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
![]() |
PDF
- Published Version
Restricted to SRO admin only Download (294kB) |
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 |
View download statistics for this item
📧 Request an update