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Clues from the ‘Connectome’

EEGs could help doctors diagnose attention disorders

Resembling cat’s cradle patterns, brain electroencephalograms distinguished study participants with attention deficit disorder from neurotypical controls. White dots show electrode positions. Yellow connections indicate decreased coherence, and red connections indicate greater coherence, in participants with ADD. Image: Frank Duffy

Attention deficit disorder (ADD), with or without hyperactivity, affects up to 5 percent of the population, according to the DSM-5. It can be difficult to diagnose behaviorally, and coexisting conditions like autism spectrum disorder or mood disorders can mask it.

While recent MRI studies have indicated differences in the brains of people with ADD, the differences are too subtle and the tests too expensive to be a practical diagnostic measure.

New research suggests a role for an everyday, relatively cheap alternative: electroencephalography, or EEG.

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“EEG has been around a long time and people have forgotten how good it is.” —Frank Duffy

Frank Duffy, Harvard Medical School associate professor of neurology at Boston Children’s Hospital, and colleagues analyzed EEG recordings from 347 children and young adults with an ADD diagnosis and 619 neurotypical controls. But this wasn’t the usual kind of EEG reading.

Duffy, originally trained as an engineer, took a deep, computational look inside the EEG signals. He compared recordings from 24 electrodes in the brain to quantify their coherence—the degree of synchrony between EEG readouts from two or more regions.

The idea is that if two or more EEG waves rise and fall together over time, their coherence is high, indicating that those areas are connected and in communication. Overall, the researchers say, coherence can reveal how the brain is organized.

Calculating coherence

Duffy previously showed differences in EEG coherence between children with autism spectrum disorder and neurotypical controls.

In the new study, published in BMC Medicine, he started with 4,416 potential coherence variables and identified 40 that explained half of the difference between the ADD and control groups. These factors were even better at distinguishing ADD when the children were grouped by age. They held up even among children who were taking ADD medications or had coexisting disorders.

“We are able to look at the brain pattern and pick up disorders of attention, irrespective of any coexisting diagnoses or use of medications,” Duffy said.

Seven coherence factors remained highly statistically significant when subjected to rigorous validation testing. Factor 13-1 (top left in the image above) was the most significant of all. It indicates a strong disconnection between and within the temporal and occipital regions on both sides of the brain.

“We are able to look at the brain pattern and pick up disorders of attention, irrespective of any coexisting diagnoses or use of medications.” —Frank Duffy

Duffy also applied the EEG connectome analysis to his previous cohort of children and youth with autism spectrum disorder. The ADD coherence factors identified 30 percent of them as also having attention issues. This suggests to Duffy that some people with autism may benefit from the stimulants used to treat ADD.

Symptoms versus disease

Duffy and colleagues don’t think the ADD connectome is ready to be used as a diagnostic test. To avoid confusing symptoms with disease, they first want to develop connectomes for psychiatric disorders that often coexist with ADD.

“What we’re detecting are the brain patterns that show a disorder of attention, regardless of the underlying disease that got the child there,” Duffy said.

Ultimately, Duffy envisions a much larger diagnostic role for EEG beyond its current use in epilepsy. He has also published successful EEG coherence studies in chronic fatigue syndrome (which can be hard to distinguish from depression), Asperger’s syndrome and schizophrenia prodrome syndrome. He’s planning other studies as well.

Someday, in Duffy’s thinking, patients with complex neurobehavioral symptoms could have a single EEG. From this, clinicians could analyze a variety of connectomes to identify disease states.

“We could potentially look at brain patterns associated with key behaviors, such as autistic features or attentional issues, and recompose these into diagnoses,” he said.

An objective, EEG-based diagnostic measure could be very useful in settings where neurologists, psychiatrists and other behavioral specialists are in short supply.

“EEG has been around a long time and people have forgotten how good it is,” Duffy said.

Adapted from a post on Vector, the Boston Children’s research and clinical innovation blog.