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1.	Villani, Gianluca, et al. (author) Analysis of free recall dynamics of an abstract working memory model 2020 In: 2020 American Control Conference (ACC). - : IEEE. ; , s. 2562-2567 Conference paper (peer-reviewed)abstract This paper analyzes the free recall dynamics of a working memory model. Free recalling is the reactivation of a stored pattern in the memory in the absence of the pattern. Our free recall model is based on an abstract model of a modular neural network composed on N modules, hypercolumns, each of which is a bundle of minicolumns. This paper considers a network of N modules, each consisting of two minicolumns, over a complete graph topology. We analyze the free recall dynamics assuming a constant, and homogeneous coupling between the network modules. We obtain a sufficient condition for synchronization of network's minicolumns whose activities are positively correlated. Furthermore, for the synchronized network, the bifurcation analysis of one module is presented. This analysis gives a necessary condition for having a stable limit cycle as the attractor of each module. The latter implies recalling a stored pattern. Numerical results are provided to verify the theoretical analysis.

Villani, Gianluca, et al. (author)
Analysis of free recall dynamics of an abstract working memory model
2020
In: 2020 American Control Conference (ACC). - : IEEE. ; , s. 2562-2567
Conference paper (peer-reviewed)abstract
- This paper analyzes the free recall dynamics of a working memory model. Free recalling is the reactivation of a stored pattern in the memory in the absence of the pattern. Our free recall model is based on an abstract model of a modular neural network composed on N modules, hypercolumns, each of which is a bundle of minicolumns. This paper considers a network of N modules, each consisting of two minicolumns, over a complete graph topology. We analyze the free recall dynamics assuming a constant, and homogeneous coupling between the network modules. We obtain a sufficient condition for synchronization of network's minicolumns whose activities are positively correlated. Furthermore, for the synchronized network, the bifurcation analysis of one module is presented. This analysis gives a necessary condition for having a stable limit cycle as the attractor of each module. The latter implies recalling a stored pattern. Numerical results are provided to verify the theoretical analysis.

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