Implementing temporal codes in the brain requires that neurons are capable of following a stimulus with millisecond precision as well as of responding consistently to it in repetitions of the same stimulus. The biophysical mechanisms that endow neurons with this fundamental property remain unknown. We have explored in simulations, experiments and mathematical models how cell-intrinsic as well as extrinsic (stimulus related) properties influence spike-time reliability (Journal of Neurophysiology, 99, p.277-283 [PDF]). We have shown that 1) spike-time reliability depends on an intrinsic property of the neurons: the spike-triggered average; 2) spike-time reliability is maximal when the time scale of the input is in the range of a few (2-5) milliseconds and decreases quickly for slower and faster inputs. This suggests that neurons are adapted to optimally respond to their most natural input signal: fast synaptic currents.
Our findings on spike-time reliability and its optimal time scale are immediately applicable to stochastic synchrony, since both phenomena are closely related. In the former case the timing of the spikes is preserved in repeated trials with the same fluctuating stimulus. In the later case, identical neurons receiving similar (correlated) fluctuating stimuli trigger synchronous spikes. In particular, barrages of spatially correlated synaptic input currents will synchronize postsynaptic neurons quickly. Analogously, in the case of a single neuron, a reproducible barrage of synaptic pulses will trigger highly reliable responses [more].
Figure: Maximal reliability in real cells. Aperiodic frozen currents are injected five times into a mitral cell (a) and into a neocortical pyramidal cell (b). In both neurons, virtually all spikes and their timing are consistent across all trials.
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