How the Brain Formulates Memory : A Spatio-Temporal Model Research Frontier
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Detail(s)
Original language | English |
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Article number | 7450278 |
Pages (from-to) | 56-68 |
Journal / Publication | IEEE Computational Intelligence Magazine |
Volume | 11 |
Issue number | 2 |
Publication status | Published - 1 May 2016 |
Externally published | Yes |
Link(s)
Abstract
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.
Research Area(s)
- Computational modeling, Encoding, Learning systems, Memory, Neurons, Spatio-temporal models, Statistics
Citation Format(s)
How the Brain Formulates Memory: A Spatio-Temporal Model Research Frontier. / Hu, Jun; Tang, Huajin; Tan, K. C. et al.
In: IEEE Computational Intelligence Magazine, Vol. 11, No. 2, 7450278, 01.05.2016, p. 56-68.
In: IEEE Computational Intelligence Magazine, Vol. 11, No. 2, 7450278, 01.05.2016, p. 56-68.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review