A hierarchy of macrodynamical equations for associative memory
Neural Networks
Notions of associative memory and sparse coding
Neural Networks - 1996 Special issue: four major hypotheses in neuroscience
Temporally asymmetric Hebbian learning, spike timing and neuronal response variability
Proceedings of the 1998 conference on Advances in neural information processing systems II
Self-regulation mechanism of temporally asymmetric Hebbian plasticity
Neural Computation
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Recent biological experimental findings have shown that synaptic plasticity depends on the relative timing of pre- and post-synaptic spikes and this is called spike-timing-dependent plasticity (STDP). Many authors have claimed that a precise balance between long-term potentiation (LTP) and long-term depression (LTD) of STDP is crucial in the storage of spatio-temporal patterns. Some authors have numerically investigated the impact of an imbalance between LTP and LTD on the network properties. However, the mathematical mechanism remains unknown. We analytically show that an associative memory network has the robust retrieval properties of spatio-temporal patterns, and these properties make the network less vulnerable to any deviation from a precise balance between LTP and LTD when the network contains a finite number of neurons.