Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays.
Spike Detection for Large Neural Populations Using High Density Multielectrode Arrays.
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DOI：
10.3389/fninf.2015.00028
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发表时间：
2015
影响因子：
3.5
通讯作者：
Hennig MH
中科院分区：
文献类型：
--
作者：
Muthmann JO;Amin H;Sernagor E;Maccione A;Panas D;Berdondini L;Bhalla US;Hennig MH
新一代的高密度微电极阵列（MEA）现在能够同时记录数千个神经元的尖峰活动。由于大量的原始数据和具有紧密间隔的电极的尖峰的密集采样，在这样的记录中可靠的尖峰检测和分析是具有挑战性的。在这里，我们提出了一个高效的，在线的尖峰检测算法，和离线的方法，提高了检测率，这使得空间事件的位置估计在一个分辨率高于由阵列提供的结合来自多个电极的信息。使用4096通道MEA从神经元培养物和新生儿视网膜获得的数据以及合成数据来测试和验证这些方法。我们证明，这些算法优于传统的方法，由于更好的噪声估计和改善的信噪比（SNR），通过结合来自多个电极的信息。最后，我们提出了一种新的方法来分析人口活动的时空事件配置文件的特征的基础上，它不需要隔离的单个单元。总的来说，我们展示了如何提高高密度，大规模MEA提供的空间分辨率可以可靠地利用大型神经群体和大脑回路的活动特征。
An emerging generation of high-density microelectrode arrays (MEAs) is now capable of recording spiking activity simultaneously from thousands of neurons with closely spaced electrodes. Reliable spike detection and analysis in such recordings is challenging due to the large amount of raw data and the dense sampling of spikes with closely spaced electrodes. Here, we present a highly efficient, online capable spike detection algorithm, and an offline method with improved detection rates, which enables estimation of spatial event locations at a resolution higher than that provided by the array by combining information from multiple electrodes. Data acquired with a 4096 channel MEA from neuronal cultures and the neonatal retina, as well as synthetic data, was used to test and validate these methods. We demonstrate that these algorithms outperform conventional methods due to a better noise estimate and an improved signal-to-noise ratio (SNR) through combining information from multiple electrodes. Finally, we present a new approach for analyzing population activity based on the characterization of the spatio-temporal event profile, which does not require the isolation of single units. Overall, we show how the improved spatial resolution provided by high density, large scale MEAs can be reliably exploited to characterize activity from large neural populations and brain circuits.