title: How to compare two quantities? A computational model of flutter discrimination.
abstract: A task that has been intensively studied at the neural level is f lutter discrimination. I argue that f lutter discrimination entails a combination of a temporal assignment problem and a quantity comparison problem, and propose a neural network model of how these problems are solved. The network combines unsupervised and one-layer supervised training. The unsupervised part clusters input features (stimulus + time window) and the supervised part categorizes the resulting clusters. After training, the model shows a good fit with both neural and behavioral properties. New predictions are outlined and links with other cognitive domains are pointed out.
authors.affiliation: Ghent University, Belgium. Tom.Verguts@UGent.be
authors.forename: Tom
authors.initials: T
authors.lastname: Verguts
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology; D004192:Discrimination, Psychological / Q000502:physiology*; D008959:Models, Neurological; D016571:Neural Networks, Computer; D009474:Neurons / Q000502:physiology; D010775:Photic Stimulation; D015203:Reproducibility of Results; D014110:Touch / Q000502:physiology*; D014732:Vibration