A subcortical circuit linking the cerebellum to the basal ganglia engaged in vocal learning

Speech is a complex sensorimotor skill, and vocal learning involves both the basal ganglia and the cerebellum. These subcortical structures interact indirectly through their respective loops with thalamo-cortical and brainstem networks, and directly via subcortical pathways, but the role of their interaction during sensorimotor learning remains undetermined. While songbirds and their song-dedicated basal ganglia-thalamo-cortical circuitry offer a unique opportunity to study subcortical circuits involved in vocal learning, the cerebellar contribution to avian song learning remains unknown. We demonstrate that the cerebellum provides a strong input to the song-related basal ganglia nucleus in zebra finches. Cerebellar signals are transmitted to the basal ganglia via a disynaptic connection through the thalamus and then conveyed to their cortical target and to the premotor nucleus controlling song production. Finally, cerebellar lesions impair juvenile song learning, opening new opportunities to investigate how subcortical interactions between the cerebellum and basal ganglia contribute to sensorimotor learning.


Sample-size estimation
· You should state whether an appropriate sample size was computed when the study was being designed · You should state the statistical method of sample size computation and any required assumptions · If no explicit power analysis was used, you should describe how you decided what sample (replicate) size (number) to use Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission:

Replicates
· You should report how often each experiment was performed · You should include a definition of biological versus technical replication · The data obtained should be provided and sufficient information should be provided to indicate the number of independent biological and/or technical replicates · If you encountered any outliers, you should describe how these were handled · Criteria for exclusion/inclusion of data should be clearly stated · High-throughput sequence data should be uploaded before submission, with a private link for reviewers provided (these are available from both GEO and ArrayExpress) Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: We did not compute appropriate sample size when designing the study, as we did not have a clear idea neither of the magnitude of the effect of lesions on our indicator (song similarity), nor of the variability of this indicator in controls at the specific time points relevant to our study (before/after lesion and cristalization). Therefore, adequate sample size was estimated after assessing the variability of song similarity among controls, and the magnitude of the effect of lesions on the first bird with a DCN lesion.
How often experiments were performed (n) is indicated in Methods section and in Results section. To lighten Results section, n is indicated only at the first quotation of each experiment. Outliers/ exclusion and inclusion parameters are indicated in Methods section. Statistical reporting · Statistical analysis methods should be described and justified · Raw data should be presented in figures whenever informative to do so (typically when N per group is less than 10) · For each experiment, you should identify the statistical tests used, exact values of N, definitions of center, methods of multiple test correction, and dispersion and precision measures (e.g., mean, median, SD, SEM, confidence intervals; and, for the major substantive results, a measure of effect size (e.g., Pearson's r, Cohen's d) · Report exact p-values wherever possible alongside the summary statistics and 95% confidence intervals. These should be reported for all key questions and not only when the p-value is less than 0.05.
Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: (For large datasets, or papers with a very large number of statistical tests, you may upload a single table file with tests, Ns, etc., with reference to sections in the manuscript.)

Group allocation
· Indicate how samples were allocated into experimental groups (in the case of clinical studies, please specify allocation to treatment method); if randomization was used, please also state if restricted randomization was applied · Indicate if masking was used during group allocation, data collection and/or data analysis Please outline where this information can be found within the submission (e.g., sections or figure legends), or explain why this information doesn't apply to your submission: Additional data files ("source data") · We encourage you to upload relevant additional data files, such as numerical data that are represented as a graph in a figure, or as a summary table · Where provided, these should be in the most useful format, and they can be uploaded as "Source data" files linked to a main figure or table · Include model definition files including the full list of parameters used · Include code used for data analysis (e.g., R, MatLab) · Avoid stating that data files are "available upon request"