Abstract
Cortical neurons receive barrages of excitatory and inhibitory inputs which are not independent, as network structure and synaptic kinetics impose statistical correlations. Experiments in vitro and in vivo have demonstrated correlations between inhibitory and excitatory synaptic inputs in which inhibition lags behind excitation in cortical neurons. This delay arises in feed-forward inhibition (FFI) circuits and ensures that coincident excitation and inhibition do not preclude neuronal firing. Conversely, inhibition that is too delayed broadens neuronal integration times, thereby diminishing spike-time precision and increasing the firing frequency. This led us to hypothesize that the correlation between excitatory and inhibitory synaptic inputs modulates the encoding of information of neural spike trains. We tested this hypothesis by investigating the effect of such correlations on the information rate (IR) of spike trains using the Hodgkin-Huxley model in which both synaptic and membrane conductances are stochastic. We investigated two different synaptic input regimes: balanced synaptic conductances and balanced currents. Our results show that correlations arising from the synaptic kinetics, τ, and millisecond lags, δ, of inhibition relative to excitation strongly affect the IR of spike trains. In the regime of balanced synaptic currents, for short time lags (δ ~ 1 ms) there is an optimal τ that maximizes the IR of the postsynaptic spike train. Given the short time scales for monosynaptic inhibitory lags and synaptic decay kinetics reported in cortical neurons under physiological contexts, we propose that FFI in cortical circuits is poised to maximize the rate of information transfer between cortical neurons. Our results also provide a possible explanation for how certain drugs and genetic mutations affecting the synaptic kinetics can deteriorate information processing in the brain.
Highlights
The rate and timing of firing in cortical neurons is strongly affected by the interaction between synaptic excitation and inhibition (Salinas and Sejnowski, 2000)
MAGNITUDE, KINETICS, AND CORRELATION OF SYNAPTIC EXCITATION AND INHIBITION We modeled excitatory and inhibitory conductances as two separate channels of Poisson-distributed events whose rate was set by the fixed parameter λ (5 ms−1), which is inversely proportional to the average inter-event interval, and whose kinetics were varied across a range of τ values (1–10 ms), representing the time-constant of the synaptic conductance decay
This motif enables disynaptic inhibition generated by local interneurons to lag behind monosynaptic excitation with delays ranging from 1 to 10 ms (Wehr and Zador, 2003; Okun and Lampl, 2008; Wu et al, 2008) providing cortical neurons with windows of integration whose width is determined by the relative lag between excitatory and inhibitory conductances and their decay kinetics
Summary
The rate and timing of firing in cortical neurons is strongly affected by the interaction between synaptic excitation and inhibition (Salinas and Sejnowski, 2000). The architecture of cortical circuits ensures that the magnitude of excitatory and inhibitory synaptic inputs is approximately balanced on average and temporally correlated (Shu et al, 2003b; Haider et al, 2006), albeit with a small time delay for inhibition of ∼1–10 ms (Wehr and Zador, 2003; Okun and Lampl, 2008; Wu et al, 2008).
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