Towards a neural model of timing.
This paper describes a neural model of interval timing, which reproduces the duration discrimination experiments of Wearden, J.H., 1992, J. Exp. Psychol. 18, 134-144. The model comprises three layers of neural units. The units in the first layer represent clusters of neurons with probabilistic internal feedback that maintains self-sustained (short-term memory) activity for a random time. The unit in the second layer is a spiking neuron that fires as long as a sufficient number of input clusters are active. The unit in the third layer detects the offset of firing in the previous layer by producing a short burst of spikes. Analysis and simulation of the model shows spikes produced at random times with a distribution determined by the number of units in the first layer, their survival time constant, and the threshold of the unit in layer 2. Interval times can be learned with any of these parameters but lead to different Weber law relations. A variable threshold in layer 2 predicts S-shaped Weber curves, a variable number of units in layer 1 leads to a saturation of the Weber curve (decreasing Weber fraction) and a variable time constant in layer 1 causes a linear Weber curve.
Bugmann
G
G
School of Computing, University of Plymouth, UK. gbugmann@soc.plym.ac.uk
D008959:Models, Neurological; D009474:Neurons / Q000502:physiology*; D010507:Periodicity; D012621:Seasons