4.4 Article

Electrophysiological characterization and computational models of HVC neurons in the zebra finch

期刊

JOURNAL OF NEUROPHYSIOLOGY
卷 110, 期 5, 页码 1227-1245

出版社

AMER PHYSIOLOGICAL SOC
DOI: 10.1152/jn.00162.2013

关键词

birdsong; computational model; ionic currents; song system

资金

  1. National Science Foundation [IOS-1146607]
  2. Direct For Biological Sciences
  3. Division Of Integrative Organismal Systems [1146607] Funding Source: National Science Foundation

向作者/读者索取更多资源

The nucleus HVC (proper name) within the avian analog of mammal premotor cortex produces stereotyped instructions through the motor pathway leading to precise, learned vocalization by songbirds. Electrophysiological characterization of component HVC neurons is an important requirement in building a model to understand HVC function. The HVC contains three neural populations: neurons that project to the RA (robust nucleus of arcopallium), neurons that project to Area X (of the avian basal ganglia), and interneurons. These three populations are interconnected with specific patterns of excitatory and inhibitory connectivity, and they fire with characteristic patterns both in vivo and in vitro. We performed whole cell current-clamp recordings on HVC neurons within brain slices to examine their intrinsic firing properties and determine which ionic currents are responsible for their characteristic firing patterns. We also developed conductance-based models for the different neurons and calibrated the models using data from our brain slice work. These models were then used to generate predictions about the makeup of the ionic currents that are responsible for the different responses to stimuli. These predictions were then tested and verified in the slice using pharmacological manipulations. The model and the slice work highlight roles of a hyperpolarization-activated inward current (I-h), a low-threshold T-type Ca2+ current (ICa-T), an A-type K+ current (I-A), a Ca2+ activated K+ current (I-SK), and a Na+-dependent K+ current (I-KNa) in driving the characteristic neural patterns observed in the three HVC neuronal populations. The result is an improved characterization of the HVC neurons responsible for song production in the songbird.

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