title: On aims and methods in the neuroimaging of derived relations.
abstract: Ingenious and seemingly powerful technologies have been developed recently that enable the visualization in some detail of events in the brain concomitant upon the ongoing behavioral performance of a human participant. Measurement of such brain events offers at the very least a new set of dependent variables in relation to which the independent variables familiarly manipulated in the operant laboratory may be explored. Two related paradigms in which a start has been made in such research concern the derivation of novel or emergent relations from a baseline set of trained relations, and include the phenomenon of transitive inference (TI), observed in studies of stimulus equivalence (SE) and serial learning (SL) or seriation. This paper reviews some published and forthcoming neuroimaging studies of these and related phenomena, and considers how this line of research both demands and represents a welcome synthesis between types of question and levels of explanation in behavioral science that often have been seen as antithetical.
authors.affiliation: School of Psychology, University of Liverpool, United Kingdom. dickins@liverpool.ac.uk
authors.forename: David W
authors.initials: DW
authors.lastname: Dickins
mesh_terms: D000818:Animals; D001245:Association Learning / Q000502:physiology*; D001288:Attention / Q000502:physiology*; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology*; D003210:Concept Formation / Q000502:physiology*; D004193:Discrimination Learning / Q000502:physiology*; D004292:Dominance, Cerebral / Q000502:physiology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008128:Logic; D008279:Magnetic Resonance Imaging; D008570:Memory, Short-Term / Q000502:physiology; D010364:Pattern Recognition, Visual / Q000502:physiology*; D011340:Problem Solving / Q000502:physiology*; D012660:Semantics; D012691:Serial Learning / Q000502:physiology*; D014163:Transfer, Psychology; D014706:Verbal Learning / Q000502:physiology