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首页> 外文期刊>Physica, A. Statistical mechanics and its applications >Seeking the foundations of cognition in bacteria: From Schrodinger's negative entropy to latent information
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Seeking the foundations of cognition in bacteria: From Schrodinger's negative entropy to latent information

机译：寻找细菌的认知基础：从薛定inger的负熵到潜在信息

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We reexamine Schrodinger's reflections on the fundamental requirements for life in view of new observations about bacterial self-organization and the emerging understanding of gene-network regulation mechanisms and dynamics. Focusing on the energy, matter and thermodynamic imbalances provided by the environment, Schrodinger proposed his consumption of negative entropy requirement for life. We take the criteria further and propose that, besides "negative entropy", organisms extract latent information embedded in the complexity of their environment. By latent information we refer to the non-arbitrary spatio-temporal patterns of regularities and variations that characterize the environmental dynamics. Hence it can be used to generate an internal condensed description (model or usable information) of the environment which guides the organisms functioning. Accordingly, we propose that Schrodinger's criterion of "consumption of negative entropy" is not sufficient and "consumption of latent information" is an additional fundamental requirement of Life. In other words, all organisms, including bacteria, the most primitive (fundamental) ones, must be able to sense the environment and perform internal information processing for thriving on latent information embedded in the complexity of their environment. We then propose that by acting together, bacteria can perform this most elementary cognitive function more efficiently as can be illustrated by their cooperative behavior (colonial or inter-cellular self-organization). As a member of a complex superorganism-the colony-each unit (bacteria) must possess the ability to sense and communicate with the other units comprising the collective and perform its task within a distribution of tasks. Bacterial communication thus entails collective sensing and cooperativity. The fundamental (primitive) elements of cognition in such systems include interpretation of (chemical) messages, distinction between internal and external information, and some self vs., non-self distinction (peers and cheaters). We outline how intra-cellular self-organization together with genome plasticity and membrane dynamics might, in principle, provide the intra-cellular mechanisms needed for these fundamental cognitive functions. In regard to intra-cellular processes, Schrodinger postulated that new physics is needed to explain the convertion of the genetically stored information into a functioning cell. At present, his ontogenetic dilemma is generally perceived to be solved and is attributed to a lack of knowledge when it was proposed. So it is widely accepted that there is no need for some unknown laws of physics to explain cellular ontogenetic development. We take a different view and in Schrodinger's foot steps suggest that yet unknown physics principles of self-organization in open systems are missing for understanding how to assemble the cell's component into an information-based functioning "machine". (c) 2005 Elsevier B.V. All rights reserved.
机译：鉴于细菌自组织的新发现以及对基因网络调节机制和动力学的新认识，我们重新审视了薛定inger对生命基本要求的思考。 Schrodinger着眼于环境提供的能量，物质和热力学不平衡，提出了他对生命负熵需求的消耗。我们进一步采用该标准，并提出除了“负熵”之外，生物还提取嵌入其环境复杂性中的潜在信息。通过潜在信息，我们指的是表征环境动态的规律性和变异性的非任意时空模式。因此，它可用于生成指导生物体功能的内部浓缩环境描述（模型或可用信息）。因此，我们认为薛定inger准则的“负熵的消耗”是不够的，而“潜在信息的消耗”是生命的另一个基本要求。换句话说，所有生物，包括细菌，最原始的（基本的）细菌，都必须能够感知环境并执行内部信息处理，以获取嵌入在环境复杂性中的潜在信息。然后我们提出，通过共同行动，细菌可以更有效地执行这种最基本的认知功能，这可以通过它们的协作行为（殖民地或细胞间的自组织）来说明。作为复杂的超级生物的成员，每个菌落（细菌）必须具备感知和与组成该集体的其他单位进行交流的能力，并在任务分配范围内执行其任务。因此，细菌交流需要集体感知和合作。在这种系统中，认知的基本（原始）元素包括（化学）信息的解释，内部和外部信息之间的区分，以及一些自我与非自我的区别（同伴和作弊者）。我们概述了细胞内自组织与基因组可塑性和膜动力学一起原则上如何提供这些基本认知功能所需的细胞内机制。关于细胞内过程，Schrodinger假定需要新的物理学来解释遗传存储的信息向功能细胞的转化。目前，人们普遍认为他的本体论难题已得到解决，这归因于提出时缺乏知识。因此，人们普遍认为不需要某些未知的物理定律来解释细胞个体发育。我们采取了不同的观点，并以薛定inger的脚步表明，在开放系统中缺少未知的自组织物理学原理，无法理解如何将细胞的组件组装成基于信息的功能“机器”。 （c）2005 Elsevier B.V.保留所有权利。

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