Using 6-minute free-running intracranial-electroencephalogram (icEEG) during sleep, an optimized multilayer perceptron (MLP) neural network accurately maps the sensorimotor cortex (SM) and identifies the anterior lip of the central sulcus (CS) in intractable epilepsy patients. We calculated 6 performance metrics to evaluate the MLP's efficacy: accuracy, area under the curve (AUC), recall, precision, F1-scores, and specificity. Each layer had 4 neurons with hyperbolic TanH activation function and 4 with Gaussian distribution function. Conventional 10-fold cross-validation was used. Feature extension (ε) and weighted imbalanced data (w) improved MLP performance. ANN NEUROL 2024;96:187–193

中文翻译：

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基于几分钟颅内脑电图数据的优化多层感知器，用于感觉运动功能映射


利用睡眠期间 6 分钟自由运行的颅内脑电图 (icEEG)，优化的多层感知器 (MLP) 神经网络可以准确地绘制顽固性癫痫患者的感觉运动皮层 (SM) 并识别中央沟 (CS) 的前唇。我们计算了 6 个性能指标来评估 MLP 的功效：准确性、曲线下面积 (AUC)、召回率、精度、F1 分数和特异性。每层有 4 个具有双曲 TanH 激活函数的神经元和 4 个具有高斯分布函数的神经元。使用传统的10倍交叉验证。特征扩展 (ε) 和加权不平衡数据 (w) 提高了 MLP 性能。安神经学 2024 年；96：187–193