They developed a new type of algorithm called “basis profile curve identification”.
“Our findings show that this new type of algorithm may help us understand which brain regions directly interact with one another, which in turn may help guide placement of electrodes for stimulating devices to treat network brain diseases,” said Kai Miller, a Mayo Clinic neurosurgeon.
The new technique was demonstrated for an array of implanted brain surface electrodes in a human patient. A patient with a brain tumour underwent placement of an electrocorticographic electrode array to locate seizures and map brain function before a tumour was removed.
Every electrode interaction resulted in hundreds to thousands of time points to be studied using the new algorithm.
The framework enables straightforward interpretation of single-pulse brain stimulation data, and can be applied generically to explore the diverse milieu of interactions that comprise the connectome, the researchers explained in the study published in PLOS Computational Biology.
“Neurologic data to date is perhaps the most challenging and exciting data to model for AI researchers,” said Klaus-Robert Mueller, member of the Google Research Brain Team.
Source: IANS
Stay connected with us on social media platform for instant update click here to join our Twitter, & Facebook
We are now on Telegram. Click here to join our channel (@TechiUpdate) and stay updated with the latest Technology headlines.
For all the latest Health News Click Here
For the latest news and updates, follow us on Google News.
Denial of responsibility! NewsAzi is an automatic aggregator around the global media. All the content are available free on Internet. We have just arranged it in one platform for educational purpose only. In each content, the hyperlink to the primary source is specified. All trademarks belong to their rightful owners, all materials to their authors. If you are the owner of the content and do not want us to publish your materials on our website, please contact us by email – [email protected]. The content will be deleted within 24 hours.
