Attention: Noisy Networks Are Tuned Out by the Claustrum

Jesse Jackson

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Attention: Noisy Networks Are Tuned Out by the Claustrum

机译：注意：窃听网络由克劳斯特调整出来

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The claustrum is one of the most well connected regions of the brain, yet its function has remained a mystery. A new study involving selective suppression of the activity of claustrum neurons has provided insight into the role of the claustrum in mediating attention.

机译：克劳斯是大脑最良好的连接区域之一，但其功能仍然是一个谜。涉及选择性抑制Claustrum神经元的活动的新研究已经为猫堡在介导注意中的作用提供了深入。

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《Current Biology: CB》 |2018年第17期|共3页
作者
Jesse Jackson;
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作者单位

Department of Physiology and Neuroscience Mental Health Institute University of Alberta;

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中图分类生物科学;
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1. Attention: Noisy Networks Are Tuned Out by the Claustrum [J] . Jesse Jackson Current Biology: CB . 2018,第17期

机译：注意：窃听网络由克劳斯特调整出来
2. A pilot study of the role of the claustrum in attention and seizures in rats [J] . Bayat Arezou, Joshi Sweta, Jahan Sahar, Epilepsy research . 2018,第期

机译：试验研究职务在大鼠注意力和癫痫发作中的作用
3. Attention: the claustrum [J] . Goll Yael, Atlan Gal, Citri Ami Trends in Neurosciences . 2015,第8期

机译：注意：外壳
4. Spatial and Channel Attention Based Convolutional Neural Networks for Modeling Noisy Speech [C] . Sirui Xu, Eric Fosler-Lussier IEEE International Conference on Acoustics, Speech and Signal Processing . 2019

机译：基于空间和通道注意的卷积神经网络用于建模嘈杂语音
5. Detection of Small Synaptic Signals in Noisy Electrophysiological Data by Means of Artificial Neural Networks [D] . Marino, Marc Joseph. 2020

机译：通过人工神经网络检测噪声电生理数据中的小突触信号
6. Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data [O] . Markus Helmer, Vladislav Kozyrev, Valeska Stephan, 2011

机译：基于稀疏和噪声数据的调谐曲线及其注意调制的无模型估计
7. Model-Free Estimation of Tuning Curves and Their Attentional Modulation, Based on Sparse and Noisy Data [O] . Helmer, Markus, Kozyrev, Vladislav, Stephan, Valeska, 2016

机译：基于稀疏和噪声数据的调谐曲线及其注意调制的无模型估计

Attention: Noisy Networks Are Tuned Out by the Claustrum

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