Network stabilization on unstable manifolds: Computing with middle layer transients

Abstract

Studies have failed to yield definitive evidence for the existence and/or role of well-defined chaotic attractors in real brain systems. Tsuda's transients stabilized on unstable manifolds of unstable fixed points using mechanisms similar to Ott's algorithmic “control of chaos” are demonstrable. Grebogi's order in preserving “strange nonchaotic” attractor with fractal dimension but Lyapounov is suggested for neural network tasks dependent on sequence.