%A Oaksford,Mike %D 2015 %J Frontiers in Human Neuroscience %C %F %G English %K Marr's levels,Bayesian inference,brain imaging,new paradigm psychology of reasoning,Dual Process Models %Q %R 10.3389/fnhum.2015.00101 %W %L %M %P %7 %8 2015-February-27 %9 Review %+ Prof Mike Oaksford,Department of Psychological Sciences, Birkbeck College, University of London,London, UK,mike.oaksford@bbk.ac.uk %# %! Imaging Deductive Reasoning and the New Paradigm %* %< %T Imaging deductive reasoning and the new paradigm %U https://www.frontiersin.org/articles/10.3389/fnhum.2015.00101 %V 9 %0 JOURNAL ARTICLE %@ 1662-5161 %X There has been a great expansion of research into human reasoning at all of Marr’s explanatory levels. There is a tendency for this work to progress within a level largely ignoring the others which can lead to slippage between levels (Chater et al., 2003). It is argued that recent brain imaging research on deductive reasoning—implementational level—has largely ignored the new paradigm in reasoning—computational level (Over, 2009). Consequently, recent imaging results are reviewed with the focus on how they relate to the new paradigm. The imaging results are drawn primarily from a recent meta-analysis by Prado et al. (2011) but further imaging results are also reviewed where relevant. Three main observations are made. First, the main function of the core brain region identified is most likely elaborative, defeasible reasoning not deductive reasoning. Second, the subtraction methodology and the meta-analytic approach may remove all traces of content specific System 1 processes thought to underpin much human reasoning. Third, interpreting the function of the brain regions activated by a task depends on theories of the function that a task engages. When there are multiple interpretations of that function, interpreting what an active brain region is doing is not clear cut. It is concluded that there is a need to more tightly connect brain activation to function, which could be achieved using formalized computational level models and a parametric variation approach.