Using high-throughput mapping techniques to reveal mechanisms of vocal learning

Understanding how humans and non-human animals communicate with each other continues to be a central question in neuroscience. Songbirds serve as powerful animal models for this endeavor because they learn their vocalizations (“songs”) in a manner that resembles how humans learn to speak and because vocal learning in songbirds is regulated by discrete brain circuits that are analogous to brain areas implicated in speech acquisition in humans. We propose to take advantage of a novel, high-throughput, and barcode-based sequencing technique called MAPseq (Multiplexed Analysis of Projections by Sequencing) to simultaneously map the projections of thousands of individual neurons in the songbird brain. Our analyses will target a brain region (“RA”) that plays a central role in vocal learning and performance in songbirds. The direct projection from RA to a hindbrain area for vocal control (“nXIIts”) is observed only in bird species that evolved the ability to learn their vocalizations and, thus, implicated in the evolution of vocal learning. [Comparative studies in mammals also underscore the importance of a direct cortical-hindbrain projection for vocal learning.]

Faculty Supervisor:

Jon Sakata

Student:

Partner:

Johns Hopkins University

Discipline:

Life Sciences

Sector:

Life Sciences (not health); Biotechnology

University:

McGill University

Program: