Temporal patterns of synchrony in a pyramidal-interneuron gamma (PING) network

Synchronization in neural systems plays an important role in many brain functions. Synchronization in the gamma frequency band (30-100 Hz) is involved in a variety of cognitive phenomena; abnormalities of the gamma synchronization are found in schizophrenia and autism spectrum disorder. Frequently, the strength of synchronization is not high, and synchronization is intermittent even on short time scales (few cycles of oscillations). That is, the network exhibits intervals of synchronization followed by intervals of desynchronization. Neural circuit dynamics may show different distributions of desynchronization durations even if the synchronization strength is fixed. We use a conductance-based neural network exhibiting pyramidal-interneuron gamma rhythm to study the temporal patterning of synchronized neural oscillations. We found that changes in the synaptic strength (as well as changes in the membrane kinetics) can alter the temporal patterning of synchrony. Moreover, we found that the changes in the temporal pattern of synchrony may be independent of the changes in the average synchrony strength. Even though the temporal patterning may vary, there is a tendency for dynamics with short (although potentially numerous) desynchronizations, similar to what was observed in experimental studies of neural synchronization in the brain. Recent studies suggested that the short desynchronizations dynamics may facilitate the formation and the breakup of transient neural assemblies. Thus, the results of this study suggest that changes of synaptic strength may alter the temporal patterning of the gamma synchronization as to make the neural networks more efficient in the formation of neural assemblies and the facilitation of cognitive phenomena.

Automated summary

Synchronization in neural systems, particularly in the gamma frequency band, plays a crucial role in cognitive phenomena; the strength of synchronization is often low and intermittent, with intervals of synchronization followed by desynchronization. Changes in synaptic strength can alter the temporal patterning of synchrony, independent of changes in synchrony strength, potentially leading to efficient formation and breakup of transient neural assemblies.