A Spike-Based Model of Neuronal Intrinsic Plasticity

作者：Li, Chunguang^*; Li, Yuke

来源：IEEE Transactions on Autonomous Mental Development, 2013, 5(1): 62-73.

DOI：10.1109/TAMD.2012.2211101

• Homeostasis
• integrate-and-fire model
• intrinsic plasticity
• spike-count distribution

The discovery of neuronal intrinsic plasticity (IP) processes which persistently modify a neuron's excitability necessitates a new concept of the neuronal plasticity mechanism and may profoundly influence our ideas on learning and memory. In this paper, we propose a spike-based IP model/adaptation rule for an integrate-and-fire (IF) neuron to model this biological phenomenon. By utilizing spikes denoted by Dirac delta functions rather than computing instantaneous firing rates for the time-dependent stimulus, this simple adaptation rule adjusts two parameters of an individual IF neuron to modify its excitability. As a result, this adaptation rule helps an IF neuron to keep its firing activity in a relatively "low but not too low" level and makes the spike-count distributions computed with adjusted window sizes similar to the experimental results.

• 出版日期2013-3
• 单位浙江大学