Increased Firing Irregularity as an Emergent Property of Neural-State Transition in Monkey Prefrontal Cortex
Figure 4
Neural network models show changes in firing variability with stability.
(A and B) Phase-plane plots (left) for a mutual-excitation circuit and firing of a neuron in node X1 (right). Each node represents a population of neurons. The thick and thin orange lines in the plots are gain functions for X1 and X2, respectively. Arrows represent vector fields, and black circles delineate point attractors. (C and D) Mutual inhibition is presented by green lines, and represents gain functions. In these phase plane plots, these gain functions denote null clines, where (i = 1, 2). (E and G) Increases in the firing variability of the X1 neuron with the maximum Lyapunov exponent (MLE) from the initial states. The corresponding firing rates (F and H), mutual excitation (E and F), and mutual inhibition (G and H) are presented. Error bars = SEM.
