What The Retina Might Know About Natural Scenes

生物有机体从自然环境中收集它们生存所必需的信息。负责收集这些数据的神经系统设计的一个重要事实是它们具有巨大的并行性。例如，视网膜表达至少15种平行的信息通道，这些通道将与行为相关的不同类型的信息传输到大脑，而不是使用几条带有适当复杂代码的通用电缆。一个典型的例子是视觉系统中的开和离通路的分离，以在场景的明暗特征中处理信息。这些平行的通道具有惊人的异质性，神经纤维直径的50倍范围和电压尖峰放电频率的10倍范围。是什么决定了这种大规模并行设计的选择，以及所表达的特定渠道？这个项目将探索一个基本假设：平行通道的存在可以最大限度地减少从自然刺激中提取与行为相关的信息并将其传输到大脑所需的代谢和空间成本。为了实现这一目标，PI打算1)检查由不同视网膜神经元编码的时间精度、重复性、信息率和每峰信息，2)研究神经元电路结构如何与自然图像的结构相关，3)测量不同通道的空间和代谢成本，并检查并行性如何影响信息传输。该项目旨在开发新的理论和分析技术，以研究神经编码中的时空限制，适应不断变化的刺激统计，以及为什么需要昂贵的大细胞来以高平均速率传输信息的生物物理学。这个项目，结合理论物理学和实验生物学，将产生广泛的跨学科影响：(A)培训物理学研究生神经科学的问题和技术，以及(B)将物理学的分析和理论工具转移给神经科学家。国际物理学会还通过在宾夕法尼亚大学和卡夫利理论物理研究所组织物理-神经科学联合讲习班，鼓励物理学和生物学之间的这种协同作用。

Biological organisms collect information from the natural environment that is necessary for their survival. A significant fact about the design of the neural systems responsible for collecting this data is their massive parallelism. For example, the retina expresses at least 15 kinds of parallel information channels which transmit different kinds of information relevant to behaviour to the brain, rather than using a few general purpose cables with a suitably complicated code. A prototypical example is the segregation of ON and OFF pathways in the visual system to process information in bright vs. dark features of a scene. The parallel channels are strikingly heterogeneous, spanning a 50-fold range in nerve fiber diameter and a 10-fold range in voltage spike firing rate. What determines this choice of massively parallel design, and the particular channels that are expressed? This project will explore a basic hypothesis: parallel channels exist to minimize the metabolic and spatial costs necessary to extract behaviorally relevant information from natural stimuli and transmit it to the brain. To accomplish this goal, the PI intends to 1) examine timing precision, reproducibility, information rate, and information per spike encoded by different retinal neurons, 2) study how neuronal circuit structure relates to the structure of natural images, and 3) measure spatial and metabolic costs of different channels and examine how parallelism affects information transmission. The project intends to develop new theory and analysis techniques to study spatio-temporal constraints in neural coding, adaptation to changing stimulus statistics and the biophysics of why large, expensive cells appear to be needed to transmit information at high average rates.This project, joining theoretical physics and experimental biology, will have a broad inter-disciplinary impact by: (a) training physics graduate students in the problems and techniques of neuroscience, and (b) transferring analytical and theoretical tools of physics to neuroscientists. The PI is also involved in encouraging such synergy between physics and biology by organizing joint physics-neuroscience workshops at Penn and at the Kavli Institute for Theoretical Physics.