Abstract

AbstractWe present a time-dependent level-crossing theory for linear dynamical systems perturbed by colored Gaussian noise. We apply these results to approximate the firing statistics of conductance-based integrate-and-fire neurons receiving excitatory and inhibitory Poissonian inputs. Analytical expressions are obtained for three key quantities characterizing the neuronal response to time-varying inputs: the mean firing rate, the linear response to sinusoidally-modulated inputs, and the pairwise spike-correlation for neurons receiving correlated inputs. The theory yields tractable results that are shown to accurately match numerical simulations, and provides useful tools for the analysis of interconnected neuronal populations.

Highlights

  • We present a time-dependent level-crossing theory for linear dynamical systems perturbed by colored Gaussian noise

  • Synaptic input consists of discrete action potentials, which results in non-Gaussian voltage distributions and affects firing statistics [5,6,7,8]

  • The majority of theoretical studies include only one synaptic type and assume either fast (e.g., [9,10,11]) or slow [11, 12] kinetics compared with the membrane integration time, but experimental evidence suggests that these timescales are often comparable [13]

Read more

Summary

MODEL DEFINITION

A neuron, with capacitance C and charged at a voltage V , obeys the current-balance equation. The synaptic current Isyn comprises excitatory and inhibitory conductances Isyn = Ge(Ee − V ) + Gi(Ei − V ) with reversals Ee = 0 and Ei = −80mV. Synaptic channels activate rapidly but close with a characteristic time particular to excitation (τe = 3ms) or inhibition (τi = 10ms). The assumption that these conductances are activated stochastically with a short autocταorGreαla=tionGαal−lowGsαa+Lσaαn√ge2vτiαnξαeqfuoartiαon to be written, ∈ {e, i}, where. The general form of this equation can be related to a family of underlying models; in our simulations a process is considered in which synaptic conductances increase by an amount.

FIRING RATE
FREQUENCY RESPONSE
CROSS-CORRELATIONS
Implications for synchrony
RANGE OF VALIDITY
DISCUSSION
Level-crossing rates for Gaussian processes
Moments for time-dependent input
Response to modulations in input current
Response to modulations in presynaptic firing rates
Joint firing rate
Conditional moments
Example of correlated populations
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call