So I close my eyes, turn around, open them for just a blink and close again. I have observed a chair. I can't tell you how the chair looks like in detail, but I can more or less tell its shape and color. What's more, if I'm not disturbed, I can remember that shape and color for at least a minute.
What if I wanted to construct a device that could repeat this process. With digital hardware its not too hard - take a digital camera and a solid state memory device. For every bit of info in my solid state drive, I can call the operation "store" and my bit will be stored, or "erase" and it will be erased. Don't know how reliably each physical bit works with current technology, but given sufficient number of physical bits per logical bit I can theoretically make a device that will store my picture for as long as I want.
What about building a spiking neuronal network to do the same thing? I have tried some naive approaches, and I arrive at a fundamental problem: spiking neuronal networks seem to have almost no inertia on the fast timescale. A neuron only fires while there is sufficient input. When input is gone, it no longer fires (besides some resting state activity). I can construct a network with recurrently-connected neurons, in which case, in principle, the activity of the network could sustain itself after the input is gone. However, depending on the parameters of the network I observe a rapid switch between two very extreme behaviours. In one case, the feedback strength of the network is too weak, and the activity drops as soon as the input is gone. In the other, the feedback weight is too strong, and the activity of the network quickly reaches some maximal firing state independently of which exact input the network has received. These transitions happen exponentially fast. Theoretically, there are adaptive control mechanisms in neuronal networks, such as inhibition and synaptic plasticity. However, I am struggling to understand how such mechanisms can ever be fast enough to compensate for the sudden increase or drop of input.
TL;DR: Naively neuronal networks do not seem stable enough to implement robust short-term memory. What are the known mechanisms that nevertheless make it possible?
Note: I'm not asking how exactly short-term memory works. I am aware that nobody really knows. I'm asking for intuition to help disprove my argument that it should not work when implemented using neurons.