Abstract
Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate. To understand its underlying mechanism, it has recently been shown that it is possible to have a long-period rhythmic synchronous firing in a scale-free network, provided the existence of both the high-degree hubs and the loops formed by low-degree nodes. We here present a simplified memory network model to show that the self-sustained synchronous firing can be observed even without these two necessary conditions. This simplified network consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales. A theoretical analysis is presented to explain the underlying mechanism of firing patterns.
Highlights
Many experiments have evidenced the transition with different time scales from short-term memory (STM) to long-term memory (LTM) in mammalian brains, while its theoretical understanding is still under debate
This model can be further used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales
Instead of considering a large network, we here present a simplified memory network model to represent the core of a brain function network, which consists of two loops of coupled excitable neurons with different synaptic conductance and with one node being the sensory neuron to receive an external stimulus signal. By this core network we show that the self-sustained synchronous firings can be observed even without the two necessary conditions in Ref. 41. We find that this model may be used to show how the diversity of firing patterns can be selectively formed by varying the signal frequency, duration of the stimulus and network topology, which corresponds to the patterns of STM and LTM with different time scales
Summary
A simplified memory network model of coupled excitable neurons based on complex networks. From the aspect of patterns, it is maybe convenient and important if we can grasp the characteristic feature of a large brain functional network by a core network with small size For this purpose, we here present a simplified memory network model to implement the process from STM to LTM as shown, which may come from a typical motif or core part of a large-size network such as the network of Cayley tree in Fig. 1 (b) where the blue and red nodes denote the core part and the green nodes represent the grown surrounding nodes by an approach of Cayley tree[43].
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