Correlations between Intelligence and Components of Serial Timing Variability

Autor/inn/en	Madison, Guy; Forsman, Lea; Blom, Orjan; Karabanov, Anke; Ullen, Fredrik
Titel	Correlations between Intelligence and Components of Serial Timing Variability
Quelle	In: Intelligence, 37 (2009) 1, S.68-75 (8 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0160-2896
DOI	10.1016/j.intell.2008.07.006
Schlagwörter	Intelligence; Intervals; Reaction Time; Psychometrics; Cognitive Processes; Correlation; Brain; Serial Learning; Acoustics; Attention; Raven Progressive Matrices + Suchen Sie Ihr Suchwort? Intelligenz; Klugheit; Reaktionsvermögen; Psychometry; Psychometrie; Cognitive process; Kognitiver Prozess; Korrelation; Gehirn; Serielles Lernen; Akustik; Aufmerksamkeit
Abstract	Psychometric intelligence correlates with reaction time in elementary cognitive tasks, as well as with performance in time discrimination and judgment tasks. It has remained unclear, however, to what extent these correlations are due to top-down mechanisms, such as attention, and bottom-up mechanisms, i.e. basic neural properties that influence both temporal accuracy and cognitive processes. Here, we assessed correlations between intelligence (Raven SPM Plus) and performance in isochronous serial interval production, a simple, automatic timing task where participants first make movements in synchrony with an isochronous sequence of sounds and then continue with self-paced production to produce a sequence of intervals with the same inter-onset interval (IOI). The target IOI varied across trials. A number of different measures of timing variability were considered, all negatively correlated with intelligence. Across all stimulus IOIs, local interval-to-interval variability correlated more strongly with intelligence than drift, i.e. gradual changes in response IOI. The strongest correlations with intelligence were found for IOIs between 400 and 900 ms, rather than above 1 s, which is typically considered a lower limit for cognitive timing. Furthermore, poor trials, i.e. trials arguably most affected by lapses in attention, did not predict intelligence better than the most accurate trials. We discuss these results in relation to the human timing literature, and argue that they support a bottom-up model of the relation between temporal variability of neural activity and intelligence. (Contains 2 figures and 2 tables.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10