Monday, September 26, 2005

Parietal Prodigies?: Superior Intelligence in the Parietal Lobe?

In this latest fMRI investigation into superior fluid intelligence, the frontal-parietal networks again emerge as important in a visualspatial problem solving paradigms given to superior-g subjects, but the posterior parietal lobe emerges as the most critical factor separating superior from average problem solving and reasoning ability.

This is a shift in thinking. For quite some time, superior intelligence has had been thought to reside in the frontal lobe activity. Some of the bias of 'frontal' intelligence came from lesion studies - and this is probably not the best way to see how 'superior' problem solvers were better than 'average' problem solvers.

The study is also interesting to consider for its implications for education. Are we doing enough to teach problem solving? And what might be the best approaches to teaching representational and fluid analytical thinking?

(BTW: The superior-g subjects were chosen by having won first or second prize in nationwide Science / Math Olympiad, teacher & principal recommendations, and successful performance on a novel problem solving test)

Neural Correlates of Superior Intelligence
Neurobiology of Intelligence
Neural Mechanisms of Fluid Intelligence


  1. When we have artificial minds whose functionality can be mapped back onto the human brain, we will have a much clearer answer as to whether superior intelligence resides in the frontal lobes or the parietal lobes. Meanwhile, university students who stumble upon a free artificial intelligence program and run it in Tutorial mode will be able to observe the thinking of the AI Mind in action.

  2. Hello Drs. Eide,

    Perhaps the more active visualspatial aspect explains the processing speed aspect of g when we say of someone who is exceptionally bright " He's quick" or " a fast learner".

    I think you two would be interested in this article by a CIA analyst who covers linear-static model-analytical reasoning vs. nonlinear -dynamic/uncertainty model-synthetic reasoning.