Neural model approach to the basic law of psychophysics
Stevens' law, which is one of the well-known psychophysical laws, suggests that the perceived intensity R of a biological system is proportional to the power of the stimulus strength I, R alpha I(n). In order to realize a self-sustainable system that adapts to changes of the environment, it is important to understand the neural mechanism behind this law. Here, we propose a new neural scheme based on the shunting short-term memory (STM) model with the physiological properties of the nervous system, and examine the relation between the neural system and Stevens' law through computer simulations of the firing rate f with respect to the stimulus strength I. The simulations showed that the feedback-inputting connectivity plays an important role in reproducing the n > 1 and n < 1 cases of Stevens' law.
stevens' law perceived intensity stimulus strength neural networks