Summary: Researchers have identified spatial and temporal abnormalities in spontaneous fixational saccades as a potential biomarker for cognitive and positive symptoms in schizophrenia. Researchers combined patient data of fixational eye movement recorded over 60 seconds with machine learning technology, which was able to determine schizophrenia with 85% accuracy. This discovery suggests that fixational saccades could serve as an easily obtainable complementary diagnostic tool for the condition.

Source: Chinese Academy of Science.

In a study published online in the Schizophrenia Bulletin, researchers from Dr. Wang Wei’s lab at the Center for Excellence in Brain Science and Intelligence Technology of the Chinese Academy of Sciences, and Dr. Wang Jijun’ team at Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, demonstrated spatial and temporal abnormalities of spontaneous fixational saccades and their correlates with positive and cognitive symptoms in schizophrenia, suggesting that fixational saccades are a promising and easily obtainable biomarker for cognitive and positive symptoms and for complementary diagnosis in schizophrenia.

“A human brain model can simulate an experiment a million times for many different conditions, but the actual human experiment can be performed only once or a few times,” said Viktor Jirsa, a professor at Aix-Marseille University.

Responding to such critiques, the HBP worked to restructure the effort in its early days with new leadership, organization, and goals that were more flexible and attainable. “The HBP got a more versatile, pluralistic approach,” said Viktor Jirsa, a professor at Aix-Marseille University and one of the HBP lead scientists. He believes that these changes fixed at least some of HBP’s issues. “The project has been on a very productive and scientifically fruitful course since then.”

After restructuring, the HBP became a European hub on brain research, with hundreds of scientists joining its growing network. The HBP created projects focused on various brain topics, from consciousness to neurodegenerative diseases. HBP scientists worked on complex subjects, such as mapping out the brain, combining neuroscience and robotics, and experimenting with neuromorphic computing, a computational technique inspired by the human brain structure and function—to name just a few.

Language and speech are how we express our inner thoughts. But neuroscientists just bypassed the need for audible speech, at least in the lab. Instead, they directly tapped into the biological machine that generates language and ideas: the brain.

Using brain scans and a hefty dose of machine learning, a team from the University of Texas at Austin developed a “language decoder” that captures the gist of what a person hears based on their brain activation patterns alone. Far from a one-trick pony, the decoder can also translate imagined speech, and even generate descriptive subtitles for silent movies using neural activity.

Here’s the kicker: the method doesn’t require surgery. Rather than relying on implanted electrodes, which listen in on electrical bursts directly from neurons, the neurotechnology uses functional magnetic resonance imaging (fMRI), a completely non-invasive procedure, to generate brain maps that correspond to language.