An Information Theoretic Approach to Stimulus Processing in the Olfactory System II

嗅觉系统刺激处理的信息论方法 II

• 批准号: 214286491
• 负责人: Professor Dr. Rudolf Mathar
• 金额: --
• 依托单位: Arbeitsgruppe Chemosensorik
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2012
• 资助国家: 德国
• 起止时间: 2011-12-31 至 2016-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/214286491?language=en
• 关键词: Information; Theoretic; Approach; Stimulus; Processing

A fundamental question in neurobiology is how external stimuli are coded by the activity of neurons in the brain. An emerging prototypical model system to address this question is in the neuronal network of the mouse OB. For neurons in general, stimuli have dimensions of millivolts per millisecond and action potentials (spikes) are the sole binary means of both encoding and propagating information. How exactly stimulus information is transformed and contained in spike trains of output neurons, however, remains controversial. The relative anatomical simplicity of the OB, the combined computation of sensory and state-dependent activity within the OB network, and its direct (and partly reciprocal) connection to the cortex, bypassing the sensory thalamus, render the OB an attractive model to study the basic principles of sensory information processing.As a corollary to the on-going research detailed in our previous proposal, we now aim to extend and refine the scope of information theoretic models to more closely match / describe neuronal communication and network processing in the mouse OB model. Specific predictions / hypotheses based on extended channel models will then be systematically investigated in neurophysiological experiments and, in turn, model parameters will be adapted according to experimental findings. While we intentionally confine ourselves to the mouse olfactory system, we expect that the obtained results can be largely generalized to a variety of (neuro)biological communication systems. Following the research logic of the current funding period, we propose a multi-disciplinary strategy that will focus on two major goals:A. Neurobiologists will be provided with analytical models to simulate neural information processing on a purely numerical basis - an innovative approach that we expect to be instrumental in gaining novel insights into the principle rules that govern sensory coding in the brain.B. Neural information coding and propagation is robust, energy efficient and highly error tolerant. Nonetheless, neural networks are fast and efficient - features sought after in technical communication systems. Using models and analyses that emerge from our collaborative efforts, we will adapt bio-inspired design principles to the field of communications, which in the past has turned out very fruitful for a variety of applications.We firmly believe that synergy from theoretical and experimental approaches will substantially advance our understanding of brain computations and, in parallel, fuel novel ideas in communication theory.

神经生物学的一个基本问题是外部刺激是如何被大脑中神经元的活动编码的。解决这个问题的一个新出现的原型模型系统是在小鼠OB的神经网络中。对于一般的神经元，刺激具有每毫秒毫伏的尺寸，动作电位（尖峰）是编码和传播信息的唯一二进制手段。然而，刺激信息究竟是如何转化并包含在输出神经元的尖峰序列中，仍然存在争议。OB相对简单的解剖结构，OB网络中感觉和状态依赖活动的组合计算，以及它与皮层的直接（部分互惠）连接，绕过感觉丘脑，使OB成为研究感觉信息处理基本原理的一个有吸引力的模型。作为我们在之前的提案中详细描述的正在进行的研究的推论，我们现在的目标是扩展和完善信息理论模型的范围，以更紧密地匹配/描述小鼠OB模型中的神经元通信和网络处理。基于扩展通道模型的具体预测/假设将在神经生理学实验中进行系统研究，反过来，模型参数将根据实验结果进行调整。虽然我们有意将自己局限于小鼠的嗅觉系统，但我们希望所获得的结果可以在很大程度上推广到各种（神经）生物通信系统。根据当前资助期的研究逻辑，我们提出了一个多学科战略，将重点关注两个主要目标：a。我们将为神经生物学家提供分析模型，在纯粹的数值基础上模拟神经信息的处理——我们期望这种创新的方法有助于对控制大脑感觉编码的基本规则获得新的见解。神经信息编码和传播具有鲁棒性、高能效和高容错性。尽管如此，神经网络具有快速和高效的特点，这是技术通信系统所追求的。利用我们共同努力产生的模型和分析，我们将把生物启发的设计原则应用到通信领域，这在过去已经在各种应用中取得了丰硕的成果。我们坚信，理论和实验方法的协同作用将极大地促进我们对大脑计算的理解，同时，为通信理论的新思想提供动力。