A Neurobiologically Inspired Model of Working Memory Based on Neuronal Synchrony and Rythmicity

机译：基于神经元同步和rythmicity的神经生物学上的工作记忆模型

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The connectionist model of reasoning presented here, INFERNET, implements a working memory that is the activated part of long-term memory. This is achieved by making use of temporal properties of the node spikes. A particular solution of the problem of multiple instantiation is proposed. This model makes predictions that have been tested experimentally and the results of these experiments are reported here. These results would seem to challenge modular models of memory.

机译：此处呈现的连接仪的推理模型IderNet实现了一个是长期内存的激活部分的工作内存。这是通过利用节点峰值的时间特性来实现的。提出了多种实例化问题的特定解决方案。该模型使已经通过实验测试的预测，并在此报告这些实验的结果。这些结果似乎挑战了模块化模型。

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《Neural Computation and Psychology Workshop》|1998年||共13页
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Jacques Sougne; Robert M. French;
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中图分类 TP18-532;
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4. A Neurobiologically Inspired Model of Working Memory Based on Neuronal Synchrony and Rythmicity [C] . Jacques Sougne, Robert M. French Neural Computation and Psychology Workshop . 1998

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5. The dopamine imbalance hypothesis: A potential neurobiological model for working memory impairment in schizotypy [D] . Smith, Nathan Tye 2007

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6. Neuronal synchrony reveals working memory networks and predicts individual memory capacity [O] . J. Matias Palva, Simo Monto, Shrikanth Kulashekhar, 2010

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7. A Neurobiologically Inspired Model of Working Memory Based on Neuronal Synchrony and Rythmicity [O] . Sougné, Jacques, French, R. M. 1997

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8. Neurobiologically Inspired Approaches to Nonlinear Process Control and Modeling [R] . Doyle, F. J. 1999

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A Neurobiologically Inspired Model of Working Memory Based on Neuronal Synchrony and Rythmicity

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