Amygdala Stimulation Leads to Functional Network Connectivity State Transitions in the Hippocampus.
Amygdala Stimulation Leads to Functional Network Connectivity State Transitions in the Hippocampus.
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DOI：
10.1109/embc44109.2020.9176742
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发表时间：
2020-07
期刊：
影响因子：
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通讯作者：
Mahmoudi B
中科院分区：
文献类型：
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作者：
Sendi MSE;Kanta V;Inman CS;Manns JR;Hamann S;Gross RE;Willie JT;Mahmoudi B
几项研究表明，直接刺激大脑可以增强人类和动物的记忆。研究脑刺激引起的神经生理变化是理解记忆功能背后的神经过程的重要一步。此外，它为开发更有效的神经调节方法来增强记忆铺平了道路。在这项研究中，我们结合使用无监督和有监督的机器学习方法来研究杏仁核刺激如何在编码阶段调节海马网络活动。利用时间滑动窗口，我们基于海马体4个亚区局部场电位记录的协方差估计了刺激后和假试验期间的海马体动态功能网络连通性（dFNC）。结合5个被试的dFNC样本，采用k-means聚类方法提取不同的网络状态。接下来，我们使用状态间转换数作为潜在特征对所有受试者的杏仁核刺激和假试验进行分类。通过训练逻辑回归模型，我们可以在所有受试者中以67%的准确率区分刺激试验和假试验。利用弹性网正则化作为特征选择方法，我们确定了杏仁核刺激下海马网络状态转换的特定模式。这些结果为更好地理解海马网络动力学和增强记忆的杏仁核刺激之间的因果关系提供了新的途径。
Several studies have shown that direct brain stimulation can enhance memory in humans and animal models. Investigating the neurophysiological changes induced by brain stimulation is an important step towards understanding the neural processes underlying memory function. Furthermore, it paves the way for developing more efficient neuromodulation approaches for memory enhancement. In this study, we utilized a combination of unsupervised and supervised machine learning approaches to investigate how amygdala stimulation modulated hippocampal network activities during the encoding phase. Using a sliding window in time, we estimated the hippocampal dynamic functional network connectivity (dFNC) after stimulation and during sham trials, based on the covariance of local field potential recordings in 4 subregions of the hippocampus. We extracted different network states by combining the dFNC samples from 5 subjects and applying k-means clustering. Next, we used the between-state transition numbers as the latent features to classify between amygdala stimulation and sham trials across all subjects. By training a logistic regression model, we could differentiate stimulated from sham trials with 67% accuracy across all subjects. Using elastic net regularization as a feature selection method, we identified specific patterns of hippocampal network state transition in response to amygdala stimulation. These results offer a new approach to better understanding of the causal relationship between hippocampal network dynamics and memory-enhancing amygdala stimulation.