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Strong evidence of an information-theoretical conservation principle linking all discrete systems.

ABSTRACT: Diverse discrete systems share common global properties that lack a unifying theoretical explanation. However, constraining the simplest measure of total information (Hartley-Shannon) in a statistical mechanics framework reveals a principle, the conservation of Hartley-Shannon information (CoHSI) that directly predicts both known and unsuspected common properties of discrete systems, as borne out in the diverse systems of computer software, proteins and music. Discrete systems fall into two categories distinguished by their structure: heterogeneous systems in which there is a distinguishable order of assembly of the system's components from an alphabet of unique tokens (e.g. proteins assembled from an alphabet of amino acids), and homogeneous systems in which unique tokens are simply binned, counted and rank ordered. Heterogeneous systems are characterized by an implicit distribution of component lengths, with sharp unimodal peak (containing the majority of components) and a power-law tail, whereas homogeneous systems reduce naturally to Zipf's Law but with a drooping tail in the distribution. We also confirm predictions that very long components are inevitable for heterogeneous systems; that discrete systems can exhibit simultaneously both heterogeneous and homogeneous behaviour; and that in systems with more than one consistent token alphabet (e.g. digital music), the alphabets themselves show a power-law relationship.

SUBMITTER: Hatton L

PROVIDER: S-EPMC6837184 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Strong evidence of an information-theoretical conservation principle linking all discrete systems.

Hatton Les L Warr Gregory G

Royal Society open science 20191023 10

Diverse discrete systems share common global properties that lack a unifying theoretical explanation. However, constraining the simplest measure of total information (Hartley-Shannon) in a statistical mechanics framework reveals a principle, the conservation of Hartley-Shannon information (CoHSI) that directly predicts both known and unsuspected common properties of discrete systems, as borne out in the diverse systems of computer software, proteins and music. Discrete systems fall into two cate ...[more]

PMID: 31824716

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Project description:This paper introduces a time- and state-dependent measure of integrated information, phi, which captures the repertoire of causal states available to a system as a whole. Specifically, phi quantifies how much information is generated (uncertainty is reduced) when a system enters a particular state through causal interactions among its elements, above and beyond the information generated independently by its parts. Such mathematical characterization is motivated by the observation that integrated information captures two key phenomenological properties of consciousness: (i) there is a large repertoire of conscious experiences so that, when one particular experience occurs, it generates a large amount of information by ruling out all the others; and (ii) this information is integrated, in that each experience appears as a whole that cannot be decomposed into independent parts. This paper extends previous work on stationary systems and applies integrated information to discrete networks as a function of their dynamics and causal architecture. An analysis of basic examples indicates the following: (i) phi varies depending on the state entered by a network, being higher if active and inactive elements are balanced and lower if the network is inactive or hyperactive. (ii) phi varies for systems with identical or similar surface dynamics depending on the underlying causal architecture, being low for systems that merely copy or replay activity states. (iii) phi varies as a function of network architecture. High phi values can be obtained by architectures that conjoin functional specialization with functional integration. Strictly modular and homogeneous systems cannot generate high phi because the former lack integration, whereas the latter lack information. Feedforward and lattice architectures are capable of generating high phi but are inefficient. (iv) In Hopfield networks, phi is low for attractor states and neutral states, but increases if the networks are optimized to achieve tension between local and global interactions. These basic examples appear to match well against neurobiological evidence concerning the neural substrates of consciousness. More generally, phi appears to be a useful metric to characterize the capacity of any physical system to integrate information.

Project description:Almost every biomedical systems analysis requires early decisions regarding the choice of the most suitable representations to be used. De facto the most prevalent choice is a system of ordinary differential equations (ODEs). This framework is very popular because it is flexible and fairly easy to use. It is also supported by an enormous array of stand-alone programs for analysis, including many distinct numerical solvers that are implemented in the main programming languages. Having selected ODEs, the modeler must then choose a mathematical format for the equations. This selection is not trivial as nearly unlimited options exist and there is seldom objective guidance. The typical choices include ad hoc representations, default models like mass-action or Lotka-Volterra equations, and generic approximations. Within the realm of approximations, linear models are typically successful for analyses of engineered systems, but they are not as appropriate for biomedical phenomena, which often display nonlinear features such as saturation, threshold effects or limit cycle oscillations, and possibly even chaos. Power-law approximations are simple but overcome these limitations. They are the key ingredient of Biochemical Systems Theory (BST), which uses ODEs exclusively containing power-law representations for all processes within a model. BST models cover a vast repertoire of nonlinear responses and, at the same time, have structural properties that are advantageous for a wide range of analyses. Nonetheless, as all ODE models, the BST approach has limitations. In particular, it is not always straightforward to account for genuine discreteness, time delays, and stochastic processes. As a new option, we therefore propose here an alternative to BST in the form of discrete Biochemical Systems Theory (dBST). dBST models have the same generality and practicality as their BST-ODE counterparts, but they are readily implemented even in situations where ODEs struggle. As a case study, we illustrate dBST applied to the dynamics of the aryl hydrocarbon receptor (AhR), a signal transduction system that simultaneously involves time delays and stochasticity.

Project description:ObjectiveThis systematic review aimed to: (1) determine the prevalence and scope of existing research on human resource information systems (HRIS) in health organizations; (2) analyze, classify, and synthesize evidence on the processes and impacts of HRIS development, implementation, and adoption; and (3) generate recommendations for HRIS research, practice, and policy, with reference to the needs of different stakeholders.MethodsA structured search strategy was used to interrogate 10 electronic databases indexing research from the health, social, management, technology, and interdisciplinary sciences, alongside gray literature sources and reference lists of qualifying studies. There were no restrictions on language or publication year. Two reviewers screened publications, extracted data, and coded findings according to the innovation stages covered in the studies. The Critical Appraisal Skills Program checklist was adopted to assess study quality. The process of study selection was charted using a Preferred Items for Systematic Reviews and Meta-Analysis (PRISMA) diagram.ResultsOf the 6824 publications identified by the search strategy, 68, covering 42 studies, were included for final analysis. Research on HRIS in health was interdisciplinary, often atheoretical, conducted primarily in the hospital sector of high-income economies, and largely focused uncritically on use and realized benefits.Discussion and conclusionsWhile studies of HRIS in health exist, the overall lack of evaluative research raises unanswered questions about their capacity to improve quality and efficiency and enable learning health systems, as well as how sociotechnical complexity influences implementation and effectiveness. We offer this analysis to decision makers and managers considering or currently implementing an HRIS, and make recommendations for further research.Trial registrationInternational Prospective Register of Systematic Reviews (PROSPERO): CRD42015023581. http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42015023581#.VYu1BPlVjDU .

Dataset Information

Strong evidence of an information-theoretical conservation principle linking all discrete systems.

Publications

Strong evidence of an information-theoretical conservation principle linking all discrete systems.

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