Direct experimental evidence for alternative stable states: a review

A large number of studies have presented empirical arguments for the existence of alternative stable states (ASS) in a wide range of ecological systems. However, most of these studies have used non-manipulative, indirect methods, which findings remain open for alternative explanations. Here, we review the direct evidence for ASS resulting from manipulation experiments. We distinguish four conclusive experimental approaches which test for predictions made by the hysteresis effect: (1) discontinuity in the response to an environmental driving parameter, (2) lack of recovery potential after a perturbation, (3) divergence due to different initial conditions and (4) random divergence. Based on an extensive literature search we found 35 corresponding experiments. We assessed the ecological stability of the reported contrasting states using the minimum turnover of individuals in terms of life span and classified the studies according to 4 categories: (1) experimental system, (2) habitat type, (3) involved organisms and (4) theoretical framework. 13 experiments have directly demonstrated the existence of alternative stable states while 8 showed the absence of ASS in other cases. 14 experiments did not fulfil the requirements of a conclusive test, mostly because they applied a too short time scale. We found a bias towards laboratory experiments compared to field experiments in demonstrating bistability. There was no clear pattern of the distribution of ASS over categories. The absence of ASS in 38% of the tested systems indicates that ASS are just one possibility of how ecological systems can behave. The relevance of the concept of ASS for natural systems is discussed, in particular under consideration of the observed laboratory bias, perturbation frequency and variable environments. It is argued, that even for a permanently transient system, alternative attractors may still be of relevance.     

Representational switching by dynamical reorganization of attractor structure in a network model of the prefrontal cortex

The prefrontal cortex (PFC) plays a crucial role in flexible cognitive behavior by representing task relevant information with its working memory. The working memory with sustained neural activity is described as a neural dynamical system composed of multiple attractors, each attractor of which corresponds to an active state of a cell assembly, representing a fragment of information. Recent studies have revealed that the PFC not only represents multiple sets of information but also switches multiple representations and transforms a set of information to another set depending on a given task context. This representational switching between different sets of information is possibly generated endogenously by flexible network dynamics but details of underlying mechanisms are unclear. Here we propose a dynamically reorganizable attractor network model based on certain internal changes in synaptic connectivity, or short-term plasticity. We construct a network model based on a spiking neuron model with dynamical synapses, which can qualitatively reproduce experimentally demonstrated representational switching in the PFC when a monkey was performing a goal-oriented action-planning task. The model holds multiple sets of information that are required for action planning before and after representational switching by reconfiguration of functional cell assemblies. Furthermore, we analyzed population dynamics of this model with a mean field model and show that the changes in cell assemblies' configuration correspond to those in attractor structure that can be viewed as a bifurcation process of the dynamical system. This dynamical reorganization of a neural network could be a key to uncovering the mechanism of flexible information processing in the PFC.     

Seeking alternative stable states in a deep lake

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