* Division of Digital Signal Processing, IDeTIC, University of Las Palmas de Gran Canaria, Las Palmas 35017, Spain.
† College of Medicine, Swansea University, Swansea, SA2 8PP, Wales, UK.
Int J Neural Syst. 2018 Feb;28(1):1750035. doi: 10.1142/S0129065717500356. Epub 2017 Jul 3.
Genetic and neurophysiological studies of electroencephalogram (EEG) have shown that an individual's brain activity during a given cognitive task is, to some extent, determined by their genes. In fact, the field of biometrics has successfully used this property to build systems capable of identifying users from their neural activity. These studies have always been carried out in isolated conditions, such as relaxing with eyes closed, identifying visual targets or solving mathematical operations. Here we show for the first time that the neural signature extracted from the spectral shape of the EEG is to a large extent independent of the recorded cognitive task and experimental condition. In addition, we propose to use this task-independent neural signature for more precise biometric identity verification. We present two systems: one based on real cepstrums and one based on linear predictive coefficients. We obtained verification accuracies above 89% on 4 of the 6 databases used. We anticipate this finding will create a new set of experimental possibilities within many brain research fields, such as the study of neuroplasticity, neurodegenerative diseases and brain machine interfaces, as well as the mentioned genetic, neurophysiological and biometric studies. Furthermore, the proposed biometric approach represents an important advance towards real world deployments of this new technology.
脑电图（EEG）的遗传和神经生理学研究表明，个体在给定认知任务期间的大脑活动在某种程度上取决于他们的基因。事实上，生物识别领域已经成功地利用这一特性构建了能够从神经活动中识别用户的系统。这些研究一直是在隔离的条件下进行的，例如闭眼放松、识别视觉目标或解决数学运算。在这里，我们首次表明，从 EEG 频谱形状中提取的神经特征在很大程度上独立于记录的认知任务和实验条件。此外，我们建议使用这种与任务无关的神经特征进行更精确的生物识别身份验证。我们提出了两个系统：一个基于真实倒谱，另一个基于线性预测系数。我们在使用的 6 个数据库中的 4 个上获得了超过 89%的验证精度。我们预计这一发现将在许多脑研究领域内创造一系列新的实验可能性，例如神经可塑性、神经退行性疾病和脑机接口的研究，以及上述遗传、神经生理学和生物识别研究。此外，所提出的生物识别方法代表了向这项新技术的实际部署迈出的重要一步。
