Brainwave Study Reveals Oscillation Patterns That May Predict Transition to Psychosis

Brainwave Study Reveals Oscillation Patterns That May Predict Transition to Psychosis

Posted: August 20, 2020
Brainwave Study Reveals Oscillation Patterns That May Predict Transition to Psychosis

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Researchers using a technology that measures brainwave patterns have identified signatures that may make it possible to clinically predict which people at high risk for psychosis will in fact progress to psychosis.

 

Researchers led by a BBRF grantee have reported progress in analyzing neural oscillations or “brainwaves” that may make it possible to clinically characterize which individuals at high risk of developing psychosis will in fact go on to develop psychosis. Predicting this transition—thus making early or preventive treatment possible—has long been among the most urgent objectives of neuropsychiatric research.

An individual’s first experience of psychosis is typically very upsetting for a variety of reasons. The symptoms are highly disorienting and unfamiliar—a loss of touch with reality, frequently marked by seeing, hearing, or believing things that are not objectively present or true. In addition to the disconnect between one’s sense-perceptions and “reality,” a first episode of psychosis is one among several other symptoms (attention difficulties, a recent history of cognitive decline, and social withdrawal) that often occur as one makes a transition to schizophrenia.

Only a minority of individuals at clinical high risk of psychosis (a recently published analysis puts the figure at 22%) will develop psychosis within 4 years. But is there a way to identify these people in advance?

A growing body of research has suggested that connectivity between the brain’s frontal cortex and sensory regions is impaired both in individuals who have had first-episode psychosis (FEP) and those who are at “clinically high-risk” (CHR) for having such an episode. Peter J. Uhlhaas, Ph.D., of Charité Universitätsmedizin, Berlin, Germany, led a team in pursuing one important aspect of this research, which has suggested that emerging psychosis is accompanied by aberrant brainwave activity in the visual cortex.

In 2009, Dr. Uhlhaas received a BBRF Young Investigator grant to explore the hypothesis that imprecise timing of neural activity is among the core aspects of schizophrenia pathophysiology. In a paper recently published in JAMA Psychiatry, Dr. Uhlhaas, with co-authors including 2009 BBRF Distinguished Investigator Stephen Lawrie, M.D., are now able to report that the timing of high-frequency oscillations in visual cortices of the brain “is the first impairment to emerge” in individuals at clinical high risk of first-episode psychosis, and that other features of brainwave oscillations do indeed seem to predict clinical course.

The team recruited 232 participants, most of them in their late teens or twenties: 119 met criteria for being at clinical high risk (CHR) of psychosis; 38 did not meet these criteria but had been diagnosed with non-psychotic psychiatric disorders; 26 had experienced first-episode psychosis (FEP); and 49 were healthy controls. All were regularly evaluated over a 3-year period. And all were given, at baseline, a task to perform on a computer which required them to press a button in response to visual stimuli on the screen that varied in duration from ¾ of a second to 3 seconds. While participants performed 3 blocks of 80 such tests, their brainwaves were monitored using a technology called magnetoencephalography (MEG).

MEG, an approach similar to EEG (electroencephalography), allows the assessment of brainwaves with high sensitivity. In addition, it is possible to identify with MEG where in the brain these oscillations are generated.

Results of the trial broadly corroborated past research highlighting the importance of the visual cortex in cognitive processing in the healthy brain—and offering new evidence helping to show how specific aberrations in brainwaves generated by neural activity in the visual cortex relate to various cognitive deficits seen in FEP, schizophrenia, as well as, in certain respects, in those at high risk of developing FEP.

First, the team demonstrated that in both FEP and those at high risk for it, the “synchrony” of waveforms generated in the visual cortex in two high-frequency bands—gamma waves (up to 100 oscillations per second) and beta waves (up to 40 oscillations per second)—was notably inconsistent. Such inconsistency in the relationship between these waves suggests processes within neural networks in the visual cortex that contribute to psychosis. This new research shows, importantly, that such inconsistencies are present in people with pre-psychosis symptoms.

Second, in both FEP participants and those at high risk of psychosis, connectivity between the frontal portion of the brain and occipital areas containing the visual cortex were observed to be impaired.

Third, in contrast to participants at high-risk, those who already had a first psychotic episode displayed reduced power in the high-frequency gamma waves emanating from the occipital lobe.

A fourth and most important finding, the team said, was their observation, after following participants over 3 years, that those at high risk for psychosis who had displayed increased variability of certain waveform patterns between different “runs” in the visual processing test went on to have more persistent “subthreshold” symptoms of psychosis—an indication that they would have poorer clinical courses and increased likelihood of progressing to a first psychotic episode and perhaps also schizophrenia.

“Impaired high-frequency oscillations in the visual cortex are an important aspect of circuit dysfunction, which could constitute a biomarker for clinical staging of emerging psychosis,” Dr. Uhlhaas and colleagues concluded. Their future research will focus on circuit mechanisms regulating neural responses, “which may offer targets for preventive approaches.”