ArticleCold Spring Harbor protocols2014
In vivo recording of single-unit activity during singing in zebra finches.
Article in Cold Spring Harbor protocols, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- An avian cortical circuit for chunking tutor song syllables into simple vocal-motor units.Nature communications · 2020Article
- Rhythmic syllable-related activity in a songbird motor thalamic nucleus necessary for learned vocalizations.PloS one · 2017Article
- Article
- The zebra finch, Taeniopygia guttata: an avian model for investigating the neurobiological basis of vocal learning.Cold Spring Harbor protocols · 2014Review
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Authors and funding
3 authors.
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Abstract
The zebra finch is an important model for investigating the neural mechanisms that underlie vocal production and learning. Previous anatomical and gene expression studies have identified an interconnected set of brain areas in this organism that are important for singing. To advance our understanding of how these various brain areas act together to learn and produce a highly stereotyped song, it is necessary to record the activity of individual neurons during singing. Here, we present a protocol for recording single-unit activity in freely moving zebra finches during singing using a miniature, motorized microdrive. It includes procedures for both the microdrive implant surgery and the electrophysiological recordings. There are several advantages of this technique: (1) high-impedance electrodes can be used in the microdrive to obtain well-isolated single units; (2) a motorized microdrive is used to remotely control the electrode position, allowing neurons to be isolated without handling the bird, and (3) a lateral positioner is used to move electrodes into fresh tissue before each penetration, allowing recordings from well-isolated neurons over the course of several weeks. We also describe the application of the antidromic stimulation and the spike collision test to identify neurons based on the axonal projection patterns.
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