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Information filtering in resonant neurons. (English) Zbl 1382.92041
Summary: Neuronal information transmission is frequency specific. In single cells, a band-pass like frequency preference can arise from the subthreshold dynamics of the membrane potential, shaped by properties of the cell’s membrane and its ionic channels. In these cases, a cell is termed resonant and its membrane impedance spectrum exhibits a peak at non-vanishing frequencies. Here, we show that this frequency selectivity of neuronal response amplitudes need not translate into a similar frequency selectivity of information transfer. In particular, neurons with resonant but linear subthreshold voltage dynamics (without threshold) do not show a resonance of information transfer at the level of subthreshold voltage; the corresponding coherence has low-pass characteristics. Interestingly, we find that when combined with nonlinearities, subthreshold resonances do shape the frequency dependence of coherence and the peak in the subthreshold impedance translates to a peak in the coherence function. In other words, the nonlinearity inherent to spike generation allows a subthreshold impedance resonance to shape a resonance of voltage-based information transfer. We demonstrate such nonlinearity-mediated band-pass filtering of information at frequencies close to the subthreshold impedance resonance in three different model systems: the resonate-and-fire model, the conductance-based Morris-Lecar model, and linear resonant dynamics combined with a simple static nonlinearity. In the spiking neuron models, the band-pass filtering is most pronounced for low firing rates and a high variability of interspike intervals, similar to the spiking statistics observed in vivo. We show that band-pass filtering is achieved by reducing information transfer over low-frequency components and, consequently, comes along with an overall reduction of information rate. Our work highlights the crucial role of nonlinearities for the frequency dependence of neuronal information transmission.

92C20 Neural biology
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