From synapse to network: models of information storage and retrieval in neural circuits.

From synapse to network: models of information storage and retrieval in neural circuits.
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DOI:
10.1016/j.conb.2021.05.005
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发表时间:
2021-10
影响因子:
5.7
通讯作者:
Brunel N
Brunel N
中科院分区:
医学2区
文献类型:
--
作者:
Aljadeff J;Gillett M;Pereira Obilinovic U;Brunel N

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大脑回路中信息存储和检索的机制仍然是争论的主题。人们普遍认为,信息的存储至少部分是通过编码信息的网络中突触连通性的变化,这些变化反过来导致网络动力学的修改,这样存储的信息可以在以后的时间被检索。在此,我们回顾了从实验数据中推导突触可塑性规则的最新进展,以及可塑性规则如何影响循环网络的动态。我们表明,这种网络产生的动态表现出很大程度的多样性,取决于参数,类似于延迟响应任务期间体内的实验观察。
The mechanisms of information storage and retrieval in brain circuits are still the subject of debate. It is widely believed that information is stored at least in part through changes in synaptic connectivity in networks that encode this information, and that these changes lead in turn to modifications of network dynamics, such that the stored information can be retrieved at a later time. Here, we review recent progress in deriving synaptic plasticity rules from experimental data, and in understanding how plasticity rules affect the dynamics of recurrent networks. We show that the dynamics generated by such networks exhibit a large degree of diversity, depending on parameters, similar to experimental observations in vivo during delayed response tasks.
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