It's always seemed intuitively surprising that there's no feedback mechanism within neurons to aid learning. What's the currently favoured mechanism for learning, neurons feeding back to previous neurons?
There's no single mechanism in neuroscience to explain learning in general, because the current understanding is that "learning" is a very vague term that covers many types of adaptation, and each has its own mechanism.
I'm not familiar with any network-level mechanisms, but there are many local (synapse- or dendrite-level) ones. The one I'm most familiar with is spike-timing dependent plasticity (STDP) [1], which modifies the strength of a synapse based on the millisecond-level timing of action potentials. When cell A tends to fire just before cell B, and the two have synapses connecting them, then cell B will increase the strength of its synapses to A. The reverse is true too: if cell A tends to fire just after cell B, then the synapses will decrease in strength. This is a form of Hebbian learning [2].
Yes, recurrent connections are one of the mechanisms that could be responsible for learning. These are used to 'steer' front-end neurons, for example to focus on a certain feature.
There is also 'Hebbian learning', which means that the connections between neurons that fire at the same time become stronger.
