title: Theoretical accounts of spatial learning: a neurobiological view (commentary on Pearce, 2009).
abstract: Theories of learning have historically taken, as their starting point, the assumption that learning processes have universal applicability. This position has been argued on grounds of parsimony, but has received two significant challenges: first, from the observation that some kinds of learning, such as spatial learning, seem to obey different rules from others, and second, that some kinds of learning take place in processing modules that are separate from each other. These challenges arose in the behavioural literature but have since received considerable support from neurobiological studies, particularly single neuron studies of spatial learning, confirming that there are indeed separable (albeit highly intercommunicating) processing modules in the brain, which may not always interact (within or between themselves) according to classic associative principles. On the basis of these neurobiological data, reviewed here, it is argued that rather than assuming universality of associative rules, it is more parsimonious to assume sets of locally operating rules, each specialized for a particular domain. By this view, although almost all learning is associative in one way or another, the behavioural-level characterization of the rules governing learning may vary depending on which neural modules are involved in a given behaviour. Neurobiological studies, in tandem with behavioural studies, can help reveal the nature of these modules and the local rules by which they interact.
authors.affiliation: Department of Cognitive, Perceptual and Brain Sciences, Division of Psychology and Language Sciences, Institute of Behavioural Neuroscience, University College London, London, UK. k.jeffery@ucl.ac.uk
authors.forename: Kathryn J
authors.initials: KJ
authors.lastname: Jeffery
mesh_terms: D000818:Animals; D001519:Behavior / Q000502:physiology*; D001921:Brain / Q000166:cytology / Q000502:physiology; D006801:Humans; D007858:Learning / Q000502:physiology*; D008954:Models, Biological; D009446:Neurobiology; D009474:Neurons / Q000502:physiology; D013028:Space Perception / Q000502:physiology*