Pattern perception and computational complexity: introduction to the special issue.
Research on pattern perception and rule learning, grounded in formal language theory (FLT) and using artificial grammar learning paradigms, has exploded in the last decade. This approach marries empirical research conducted by neuroscientists, psychologists and ethologists with the theory of computation and FLT, developed by mathematicians, linguists and computer scientists over the last century. Of particular current interest are comparative extensions of this work to non-human animals, and neuroscientific investigations using brain imaging techniques. We provide a short introduction to the history of these fields, and to some of the dominant hypotheses, to help contextualize these ongoing research programmes, and finally briefly introduce the papers in the current issue.
Department of Cognitive Biology, University of Vienna, Althanstrasse 14, Vienna 1090, Austria. tecumseh.fitch@univie.ac.at
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Fitch
Angela D
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Friederici
Peter
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Hagoort
D000818:Animals; D001185:Artificial Intelligence; D019295:Computational Biology; D036262:Empirical Research; D007802:Language; D007858:Learning / Q000502:physiology*; D059906:Neuroimaging; D009488:Neurosciences / Q000379:methods; D010364:Pattern Recognition, Visual; D010465:Perception / Q000502:physiology*