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Published September 15, 1996 | Published
Journal Article Open

Intracellular Characterization of Song-Specific Neurons in the Zebra Finch Auditory Forebrain

Abstract

Auditory neurons in the forebrain nucleus HVc (hyperstriatum ventrale pars caudale) are highly sensitive to the temporal structure of the bird's own song. These "song-specific" neurons respond strongly to forward song, weakly to the song with the order of the syllables reversed, and little or not at all to reversed song. To investigate the cellular mechanisms underlying these responses,in vivo intracellular recordings were made from adult HVc neurons. Song-specific cells could be divided into those that responded strongly throughout autogenous song (tonic cells) and those that responded with bursts of action potentials at specific points during the song (phasic cells). Phasic cells were hyperpolarized during autogenous song, even though this stimulus also elicited the strongest response. Less hyperpolarization was seen to the same song with the syllables in reverse order, and none was seen to reversed song. The responses of both types of song-specific cells contained high-frequency bursts of action potentials. The bursts of the phasic cells showed attenuation of the action potential height and lack of full repolarization after each spike. This type of bursting was significantly correlated with the amount of hyperpolarization before each burst in phasic cells and nonauditory cells that generated such bursts spontaneously. These data suggest that song-specific neurons use long-lasting hyperpolarization as a mechanism to integrate auditory context, an important component of temporal order selectivity. Hyperpolarization also may increase the precision of spike timing, which could be important for the neural code subserving song learning and production.

Additional Information

© 1996 Society for Neuroscience. Received March 26, 1996; revised June 14, 1996; accepted June 25, 1996. This work was supported by a National Institutes of Health Research Training grant and a Caltech Engineering Research Center fellowship. I thank Allison Doupe, Rich Jeo, Mark Konishi, Jamie Mazer, and Marc Schmidt for valuable comments on this manuscript.

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August 22, 2023
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