A Basal Ganglia Circuit Sufficient to Guide Birdsong Learning

Abstract

Learning vocal behaviors, like speech and birdsong, is thought to rely on continued performance evaluation. Whether candidate performance evaluation circuits in the brain are sufficient to guide vocal learning is not known. Here, we test the sufficiency of VTA projections to the vocal basal ganglia in singing zebra finches, a songbird species that learns to produce a complex and stereotyped multi-syllabic courtship song during development. We optogenetically manipulate VTA axon terminals in singing birds contingent on how the pitch of an individual song syllable is naturally performed. We find that optical inhibition and excitation of VTA terminals are each sufficient to reliably guide learned changes in song. Inhibition and excitation have opponent effects on future performances of targeted song syllables, consistent with positive and negative reinforcement of performance outcomes. These findings define a central role for reinforcement mechanisms in learning vocalizations and demonstrate minimal circuit elements for learning vocal behaviors. VIDEO ABSTRACT.

Expression of FoxP2 in the Basal Ganglia Regulates Vocal Motor Sequences in the Adult Songbird

“…Light pulse delivery was dependent 382 on natural trial-to-trial variation in the pitch of the targeted syllable. In agreement with our previous results 383 (Xiao et al, 2018), we found that optogenetic excitation and inhibition elicited learned changes in the pitch 384 of the targeted syllable on future performances ( Figure 5C). In addition to changes in the pitch of the targeted 385 syllable, we found that phasic increases in dopamine also resulted in disruptions in song syntax similar to 386 birds in which we knocked down FoxP2 expression in Area X (Figures 5D, 5E and S7C), and phasic excitation 387 of dopaminergic terminals in Area X resulted in a significant increase in the number of times birds repeated 388 syllables at the beginning and/or end of their song motif ( Figures 5B, 5D and 5E).…”

“…Recent studies have emphasized the idiosyncratic role of dopamine in 358 reward-based learning and the control of coordinated movements(Coddington and Dudman, 2019). We have 359 previously shown that acute manipulation of dopaminergic inputs to Area X does not affect ongoing vocal-360 motor actions but can instruct rapid bidirectional learned changes in song, consistent with reinforcement-361 based models for motor learning(Xiao et al, 2018). More broadly however, it is known that physical 362 manifestations of dopamine related impairments, like chorea or akinesia, can progressively develop with long 363 term disruptions in dopamine signaling(Chen et al, 2013).…”

“…Optogenetic Manipulation of VTA Axon Terminals in Behaving Birds 52 All procedures were reported previously (Xiao et al, 2018). Briefly, male birds were randomly assigned bilateral 53 injection of either AAV-ChR2, -ArchT or GFP constructs in VTA at ~70 days post hatch(dph).…”

“…Birds were anesthetized using isoflurane inhalation 36 (1.5-2%) and placed in a stereotaxic apparatus. Viral injections and cannula or microdialysis probe implantation were 37 performed using previously described procedures(Xiao et al, 2018) at the following approximate stereotaxic 38 coordinates relative to interaural zero and the brain surface were (rostral, lateral, depth, in mm): Ov (2.8, 1.0, 4.75), 39 the center of Ov was located and mapped based on its robust white noise responses; VTA relative to the center of Ov 40 (+0.3, -0.2, +1.8); Area X (5.1, 1.6, 3.3) with 43-degree head angle or (5.7, 1.6, 3) with 20-degree head angle, the 41 boundary of Area X was verified using extracellular electrophysiological recordings. 0.7-2 μl AAVs were injected 42 according to the titer of constructs and allowed 3-8 weeks for expression before birds were subjected for behavioral 43 tests, immunohistochemistry and/or sequencing experiments.44 45Behavioral assays.…”

“…The brains were sectioned at 50 µm, using a Leica VT1000S 116 vibratome. Immunohistochemistry (IHC) was performed as described previously (Xiao et al, 2018 The resulting count matrices from the data pre-processing steps were analyzed with the Seurat analysis pipeline in R…”