ArticleScientific reports2014
Transfer entropy and transient limits of computation.
Article in Scientific reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed.
- A combined study of molecular dynamics simulations, information theory, molecular graph theory, and machine learning in protein structure and dynamics.Journal of computer-aided molecular design · 2026Article
- Detecting existence of a hidden mediator between a pair of individual time series.Scientific reports · 2025Article
- Landauer Bound in the Context of Minimal Physical Principles: Meaning, Experimental Verification, Controversies and Perspectives.Entropy (Basel, Switzerland) · 2024Article
- Fractal Geometry Meets Computational Intelligence: Future Perspectives.Advances in neurobiology · 2024Article
- The Consensus Problem in Polities of Agents with Dissimilar Cognitive Architectures.Entropy (Basel, Switzerland) · 2022Article
- Direction of information flow between brain regions in ADHD and healthy children based on EEG by using directed phase transfer entropy.Cognitive neurodynamics · 2021Article
- Measuring information flux between social media and stock prices with Transfer Entropy.PloS one · 2021Article
- Transfer entropy as a variable selection methodology of cryptocurrencies in the framework of a high dimensional predictive model.PloS one · 2020Article
- Thermodynamic efficiency of contagions: a statistical mechanical analysis of the SIS epidemic model.Interface focus · 2018Article
- The thermodynamic efficiency of computations made in cells across the range of life.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2017Article
- A regime shift in the Sun-Climate connection with the end of the Medieval Climate Anomaly.Scientific reports · 2017Article
- Directional information flow in patients with Alzheimer's disease. A source-space resting-state MEG study.NeuroImage. Clinical · 2017Article
- Information theoretic approaches for inference of biological networks from continuous-valued data.BMC systems biology · 2016Article
- Neurobiology as Information Physics.Frontiers in systems neuroscience · 2016Review
- New scaling relation for information transfer in biological networks.Journal of the Royal Society, Interface · 2015Article
- Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis.Scientific reports · 2015Article
- Extracting information from qubit-environment correlations.Scientific reports · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Transfer entropy is a recently introduced information-theoretic measure quantifying directed statistical coherence between spatiotemporal processes, and is widely used in diverse fields ranging from finance to neuroscience. However, its relationships to fundamental limits of computation, such as Landauer's limit, remain unknown. Here we show that in order to increase transfer entropy (predictability) by one bit, heat flow must match or exceed Landauer's limit. Importantly, we generalise Landauer's limit to bi-directional information dynamics for non-equilibrium processes, revealing that the limit applies to prediction, in addition to retrodiction (information erasure). Furthermore, the results are related to negentropy, and to Bremermann's limit and the Bekenstein bound, producing, perhaps surprisingly, lower bounds on the computational deceleration and information loss incurred during an increase in predictability about the process. The identified relationships set new computational limits in terms of fundamental physical quantities, and establish transfer entropy as a central measure connecting information theory, thermodynamics and theory of computation.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.