(A) Receptive field refinement with adaptive H-events and different H-inter-event-intervals, . Top: ; bottom: . (B) Receptive field sizes from 500 Monte Carlo simulations for combinations of and . Bottom: Percentage of simulation outcomes classified as ‘selective’ when the average receptive field size is smaller than one and larger than 0, ‘non-selective’ when the average receptive field size is equal to 1, and ‘decoupled’ when the average receptive field size is 0 for the two rules. (C) Topography of receptive fields classified as selective in B. Horizontal line indicates median, the box is drawn between the 25th and 75th percentile, whiskers extend above and below the box to the most extreme data points that are within a distance to the box equal to 1.5 times the interquartile range and points indicate all data points. Distributions are not significantly different (ns) as measured by a two-sample Kolmogorov-Smirnov test ( selective outcomes for each rule out of 500; ; D = 0.45). (D) Top: Reduction of the full weight dynamics into two dimensions. Two sets of weights were averaged: those which potentiate and form the receptive field, , and the complementary set of weights that depress, . Bottom: Initial conditions in the reduced two-dimensional phase plane were classified into three outcomes: ‘selective’, ‘non-selective’, and ‘decoupled’. We sampled 2500 initial conditions which evolved according to Equation 16 until the trajectories reached one of the selective fixed points, and , or resulted in no selectivity either because both weights depressed to or potentiated to . The normalized number of initial coordinates generating each region can be interpreted as the area of the phase plane that results in each outcome. (E) Top: Normalized area of the phase plane of the reduced two-dimensional system that resulted in ‘selective’, ‘non-selective’, and ‘decoupled’ outcomes for as a function of H-event strength. The darker shading indicates ranges of non-adapted H-event strength where the selectivity area is maximized. Bottom: The corresponding adapted strength of H-events was calculated in simulations with adaptive H-events and plotted as a function of the nominal, non-adapted strength of H-events. The range of adapted H-event strengths (bottom) corresponds to the range of non-adaptive values that maximize the selectivity area (top). Each point shows the average over 10 runs and the bars the standard deviation (which are very small).