Cortical neurons receive balanced excitatory and inhibitory synaptic currents. Such a balance could be established and maintained in an experience-dependent manner by synaptic plasticity at inhibitory synapses. We show that this mechanism provides an explanation for the sparse firing patterns observed in response to natural stimuli and fits well with a recently observed interaction of excitatory and inhibitory receptive field plasticity. The introduction of inhibitory plasticity in suitable recurrent networks provides a homeostatic mechanism that leads to asynchronous irregular network states. Further, it can accommodate synaptic memories with activity patterns that become indiscernible from the background state but can be reactivated by external stimuli. Our results suggest an essential role of inhibitory plasticity in the formation and maintenance of functional cortical circuitry.
The authors show that, if the same input to an output neuron arrives through an excitatory and a delayed inhibitory channel, synaptic plasticity (a symmetric STDP rule) at the inhibitory synapses leads to “detailed balance”, i.e., to cancellation of excitatory and inhibitory input currents. Then, the output neuron fires sparsely and irregularly (as observed for real neurons) only when an excitatory input was not predicted by the implicit model encoded by the synaptic weights of the inhibitory inputs. The adaptation of the inhibitory synapses also matches potential changes in the excitatory synapses, although here they only present simulations in which excitatory synapses changed abruptly and stayed constant afterwards. (What happens when excitatory and inhibitory synapses change concurrently?) Finally, the authors show that similar results apply to recurrently connected networks of neurons with dedicated inhibitory neurons (balanced networks). Arbitrary activity patterns can be encoded by the excitatory connections, activity in these patterns is then suppressed by the inhibitory neurons, while partial activation of the patterns through external input reactivates the whole patterns (cf. recall of memory) without suppressing potential reactivation of other patterns in the network.
These are interesting ideas, clearly presented and with very detailed supplementary information. The large number of inhibitory neurons in cortex makes the assumed pairing of excitatory and inhibitory input at least possible, but I don’t know how prevalent this really is. Another important assumption here is that the inhibitory input is a bit slower than the excitatory input. This makes intuitive sense, if you assume that the inhibitory input needs to be relayed through an additional inhibitory neuron, but I’ve seen the opposite assumption before, too.