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EEG study aims to predict psychosis

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EEG study aims to predict psychosis

As schizophrenia is considered one of the more severe forms of mental illness, an active area of research at the Centre for Addiction and Mental Health (CAMH) is to identify, as early as possible, those who are likely to develop the illness.

“If we can find a way to predict who will develop psychosis, we can work towards preventing the onset,” says Dr. Michael Kiang, Clinician-Scientist and Psychiatrist in the Schizophrenia Division and in the Temerty Centre for Therapeutic Brain Intervention at CAMH.

Dr. Michael Kiang

Long before symptoms appear, subtle brain changes are taking place in people who eventually develop psychosis, changes that can be measured and compared to those who are healthy.

Dr. Kiang and his colleagues hope to determine whether one type of change – cognitive brain responses that are obtained using electroencephalography (EEG) – can be used to predict who will develop schizophrenia. EEG is a well-established and inexpensive test that measures brain electrical activity non-invasively from the scalp.

Defining who is at risk

This new research, funded by the Ontario Mental Health Foundation, focuses on a small group of people who have a 400 times higher risk of developing schizophrenia: young people aged 16 to 35, who are experiencing symptoms similar to psychosis, but in a milder form.

For example, explains Dr. Kiang, people with schizophrenia may falsely believe that someone wants to hurt them. Those in the high-risk group could have such thoughts, but are able to question them. Instead of hearing voices, another symptom of schizophrenia, those at high risk may hear sounds but are aware that there’s no source of the sound. In both cases, these experiences cause distress.

At CAMH, the Focus on Youth Psychosis Prevention Clinic provides a short-term program, involving education and stress management, for young people experiencing these symptoms.

“Between 25 and 40 per cent of this high-risk group will develop schizophrenia, but the rest won’t,” says Dr. Kiang. “If we can find a way to identify those who will, we can target more intensive treatments to patients who are at the highest risk.”

Brain activity differences

As one part of the study, participants view a series of words. Some words will logically go together, such as “cat” and “mouse.” But others will not have any connection, such as “cat” and “arrow.”

The brain’s reactions to different word pairs can be measured to a fine degree. In fact, tests have shown that there are well-established differences in brain activity between people who have schizophrenia and those who don’t, says Dr. Kiang.

Brain activity is measured through voltage fluctuations at the scalp, using EEG, which shows changes in real time. More specifically, researchers are interested in the N400 ”brainwave,” so described because it measures a response 400 milliseconds after the stimulus – in this case, reading a word – occurs.

In people with no schizophrenia diagnosis, the N400 wave is smaller if the word is related to a preceding one, such as cat-MOUSE. The wave is larger for unconnected words, like cat-ARROW. But in people with schizophrenia, the wave remains large in both cases, says Dr. Kiang.

“This suggests that those with schizophrenia don’t distinguish the relationships between words in the same way as people without a diagnosis, who predict what will come next, based on these relationships.”

Through this study, Dr. Kiang hopes to see if these differences also exist in those who are at high risk of developing schizophrenia. This would show that these differences in brain processing can be identified even before an episode of psychosis.

By tracking study participants over two years, a second aim is to determine if the size of the N400 waveform matters. The question of interest is whether the largest N400 waveforms in response to unrelated words predict a diagnosis of schizophrenia. Such results would provide the evidence to add this technique as a component of algorithms to predict psychosis, and intensify prevention efforts among this group.

The research team plans to recruit 50 participants over the next two years, and track the progress of each participant for two years after entering the study.







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