Thursday, October 30, 2008

The brain clock and IQ: Another supporting article

I've blogged extensively on the intriguing relation between the hypothesized internal brain clock and intelligence. I've found the research supporting the notion of a temporal g (temporal general intelligence mechanism) particularly intriguing.

There is a new article "in press" in the journal Intelligence that adds support to the hypothesis that temporal processing may be more related to general intelligence than the "holy grail" research that attempts to explain g via reaction time (RT). The focus of the article is an attempt to identify the underlying mechanisms that explain the relation between general intelligence and temporal processing (in this case, the authors used a isochronous serial interval production task as the measure of temporal processing). The article is rather technical, so I'll cut to the bottom line take-away messages.

The authors argue that their findings support a bottom-up (BU) explanation of temporal processing, in contrast to the alternative top-down (TD) explanation. The supported BU explanation suggests that the aspect of temporal processing related to general intelligence is grounded in certain basic neural properties that influence temporal variability in neural activity. The alternative TD hypothesis suggests that some form of higher-order component of the neural system (e.g., the construct of attention) is responsible for the link. The authors suggest that the support for the BU hypothesis, and not the TD hypothesis, supports a biological underpinning for intelligence and, more importantly, the hypothesis that temporal accuracy of neural activity has a causal effect on the neural processes that are involved in cognition (intelligence).

Also of interest was the authors suggestion that this basic underlying mechanism (of the brain clock?) is the result of a network of brain regions (sensorimotor cortx, supplementary and pre-supplementary motor areas, later premotor areas of the frontal lobe, auditory regions in the superious temporal gyrus, the basal ganglia and cerebellum). The efficient networked interaction of many of these brain regions have been implicated in other research discussed at this blog.

Of course, the small sample (n=36) and the reliance on a single psychometric measure (Raven's matrix test) of fluid intelligence (Gf) to define intelligence are significant limitations that argue for caution and the need for replication in larger samples and a broader array of indicators of the construct of intelligence. Click here for a prior discussion of my concerns for the reliance on the Raven's Gf test.

Madison, G., Forsman, L., Blom, O., Karabanov, A & UllĂ©n, F. (2009) Correlations between intelligence and components of serial timing variability. Intelligence,37, 68–75 (click to view)

  • 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 in?uence 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 ?rst 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.

Technorati Tags: , , , , , , , , , , , ,

No comments: