• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Annual Conference on Neural Information Processing Systems >Receptive Fields without Spike-Triggering
【24h】

Receptive Fields without Spike-Triggering

机译：没有尖峰触发的接收场

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Stimulus selectivity of sensory neurons is often characterized by estimating their receptive field properties such as orientation selectivity. Receptive fields are usually derived from the mean (or covariance) of the spike-triggered stimulus ensemble. This approach treats each spike as an independent message but does not take into account that information might be conveyed through patterns of neural activity that are distributed across space or time. Can we find a concise description for the processing of a whole population of neurons analogous to the receptive field for single neurons? Here, we present a generalization of the linear receptive field which is not bound to be triggered on individual spikes but can be meaningfully linked to distributed response patterns. More precisely, we seek to identify those stimulus features and the corresponding patterns of neural activity that are most reliably coupled. We use an extension of reverse-correlation methods based on canonical correlation analysis. The resulting population receptive fields span the subspace of stimuli that is most informative about the population response. We evaluate our approach using both neuronal models and multi-electrode recordings from rabbit retinal ganglion cells. We show how the model can be extended to capture nonlinear stimulus-response relationships using kernel canonical correlation analysis, which makes it possible to test different coding mechanisms. Our technique can also be used to calculate receptive fields from multi-dimensional neural measurements such as those obtained from dynamic imaging methods.
机译：感觉神经元的刺激选择性通常以估计其感受野特性（例如方向选择性）为特征。感受野通常来自于尖峰触发的刺激集合的平均值（或协方差）。这种方法将每个尖峰视为独立的消息，但没有考虑到信息可能会通过分布在空间或时间上的神经活动模式来传达。我们能找到一个简单的描述来处理整个神经元群体，类似于单个神经元的感受野吗？在这里，我们介绍了线性接受域的一般化，它不必然在单个尖峰上触发，但可以有意义地链接到分布式响应模式。更确切地说，我们试图确定最可靠地耦合的那些刺激特征和相应的神经活动模式。我们使用基于规范相关分析的反向相关方法的扩展。由此产生的种群感受野跨越了对种群反应最有帮助的刺激子空间。我们使用来自兔视网膜神经节细胞的神经元模型和多电极记录来评估我们的方法。我们展示了如何使用内核规范相关分析扩展该模型以捕获非线性刺激-响应关系，从而可以测试不同的编码机制。我们的技术还可以用于从多维神经测量（例如从动态成像方法获得的测量）来计算感受野。

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