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Self-organisation  ·  Article

Downward causation and coarse-graining

Coarse-graining replaces many microscopic details with a few macroscopic variables. Downward causation is the idea that such higher-level quantities can influence the lower-level parts. Flack proposed an operational reading, in which components collectively compute macroscopic properties and then tune their behaviour to them.23 Later bioelectric work treats variables such as membrane voltage as coarse-grained quantities that cells can respond to.8

Earliest held
1890, James, W.
Most discussed in
Coarse-graining as a downward causation…, 2017
In the library
77 passages in 19 works
Rewritten
2026-10-06
18501875190019251950197520002025Craddock TJ, Tuszynski JA, Hameroff S, 20121Flack JC, 20172Flack JC, 20173Flack JC, 20174Manicka S, Levin M, 20195Levin M, 20196Fields C, Levin M, 20227Levin M, 20228Cervera J, Levin M, Mafe S, 20249
01

Coarse models in biology

Craddock, Tuszynski and Hameroff (2012) contrasted their proposed memory encoding in microtubules with more coarse-grained forms of neuronal information processing, which they said carry significantly higher metabolic costs.1 Manicka and Levin (2019) noted that logic gates, though usually built as electronic circuits, have served as coarse-grained models of neurons, genes and even physiology.5 They used this to argue that non-neural tissue networks could be modelled with the same logical building blocks. In both works the term describes a level of description, not a claim about causes.

02

Flack's operational proposal

Flack (2017) described downward causation as a controversial idea: higher levels of organization can causally influence behaviour at lower levels.2 She proposed to make it operational. Adaptive systems find regularities in evolutionary or learning time, and their components collectively compute macroscopic properties by coarse-graining. In her account, a system moves from simple feedback to downward causation when components tune behaviour in response to estimates of those collectively computed properties.3 She also raised a doubt. Components are error prone and have finite data and computing capacity, so it is unclear whether a single correct coarse-graining exists.4 She left this as an open question.

03

Voltage as a macrovariable

Levin (2019) asked whether gene-regulatory and bioelectric networks coarse-grain themselves, and whether information-theoretic tools could find signatures of this in time-series data of regulatory events.6 Fields and Levin (2022) suggested a case in planaria. The many ways to depolarize tissue might be coarse-grained into one problem, a voltage change met by one set of transcriptional actions.7 They presented this as a possibility, not a finding. Levin (2022) called each cell's Vmem level a coarse-grained parameter that subsumes many combinations of ion levels and channel states.8 Cervera, Levin and Mafe (2024) used an effective rate constant as a coarse-graining approximation linking bioelectrical and transcriptional spaces.9

SourcesEach quotation was checked word for word against the passage it opens.
  1. Metabolic energy for the proposed memory encoding by CaMKII phosphorylation of MTs should be distinguished from significantly higher metabolic costs of more coarse-grained forms of neuronal information processing.Craddock TJ, Tuszynski JA, Hameroff S, 2012 · Cytoskeletal signaling: is memory encoded in microtubule lattices by CaMKII… · open at passage 23
  2. Downward causation is the controversial idea that ‘higher’ levels of organization can causally influence behaviour at ‘lower’ levels of organization.Flack JC, 2017 · Coarse-graining as a downward causation mechanism · open at passage 0
  3. I further suggest we move from simple feedback to downward causation when components tune behaviour in response to estimates of collectively computed macroscopic properties.Flack JC, 2017 · Coarse-graining as a downward causation mechanism · open at passage 0
  4. Does it make sense to talk about a ‘correct’ coarse-graining when the components performing the computation are error prone and have finite data and computational capacity?Flack JC, 2017 · Coarse-graining as a downward causation mechanism · open at passage 40
  5. the underlying mathematical formulations have been used as coarse-grained models of neurons38,39, genes40,41, and even physiology12.Manicka S, Levin M, 2019 · Modeling somatic computation with non-neural bioelectric networks · open at passage 4
  6. Can tools such as information theory or other approaches be used to identify signatures in time-series data of regulatory events of attempts by gene-regulatory and bioelectric networks to coarse-grain themselvesLevin M, 2019 · The Computational Boundary of a "Self": Developmental Bioelectricity Drives… · open at passage 74
  7. the many ways to depolarize tissue could be naturally coarse-grained to represent a single problem: a change in membrane voltage addressable by a single set of transcriptional actions.Fields C, Levin M, 2022 · Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing… · open at passage 14
  8. Voltage is especially interesting because each Vmem level in a single cell is a coarse-grained parameter, subsuming many distinct combinations of sodium, potassium, chloride, etc., levelsLevin M, 2022 · Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework… · open at passage 83
  9. can be seen as a coarse-graining approximation for the complex connection between the bioelectrical and transcriptional spaces.Cervera J, Levin M, Mafe S, 2024 · Multicellular adaptation to electrophysiological perturbations analyzed by… · open at passage 18
Linked ideas
Resting membrane potentialpart of / contains
Membrane voltage is the main worked example of a coarse-grained variable in these texts, summarising many ion levels and channel states.
Flack's move from simple feedback to downward causation bears on what counts as a system acting on a macroscopic target.
Basal cognitionrelated to
Fields and Levin read coarse-graining of physiological states as a minimal form of generalisation in cells.
Flack's components collectively compute macroscopic properties, which is a collective computation among parts.
Vitalism and mechanismin tension with
Downward causation is controversial partly because it can sound like a non-mechanical higher-level force; Flack seeks an operational account.
Levin asks whether networks model and coarse-grain themselves, which bears on where a self's computational boundary lies.
Evolvabilityrelated to
Levin passages link the two: polyploid newt tubule formation shows downward causation toward one large-scale outcome, which 'evolution does' not hardwire; anatomical homeostasis coarse-grains robustness. Evolvability is implied, not directly analysed.
Grouping micro-states into macro-nodes is a form of coarse-graining, and causal emergence asks when the coarser description carries more causal information.
Macro-nodes found by partitioning a GRN state space are a coarse-graining of the micro-scale network.
Higher-level blankets are built from mixtures of lower-level blanket states, a coarse-graining move.
Pai and colleagues frame their transcriptome study as a test of the top-down influence of morphology over gene expression.
Kirchhoff and colleagues describe collective dynamics feeding back into the scale below, a form of downward influence.
Noble's view that lower-level changes are buffered at higher phenotype levels concerns how levels relate causally.
Where it is discussedPassages matching downward causation, coarse-graining, coarse graining, slow variables
2017Coarse-graining as a downward causation mechanism · Flack JC41
2022Rotational Mechanism of FO Motor in the F-Type ATP Synthase Driven by the… · Kubo S, Takada S9
2022Technological Approach to Mind Everywhere: An Experimentally-Grounded Framework… · Levin M5
2022Competency in Navigating Arbitrary Spaces as an Invariant for Analyzing… · Fields C, Levin M3
2022Minimal Developmental Computation: A Causal Network Approach to Understand… · Manicka S, Levin M2
2025The Multiscale Wisdom of the Body: Collective Intelligence as a Tractable… · Levin M2
2023Darwin's agential materials: evolutionary implications of multiscale competency… · Levin M2
2018Memory functions reveal structural properties of gene regulatory networks · Herrera-Delgado E, Perez-Carrasco R…2
2015What can ecosystems learn? Expanding evolutionary ecology with learning theory · Power DA, Watson RA, Szathmáry E, Mills…1
2022Information Theory as an Experimental Tool for Integrating Disparate… · McMillen P, Walker SI, Levin M1