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Stability criteria for the contextual emergence of macrostates in neural networks
journal contribution
posted on 2023-06-09, 00:49 authored by Peter beim Graben, Adam BarrettAdam Barrett, Harald AtmanspacherMore than thirty years ago, Amari and colleagues proposed a statistical framework for identifying structurally stable macrostates of neural networks from observations of their microstates. We compare their stochastic stability criterion with a deterministic stability criterion based on the ergodic theory of dynamical systems, recently proposed for the scheme of contextual emergence and applied to particular inter-level relations in neuroscience. Stochastic and deterministic stability criteria for macrostates rely on macro-level contexts, which make them sensitive to differences between different macro-levels.
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- Published
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- Published version
Journal
Network: Computation in Neural SystemsISSN
0954-898XPublisher
Taylor and FrancisExternal DOI
Issue
3Volume
20Page range
178-196Department affiliated with
- Informatics Publications
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- No
Peer reviewed?
- Yes
Legacy Posted Date
2016-04-12First Compliant Deposit (FCD) Date
2016-04-12Usage metrics
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