Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems
Abstract
The system presented here is based on neurophysiological and electrophysiological data. It computes three types of increasingly integrated temporal and probability contexts, in a bottom-up mode. To each of these contexts corresponds an increasingly specific top-down priming effect on lower processing stages, mostly pattern recognition and discrimination. Contextual learning of time intervals, events' temporal order or sequential dependencies and events' prior probability results from the delivery of large stimuli sequences. This learning gives rise to emergent properties which closely match the experimental data.Institut national de la santé et de la recherche médicale; Ministère de la Défense Nationale (DGA/DRET 911470/AOOO/DRET/DS/DR); Consejo Nacional de Ciencia y Tecnología (63462
