Burst Firing Enhances Neural Output Correlation

Abstract

Neurons communicate and transmit information predominantly through spikes. Given that experimentally observed neural spike trains in a variety of brain areas can be highly correlated, it is important to investigate how neurons process correlated inputs. Most previous work in this area studied the problem of correlation transfer analytically by making significant simplifications on neural dynamics. Temporal correlation between inputs that arises from synaptic filtering, for instance, is often ignored when assuming that an input spike can at most generate one output spike. Through numerical simulations of a pair of leaky integrate-and-fire (LIF) neurons receiving correlated inputs, we demonstrate that neurons in the presence of synaptic filtering by slow synapses exhibit strong output correlations. We then show that burst firing plays a central role in enhancing output correlations, which can explain the above-mentioned observation because synaptic filtering induces bursting. The observed changes of correlations are mostly on a long time scale. Our results suggest that other features affecting the prevalence of neural burst firing in biological neurons, e.g., adaptive spiking mechanisms, may play an important role in modulating the overall level of correlations in neural networks.

Synchrony of Spontaneous Burst Firing between Retinal Ganglion Cells Across Species

“…While a single spike may not pass through a synapse, multiple spikes in a burst will cross the synapse more reliably, improving the possibility of eliciting postsynaptic spikes. Besides, some studies reported that the correlation strength between neurons could be enhanced through the bursts rather than individual spikes [ 29 , 30 ]. The bursting activity can efficiently enhance the transfer of information either by storing information in the burst or by strengthening the connection with other neurons.…”

Neural Coding With Bursts—Current State and Future Perspectives

“…Chan et al ( 2016 ) address the interaction between input and output correlations for different synaptic dynamics using numerical simulation of a pair of neurons. They find that slow synaptic filtering lead to bursts in the output, which results in increased output correlation and synchrony on longer time-scales.…”

Mixtures are more salient stimuli in olfaction

“…The responses we generated in the previous part are assumed to describe conductances. To obtain the firing rate of the ORNs from its input conductances, we approximated the dynamics of a neuron by the conductance-based leaky integrate-and-fire model with adaptation (Richardson and Gerstner, 2005;Chan et al, 2016).…”

“…While we do add external noise to ORNs, for the purpose of obtaining realistic response latencies as described in the next section, and PNs, for the purpose of mimicking their spontaneous activity, the noise effects are small and only visible at low stimulus concentrations. The general effects of noise on neural response and correlation have been well studied (Shadlen and Newsome, 1998;Brunel et al, 2001;Ostojic et al, 2009;Chan, 2015;Chan et al, 2016) and are beyond the scope of this study.…”