Memory is a complex process across different brain regions and a fundamental function for many cognitive behaviors. Emerging experimental results suggest that memories are represented by populations of neurons and organized in a categorical and hierarchical manner. However, it is still not clear how the neural mechanisms are emulated in computational models. In this paper, we present a spatio-temporal memory (STM) model using spiking neurons to explore the memory formulation and organization in the brain. Unlike previous approaches, this model employs temporal population codes as the neural representation of information and spiketiming-based learning methods to formulate the memory structure. It explicitly demonstrates that the complex spatio-temporal patterns are the internal neural representations of memory items. Two types of memory processes are analyzed and emulated: associative memory, i.e., spatio-temporal patterns driven by intra-assembly connections, and episodic memory, i.e., temporally separated spatio-temporal patterns linked by inter-assembly connections. Our model will provide a computational substrate based on lowlevel neural circuits for developing neuromorphic cognitive systems with wide applications.
['Jun Hu', 'Huajin Tang', 'Kay Chen Tan', 'Haizhou Li']
How the Brain Formulates Memory: A Spatio-Temporal Model Research Frontier