title: Intelligence and individual differences in becoming neurally efficient.
abstract: Physiological approaches to human psychometric intelligence have shown a higher neural efficiency (i.e. less cortical activation) during cognitive performance in brighter subjects. The main aim of this study was to explore the relationship between intelligence and cortical activation patterns in the framework of the learning test concept. In 27 participants we assessed the topography and extent of cortical activation by means of event-related desynchronization (ERD) during reasoning tests in a pre-test--training--post-test design and related it to psychometric intelligence (measured by the German Leistungs-Prüf-System, LPS). Significant associations between intelligence and cortical activation patterns were exclusively found at anterior (frontal) recording sites, which corroborates the central role of the frontal lobe for higher-order cognitive functions. The hypothesized negative intelligence-activation correlation was observed only after the training, i.e. in the post-test, but not in the pre-test. More important, the decrease in cortical investment from pre-test to post-test correlated negatively with intelligence, indicating that the higher the subjects' general mental ability the larger the decrease in the amount of cortical activation. These findings suggest intelligence-related individual differences in becoming neurally efficient.
authors.affiliation: Institute of Psychology, Karl-Franzens-University Graz, Universitätsplatz 2, A-8010 Graz, Austria. aljoshca.neubauer@uni-graz.at
authors.forename: Aljoscha C
authors.initials: AC
authors.lastname: Neubauer
authors.forename: Roland H
authors.initials: RH
authors.lastname: Grabner
authors.forename: H Harald
authors.initials: HH
authors.lastname: Freudenthaler
authors.forename: Jens F
authors.initials: JF
authors.lastname: Beckmann
authors.forename: Jürgen
authors.initials: J
authors.lastname: Guthke
mesh_terms: D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000502:physiology*; D004569:Electroencephalography; D006801:Humans; D007360:Intelligence / Q000502:physiology*; D007858:Learning / Q000502:physiology*; D016014:Linear Models; D008297:Male; D008875:Middle Aged; D009431:Neural Conduction / Q000502:physiology*; D011930:Reaction Time