We know quite a bit about how long-term memory is formed in the brain - it's all about strengthening of synaptic connections between neurons. But what about remembering something over the course of just a few seconds? Like how you (hopefully) still recall what that last sentence as about? Short-term memory is formed and lost far too quickly for it to be explained by any (known) kind of synaptic plasticity. So how does it work? British mathematicians Samuel Johnson and colleagues say they have the answer: Robust Short-Term Memory without Synaptic Learning. They write:
The mechanism, which we call Cluster Reverberation (CR), is very simple. If neurons in a group are more densely connected to each other than to the rest of the network, either because they form a module or because the network is significantly clustered, they will tend to retain the activity of the group: when they are all initially firing, they each continue to receive many action potentials and so go on firing.
The idea is that a neural network will naturally exhibit short-term memory - i.e. a pattern of electrical activity will tend to be maintained over time - so long as neurons are wired up in the form of clusters of cells mostly connected to their neighbours:
The cells within a cluster (or module) are all connected to each other, so once a module becomes active, it will stay active as the cells stimulate each other. Why, you might ask, are the clusters necessary? Couldn't each individual cell have a memory - a tendency for its activity level to be 'sticky' over time, so that it kept firing even after it had stopped receiving input? The authors say that even 'sticky' cells couldn't store memory effectively, because we know that the firing pattern of any individual cell is subject to a lot of random variation. If all of the cells were interconnected, this noise would quickly erase the signal. Clustering overcomes this problem. But how could a neural clustering system develop in the first place? And how would the brain ensure that the clusters were 'useful' groups, rather than just being a bunch of different neurons doing entirely different things? Here's the clever bit:
If an initially homogeneous (i.e., neither modular nor clustered) area of brain tissue were repeatedly stimulated with different patterns... then synaptic plasticity mechanisms might be expected to alter the network structure in such a way that synapses within each of the imposed modules would all tend to become strengthened.
In other words, even if the brain started out life with a random pattern of connections, everyday experience (e.g. sensory input) could create a modular structure of just the right kind to allow short-term memory. Incidentally, such a 'modular' network would also be one of those famous small-world networks. It strikes me as a very elegant model. But it is just a model, and neuroscience has a lot of those; as always, it awaits experimental proof. One possible implication of this idea, it seems to me, is that short-term memory ought to be pretty conservative, in the sense that it could only store reactivations of existing neural circuits, rather than entirely new patterns of activity. Might it be possible to test that...?
Johnson S, Marro J, and Torres JJ (2013). Robust Short-Term Memory without Synaptic Learning. PloS ONE, 8 (1) PMID: 23349664
