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 MRI too expensive to be a practical diagnostic measure. But new research suggests a role for an everyday, relatively cheap alternative: electroencephalography (EEG).
Boston Children’s Hospital neurologist Frank H. Duffy, MD, with colleagues in the Department of Psychiatry, 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 signal. 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, coherence can reveal how the brain is organized. You can think of it as a poor man’s alternative to the neuroimaging-based Human Connectome Project.
At right (click to enlarge) are 28 brain EEG “coherence factors” distinguishing subjects with ADD from neurotypical controls. Brains are viewed from above, and the white dots show electrode positions. The yellow connections between electrodes denote decreased coherence in subjects with ADD. The red connections denote increased coherence.
Duffy has previously shown 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. And 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 says.
Seven coherence factors remained highly statistically significant when subjected to rigorous validation testing. Factor 13-1 (top left in the image) 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.
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 attentional 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 — yet. 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 says.
EEG has been around a long time and people have forgotten how good it is.Ultimately, though, 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. And he’s planning other studies.
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.”
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 says.
Duffy details his vision in this blog post for BioMedCentral.