Project Team MathNeuro, INRIA-CNRS-UNS, Sophia Antipolis, France.
Lab by MANTU, Amaris Research Unit, Route des Colles, Biot, France.
PLoS One. 2020 Apr 16;15(4):e0231165. doi: 10.1371/journal.pone.0231165. eCollection 2020.
In this article we present a biologically inspired model of activation of memory items in a sequence. Our model produces two types of sequences, corresponding to two different types of cerebral functions: activation of regular or irregular sequences. The switch between the two types of activation occurs through the modulation of biological parameters, without altering the connectivity matrix. Some of the parameters included in our model are neuronal gain, strength of inhibition, synaptic depression and noise. We investigate how these parameters enable the existence of sequences and influence the type of sequences observed. In particular we show that synaptic depression and noise drive the transitions from one memory item to the next and neuronal gain controls the switching between regular and irregular (random) activation.
在本文中,我们提出了一个受生物启发的记忆项目序列激活模型。我们的模型产生了两种类型的序列,分别对应于两种不同类型的大脑功能:规则序列和不规则序列的激活。两种激活类型之间的切换是通过调节生物参数来实现的,而无需改变连接矩阵。我们的模型中包含的一些参数包括神经元增益、抑制强度、突触抑制和噪声。我们研究了这些参数如何使序列存在,并影响观察到的序列类型。特别是,我们表明,突触抑制和噪声驱动从一个记忆项目到下一个记忆项目的转换,而神经元增益控制着规则和不规则(随机)激活之间的切换。