...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Journal of Neurophysiology >Top-Down Regulation of Plasticity in the Birdsong System: 'Premotor' Activity in the Nucleus HVC Predicts Song Variability Better Than It Predicts Song Features.
【24h】

Top-Down Regulation of Plasticity in the Birdsong System: 'Premotor' Activity in the Nucleus HVC Predicts Song Variability Better Than It Predicts Song Features.

机译：自上而下调节鸟类歌曲系统中的可塑性：HVC核中的“前运动”活动预测的歌曲变异性胜于预测歌曲的特征。

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We studied real-time changes in brain activity during active vocal learning in the zebra finch songbird. The song nucleus HVC is required for the production of learned song. To quantify the relationship of HVC activity and behavior, HVC population activity during repeated vocal sequences (motifs) was recorded and temporally aligned relative to the motif, millisecond by millisecond. Somewhat surprisingly, HVC activity did not reliably predict any vocal feature except amplitude and, to a lesser extent, entropy and pitch goodness (sound periodicity). Variance in "premotor" HVC activity did not reliably predict variance in behavior. In contrast, HVC activity inversely predicted the variance of amplitude, entropy, frequency, pitch, and FM. We reasoned that, if HVC was involved in song learning, the relationship of HVC activity to learned features would be developmentally regulated. To test this hypothesis, we compared the HVC song feature relationships in adults and juveniles in the sensorimotor "babbling" period. We found that the relationship of HVC activity to variance in FM was developmentally regulated, with the greatest difference at an HVC vocalization lag of 50 ms. Collectively, these data show that, millisecond by millisecond, bursts in HVC activity predict song stability on-line during singing, whereas decrements in HVC activity predict plasticity. These relationships between neural activity and plasticity may play a role in vocal learning in songbirds by enabling the selective stabilization of parts of the song that match a learned tutor model.
机译：我们研究了在斑马雀科鸣禽的主动发声学习过程中大脑活动的实时变化。歌曲核HVC是生成学习歌曲所必需的。为了量化HVC活性与行为之间的关系，记录了重复的声音序列（基序）中的HVC群体活动，并相对于主题在时间上进行了毫秒（毫秒）对齐。令人惊讶的是，HVC活动不能可靠地预测任何声音特征，只有振幅，以及在较小程度上是熵和音高（声音周期性）。 “运动前” HVC活动的差异不能可靠地预测行为差异。相反，HVC活动反向预测振幅，熵，频率，音高和FM的变化。我们认为，如果HVC参与了歌曲学习，那么HVC活动与所学功能之间的关系将受到发展调节。为了验证这一假设，我们比较了感觉运动“冒泡”时期成人和青少年的HVC歌曲特征关系。我们发现，HVC活动与FM方差之间的关系受到发育调节，在HVC发声延迟为50毫秒时差异最大。总的来说，这些数据表明，每毫秒毫秒，HVC活动的爆发预示着唱歌过程中的歌曲稳定性，而HVC活动的减少预示了可塑性。神经活动和可塑性之间的这些关系可能通过使歌曲中与学习的导师模型匹配的部分的选择性稳定化而在鸣禽的声音学习中发挥作用。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号