the brain activity both in animal and human subjects. There is a lack of guidelines in the literature as to how the array geometry, particularly the via holes in the substrate, affects the recorded signals. A finite element (FE) model was developed to simulate the electric field generated by neurons located at different depths in the rat brain cortex and a micro ECoG array (μECoG) was placed on the pia surface for recording the neural signal. The array design chosen was a typical array of 8 × 8 circular (100 μm in diam.) contacts with 500 μm pitch. The size of the via holes between the recording contacts was varied to see the effect.

Results: The results showed that recorded signal amplitudes were reduced if the substrate was smaller than about four times the depth of the neuron in the gray matter. The signal amplitude profiles had dips around the via holes and the amplitudes were also lower at the contact sites as compared to the design without the holes; an effect that increased with the hole size. Another noteworthy result is that the spatial selectivity of the multi-contact recordings could be improved or reduced by the selection of the via hole sizes, and the effect depended on the distance between the neuron pair targeted for selective recording and its depth.

Conclusions: The results suggest that the via-hole size clearly affects the recorded neural signal amplitudes and it can be leveraged as a parameter to reduce the inter-channel correlation and thus maximize the information content of neural signals with μECoG arrays.

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