PMID-12433288[0] Real-time computing without stable states: a new framework for neural computation based on perturbations.
- It is shown that the inherent transient dynamics of the high-dimensional dynamical system formed by a sufficiently large and heterogeneous neural circuit may serve as universal analog fading memory. Readout neurons can learn to extract in real time from the current state of such recurrent neural circuit information about current and past inputs that may be needed for diverse tasks.
- Stable states, e.g. Turing machines and attractor-based networks are not requried!
- How does this compare to Shenoy's result that neuronal dynamics converge to a 'stable' point just before movement?
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[0] Maass W, Natschläger T, Markram H, Real-time computing without stable states: a new framework for neural computation based on perturbations.Neural Comput 14:11, 2531-60 (2002 Nov) |
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