Vague-to-crisp dynamics of percept formation modeled as operant (selectionist) process.
We model the vague-to-crisp dynamics of forming percepts in the brain by combining two methodologies: dynamic logic (DL) and operant learning process. Forming percepts upon the presentation of visual inputs is likened to model selection based on sampled evidence. Our framework utilizes the DL in selecting the correct "percept" among competing ones, but uses an intrinsic reward mechanism to allow stochastic online update in lieu of performing the optimization step of the DL framework. We discuss the connection of our framework with cognitive processing and the intentional neurodynamic cycle.
Sensors Directorate, Air Force Research Laboratory, Building 620, Sensors Directorate, WPAFB, OH USA.
Roman
R
Ilin
Department of Psychology, University of Michigan, 530 Church Street, Ann Arbor, MI USA.
Jun
J
Zhang
Sensors Directorate, Air Force Research Laboratory, Building 600, Sensors Directorate, WPAFB, OH USA.
Leonid
L
Perlovsky
Department of Mathematical Sciences, The University of Memphis, 373 Dunn Hall, Memphis, TN 38152 USA.
Robert
R
Kozma
Dynamic logic; Intrinsic reward; Mixture models; Model selection; Operant conditioning; Operant learning