Deformation of Attractor Landscape via Cholinergic Presynaptic Modulations: A Computational Study Using a Phase Neuron Model
(A) and (D) Quasi-attractors observed when the concentration of ACh does not exceed its baseline level. In Figure A, the instability of the quasi-attractor is represented by the shallow depth of potential in the landscape, and each quasi-attractor is found to be unstable because there exist repelling orbits from itself. In Figure D, the instability of the quasi-attractor is shown as crossings of trajectories over the boundaries, and each quasi-attractor is unstable because there are many crossing points. The trajectories of the network state successively transit among quasi-attractors as indicated by red arrows. By the top-down Glu spike volleys indicated by green arrows, the network state would jump to another quasi-attractor. However, it would soon transit to other quasi-attractors again. (B) and (E) Quasi-attractors observed when the ACh level is somewhat high. The probability of transitions becomes low, but each quasi-attractor remains unstable. (C) and (F) Stable attractors observed when the concentration of ACh is much higher. Transitive dynamics are not observed because quasi-attractors are stabilized and they become attractors. When top-down Glu spike volleys are injected to cortical layer 1, the trajectories jump to the target pattern (in this example, the attractor of pattern 2) in a short time.