Abstract:

BACKGROUND: Hippocampus is one of an important brain areas related with memory, and plays a critical role in associative memory function. Hippocampal CA3 is one of the most important regions to form associative memory. CA3 is functionally divided into autoassociative and heteroassociative memories, and memory formation and retrieval require the development of detailed models of hippocampal function.
OBJECTIVE: To establish a detailed model of hippocampal CA3 function according to CA3 structure.
METHODS: The model was a three-layered Hopfield-like neural network and was constituted by 280 Izhikevich artificial neurons, and is modulated by Hebbian rules. The model was simulated using MATLAB under the condition of adding the Gaussian white noise to its input. In the simulation, memories were represented by synchronous firing sequences.
RESULTS AND CONCLUSION: The simulating results show that the third layer of model had heteroassociative memory function; the first and the second layer of the model could implement autoassociative memory. The model implemented well the memory functions of three subregions of hippocampal CA3. But it is impossible to understand the functions and dynamics of a real biological neural network by constructing a simple model. The model proposed has 280 neurons, which are far less than the real number of neurons. It suggests that there is a big gap between the properties of the model and a real biological neural network of CA3.