ReviewPhilosophical transactions. Series A, Mathematical, physical, and engineering sciences2022
Greater than the parts: a review of the information decomposition approach to causal emergence.
Review in Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
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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.
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Who cites it
31 citing papers in PubMed.
- Evolving reservoir computers reveal bidirectional coupling between predictive power and emergent dynamics.Patterns (New York, N.Y.) · 2026Article
- Emergent multiscale organisation of neural dynamics fragments in anaesthesia.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Identifying and investigating emergent behaviour in neural systems.Frontiers in neuroscience · 2026Article
- We need to explain subjective experience, but its explanation may not be mechanistic.Neuroscience of consciousness · 2026Article
- Null models for comparing information decomposition across complex systems.PLoS computational biology · 2025Article
- Toward a unified taxonomy of information dynamics via Integrated Information Decomposition.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Consilience in Causation: Causal Emergence Is Found Across Measures of Causation.Entropy (Basel, Switzerland) · 2025Article
- Entropy and Complexity Tools Across Scales in Neuroscience: A Review.Entropy (Basel, Switzerland) · 2025Review
- Graph models of brain state in deep anesthesia reveal sink state dynamics of reduced spatiotemporal complexity.Network neuroscience (Cambridge, Mass.) · 2025Article
- Dynamic Network Plasticity and Sample Efficiency in Biological Neural Cultures: A Comparative Study with Deep Reinforcement Learning.Cyborg and bionic systems (Washington, D.C.) · 2025Article
- Synergy as the Failure of Distributivity.Entropy (Basel, Switzerland) · 2024Article
- Two Levels of Integrated Information Theory: From Autonomous Systems to Conscious Life.Entropy (Basel, Switzerland) · 2024Article
- A synergistic workspace for human consciousness revealed by Integrated Information Decomposition.eLife · 2024Article
- Viscous dynamics associated with hypoexcitation and structural disintegration in neurodegeneration via generative whole-brain modeling.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Embodied Neural Systems Can Enable Iterative Investigations of Morally Relevant States.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Article
- Article
- The case for neurons: a no-go theorem for consciousness on a chip.Neuroscience of consciousness · 2024Article
- The serotonergic psychedelic N,N-dipropyltryptamine alters information-processing dynamics in in vitro cortical neural circuits.Network neuroscience (Cambridge, Mass.) · 2024Article
- How to be an integrated information theorist without losing your body.Frontiers in computational neuroscience · 2024Article
- Content-state dimensions characterize different types of neuronal markers of consciousness.Neuroscience of consciousness · 2024Article
Corrections and comments
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8 authors.
Funding
Abstract
Emergence is a profound subject that straddles many scientific disciplines, including the formation of galaxies and how consciousness arises from the collective activity of neurons. Despite the broad interest that exists on this concept, the study of emergence has suffered from a lack of formalisms that could be used to guide discussions and advance theories. Here, we summarize, elaborate on, and extend a recent formal theory of causal emergence based on information decomposition, which is quantifiable and amenable to empirical testing. This theory relates emergence with information about a system's temporal evolution that cannot be obtained from the parts of the system separately. This article provides an accessible but rigorous introduction to the framework, discussing the merits of the approach in various scenarios of interest. We also discuss several interpretation issues and potential misunderstandings, while highlighting the distinctive benefits of this formalism. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.
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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.