Encoding Temporal Regularities and Information Copying in Hippocampal Circuits.
Encoding Temporal Regularities and Information Copying in Hippocampal Circuits.
复制标题
对海马回路中的时间规律和信息复制进行编码。
DOI：
10.1038/s41598-019-55395-1
复制
发表时间：
2019
影响因子：
4.6
通讯作者：
Roberts TP
中科院分区：
文献类型：
--
作者：
Roberts TP
识别、提取和编码时间序列是大脑中的关键要求，与感觉运动处理和学习有关。然而，负责的细胞机制仍然是个谜;例如，这种能力是否需要特定的，精心组织的神经网络，或者来自神经元更基本的固有特性。在这里，使用多电极阵列技术，并专注于间隔学习，我们证明了稀疏重构大鼠海马神经回路本质上能够编码和存储亚二阶时间间隔超过一个小时的时间尺度，在神经元群体之间的放电关系的时空结构的变化表示。这种学习伴随着互信息和传递熵的增加，这是与信息存储和流动相关的正式措施。此外，从先前训练的电路中导出的时间关系可以作为将间隔复制到未经训练的网络中的模板，这表明电路到电路信息传输的可能性。我们的研究结果表明，动态编码和稳定复制的时间关系是简单的vitronetworks的基本属性，理解信息处理，存储和复制的基本原则具有普遍意义。
Discriminating, extracting and encoding temporal regularities is a critical requirement in the brain, relevant to sensory-motor processing and learning. However, the cellular mechanisms responsible remain enigmatic; for example, whether such abilities require specific, elaborately organized neural networks or arise from more fundamental, inherent properties of neurons. Here, using multi-electrode array technology, and focusing on interval learning, we demonstrate that sparse reconstituted rat hippocampal neural circuits are intrinsically capable of encoding and storing sub-second-order time intervals for over an hour timescale, represented in changes in the spatial-temporal architecture of firing relationships among populations of neurons. This learning is accompanied by increases in mutual information and transfer entropy, formal measures related to information storage and flow. Moreover, temporal relationships derived from previously trained circuits can act as templates for copying intervals into untrained networks, suggesting the possibility of circuit-to-circuit information transfer. Our findings illustrate that dynamic encoding and stable copying of temporal relationships are fundamental properties of simplein vitronetworks, with general significance for understanding elemental principles of information processing, storage and replication.