Brainwave Patterns Could Help Predict Schizophrenia, Depression

A teen's study has revealed a unique and consistent signature brainwave patterns. "Showing that these fingerprints may open up future possibilities in using this kind of analysis in larger samples to look for endophenotypes that might be predictive of someone, say, who might go on to develop schizophrenia or depression." Despite the major neural overhaul underway during adolescence, most individuals maintained a unique and consistent pattern of underlying brain oscillations.

"Is there some inherent quality of the brainwave signal that is a core quality that is sustained, even in the face of these large developmental changes?" asked co-author Mary Carskadon, professor of psychiatry at the Warren Alpert Medical School of Brown University.

Carskadon recruited 19 volunteers who were 9 or 10 years old and 26 who were 15 or 16 years old to sleep for two consecutive nights in the lab while EEG electrodes recorded oscillations in their brains during both REM and non-REM sleep. For each child she repeated the measurements about two years later.

Carskadon sent the data to collaborators Leila Tarokh and Peter Achermann at the University of Zurich.

They fed mathematical descriptions of the EEG waves into a computer armed with an algorithm to group waves of similar shapes and frequencies together.

The computers had no information about which waves came from which night from which teen, but the algorithm ended up matching all four nights of sleep for most of the kids, a striking sign of their consistent but unique nature.

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"I was pretty astounded about how well the algorithm was able to sort these individuals' patterns together," said Tarokh, the paper's lead author.

The research was recently published in the Journal of Neuroscience.

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Source-ANI