Orientation selectivity, as an emergent property of neurons in the visual cortex, is of critical importance in the processing of visual information. Characterizing the orientation selectivity based on neuronal firing activities or local field potentials (LFPs) is a hot topic of current research. In this paper, we used cross-frequency coupling and least absolute shrinkage and selection operator (LASSO) to predict the grating orientations in V1 and V4 of two rhesus monkeys. The experimental data were recorded by utilizing two chronically implanted multi-electrode arrays, which were placed, respectively, in V1 and V4 of two rhesus monkeys performing a selective visual attention task. The phase–amplitude coupling (PAC) and amplitude–amplitude coupling (AAC) were employed to characterize the cross-frequency coupling of LFPs under sinusoidal grating stimuli with different orientations. Then, a LASSO logistic regression model was constructed to predict the grating orientation based on the strength of PAC and AAC. Moreover, the cross-validation method was used to evaluate the performance of the model. It was found that the average accuracy of the prediction based on the combination of PAC and AAC was 73.9%, which was higher than the predicting accuracy with PAC or AAC separately. In conclusion, a LASSO logistic regression model was introduced in this study, which can predict the grating orientations with relatively high accuracy by using PAC and AAC together. Our results suggest that the principle behind the LASSO model is probably an alternative direction to explore the mechanism for generating orientation selectivity.

中文翻译：

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在恒河猴的 V1 和 V4 中使用交叉频率耦合和最小绝对收缩和选择算子预测光栅方向

方向选择性作为视觉皮层神经元的一种突现特性，在视觉信息的处理中至关重要。基于神经元放电活动或局部场电位 (LFP) 表征方向选择性是当前研究的热门话题。在本文中，我们使用交叉频率耦合和最小绝对收缩和选择算子（LASSO）来预测两只恒河猴的 V1 和 V4 中的光栅方向。通过使用两个长期植入的多电极阵列记录实验数据，这些阵列分别放置在执行选择性视觉注意任务的两只恒河猴的 V1 和 V4 中。相位-幅度耦合（PAC）和幅度-幅度耦合（AAC）被用来表征LFP在不同方向的正弦光栅刺激下的交叉频率耦合。然后，构建LASSO逻辑回归模型以基于PAC和AAC的强度预测光栅方向。此外，使用交叉验证方法来评估模型的性能。发现PAC和AAC结合的预测平均准确率为73.9%，高于PAC和AAC单独预测的准确率。总之，本研究引入了LASSO逻辑回归模型，该模型可以通过PAC和AAC的结合来以较高的精度预测光栅方向。