Neuroscience Of Impulsivity Advances

A new study looking at fMRI scans of 1,896 teenagers has revealed that the kind of impulsivity that leads to substance abuse, and a kind of impulsivity that leads to ADHD are the product of particular types of networks in the brain that appear to precede the substance abuse rather than being caused by substance abuse.

[D]iminished activity in a network involving the "orbitofrontal cortex" is associated with experimentation with alcohol, cigarettes and illegal drugs in early adolescence. . . .  

The researchers were also able to show that other newly discovered networks are connected with the symptoms of attention-deficit hyperactivity disorder. These ADHD networks are distinct from those associated with early drug use. In recent years, there has been controversy and extensive media attention about the possible connection between ADHD and drug abuse. Both ADHD and early drug use are associated with poor inhibitory control -- they're problems that plague impulsive people. But the new research shows that these seemingly related problems are regulated by different networks in the brain -- even though both groups of teens can score poorly on tests of their "stop-signal reaction time," a standard measure of overall inhibitory control used in this study and other similar ones. This strengthens the idea that risk of ADHD is not necessarily a full-blown risk for drug use as some recent studies suggest.

This is one of the most direct observations ever made of the biochemical and anatomical basis of ADHD and the impulsivity associated with substance abuse. It adds to the increasing evidence that these conditions, at least by the time people are teenagers, are to some extent "hard wired" rather than merely reflecting easily changeable habits of thinking. And, it provides some very specific guidance regarding the mechanisms at work in these mental health conditions. The fact that more than one network was associated with ADHD also suggests that it may be possible to use fMRI studies to develop a more meaningful set of subtypes for ADHD based on brain mechanism rather than merely visible symptoms.

It isn't clear if the factor analysis that researchers used to discern the different neural networks would be sufficiently specific to use as a diagnostic tool in individual cases, or if they are merely capturing a statistical tendency. The fact that researchers can afford to have such a large sample of fMRI scans at all, and that they have the computational power to make sense of and see trends in such a massive four dimensional dataset is a testament to the impact that technology is having on fields like psychiatry that have until recently tended to lag behind other fields of medicine in technological sophistication.