Abstract
Synaptic unreliability is one of the major sources of biophysical noise in the brain. In the context of neural information processing, it is a central question how neural systems can afford this unreliability. Here we examine how synaptic noise affects signal transmission in cortical circuits, where excitation and inhibition are thought to be tightly balanced. Surprisingly, we find that in this balanced state synaptic response variability actually facilitates information transmission, rather than impairing it. In particular, the transmission of fast-varying signals benefits from synaptic noise, as it instantaneously increases the amount of information shared between presynaptic signal and postsynaptic current. Furthermore we show that the beneficial effect of noise is based on a very general mechanism which contrary to stochastic resonance does not reach an optimum at a finite noise level.
Highlights
Synaptic transmission in cortex is remarkably unreliable
The accumulated spike trains of the whole presynaptic population constitute the input to the postsynaptic neuron and drive the dynamics of the postsynaptic membrane potential
In a balanced code synaptic noise does not impair information transmission. It increases the amount of transmitted information: the firing rate of a postsynaptic neuron tracks a presynaptic signal more accurately if synaptic transmission is unreliable
Summary
On average most synapses respond to only less than half of the presynaptic spikes [1], and if they respond, the amplitude of the postsynaptic current varies [2] This high degree of unreliability has been puzzling as it impairs information transmission in excitatory neural networks where a presynaptic signal is represented in the mean input to a postsynaptic neuron [3]. We report a surprising finding that has gone unnoticed so far: in the balanced regime synaptic unreliability generically improves information transmission between neural populations and improves the ability of postsynaptic neurons to accurately track fast-varying signals in the presynaptic firing rate
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