Skilled behaviors such as singing and playing the piano require precise timing. The primary goal of this project is to use theoretical and experimental approaches to understand the network properties of neurons that can produce the extremely precise activity necessary to enable these actions. Such networks are likely to be wired during the development of the brain, but the precise mechanisms involved remain a mystery. Previous computational models and experimental observations suggest that the wiring process is gradual. The investigators of this project will study how individual neurons are incorporated into the network. Of particular interest are postnatally born neurons, which have more immature properties compared with other neurons within the circuit, including a higher degree of spontaneous activity, which potentially facilitates their recruitment into the network. These ideas will be tested by experimentally tagging and manipulating immature neurons, as well as by constructing computational models and simulating the network growth process. The findings may shed light on how functional neuronal networks develop. The research may also help to formulate strategies of repairing dysfunctional or injured brain networks through manipulation of neuron maturity. This research will involve a wide range of innovative experimental and computational techniques and provide opportunities for students to gain expertise in electrophysiology, neural data analysis, and modern methods of computational neuroscience. The principal investigators will train postdoctoral researchers as well as graduate students, undergraduates, and summer high school interns.
The model system used in this project is the motor control circuitry of the zebra finch, a songbird whose adult courtship song consists of a highly repeatable sequence of vocal elements (or motif) sung with millisecond precision. The timing of song is controlled by a premotor forebrain region called HVC (proper name). Each premotor HVC neuron fires once per motif with sub-millisecond timing jitter across renditions. As a population, these neurons drive downstream song production circuits to produce specific acoustic patterns. During development, precise timing within HVC gradually emerges while the bird is learning to perform his song. Previous experimental observations suggest that neurons are gradually incorporated into the network generating song-relevant neural sequences, potentially from the newly born neurons that are robustly added to HVC during this period. This project aims to investigate the cellular and synaptic mechanisms underlying the development of the sequence generating network in HVC. The central hypothesis of this work is that these spontaneously active, newly born neurons are preferentially added to the leading edge of the growing timing network. This hypothesis will be tested with a combined experimental and computational modeling approach: (1) directly imaging the dynamics of network integration of newly born neurons in vivo through a targeted retroviral method; (2) constructing a computational model of HVC that is constrained by these observations and using the model to investigate the mechanisms of the network growth; and (3) measuring the cellular and synaptic properties of newly born neurons and their spontaneous activity as they mature.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
