bioRxiv2022
Temporal synchrony of signals arriving from different neurons or brain regions is essential for proper neural processing. Nevertheless, it is not well understood how such synchrony is achieved and maintained in a complex network of time-delayed neural interactions. Myelin plasticity has been suggested as an efficient mechanism for controlling timing in brain communications through adaptive changes of axonal conduction velocity and consequently conduction time delays, or latencies; however, local rules and feedback mechanisms that oligodendrocytes (OL) use to achieve synchronization are not known. We propose a mathematical model of oligodendrocyte-mediated myelin plasticity (OMP) in which OL play an active role in providing such feedback. This is achieved without using arrival times at the synapse or modulatory signaling from astrocytes; instead, it relies on the presence of global and transient OL responses to local action potentials in the axons they myelinate. While inspired by OL morphology, we provide the theoretical underpinnings that motivated the model and explore its performance for a wide range of its parameters. Our results indicate that when the characteristic time of OLs spike responses is between 10 and 40 ms and the firing rates in individual axons are relatively low ([lap] 10 Hz), the OMP model efficiently synchronizes correlated and time-locked signals while latencies in axons carrying independent signals are unaffected. This suggests a novel form of selective synchronization in the CNS in which oligodendrocytes play an active role by modulating the conduction delays of correlated spike trains as they traverse to their targets. Significance StatementSynchronization of signals arriving from different neurons or brain regions is of great importance for proper brain function. In vertebrates, myelination provides an efficient way to achieve this by adjusting the conduction velocity and consequently the conduction delays. It is increasingly evident that myelination is an adaptive process and involved in learning; however, the local rules and the feedback that guide oligodendrocytes towards achieving desired delays are not known. Here we propose a simple and biologically plausible model of myelin plasticity in which oligodendrocytes play an active role in providing the needed feedback. We use theoretical arguments, mathematical modeling and computer simulations to show its robust synchronization capabilities which enable efficient communication between the brain regions.