Topic: sequential MNIST/CIFAR10

Spike frequency adaptation (SFA) is a well studied physiological mechanism with established computational properties at the single-neuron level, including noise mitigating effects based on efficient coding principles. Network models with adaptive neurons have revealed advantages including modulation of total activity, supporting Bayesian inference, and allowing computations over distributed timescales. Such efforts are bottom-up, modeling adaptive mechanisms from physiology and analyzing their effects. How top-down environmental and functional pressures influence the specificity of adaptation