Abstract
Reliable signal transmission constitutes a key requirement for neural circuit function. The propagation of synchronous pulse packets through recurrent circuits is hypothesized to be one robust form of signal transmission and has been extensively studied in computational and theoretical works. Yet, although external or internally generated oscillations are ubiquitous across neural systems, their influence on such signal propagation is unclear. Here we systematically investigate the impact of oscillations on propagating synchrony. We find that for standard, additive couplings and a net excitatory effect of oscillations, robust propagation of synchrony is enabled in less prominent feed-forward structures than in systems without oscillations. In the presence of non-additive coupling (as mediated by fast dendritic spikes), even balanced oscillatory inputs may enable robust propagation. Here, emerging resonances create complex locking patterns between oscillations and spike synchrony. Interestingly, these resonances make the circuits capable of selecting specific pathways for signal transmission. Oscillations may thus promote reliable transmission and, in co-action with dendritic nonlinearities, provide a mechanism for information processing by selectively gating and routing of signals. Our results are of particular interest for the interpretation of sharp wave/ripple complexes in the hippocampus, where previously learned spike patterns are replayed in conjunction with global high-frequency oscillations. We suggest that the oscillations may serve to stabilize the replay.
Highlights
The ground state of cortical networks is characterized by irregular and asynchronous spiking activity [1,2,3,4] and its dynamics are highly sensitive to perturbations, e.g., missing or additional spikes [2,3,5,6,7,8]
For networks with additive couplings we find that the critical connection strength increases with increasing oscillation amplitude Ne as illustrated in Fig. 4a,c: The additional input is balanced, so that the mean input to each neuron is constant, but both the mean excitatory and inhibitory conductances are increased
As we demonstrate below such resonant signal transmission establishes a mechanism to read out signals encoded in the structure of a recurrent network
Summary
The ground state of cortical networks is characterized by irregular and asynchronous spiking activity [1,2,3,4] and its dynamics are highly sensitive to perturbations, e.g., missing or additional spikes [2,3,5,6,7,8]. A common hypothesis states that such transmission might be achieved by propagating signals along subnetworks (layers) connected in a feed-forward manner. Robust signal transmission in synfire chains embedded in larger recurrent networks is usually obtained by an increased connectivity (compared to the embedding network) between the neurons of successive layers of the FFN [25,26,27]. Within each oscillation period Ts~1=ns, Ne spike times are drawn from a Gaussian distribution centered at tn :~n=ns (for the nth oscillation, n[Z) with standard deviation ss Each of these spikes causes an excitatory input of strength eepxt with probability peexxt and an inhibitory input of strength eemxt with probability peinxt to each neuron of the recurrent network (cf Fig. 12)
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