CRCNS: Optimality principles of auditory representations

描述（由申请人提供）：我们的项目将集中在听觉系统中的感觉表征，有两个总体目标。首先，我们将采用一种实验策略，要求对听觉系统进行最佳探测。我们将确定如何复杂的声音刺激在不同的空间位置表示在多个阶段的听觉通路在清醒的绒猴通过改进的最佳设计方法最近由同一团队的合作研究可行。这种方法在神经生理学记录期间在线工作，通过生成最大化关于分层神经网络模型获得的信息的声音刺激。在线实验得到的模型提供了一个准确的描述复杂的听觉反应，丰富的声音刺激在三维空间中，同时，我们也得到了一个合理的网络解释，如何在下丘和听觉皮层的复杂反应特性可能会产生多个声音定位线索组合在较低的水平在听觉通路。第二，我们将从假设神经种群是针对真实的世界情况优化的开始，我们将确定实验中测量的神经元反应特性的丰富多样性和异质性是否可以通过假设它们实际上形成了针对自然声音优化的有效种群来解释。预期的结果是一个原则性的计算解释的复杂性神经元群体的声音定位，包括所有的多样性和变异性与各种功能细胞类型。 智力优点：了解神经活动与外界刺激之间的关系是系统神经科学的基本目标之一。我们的合作研究可能有助于解决听觉神经科学中一个长期存在的问题，即听觉皮层和下丘的神经元反应如何在整个360 °方位角和高度范围内表示空间。我们的方法是非常普遍的，应该很容易适用于其他感官形式。特别是，最优设计方法可以尽可能快地获得刺激-反应景观的全局图像，这种快速特性对于与清醒和行为良好的动物甚至人类一起工作特别有价值。我们的研究结果可以扩展到许多学科时，需要有效地探测一个参数化的输入输出系统，或优化人口的传感器。例如，这里开发的思想和方法可以用于指导实际的神经形态工程设计或优化人工传感器的种群，这可能会发现许多实际应用。我们的研究结果也将提供一个坚实的概念基础和一套建模工具，以定性异常或疾病状态的听觉系统在皮层和皮层下的水平处理复杂的声音信号。这一进展可能会导致各种神经系统疾病的可行疗法的发展，它可以通过在声音定位线索的帮助下更好地解析复杂的听觉场景来改善神经假体的发展。 更广泛的影响：该项目有助于在几个层次的教学。它将为两名研究生提供研究培训，这些研究的结果预计将构成他们博士学位的大部分。论文此外，一名博士后研究员将接受计算神经科学合作研究的研究培训。将努力让广泛的学生和研究人员参与，并广泛宣传这些职位，以确保任职人数不足的合格候选人了解这些机会。这项研究也将纳入我们的教育工作，将结果纳入课程开发的研究生和本科生在约翰霍普金斯大学。培训，教育和推广部分将直接影响大量的学生和大学以外的其他群体，使他们接触到神经生理学和计算神经科学的开放性问题和跨学科研究方法。PI和共同PI致力于提高妇女和在研究和教育中代表性不足的少数民族的地位。此外，拟议的工作将加强我们的基础设施，进一步研究开拓新的记录技术，是基于闭环自动刺激设计。这项研究将在许多场合传播，包括国家和国际会议以及同行评审的期刊。在适用的情况下，我们的研究结果也将在流行的非技术文献中传播。与这项工作有关的所有软件将在互联网上免费提供，为该项目收集的数据的适当子集将在CRCNS资助的数据共享设施上提供。

DESCRIPTION (provided by applicant): Our project will be focused on sensory representations in the auditory system with two overall objectives. First, we will adopt an experimental strategy that calls for optimal probing of the auditory system. We will determine how complex sound stimuli at different spatial locations are represented at multiple stages of the auditory pathway in awake marmoset monkeys by improving an optimal design approach recently made feasible by the collaborative research by the same team. This method works online, during neurophysiological recording, by generating sound stimuli that maximize the information gained about a hierarchical neural network model. A model attained from the online experiment provides an accurate description of complex auditory responses to rich sound stimuli in three dimensional space, and at the same time we also obtain a plausible network explanation of how complex response properties in inferior colliculus and auditory cortex might arise from combining multiple sound localization cues at lower levels in the auditory pathway. Second, we will start with the hypothesis that neural populations are optimized for real world situations, and we will determine whether the rich variety and heterogeneity of neuronal response properties measured in experiments can be explained by the hypothesis that they actually form an efficient population optimized for natural sounds. The expected outcome is a principled computational explanation for the complexity of neuronal populations for sound localization, including all the diversity and variability associated with various functional cell types. Intellectual merit: Understanding the relationship between neural activity and the stimuli from the external world is one of the basic goals in systems neuroscience. Our collaborative research may help resolve a longstanding problem in auditory neuroscience concerning how neuronal responses in auditory cortex and inferior colliculus represent space over the full 360� range of azimuths and elevations. Our approach is very general and should apply readily to other sensory modalities as well. In particular, the optimal design method can obtain a global picture of the stimulus-response landscape as fast as possible, and this speedy feature is especially valuable for working with awake and behaving animals, and even humans. Our results may extend to many disciplines whenever one needs to efficiently probe a parameterized input-output system, or to optimize a population of sensors. For example, the ideas and the methods developed here could be used to guide practical neuromorphic engineering designs or to optimize populations of artificial sensors, which may find many practical applications. Our results will also provide a solid conceptual basis and a set of modeling tools to qualify abnormal or diseased states of the auditory system at both the cortical and subcortical levels for processing of complex sound signals. This progress could lead to the development of viable therapies for various neurological disorders, and it could improve the development of neural prostheses by better parsing complex auditory scenes with the help of sound localization cues. Broader impact: This project contributes to teaching at several levels. It will provide research training to two graduate students and the results of these studies are expected to constitute the bulk of their Ph.D. theses. In addition, a postdoctoral fellow will receive research training in collaborative research in computational neuroscience. Efforts will be made to include participation from students and researchers over a wide demographic, and the positions will be broadly advertised to ensure that qualified underrepresented candidates are aware of the opportunities. This research will also be integrated into our educational efforts by incorporating results into courses developed for both graduate and undergraduate students at Johns Hopkins University. The training, educational and outreach components will directly affect a large number of students and other groups outside of the university by exposing them to open problems and interdisciplinary research methods in neurophysiology and computational neuroscience. The PI and co-PIs are committed to advancement of women and underrepresented minorities in research and education. Furthermore, the proposed work will strengthen our infrastructure for further studies by pioneering new recording techniques that are based on closed-loop automated stimulus design. The research will be disseminated in many venues, including national and international meetings and peer reviewed journals. When applicable, our results will be disseminated in popular, non-technical literature as well. All software associated with this work will be made freely available on the internet, and appropriate subsets of the data collected for this project will be made available on the CRCNS-funded data sharing facility.