Abstract:
Vocal control and learning are dependent on auditory feedback in both songbirds and humans, rendering songbirds as an excellent model to study the neural mechanisms of complex learned behavior. The telencephalic nucleus HVC within the songbird, analogue to the mammalian pre-motor cortex, produces stereotyped instructions through the motor pathway leading to precise, learned vocalization. The forebrain projecting HVC neurons (known as HVCRA), that projects to the robust nucleus of the arcopallium, play a critical role in orchestrating the neural circuitry that guides the bird’s learning and song production. Whole cell current-clamp recordings previously performed on HVCRA neurons within brain slices have shown a diversity in their firing activity across birds, ranging from transient to stuttering patterns (Daou & Margoliash, under review). We developed a biophysical model that captures the diversity of the HVCRA firing activity. The model generated predictions about the ionic currents that HVCRA exhibit which were tested and verified in the slice using pharmacological manipulations. The model highlights important roles for the low-threshold potassium currents( I_D) and (I_M) and the Ca2+-dependent K+ current (I_SK) in driving the characteristic neural patterns observed in HVCRA.
Methods
We used a single-compartment conductance-based Hodgkin-Huxley like biophysical model of HVCRA neurons to estimate the magnitude of the ionic currents. Manual adjustment of the densities of the ionic conductances and additional parameters was performed to match the membrane potential model trajectories to the biological trace in response to applied step currents. To estimate the goodness of the fit, we adopted a feature-based comparison approach in which intrinsic features of simulated voltage traces and biological traces are compared. The model is then validated by testing the fitted model trace to predictions of different current injections.
