Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/IJCNN.2011.6033414 | IJCNN |
Keywords | Field | DocType |
phase-plane analysis,serotonin,behavior regulation,plausible network architecture,recovery ionic currents,production control,non-5-ht inhibitory neurons,behaving monkeys,heterogeneous spiking pattern,perplexing problem,brain chemical,mood regulation,dorsal raphe nucleus,cognition regulation,brain,adaptive quadratic integrate-and-fire neuronal model,feedforward inhibitory network architecture,heterogeneous spiking neuronal behavior,spiking dynamics,membrane potential reset,membranes,hyperpolarization current,spiking neuronal network model,neural nets,network architecture,low frequency,membrane potential,network model,computer model,input output,oscillations | Neuroscience,Membrane potential,Pattern recognition,Computer science,Slow afterhyperpolarization,Inhibitory postsynaptic potential,Artificial intelligence,Spiking neural network,Biological neural network,Raphe nuclei,Network model,Dorsal raphe nucleus | Conference |
ISSN | ISBN | Citations |
2161-4393 | 978-1-4244-9635-8 | 1 |
PageRank | References | Authors |
0.41 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| KongFatt Wong-Lin | 1 | 46 | 11.52 |
| Girijesh Prasad | 2 | 517 | 45.24 |
| T. Martin Mcginnity | 3 | 518 | 66.30 |