title: Computational models of perirhinal cortex function.
abstract: I review seven models of the contribution of perirhinal cortex (PRC) or neighboring neocortical regions to cognition. Five of the models address recognition memory function (Sohal and Hasselmo (2000) Network 11:169-190; Bogacz et al. (2001) J Comput Neurosci 10:5-23; Bogacz and Brown (2003a) Neurocomputing 52:1-6; Norman and O'Reilly (2003) Psychol Rev 110:611-646; Cowell et al. (2006) J Neurosci 26:12186-12197) and two account for the role of PRC in visual discrimination learning (Bussey and Saksida (2002) Eur J Neurosci 15:355-364; Cowell et al. (2010b) J Cogn Neurosci 22:2460-2479). The models span a range of biological scales and target a variety of datasets, such that like for like comparison between them is not always possible. I lay out a novel framework for facilitating comparison by defining some general abstract principles concerning the organization of cognition in the brain about which all of the models make a statement. The controversies that are revealed by scrutinizing the models within this framework highlight the fundamental questions that remain to be answered by future research. Ultimately, it is by combining these disparate accounts to build a unified model that bridges several levels of biological scale and accounts for multiple psychological phenomena that a full account of PRC function will be achieved.
authors.forename: Rosemary A
authors.initials: RA
authors.lastname: Cowell
mesh_terms: D000465:Algorithms; D000818:Animals; D002540:Cerebral Cortex / Q000033:anatomy & histology* / Q000502:physiology*; D003198:Computer Simulation; D006801:Humans; D008959:Models, Neurological