The Prognosis of Delayed Reactions in Rats Using Markov Chains Method

Abstract

The original modified method of the direct delayed reaction has been used for the evaluation of food-obtaining strategy across spatial learning tasks in T-maze alternation. The optimal behavioral algorithms for each experimental day have been identified so that the animals obtain maximum possible food amount with minimal number of mistakes. Markov chain method has been used for the prognosis of rat’s behavioral strategy during the spatial learning task. The learning and decision-making represent the probabilistic transition process where the animal choice at each step (state) depends on the learning experience from previous step (state).