Changes in synapses and resultant changes in properties of networks of neurons are well established and potent mechanisms for learning. Recent studies have identified an additional potential site of plasticity, regulation of the magnitude of ionic currents in neurons, implicating changes in the intrinsic properties (IP) of the neurons. These will affect the shape of the spike waveform, which is diagnostic, and the trains of spikes a cell will convey to a network, which has functional consequences. The relation between changes in IP and learning remains unclear, however. Here, a recently discovered compelling relation between IP and learning is investigated in the song system of the well-established model birdsong learning. In vitro intracellular recordings of avian forebrain ?HVCx? neurons projecting to the basal ganglia showed that different cells within a given animal shared similarity of waveforms and spike trains emitted in response to current injections, and these differed across animals. Modeling these data in a Hodgkin-Huxley (HH) framework to estimate the magnitudes of five pharmacologically confirmed principal ionic currents revealed that the ion current magnitudes of HVCx from each animal were tightly clustered together but showed large differences across animals. Critically, the differences in HVCX IP between birds was related to the acoustic similarity of their songs, and predictions of this observation were sustained (similarity in sibling animals, developmental changes, inhomogeneity during abnormal singing). Given this suite of unanticipated results, the proposed experiments test the novel hypothesis that sensorimotor feedback errors are transmitted by variability around an IP set point shared across populations of neurons. In the first specific aim, a detailed model relating of HVCx intrinsic properties and features of singing will be developed, relating homogeneity of HVCx IP with song learning by studying juvenile and adult animals singing songs with graded differences (resulting from controlled tutoring during development). The hypothesis that HVCx represent a single neuronal ensemble will be tested by assessing c homogeneity in species singing multiple song types.
A second aim will test the hypothesis that sensorimotor feedback errors are transmitted by HVCX variability around an IP ?set point?. Comparing changes in distributions of HVCX IP values when birds change songs in the presence of delayed or pitch shifted feedback will identify if the changes represent song features or errors. Intracellular and multisite extracellular recordings in singing birds or in a fictive singing sleeping preparation will connect in vitro and in vivo properties of the neurons, and determine the time course of changes in IP relative to onset of abnormal singing.
A third aim will develop mathematical procedures for estimating all the parameters and the global minima of HH models for each neuron, and a develop a two compartment HH HVCX model including network and IP components, that describes how burst during singing. These experiments aim to identify the cellular and network mechanisms associated with a novel and rapid form of learning mechanism associated with skilled performance.
How the brain learns is central to its function and dysfunction, with learning typically thought to reflect changes in synapses. This research tests a novel hypotheses regarding the role of intrinsic properties of neurons in regulating feedback during learning, in neurons that project to the part of the brain that is implicated in many movement disorders.
