Spike-Triggered Covariance Analysis Reveals Phenomenological Diversity of Contrast Adaptation in the Retina
Fig 5
STC analysis of contrast adaptation models.
(A) Layout of the models. (i) Spike-feedback model [35,36]. The model consists of a linear filter, a threshold operation to determine spikes, and an exponentially decaying feedback signal that is subtracted from the feedforward filter output after a spike has occurred. (ii) LNK model [37]. Adaptation is modeled by a kinetic model with a resting state R, an active state A, and two inactive states I1 and I2. Possible transitions between the states are indicated by arrows, together with the applied transition rates. The input to the kinetic model, u(t), is derived from a linear-nonlinear cascade and modulates the transition from the resting to the active state as well as from the first to the second inactive state. (B) STAs obtained from the two models under high- and low-contrast stimulation as well as corresponding STC spectra and features k1 and k2. (C) STA fits with features obtained from high-contrast STC analysis. The corresponding R2 values are indicated in the plots. The inset shows the weights for k1 and k2 obtained from the fits, with the gray line indicating the unit circle and data points near the circle corresponding to good fits. (D) Same as (C), but for STA fits with features obtained from the low-contrast STC analysis.