SAIM (Selective Attention for Identification Model) is a computational model of human visual attention and its disorders. This page summarizes how SAIM has progressed since its birth in 1997. The corresponding literature can be found on the publications web-page.
09/206 to 03/2007 Intern student Martin Kreyling integrated spiking neurons into the version from 2003. In 04/2006 Christoph Böhme began to extend SAIM with the ability to generate action parameters for objects, e.g. the grip size for holding a hammer. His PhD is supported by an EPSRC-grant to Dietmar. 2003 to 2006 Glyn W. Humphreys, Ela Claridge and Dietmar Heinke were awarded an EPSRC-grant to continue work on SAIM: In his PhD Andreas Backhaus developed an improved version of SAIM modelling a broad of visual search data, e.g. search asymmetries, similarity effects, contextual cueing, priming, etc. Dietmar Heinke, Andreas Backhaus and Yarou Sun made SAIM fit for natural images. Dietmar Heinke and Yaoru Sun added a grouping stage to SAIM. Glyn Humphreys and Dietmar published a comparison of SDAIM with other connectionist models in George Houghton’s book on Connectionist model in Psychology. 1995-2003 After several revisions and interruptions as Dietmar had to finish his PhD first, SAIM was published in Psychological Review.