A neural network model of operant conditioning

B.S. ZANUTTO, S. LEW

New Orleans, USA

Congreso; 30th Annual Meeting of the Society for Neuroscience.; 2000

Society for Neuroscience

 A neural network model of operant conditioning for appetitive and aversive stimuli is proposed. It has one neuron for each possible response of the animal (R), and from neurobiological bases we assume that there is a prediction of the unconditioned stimulus (US), computed by another artificial neuron. The inputs of response neurons are: the prediction, the short-term memory of the conditioned stimuli (CSs) and of the US. Based on Hebbian or anti-Hebbian learning, depending on the prediction of the US, the synaptic weights of the response neurons are calculated. The short-term memories of CSs, of the US and of the Rs are inputs of the neuron that computes prediction. The synaptic weights of this neuron are calculated based on the delta rule. Finally, animals execute any response higher than a threshold. The controversy between one factor and two-factor theory is analyzed. This model explains how experiments supporting one-factor theory (e.g. Herrnstein & Hineline, 1966) can be understood without the prediction of the US. In this case the function to switch from Hebbian to anti-Hebbian learning can be controlled by a function of US instead of by the prediction. Then for this experiment, the prediction is not needed to explain the data. However, it is not clear how to learn inhibition of avoidance behavior (e.g. Rescorla & LoLordo, 1965) without the prediction or a similar function. From this point of view, one factor theory can explain some experiments, but not others. The simulated and experimental data have been compared, showing that the model predicts relevant features of operant conditioning. The dynamic process is simple; for the appetitive stimulus, responses are associated with the input stimuli by the Hebbian rule if the prediction of the unconditioned stimulus is higher than a threshold, and by the anti-Hebbian rule if it is lower. For aversive stimulus the criteria is the opposite.