Correlations between intelligence and components of serial timing variability

TY - JOUR

T1 - Correlations between intelligence and components of serial timing variability

AU - Madison, Guy

AU - Forsman, Lea

AU - Blom, Örjan

AU - Karabanov, Anke Ninija

AU - Ullén, Fredrik

PY - 2009

Y1 - 2009

N2 - 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.

AB - 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.

KW - Duration-specificity

KW - Intelligence

KW - Interval production

KW - Isochronous serial interval production

KW - Neural mechanisms

KW - Neural noise

KW - Noise

KW - Ravens progressive matrices

KW - Tapping

KW - Timing

U2 - 10.1016/j.intell.2008.07.006

DO - 10.1016/j.intell.2008.07.006

M3 - Journal article

AN - SCOPUS:57349132528

SN - 0160-2896

VL - 37

SP - 68

EP - 75

JO - Intelligence

JF - Intelligence

IS - 1

ER -