An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.

An electronic neuromorphic system for real-time detection of high frequency oscillations (HFO) in intracranial EEG.
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用于实时检测高频振荡(HFO)的电子神经形态系统。

DOI:
10.1038/s41467-021-23342-2
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发表时间:
2021-05-25
影响因子:
16.6
通讯作者:
Indiveri G
Indiveri G
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Sharifshazileh M;Burelo K;Sarnthein J;Indiveri G

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用于临床研究和治疗应用的生物医学信号分析可以受益于可以本地和实时处理这些信号的嵌入式设备。一个例子是分析来自癫痫患者的颅内EEG(iEEG)以检测高频振荡(HFO),高频振荡是致癫痫脑组织的生物标志物。混合信号神经形态电路提供了构建紧凑且低功耗的神经网络处理系统的可能性,该系统可以实时在线分析数据。在这里,我们提出了一种神经形态系统,该系统将神经记录头台与尖峰神经网络(SNN)处理核心结合在同一个芯片上,用于处理iEEG,并展示了它如何可靠地检测HFO,从而实现最先进的准确性,灵敏度和特异性。这是第一个可行性研究,以确定相关功能的iEEG在实时使用混合信号神经形态计算技术。各个领域的一个主要挑战是如何在没有大量计算资源的情况下处理传感器产生的大量数据。在这里,作者提出了一种神经形态芯片,它可以检测患者颅内记录的致癫痫组织的相关特征。
The analysis of biomedical signals for clinical studies and therapeutic applications can benefit from embedded devices that can process these signals locally and in real-time. An example is the analysis of intracranial EEG (iEEG) from epilepsy patients for the detection of High Frequency Oscillations (HFO), which are a biomarker for epileptogenic brain tissue. Mixed-signal neuromorphic circuits offer the possibility of building compact and low-power neural network processing systems that can analyze data on-line in real-time. Here we present a neuromorphic system that combines a neural recording headstage with a spiking neural network (SNN) processing core on the same die for processing iEEG, and show how it can reliably detect HFO, thereby achieving state-of-the-art accuracy, sensitivity, and specificity. This is a first feasibility study towards identifying relevant features in iEEG in real-time using mixed-signal neuromorphic computing technologies. A major challenge across a variety of fields is how to process the vast quantities of data produced by sensors without large computation resources. Here, the authors present a neuromorphic chip which can detect a relevant signature of epileptogenic tissue from intracranial recordings in patients.
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