Skip to main content
. Author manuscript; available in PMC: 2009 Feb 16.
Published in final edited form as: J Exp Psychol Anim Behav Process. 2003 Jan;29(1):49–61. doi: 10.1037/0097-7403.29.1.49

Figure 4.

Figure 4

Top panel: A linear operator model of perseveration. With each trial with a peck (peck state, signified by a left circle) the probability (p) of a peck on the next trial increases by the fraction γ of the distance to 1.0. On each trial without a peck (quiet state, signified by a right circle) the probability of observing a peck on the next trial decreases by the fraction γ of the distance to 0. This constitutes an exponentially weighted moving average of the probability of responding. Bottom panel: A linear operator model of learning to associate the keylight with food and thus approach it. The rate of learning the association is given by the parameter α. On trials without a response, the probability of a response on the next trial increases by the fraction α of the distance to 1.0. On trials with a response there is no food, and the probability decreases by the fraction α of the distance toward 0. In the two-parameter learning model, it decreases by the fraction β, where β is the rate of extinguishing the association.