Model-based analyses: Promises, pitfalls, and example applications to the study of cognitive control.
We discuss a recent approach to investigating cognitive control, which has the potential to deal with some of the challenges inherent in this endeavour. In a model-based approach, the researcher defines a formal, computational model that performs the task at hand and whose performance matches that of a research participant. The internal variables in such a model might then be taken as proxies for latent variables computed in the brain. We discuss the potential advantages of such an approach for the study of the neural underpinnings of cognitive control and its pitfalls, and we make explicit the assumptions underlying the interpretation of data obtained using this approach.
Mars
Rogier B
RB
Department of Experimental Psychology, University of Oxford, Oxford, UK. rogier.mars@psy.ox.ac.uk
Shea
Nicholas J
NJ
Kolling
Nils
N
Rushworth
Matthew F S
MF
D001288:Attention; D001921:Brain / Q000033:anatomy & histology / Q000502:physiology*; D001931:Brain Mapping; D003071:Cognition / Q000502:physiology*; D003198:Computer Simulation; D003657:Decision Making / Q000502:physiology; D006801:Humans; D008959:Models, Neurological; D059906:Neuroimaging; D012201:Reward