Dynamic properties Terms Links

A recent theoretical study has suggested that persistent activity in the PFG is considered to be an attractor state, in that relatively small amounts of variation in this state lead it back to the same state. This idea has been examined in detail theoretically, especially by Amit, who described persistent activity in terms of dynamical attractors (Amit and Brunei, 1997 Rolls et al., 2008). The spontaneous state and stimulus-selective memory states are assumed to represent multiple attractors, such that a memory state can be switched on or off by transient inputs. This formulation is plausible, insomuch as stimulus-selective persistent firing patterns are dynamically stable in time. These properties of attractors result from interactions in neuronal circuits. Neural synchrony is a general mechanism for dynamically linking together cells coding task-relevant information (Salmas and Sejnowski, 2001). The dynamics of neuronal activities and the representations they reflect are two sides of a coin. 

This is because although 0 = (10), in general, cr(10) oQ (it will usually be less). In principle, the quantities we have defined, E(t), Dit), Gif), and J(i), provide a complete description of tensile and shear properties in creep and stress relaxation (and equivalent functions can be used to describe dynamic mechanical behavior). Obviously, we could fit individual sets of data to mathematical functions of various types, but what we would really like to do is develop a universal model that not only provides a good description of individual creep, stress relaxation and DMA experiments, but also allows us to relate modulus and compliance functions. It would also be nice to be able formulate this model in terms of parameters that could be related to molecular relaxation processes, to provide a link to molecular theories. 

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