Channelpedia

PubMed 21490285


Referenced in: none

Automatically associated channels: Kv4.1



Title: Localization and function of Ih channels in a small neural network.

Authors: Marie L Goeritz, Qing Ouyang, Ronald M Harris-Warrick

Journal, date & volume: J. Neurophysiol., 2011 Jul , 106, 44-58

PubMed link: http://www.ncbi.nlm.nih.gov/pubmed/21490285


Abstract
Subthreshold ionic currents, which activate below the firing threshold and shape the cell's firing properties, play important roles in shaping neural network activity. We examined the distribution and synaptic roles of the hyperpolarization-activated inward current (I(h)) in the pyloric network of the lobster stomatogastric ganglion (STG). I(h) channels are expressed throughout the STG in a patchy distribution and are highly expressed in the fine neuropil, an area that is rich in synaptic contacts. We performed double labeling for I(h) protein and for the presynaptic marker synaptotagmin. The large majority of labeling in the fine neuropil was adjacent but nonoverlapping, suggesting that I(h) is localized in close proximity to synapses but not in the presynaptic terminals. We compared the pattern of I(h) localization with Shal transient potassium channels, whose expression is coregulated with I(h) in many STG neurons. Unlike I(h), we found significant levels of Shal protein in the soma membrane and the primary neurite. Both proteins were found in the synaptic fine neuropil, but with little evidence of colocalization in individual neurites. We performed electrophysiological experiments to study a potential role for I(h) in regulating synaptic transmission. At a synapse between two identified pyloric neurons, the amplitude of inhibitory postsynaptic potentials (IPSPs) decreased with increasing postsynaptic activation of I(h). Pharmacological block of I(h) restored IPSP amplitudes to levels seen when I(h) was not activated. These experiments suggest that modulation of postsynaptic I(h) might play an important role in the control of synaptic strength in this rhythmogenic neural network.