ReviewNature neuroscience2021
Causal reductionism and causal structures.
Review in Nature neuroscience, 2021. 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
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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.
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.
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Who cites it
17 citing papers in PubMed.
- Structure Guides Function: Beyond Pairwise Neural Interactions.The Journal of comparative neurology · 2026Review
- When Wholes Resist Decomposition: A Spectral Measure of Epistemic Emergence.Entropy (Basel, Switzerland) · 2026Article
- Quantifying emergent complexity.Patterns (New York, N.Y.) · 2026Article
- We need to explain subjective experience, but its explanation may not be mechanistic.Neuroscience of consciousness · 2026Article
- Intrinsic units: identifying a system's causal grain.Neuroscience of consciousness · 2026Article
- Inferring internal states across mice and monkeys using facial features.Nature communications · 2025Article
- The Brain's Best Kept Secret Is Its Degenerate Structure.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2024Review
- The Fundamental Tension in Integrated Information Theory 4.0's Realist Idealism.Entropy (Basel, Switzerland) · 2023Article
- Integrated information theory (IIT) 4.0: Formulating the properties of phenomenal existence in physical terms.PLoS computational biology · 2023Article
- Efficient, Formal, Material, and Final Causes in Biology and Technology.Entropy (Basel, Switzerland) · 2023Article
- Computing the Integrated Information of a Quantum Mechanism.Entropy (Basel, Switzerland) · 2023Article
- When do parts form wholes? Integrated information as the restriction on mereological composition.Neuroscience of consciousness · 2023Article
- Genuine high-order interactions in brain networks and neurodegeneration.Neurobiology of disease · 2022Article
- Non-Separability of Physical Systems as a Foundation of Consciousness.Entropy (Basel, Switzerland) · 2022Article
- Classic Psychedelic Drugs: Update on Biological Mechanisms.Pharmacopsychiatry · 2022Article
- Emergence of Integrated Information at Macro Timescales in Real Neural Recordings.Entropy (Basel, Switzerland) · 2022Article
- How Should Therapists Treat Patients who are so Altruistic They Regularly Harm Themselves for the Sake of Others?Innovations in clinical neuroscienceReview
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Causal reductionism is the widespread assumption that there is no room for additional causes once we have accounted for all elementary mechanisms within a system. Due to its intuitive appeal, causal reductionism is prevalent in neuroscience: once all neurons have been caused to fire or not to fire, it seems that causally there is nothing left to be accounted for. Here, we argue that these reductionist intuitions are based on an implicit, unexamined notion of causation that conflates causation with prediction. By means of a simple model organism, we demonstrate that causal reductionism cannot provide a complete and coherent account of 'what caused what'. To that end, we outline an explicit, operational approach to analyzing causal structures.
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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.