Mechanisms of Synchrony in Heterogeneous Inhibitory Interneuronal Networks for Type 1 versus Type 2 Excitability

Abstract

PV+ fast spiking basket interneurons are often implicated in gamma rhythms. Here we focus on mechanisms present in purely inhibitory networks. Neurons with type 1 excitability can fire arbitrarily slowly, whereas those with type 2 excitability cannot fire below a minimum frequency. We systematically examine how excitability type affects synchronization of individual spikes to a population rhythm in the presence of heterogeneity and noise, using model neurons of each type with matched F/I curve, input resistance, time constant and action potential shape. Population synchrony in noisy heterogeneous networks is maintained because neurons either fire within a tight time window or skip that cycle. Type 2 neurons with hyperpolarizing inhibition skip cycles due to their intrinsic dynamics; we show here the cycle skipping mechanism for type 1 neurons or type 2 neurons with shunting inhibition is synaptic and not intrinsic. Type 2 neurons are more resistant than type 1 to partial and complete suppression in networks with hyperpolarizing inhibition that exhibit network gamma. Moreover, type 2 neurons are recruited more rapidly and more completely into theta-nested gamma. In contrast, type 1 networks perform better with shunting inhibition on both counts, because the nonlinear dynamics in that case favor suppression of type 2 compared to type 1 neurons. Conductances that control excitability type may provide a therapeutic target to improve spatial and working memory and other tasks that rely on gamma synchrony or phase amplitude coupling. Author SummaryThe collective, synchronized activity of neurons produces brain rhythms. These rhythms are thought to subserve cognitive functions such as attention and memory encoding and retrieval. Faster rhythms are nested in slower rhythms as a putative way of chunking information. A subset of neurons called fast spiking basket cells tend to inhibit other neurons from firing. These neurons play an important role in oscillations, and in the coupling of faster oscillations to slower ones. In some brain regions these neurons can fire arbitrarily slowly (type 1 dynamics) whereas in others they cannot fire below a minimum cutoff frequency (type 2 dynamics). Mathematically, these distinct origins of rhythmic firing are signatures of very different dynamics. Here, we show that these distinct excitability types affect the ability of networks of these neurons to synchronize their fast oscillatory activity, as well as the ability of slower oscillations to modulate these fast oscillations. The exact nature of the inhibitory coupling, which may vary between brain regions, determines which type synchronizes better and is modulated better.