The raphe nucleus in the brain is the main source of serotonin (5-HT), an important brain chemical in regulating mood, cognition and behavior. This paper presents a spiking neuronal network model of the dorsal region of the raphe nucleus (DRN). We solve the perplexing problem of heterogeneous spiking neuronal behavior observed in the DRN by using an adaptive quadratic integrate-and-fire neuronal model and varying only its membrane potential reset after a spike, suggesting a potential role of certain recovery ionic currents. Specifically, the model can mimic the effects of slow afterhyperpolarization current and control the production of spikes per burst as found in experiments. Our model predicts specific input-output functions of the neurons which can be experimentally tested. Phase-plane analysis confirms their spiking dynamics. By coupling the 5-HT neurons with non-5-HT inhibitory neurons, we show that the DRN neuronal spiking activities recorded in behaving monkeys can generally be reproduced by adopting a feedforward inhibitory network architecture. Our model further predicts a low frequency network oscillation (about 8 Hz) among non-5-HT neurons around the rewarding epoch of a simulated experimental trial, which can be verified through direct recordings in behaving animals. Our computational model of the DRN accounts for the heterogeneous spiking patterns found in experiments, suggests plausible network architecture, and provides model predictions which can be directly tested in experiments. The model conveniently forms the basis for building extended network models to study complex interactions of the 5-HT system with other brain regions.
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