Framsticks

This work introduces a computational model of human temporal discrimination mechanism - the Clock-Counter Timing Network. It is an artificial neural network implementation of a timing mechanism based on the informational architecture of the popular Scalar Timing Model. The model has been simulated in a virtual environment enabling computational experiments which imitate a temporal discrimination task - the two-alternative forced choice task. The influence of key parameters of the model (including the internal pacemaker speed and the variability of memory translation) on the network accuracy and the time-order error phenomenon has been evaluated. The results of simulations reveal how activities of different modules contribute to the overall performance of the model. These results can be compared and verified in empirical experiments with human participants, especially when the modes of activity of the internal timing mechanism are changed because of some external conditions, or are impaired due to some kind of a neural degradation process.