Measuring Information Transfer

2000/01/19 by Thomas Schreiber · 22 citations
Agricultural and Biological Sciences · Economics, Econometrics and Finance · Mathematics · Neuroscience · Physics and Astronomy · #Artificial intelligence #Asymmetry #Coherence (philosophical gambling strategy) #Complex Systems and Time Series Analysis #Computer science #Conditional mutual information #Data mining #Entropy (arrow of time) #Information diagram #Information theory #Information transfer #Joint quantum entropy #Mathematics #Maximum entropy thermodynamics #Measure (data warehouse) #Mutual information #Neural dynamics and brain function #Physics #Plant and Biological Electrophysiology Studies #Principle of maximum entropy #Quantum mechanics #Statistical physics #Statistics #Telecommunications #Transfer (computing) #Transfer entropy #nlin.CD

paper · pdf · doi:10.1103/physrevlett.85.461

published as Phys. Rev. Lett. 85 (2000) 461 · 4 pages, 4 Figures, Revtex

arxiv created 2000/01/19 · openalex publication_date 2000/07/10 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05

Abstract

An information theoretic measure is derived that quantifies the statistical coherence between systems evolving in time. The standard time delayed mutual information fails to distinguish information that is actually exchanged from shared information due to common history and input signals. In our new approach, these influences are excluded by appropriate conditioning of transition probabilities. The resulting transfer entropy is able to distinguish effectively driving and responding elements and to detect asymmetry in the interaction of subsystems.

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