Brain Scans Could Become EKGs for Mental Disorders

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If EKGs can detect potential problems in heart function, then doctors are asking why brain scans can’t be used in the same way, to identify disorders like depression, autism or schizophrenia.

Doctors have long relied on EKGs, or electrocardiograms, to track the electrical activity of the heart and find any potential aberrations in the normal pattern of blips and valleys that could indicate distress. It’s not invasive, not that expensive, and for the patient, only involves getting hooked up to a few leads with patches on the chest.

Now researchers say that a similarly patient-friendly technique could scour brain activity for signs of trouble. The idea is to look for any changes in the normal “resting state” of multiple brain regions recorded by functional magnetic resonance imaging (fMRI) machines. And so far, promising evidence suggests that it may be possible to detect when communication between these regions is out of sync, or otherwise different from the norm. Even more encouraging, say scientists, various mental disorders, such as depression and autism, may involve different aberrant patterns of activity, providing a type of visual fingerprint for the condition. Finding such signatures could not only lead to better diagnosis of certain neurological or developmental diseases but also track how well patients respond to treatment.

And — just as with a standard EKG test — all the patient has to do is lie still. “With resting-state fMRI, they just have to hold still for eight minutes in the scanner,” says Dr. Michael Greicius, medical director of the Stanford Center for Memory Disorders. “That’s the main practical advantage.”

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In the latest demonstration of this approach, appearing in the journal JAMA Psychiatry, researchers compared the resting-state brain activity of children with autism to that of similarly aged youngsters without the developmental disorder. The autistic children showed a distinctive pattern of hyperconnected signaling in what the authors call the brain’s “salience network,” a collection of regions that appear to regulate attention.

Other researchers have found evidence that such fMRI scans might also help diagnose attention-deficit/hyperactivity disorder (ADHD), schizophrenia and depression. In an experiment appearing in the forthcoming July issue of Psychiatry Research, Dr. Jonathan Posner of Columbia University and his colleagues looked at 22 children with ADHD who were not yet on medication and compared them with 20 youngsters around the same age without the disorder. Compared with the healthy children, those with ADHD had, on average, less coordinated brain activity between regions such as the prefrontal cortex, an area at the front of the brain thought to be involved in decisionmaking, and the caudate, a region located toward the base of the brain involved in controlling impulses. Such patterns could one day help identify children at highest risk of developing ADHD and provide them with behavioral or educational support to address symptoms early on, when such interventions might have the biggest impact.

And such scans aren’t limited to diagnosing disease but could help improve treatment of mental disorders as well. “I am most interested in us[ing] resting-state fMRI to really examine the effects of treatment,” says Posner. He also published a paper in JAMA Psychiatry last spring showing that antidepressants successfully quieted hyperconnectivity in the brains of individuals with chronic depression.

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That trial compared brain scans from 32 people with depression with those from 25 healthy counterparts and confirmed that the former group had more activity in what is known as the default mode network, a collection of disparate brain regions that makes up the baseline, or default level of brain activity necessary to keep a body functioning. When a person performs a mental task, this default network is suppressed. But in the depressed patients, this network was overactive, and that was associated with increased rumination — or overfixating on a thought that could contribute to depression.

The patients with depression were then given a 10-week course of either the antidepressant Cymbalta (duloxetine) or a placebo. At the end of the trial, patients who received the drug showed similar connectivity patterns to those seen in healthy individuals, but the depressed participants who received placebo did not. (The study received some funding support from the pharmaceutical company Eli Lilly, which markets Cymbalta.)

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Similar differences were found among those with schizophrenia. In these patients, both the default network and the salience network appear disrupted compared with those without the disorder, according to French neuroscientists who published their results in the journal Schizophrenia Research. They noted that lack of synchronicity involving a part of the brain called the left striatum, which wasn’t seen in healthy individuals, was associated with symptoms of schizophrenia like delusions.

Other research has pointed to differences in resting-state abnormalities in illnesses such as Alzheimer’s, Tourette syndrome and anxiety disorder.

So why are such brain scans not used for clinical diagnosis? Until recently, limited computing power often meant that scientists could only analyze fMRI data from one brain region at a time, and many of these patterns require a more global view to understand how certain networks interact with others.

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But as imaging technologies become more robust, such scans could increasingly become useful diagnostic tools for doctors. With autism, for example, doctors are “really desperate for a biological marker to help with diagnosis and [measuring] treatment response,” says Daniel Smith, senior director of discovery neuroscience at Autism Speaks. Currently, most children are diagnosed around the age of 2, when the behavioral symptoms of inattention and repetitive actions tend to emerge. More studies suggest, however, that intervening with behavioral therapy in children as young as 6 months old could reduce, or even normalize, some of the aberrant brain changes responsible for the disorder, so diagnosing the condition as early as possible could become critical.

For other conditions affecting the brain, fMRI may not be as helpful. “I don’t think this is going to yield insights into every neurologic disorder,” says Greicius, who is dubious that abnormalities in resting-state connectivity exist in disorders such as multiple sclerosis — in which neuronal deterioration is “willy-nilly” — or traumatic brain injury, which can disproportionately affect an isolated area. But for conditions like autism, it could provide valuable opportunities to both understand and improve treatments. First, however, as with any new technique, scientists will have to replicate and confirm the early results. If they hold up, he says, “That’s going to help shore up recent exciting preliminary findings” — and hopefully pave the way for assigning certain mental illnesses their own imaging fingerprint that could give doctors and patients a head start on treatments.