An updated model of the cortical surface improves imaging of brain activity. The human brain plays a vital role in managing basic functions such as perception, memory, language, cognition, consciousness, and emotions.

To understand how the brain works, scientists often use neuroimaging to record participants’ brain activity while the brain is performing a task or resting. Brain functions are systematically organized in the cerebral cortex, the outer layer of the human brain. Researchers often use what is called a “cortical surface model” to analyze neuroimaging data and study the functional organization of the human brain.

Every brain is shaped differently. To analyze neuroimaging data from multiple people, researchers need to record the data using the same brain template, which allows the same anatomical locations to be identified in different brain regions, even if the brains are shaped differently. These locations are called “ridges.”

Several versions of such templates have been made over the past 25 years, and the most commonly used cortical surface templates today are based on data collected from 40 brains.

“Open Neuro Averaging” Presentation

Now Dartmouth researchers have created a new cortical surface template, called “OpenNeuro Average,” or “onavg” for short, that allows for greater accuracy and efficiency in analyzing neuroimaging data.

The results are published at: Nature Methods.

“Our cortical surface model, onavg, is the first model that samples different parts of the brain in the same way,” says lead author Feilong Ma, a postdoctoral researcher in the Huxby Lab in Dartmouth’s Department of Psychological and Brain Sciences. “It’s a more computationally efficient, less biased map.”

The team created a template based on the cortical anatomy of 1,031 brains from 30 datasets on OpenNeuro, a free and open-source platform for sharing neuroimaging data. According to the co-authors, this is also the first cortical surface model based on the geometric shape of the brain.

In contrast, previous templates sampled different parts of the cortex unequally and relied on a spherical shape to determine the location of cortical vertices, leading to biases in the distribution of vertices. In contrast, previous templates sampled different parts of the cortex unequally and relied on a spherical shape to determine the location of cortical vertices, leading to biases in the distribution of vertices.

With the Onavg template, less data is required for analysis.

“Obtaining data from neuroimaging is very expensive, and for some clinical populations, for example if you are working on rare diseases, it may be difficult or impossible to obtain a lot of data, so being able to get better results with less data is a challenge,” Feilong says. “Through more efficient use of data, our template has the potential to increase the reproducibility and repeatability of academic research results.”

Broader Impacts and Contributions

“I think Onavg is a methodological advance that has broad applications in all aspects of cognitive and clinical neuroscience,” says co-author James Haxby, professor in the Department of Psychological and Brain Sciences and former director of the Center for Cognitive Neuroscience at Dartmouth.

He says cortical surface patterns could be used to study vision, hearing, language and individual differences, as well as disorders such as autism and neurodegenerative diseases such as Alzheimer’s and Parkinson’s.

“We think this will have a broad and profound impact in the field,” Huxby says. Jiahui Guo, a former postdoctoral researcher in psychological and brain sciences and an associate professor in the School of Behavioral and Brain Sciences at the University of Texas at Dallas, and Maria Ida Gobbini Bologna, an associate professor in the Department of Medicine and Surgical Sciences at the University of Texas at Dallas, also contributed to the work.