Graben, Peter beim, Barrett, Adam and Atmanspacher, Harald (2009) Stability criteria for the contextual emergence of macrostates in neural networks. Network: Computation in Neural Systems, 20 (3). pp. 178-196. ISSN 0954-898X

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Abstract

More 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.

Item Type:	Article
Schools and Departments:	School of Engineering and Informatics > Informatics
Depositing User:	Adam Barrett
Date Deposited:	12 Apr 2016 13:56
Last Modified:	02 Jul 2019 22:50
URI:	http://sro.sussex.ac.uk/id/eprint/60441

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