Collective Phenomena in Neural Population Codes

几乎在大脑的每一个部分，关于感觉环境、内部身体状态或预期运动的信息都由不止一个神经元编码。这一点早在世纪就已经从附近神经元的广泛互连性中显而易见，并且从对附近神经元的调谐曲线和相关性的大量测量中仍然显而易见。尽管群体神经密码至关重要，但人们对它的了解却很少。在这个项目中，PI将联合收割机结合大规模神经记录方法和最先进的理论分析来研究群体神经代码中的集体现象。该项目将把视网膜作为一个模型系统，实验数据的质量和完整性是最大的。该项目将使我们彻底而清晰地了解在人口水平上产生临界性所需的“成分”，这对于产生关于大脑其他区域可能在其人口代码中表现出临界性的假设非常重要。它还将探索一个新的假设，即临界种群状态如何产生神经代码的离散方面，以及对神经噪声具有高度鲁棒性的方面。这可以让我们对我们如何毫不费力地将感官世界划分为对象有新的见解。 PI在脊椎动物视网膜的多电极记录中具有广泛的跟踪记录，沿着应用最大熵模型来分析网络活动的状态。PI假设视网膜群体密码具有不寻常的和非平凡的结构，它类似于物理系统中的临界状态。这种结构导致了神经活动的“集体模式”的定义，这是一组将视觉刺激分组为离散类的神经活动状态。这些集体模式构成了一个关于群体神经编码的新假设，它与单神经元水平上的信息编码观点有质的不同。拟议项目的目标是：理解临界性的起源，包括研究刺激中相关性的作用，使用适应性来测试视网膜回路是如何被调整以产生临界性的，研究任何网络产生临界性所需的相关性的模式和强度，并制定感受野模型，以了解在不同的网络中需要何种程度的重叠和功能异质性。定义神经活动的集体模式，并研究它们编码的刺激以及它们被给定视觉刺激激活的可靠性。拟议工作的更广泛影响在于沿着三个不同的方向：（i）开发关于群体神经代码的新概念的潜力，这些新概念可以证明适用于许多不同的大脑区域;（ii）开发和传播软件，以执行最大熵拟合神经数据，这可能有助于刺激许多实验室的研究计划，这些实验室使用这些方法来分析神经群体;（3）拓宽了我们对物理学中临界系统的认识，使之包括了非对称系统，生物学中发现的中间案例。该项目由物理学系的生命系统物理学项目和生物学系的细胞动力学和功能项目共同支持。整合有机系统。

In virtually every part of the brain, information about the sensory environment, internal body states, or intended movements is encoded by more than one neuron. This was apparent as early as the nineteenth century from the extensive interconnectivity of nearby neurons and continues to be apparent from numerous measurements of the tuning curves and correlation of nearby neurons. Despite its fundamental importance, population neural codes are poorly understood. In this project, the PI will combine large-scale neural recording methods with state-of-the-art theoretical analyses to study collective phenomena in population neural codes. The project will focus on the retina as a model system, where the quality and completeness of experimental data is the greatest. The project will give us a thorough and clear understanding of what are the "ingredients" needed at the population level to give rise to criticality, which will be important in generating hypotheses about what other regions of the brain might exhibit criticality in their population codes. It will also explore a novel hypothesis about how critical population states give rise to a discrete aspect of the neural code and one that is highly robust to neural noise. This could give us new insight into how we effortlessly divide the sensory world into objects. The PI has an extensive track record in multi-electrode recording from the vertebrate retina, along with applying maximum entropy models to analyze states of network activity. The PI hypothesizes that the retinal population code has an unusual and nontrivial structure that it analogous to the critical state in physical systems. This structure leads to the definition of a "collective mode" of neural activity, which is a set of neural activity states that groups visual stimuli into discrete classes. These collective modes constitute a novel hypothesis about population neural codes that is qualitatively different from the view of information encoding at the single-neuron level. The proposed projects aims are: understanding the origin of criticality, including studying the role of correlations in the stimulus, using adaptation to test how specifically retinal circuitry is tuned to give rise to criticality, studying the pattern and strength of correlation required for any network to give rise to criticality as well as formulating receptive field models to see what degrees of overlap and functional heterogeneity are required in defining collective modes of neural activity and studying what stimuli they encode and how reliably they are activated by a given visual stimulus. The broader impacts of the proposed work lie along three distinct directions:(i) the potential to develop new concepts about population neural codes that could prove applicable across many different brain regions; (ii) the development and dissemination of software to perform maximum entropy fits to neural data, which could help spur on the research programs of many labs that use these methods to analyze neural populations; (iii) the broadening of our ideas about critical systems in physics to include the kind of asymmetric, intermediate cases found in biology.This project is being jointly supported by the Physics of Living Systems program in the Division of Physics and the Cellular Dynamics and Function Program in the Division of Integrative Organismal Systems.