Progress in defining heterogeneity and modeling periglomerular cells in the olfactory bulb

Abstract

In recent years the evolution of olfactory bulb periglomerular cells, as well as the function of periglomerular cells in olfactory encoding, has attracted increasing attention. Studies of neural information encoding based on the analysis of simulation and modeling have given rise to electrophysiological models of periglomerular cells, which have an important role in the understanding of the biology of these cells. In this review we provide a brief introduction to the anatomy of the olfactory system and the cell types in the olfactory bulb. We elaborate on the latest progress in the study of the heterogeneity of periglomerular cells based on different classification criteria, such as molecular markers, structure, ion channels and action potentials. Then, we discuss the several existing electrophysiological models of periglomerular cells, and we highlight the problems and defects of these models. Finally, considering our present work, we propose a future direction for electrophysiological investigations of periglomerular cells and for the modeling of periglomerular cells and olfactory information encoding.

Development of the main olfactory system and main olfactory epithelium-dependent male mating behavior are altered in G o -deficient mice

“…Neurotransmission between pre-and postsynaptic fibers in the GL of the OB is extensively modulated by periglomerular interneurons that exclusively express tyrosine TH, CB, or calretinin (CR) (19). Deprivation of presynaptic input from the ONL in rodents, either by treatment with zinc sulfate or by naris occlusion, was previously shown to reduce both TH expression and dopamine levels in the GL of the OB (20,21), whereas naris reopening resulted in the generation of new TH + interneurons (22).…”

A review of olfactory cell-based sensors: coupling microelectronics to olfactory cells

“…A variety of methods have been used to study the spatiotemporal patterning of olfactory system, such as biosensors and computational models (Arruda et al , 2013; Gilra and Bhalla, 2015; Kaplan and Lansner, 2014; Migliore and Shepherd, 2008; Simoes-de-Souza et al , 2014; Ye et al , 2010; Ying et al , 2012; Yu et al , 2013). Our laboratory has made certain achievements in cell-based sensors (Ling et al , 2010; Tian et al , 2015) and the olfactory modeling and simulation (Ye et al , 2010; Ying et al , 2012). We think the olfactory cell-based biosensors seem to be a promising method on the validation of simulated results.…”