000254985 001__ 254985
000254985 005__ 20181203025003.0
000254985 0247_ $$2doi$$a10.1371/journal.pcbi.1006092
000254985 02470 $$2DOI$$a10.1371/journal.pcbi.1006092
000254985 037__ $$aARTICLE
000254985 245__ $$aInteractions of spatial strategies producing generalization gradient and blocking: A computational approach
000254985 260__ $$c2018
000254985 269__ $$a2018
000254985 336__ $$aJournal Articles
000254985 520__ $$aWe present a computational model of spatial navigation comprising different learning mechanisms in mammals, i.e., associative, cognitive mapping and parallel systems. This model is able to reproduce a large number of experimental results in different variants of the Morris water maze task, including standard associative phenomena (spatial generalization gradient and blocking), as well as navigation based on cognitive mapping. Furthermore, we show that competitive and cooperative patterns between different navigation strategies in the model allow to explain previous apparently contradictory results supporting either associative or cognitive mechanisms for spatial learning. The key computational mechanism to reconcile experimental results showing different influences of distal and proximal cues on the behavior, different learning times, and different abilities of individuals to alternatively perform spatial and response strategies, relies in the dynamic coordination of navigation strategies, whose performance is evaluated online with a common currency through a modular approach. We provide a set of concrete experimental predictions to further test the computational model. Overall, this computational work sheds new light on inter-individual differences in navigation learning, and provides a formal and mechanistic approach to test various theories of spatial cognition in mammals.
000254985 700__ $$aDollé, Laurent
000254985 700__ $$aChavarriaga, Ricardo
000254985 700__ $$aGuillot, Agnès
000254985 700__ $$aKhamassi, Mehdi
000254985 773__ $$qe1006092$$k4$$j14$$tPLOS Computational Biology
000254985 8560_ $$fricardo.chavarriaga@epfl.ch
000254985 909C0 $$mjose.millan@epfl.ch$$pCNBI$$0252018$$xU12103
000254985 909CO $$pSTI$$particle$$ooai:infoscience.epfl.ch:254985
000254985 960__ $$aricardo.chavarriaga@epfl.ch
000254985 961__ $$alaurence.gauvin@epfl.ch
000254985 973__ $$aEPFL$$sPUBLISHED$$rREVIEWED
000254985 980__ $$aARTICLE
000254985 981__ $$aoverwrite