Leila May M Pascual, Aanya Vusirikala, Ilya M Nemenman, Samuel J Sober, Michael Pasek
{"title":"Millisecond-scale motor coding precedes sensorimotor learning in songbirds.","authors":"Leila May M Pascual, Aanya Vusirikala, Ilya M Nemenman, Samuel J Sober, Michael Pasek","doi":"10.1101/2024.09.27.615500","DOIUrl":null,"url":null,"abstract":"<p><p>A key goal of the nervous system in young animals is to learn motor skills. Songbirds learn to sing as juveniles, providing a unique opportunity to identify the neural correlates of skill acquisition. Prior studies have shown that spike rate variability in vocal motor cortex decreases substantially during song acquisition, suggesting a transition from rate-based neural control to the millisecond-precise motor codes known to underlie adult vocal performance. By distinguishing how the ensemble of spike patterns fired by cortical neurons (the \"neural vocabulary\") and the relationship between spike patterns and song acoustics (the \"neural code\") change during song acquisition, we quantified how vocal control changes across learning in juvenile Bengalese finches. We found that despite the expected drop in rate variability (a learning-related change in spike vocabulary), the precision of the neural code in the youngest singers is the same as in adults, with 1-2 ms variations in spike timing transduced into quantifiably different behaviors. In contrast, fluctuations in firing rates on longer timescales fail to affect the motor output in both juvenile and adult animals. The consistent presence of millisecond-scale motor coding during changing levels of spike rate and behavioral variability suggests that learning-related changes in cortical activity reflect the brain's changing its spiking vocabulary to better match the underlying motor code, rather than a change in the precision of the code itself.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11463345/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv : the preprint server for biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.27.615500","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
A key goal of the nervous system in young animals is to learn motor skills. Songbirds learn to sing as juveniles, providing a unique opportunity to identify the neural correlates of skill acquisition. Prior studies have shown that spike rate variability in vocal motor cortex decreases substantially during song acquisition, suggesting a transition from rate-based neural control to the millisecond-precise motor codes known to underlie adult vocal performance. By distinguishing how the ensemble of spike patterns fired by cortical neurons (the "neural vocabulary") and the relationship between spike patterns and song acoustics (the "neural code") change during song acquisition, we quantified how vocal control changes across learning in juvenile Bengalese finches. We found that despite the expected drop in rate variability (a learning-related change in spike vocabulary), the precision of the neural code in the youngest singers is the same as in adults, with 1-2 ms variations in spike timing transduced into quantifiably different behaviors. In contrast, fluctuations in firing rates on longer timescales fail to affect the motor output in both juvenile and adult animals. The consistent presence of millisecond-scale motor coding during changing levels of spike rate and behavioral variability suggests that learning-related changes in cortical activity reflect the brain's changing its spiking vocabulary to better match the underlying motor code, rather than a change in the precision of the code itself.