Summary: Researchers are using big data and artificial intelligence to map neural networks in the brain. The new technology could help to better understand the progression of neurodegenerative diseases.

Patients with dementia and other neural diseases show physical symptoms such as stumbling and confusion, but identifying the problem isn’t as simple as taking an X-ray. A group of researchers at Purdue University are designing data-driven tools that will help clinicians better understand the progression of neurodegenerative diseases by identifying and tracking changes in the brain.

“We’re not to the point where we’re taking X-rays to see if you have a broken bone in your leg, but we’re at least at the stage where we’re saying, ‘Your gait is very funny,’” said Tom Talavage, professor of electrical and computer engineering and biomedical engineering, and a co-investigator for the project. “We can narrow it down to something wrong with your leg, and we can make inferences about what’s wrong with your leg.

We can say, ‘You probably have a broken leg because of how you’re walking.’ That’s what we’re really getting at.” The project is led by Joaquín Goñi, an assistant professor of biomedical engineering who studies the network of neural connections composing the human brain. This network is called the connectome, the focus of an emerging field of study known as brain connectomics.

Brain-imaging techniques, such as diffusion weighted imaging and functional magnetic resonance imaging (fMRI), allow neuroscientists to model and examine the connectome to understand communication between different regions of the brain. This helps them see which parts of the brain are functioning normally – and which regions are not – by observing changes over time. Read more from…

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