AUTHOR=Zhou Pengcheng , Burton Shawn , Urban Nathan , Ermentrout G B. TITLE=Impact of neuronal heterogeneity on correlated colored noise-induced synchronization JOURNAL=Frontiers in Computational Neuroscience VOLUME=7 YEAR=2013 URL=https://www.frontiersin.org/journals/computational-neuroscience/articles/10.3389/fncom.2013.00113 DOI=10.3389/fncom.2013.00113 ISSN=1662-5188 ABSTRACT=

Synchronization plays an important role in neural signal processing and transmission. Many hypotheses have been proposed to explain the origin of neural synchronization. In recent years, correlated noise-induced synchronization has received support from many theoretical and experimental studies. However, many of these prior studies have assumed that neurons have identical biophysical properties and that their inputs are well modeled by white noise. In this context, we use colored noise to induce synchronization between oscillators with heterogeneity in both phase-response curves and frequencies. In the low noise limit, we derive novel analytical theory showing that the time constant of colored noise influences correlated noise-induced synchronization and that oscillator heterogeneity can limit synchronization. Surprisingly, however, heterogeneous oscillators may synchronize better than homogeneous oscillators given low input correlations. We also find resonance of oscillator synchronization to colored noise inputs when firing frequencies diverge. Collectively, these results prove robust for both relatively high noise regimes and when applied to biophysically realistic spiking neuron models, and further match experimental recordings from acute brain slices.