Contents
What is attractor neural network?
In general, an attractor network is a network of nodes (i.e., neurons in a biological network), often recurrently connected, whose time dynamics settle to a stable pattern. The particular pattern a network settles to is called its ‘attractor’.
How many types of attractor stability in neural networks and which they are?
Autoassociation attractor systems have two types of stable fixed point: a spontaneous state with a low firing rate, and one or more persistent states with high firing rates in which the neurons keep firing (Figure2). Each one of the high firing rate attractor states can implement a different memory.
What is a bump attractor?
A bump attractor network is a model that implements a competitive neuronal process emerging from a spike pattern related to an input source. Formally, it is a set of recurrently connected nodes (neurons) that have a stable pattern due to their time dynamics.
What does the attractor landscape model mean?
One modeling framework is the attractor landscape. Huang et al. (2005) described a high-dimensional space in which each coordinate represents the expression of a gene in the GRN. Attractors in this landscape correspond to stable equilibrium states associated with a specific cell type (Huang et al., 2005, 2009).
What is a continuous attractor?
A continuous attractor network (or continuous-attractor neural network, CANN) is an attractor network possessing one or more quasicontinuous sets of attractors that in the limit of an infinite number of neuronal units N merge into continuous attractor(s).
What is an attractor state?
In principle, an attractor state is a temporarily self-sustaining state. According to various authors (Meindertsma, 2014; De Ruiter et al., 2017), indications for attractor states can already be observed on a short-term timescale, based on the pattern of short-term variability of the elements or variables.
What is an example of an attractor?
Scientific definitions for attractor A point attractor is an attractor consisting of a single state. For example, a marble rolling in a smooth, rounded bowl will always come to rest at the lowest point, in the bottom center of the bowl; the final state of position and motionlessness is a point attractor.
What is an attractor in dynamical systems theory?
The equations of a given dynamical system specify its behavior over any given short period of time. In dynamical systems, an attractor is a set of physical properties toward which a system tends to evolve, regardless of the starting conditions of the system.
What is attractor behavior?
Motivation of attractors The equations of a given dynamical system specify its behavior over any given short period of time. The subset of the phase space of the dynamical system corresponding to the typical behavior is the attractor, also known as the attracting section or attractee.
What is strange attractor behavior?
mathematics. : the state of a mathematically chaotic system toward which the system trends : the attractor of a mathematically chaotic system Unlike the randomness generated by a system with many variables, chaos has its own pattern, a peculiar kind of order.
What is meant by chaotic attractor?
Noun. 1. chaotic attractor – an attractor for which the approach to its final point in phase space is chaotic.