Stories about: EEGs

‘See through,’ high-resolution EEG recording array gives a better glimpse of the brain

Transparent microelectrodes allow EEG recording at the single-neuron level, with simultaneous 2-photon optical imaging of calcium activity.
Transparent microelectrodes allow EEG recording at the single-neuron level, with simultaneous 2-photon optical imaging of calcium activity. (CREDIT: Yi Qiang et al. Sci. Adv. 4, eaat0626 (2018).)

Electroencephalography (EEG), which records electrical discharges in the brain, is a well-established technique for measuring brain activity. But current EEG electrode arrays, even placed directly on the brain, cannot distinguish the activity of different types of brain cells, instead averaging signals from a general area. Nor is it possible to easily compare EEG data with brain imaging data.

A collaboration between neuroscientist Michela Fagiolini, PhD at Boston Children’s Hospital and engineer Hui Fang, PhD at Northeastern University has led to a highly miniaturized, see-through EEG device. It promises to be much more useful for understanding the brain’s workings.

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Diagnosing autism in infants? EEG algorithms make accurate predictions

autism EEGs
EEG nets are easily slipped over an infant’s head and cause no discomfort. (Credit: Nelson Lab)

The earlier autism can be diagnosed, the more effective interventions typically are. But the signs are often subtle or can be misinterpreted at young ages. As a result, many children aren’t diagnosed until age 2 or even older. Now, a study shows that electroencephalograms (EEGs), which measure the brain’s electrical activity, can accurately predict or rule out autism spectrum disorder (ASD) in babies as young as 3 months old. It appears today in Scientific Reports.

The beauty of EEG is that it’s already used in many pediatric neurology or developmental pediatric settings. “EEGs are low-cost, non-invasive and relatively easy to incorporate into well-baby checkups,” says study co-author Charles Nelson, PhD, director of the Laboratories of Cognitive Neuroscience at Boston Children’s Hospital. “Their reliability in predicting whether a child will develop autism raises the possibility of intervening very early, well before clear behavioral symptoms emerge.”

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Fast brain waves: A better biomarker for epilepsy

EEG and MEG detection of HFOs, fast brain waves associated with epilepsy
Localization of fast brain waves, called HFOs, with scalp EEG (left) and MEG (right). HFOs present a new biomarker for areas of the brain responsible for epileptic seizures.

In the U.S., about one in 100 people have some form of epilepsy. A third of those people have seizures that cannot be controlled with drugs, eventually requiring surgery to remove the area of their brain tissue that is triggering seizure activity.

“If you can identify and surgically remove the entire epileptogenic zone, you will have a patient who is seizure-free,” says Christos Papadelis, PhD, who leads the Boston Children’s Brain Dynamics Laboratory in the Division of Newborn Medicine and is an assistant professor in pediatrics at Harvard Medical School.

Even experts in this field were skeptical for years about the non-invasive detection of HFOs. But now, thanks to our study and other researchers’ work, these people are changing their minds. At present, however, these surgeries are not always successful. Current diagnostics lack the ability to determine precisely which parts of an individual’s brain are inducing his or her seizures, called the epileptogenic zone. In addition, robust biomarkers for the epileptogenic zone have been poorly established.

But now, a team at Boston Children’s Hospital is doing research to improve pre-surgical pinpointing of the brain’s epileptogenic zone. They are using a newly-established biomarker for epilepsy — fast brain waves called high-frequency oscillations (HFOs) — that can be detected non-invasively using scalp electroencephalography (EEG) and magnetoencephalography (MEG).

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Brain ‘connectome’ on EEG could help diagnose attentional disorders

EEG connectome could diagnose attentional disorders ADHD
EEGs shouldn’t just be for epilepsy, say these researchers.

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).

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Intelligent ICU monitoring for patients in status epilepticus: BurSIn

The BurSIn system, in development, interprets EEG data along several key parameters and accurately identifies burst and suppression patterns.
The BurSIn system, in development, interprets EEG data along several key parameters and accurately identifies burst and suppression patterns.

Status epilepticus, a life-threatening form of persistent seizure activity in the brain, is challenging to treat. It requires hospitalization in an intensive care unit, constant monitoring and meticulous medication adjustment. An automated, intelligent monitoring system developed by clinicians and engineers at Boston Children’s Hospital could transform ICU care for this neurological emergency.

Typically, children in status epilepticus are first given powerful, short-acting seizure medications. If their seizures continue, they may need to be placed in a medically induced coma, using long-acting sedatives or general anesthetics. “The goal,” explains biomedical engineer Christos Papadelis, PhD, “is to supply enough sedating medication to suppress brain activity and protect the brain from damage, while at the same time avoiding over-sedation.”

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Could “network” analysis of the brain explain autism’s features?

Ed note: The Obama administration is expected to unveil plans for a decade-long Brain Activity Map project next month. This is Part One of a two-part series on brain mapping.

autism
How is information routed in the brains of children with autism? (Image: Jpatokal/Wikimedia Commons)

It’s now pretty well accepted that autism is a disorder of brain connectivity—demonstrated visually with advanced MRI techniques that can track the paths of nerve fibers. Recent exciting work analyzing EEG recordings supports the idea of altered connectivity, while suggesting the possibility of a diagnostic test for autism.

But what’s happening on a functional level? A study published this week zooms out to take a 30,000-foot view, tracking how the brain routes information in children with autism—in much the way airlines and electrical grids are mapped—and assessing the function of the network as a whole.

“What we found may well change the way we look at the brains of autistic children,” says investigator Jurriaan Peters, MD, of the Department of Neurology at Boston Children’s Hospital.

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The brain whisperer: Tracking EEG footprints of autism and mental illness

EEG signals may reflect underlying brain connectivity patterns in autism. This brain has less dense local clusters linked by long-range connections, which may represent a normal pattern. The brain at right has denser, more uniform local connectivity with fewer long-distance connections in some regions.

Bill Bosl is used to looking for patterns. A computer scientist trained in atmospheric physics, geophysics and mathematics, he’s invented a method for computing properties of porous materials from CT scans. At the Lawrence Livermore National Lab, he worked on remote sensing problems, reading complex wave patterns to discern the location of groundwater, oil deposits and fault lines.

Today, he’s trying to measure thought – to compute what’s going on in hard-to-understand disorders like autism, which is currently diagnosed purely on the basis of behavior.  “The mathematical methods are very similar,” he says. “You’re analyzing waves.”

The waves in this case are electroencephalograms (EEGs), those squiggly lines generated by electrical activity in the brain. In autism,

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