Institute for Theoretical Physics, Johann Wolfgang Goethe University, Frankfurt am Main, Germany.
Phys Rev Lett. 2010 Aug 6;105(6):068702. doi: 10.1103/PhysRevLett.105.068702.
The goal of polyhomeostatic control is to achieve a certain target distribution of behaviors, in contrast to homeostatic regulation, which aims at stabilizing a steady-state dynamical state. We consider polyhomeostasis for individual and networks of firing-rate neurons, adapting to achieve target distributions of firing rates maximizing information entropy. We show that any finite polyhomeostatic adaption rate destroys all attractors in Hopfield-like network setups, leading to intermittently bursting behavior and self-organized chaos. The importance of polyhomeostasis to adapting behavior in general is discussed.
多稳态控制的目标是实现某种行为的目标分布，与旨在稳定动态稳态的静态调节形成对比。我们考虑单个和网络的神经元的多稳态，以适应最大化信息熵的目标发放率分布。我们表明，任何有限的多稳态适应率都会破坏类似 Hopfield 的网络设置中的所有吸引子，导致间歇爆发行为和自组织混沌。讨论了多稳态对一般行为适应的重要性。
