A multilevel account of hippocampal function in spatial and concept learning: Bridging models of behavior and neural assemblies.

A multilevel account of hippocampal function in spatial and concept learning: Bridging models of behavior and neural assemblies.
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DOI:
10.1126/sciadv.ade6903
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发表时间:
2023-07-21
期刊:
影响因子:
13.6
通讯作者:
Love BC
Love BC
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Mok RM;Love BC

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一个完整的神经科学需要多层次的理论来解决从更高层次的认知行为到细胞内活动的现象。我们提出了一种扩展机制的方法,其中认知的计算模型位于行为和大脑之间:它解释了更高级别的行为,并可以分解为更低级别的组件机制,以提供比单独的任何级别更丰富的系统理解。为此,我们将认知模型分解为神经元样单位,使用神经群集方法,平行于海马活动。神经群集协调单元,共同形成更高层次的心理结构。分解的模型提出了大脑规模的神经种群如何协调以形成编码概念和空间表征的组件,以及为什么需要这么多的神经元来实现认知水平的鲁棒性能。这种多层次的解释提供了一种方法来理解认知和符号样表征是如何由通过学习形成的协调神经群体(组装)支持的。神经群集规则捕捉到海马体中的单元如何协调以支持学习。
A complete neuroscience requires multilevel theories that address phenomena ranging from higher-level cognitive behaviors to activities within a cell. We propose an extension to the level of mechanism approach where a computational model of cognition sits in between behavior and brain: It explains the higher-level behavior and can be decomposed into lower-level component mechanisms to provide a richer understanding of the system than any level alone. Toward this end, we decomposed a cognitive model into neuron-like units using a neural flocking approach that parallels recurrent hippocampal activity. Neural flocking coordinates units that collectively form higher-level mental constructs. The decomposed model suggested how brain-scale neural populations coordinate to form assemblies encoding concept and spatial representations and why so many neurons are needed for robust performance at the cognitive level. This multilevel explanation provides a way to understand how cognition and symbol-like representations are supported by coordinated neural populations (assemblies) formed through learning. A neural flocking rule captures how units coordinate to support learning in the hippocampus.
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