Neuroscientists unveil digital ‘translator’ for brain studies

UCLA Health researchers have helped to develop a new digital toolbox to create a “common language” for brain network studies, potentially accelerating new discoveries and treatments for neurological and psychiatric conditions.

In a study recently published in the journal Nature Communications, the authors say the open-source software will help researchers worldwide overcome a longstanding hurdle in brain imaging research.

“As long as people have been interested in studying the brain, they have tried to map it out by answering a basic question: how many brain regions are there?” said study senior author Lucina Uddin, a UCLA Health Psychiatry and Biobehavioral Sciences Professor and Director of the UCLA Brain Connectivity and Cognition Laboratory.

“You can divide the brain based on different attributes—cell structure, function or some other characteristic—and there have been multiple different brain atlases developed over the years that have given different names to these divisions,” Uddin said. “But we have to come to some common agreement if we want to talk across research groups and share findings.”

The new open-source software, named the Network Correspondence Toolbox, allows researchers to plug in their brain imaging data and compare them to 16 of the most widely used brain atlases to determine their similarity.

Researchers and doctors have increasingly relied on brain imaging methods, such as MRIs, to understand what is underlying different symptoms and disorders. Similar to the design of major airports, certain areas of the brain may act as hubs that have more complex connections to other brain regions, Uddin said. The new tool can be used to better understand how these brain hubs interact and how alterations or damage may play a role in a number of different disorders or symptoms, Uddin said.

Better understanding these broader connections may work to bolster individual-level, precision treatment for psychiatric or neurological disorders.

“I’m hoping people will use this tool to find commonalities across findings that might otherwise have been hidden because of the inconsistent naming,” she says.

“It could change the way we think about dividing up the brain. If so many different groups are creating different atlases with slight differences, can this help inform us of the most common and reproducible patterns, and can we adopt more standards that build on those commonalities?”

UCLA Health researchers have helped to develop a new digital toolbox to create a “common language” for brain network studies, potentially accelerating new discoveries and treatments for neurological and psychiatric conditions.

In a study recently published in the journal Nature Communications, the authors say the open-source software will help researchers worldwide overcome a longstanding hurdle in brain imaging research.

“As long as people have been interested in studying the brain, they have tried to map it out by answering a basic question: how many brain regions are there?” said study senior author Lucina Uddin, a UCLA Health Psychiatry and Biobehavioral Sciences Professor and Director of the UCLA Brain Connectivity and Cognition Laboratory.

“You can divide the brain based on different attributes—cell structure, function or some other characteristic—and there have been multiple different brain atlases developed over the years that have given different names to these divisions,” Uddin said. “But we have to come to some common agreement if we want to talk across research groups and share findings.”

The new open-source software, named the Network Correspondence Toolbox, allows researchers to plug in their brain imaging data and compare them to 16 of the most widely used brain atlases to determine their similarity.

Researchers and doctors have increasingly relied on brain imaging methods, such as MRIs, to understand what is underlying different symptoms and disorders. Similar to the design of major airports, certain areas of the brain may act as hubs that have more complex connections to other brain regions, Uddin said. The new tool can be used to better understand how these brain hubs interact and how alterations or damage may play a role in a number of different disorders or symptoms, Uddin said.

Better understanding these broader connections may work to bolster individual-level, precision treatment for psychiatric or neurological disorders.

“I’m hoping people will use this tool to find commonalities across findings that might otherwise have been hidden because of the inconsistent naming,” she says.

“It could change the way we think about dividing up the brain. If so many different groups are creating different atlases with slight differences, can this help inform us of the most common and reproducible patterns, and can we adopt more standards that build on those commonalities?”