{"id":32563,"date":"2018-02-02T12:05:57","date_gmt":"2018-02-02T17:05:57","guid":{"rendered":"https:\/\/sciencebusiness.technewslit.com\/?p=32563"},"modified":"2018-02-02T12:05:57","modified_gmt":"2018-02-02T17:05:57","slug":"brain-wave-data-harnessed-for-open-source-brain-model","status":"publish","type":"post","link":"https:\/\/technewslit.com\/sciencebusiness\/?p=32563","title":{"rendered":"Brain Wave Data Harnessed for Open-Source Brain Model"},"content":{"rendered":"
\"Brain<\/a>
Brain wiring illustration (Courtesy, Human Connectome Project and NIH)<\/figcaption><\/figure>\n

2 February 2018. A lab in Germany created a technique for discovering a person’s neurological patterns from brain waves captured with a headset and simulated with population-wide brain data run on open-source software. A team from Charit\u00e9 – Universit\u00e4tsmedizin<\/a> in Berlin published an advance copy of its findings in the journal eLife<\/em><\/a> (free registration required), and are preparing a mobile app to make the technique widely available.<\/p>\n

Researchers led by Charit\u00e9 neuroscientist Petra Ritter<\/a> are seeking more accessible ways of understanding a person’s brain activity that can take advantage of the Virtual Brain<\/a>, a repository of neurological data from a wide range of clinical and experimental sources, including computational models and functional MRI<\/a>, or fMRI, scans. The Virtual Brain, established by Ritter and colleagues in 2012, captures these de-identified data and and packages them for computer simulations of brain network activity, including for individuals. Plus, the Virtual Brain is freely available as open-source software, downloaded more than 10,000 times<\/a>.<\/p>\n

In this study, Ritter and colleagues — from Charit\u00e9, as well as labs in Canada, France, and Spain — devised a method for easier capture of a person’s brain activity that can run on computer models generated by Virtual Brain. The researchers use headsets to measure brain waves with electroencephalography<\/a> or EEG, which while previously available, were not integrated into brain network models like Virtual Brain. The team collected EEG brain wave data from 15 volunteers who wore the headsets for 20 minutes, then ran simulations of brain network activity with Virtual Brain for comparison against functional MRI, a noninvasive but more specialized and expensive brain imaging technique.<\/p>\n

The results show the simulations run with EEG data can predict an individual’s resting-state brain activity shown on functional MRI scans, but also a person’s brain network structure. The EEG-based simulations also correlated with several other neurological measures. “This new method of brain simulation,” says Ritter in a\u00a0Charit\u00e9 statement, “allows us to combine theories of how the nervous system works with physical measurements and integrate them into a single comprehensive model that is both physiologically and anatomically grounded.”<\/p>\n

The researchers now want to test the technique with larger numbers of people, to be able to help diagnose neurological disorders such as epilepsy and stroke. Ritter’s lab is also writing a mobile app known as BrainModes<\/a> aimed at helping individuals better understand their own brain networks and activity.<\/p>\n

The Virtual Brain software is available for download from the project’s web site<\/a>, and code and data from the study are available from GitHub<\/a>.<\/p>\n

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