Researchers have been working for many years to comprehend the relationship between brain structure, functional connectivity, and intelligence. A recent study provides the most comprehensive understanding to date of how different regions of the brain and neural networks contribute to a person’s prob
, and first author Evan Anderson, a researcher for Ball Aerospace and Technologies Corp. working at the Air Force Research Laboratory, employed the technique of “connectome-based predictive modeling” to evaluate five theories on how the brain leads to intelligence.
Historically, theories of intelligence focused on localized brain regions such as the prefrontal cortex, which plays a key role in cognitive processes such as planning, problem-solving, and decision-making. More recent theories emphasize specific brain networks, while others examine how different networks overlap and interact with one another, Barbey said.
These include the frontoparietal network, which enables cognitive control and goal-directed decision-making; the dorsal attention network, which aids in visual and spatial awareness; and the salience network, which directs attention to the most relevant stimuli. Previous studies have shown that the activity of these and other networks when a person is awake but not engaged in a task or paying attention to external events “reliably predicts our cognitive skills and abilities,” Barbey said.
The researchers found that taking into account the features of the whole brain produced the most accurate predictions of a person’s problem-solving aptitude and adaptability. This held true even when accounting for the number of brain regions included in the analysis.
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