The brain is a diverse organ that forms the basis of learning, memory, behavior and personality. Structural differences in the brain among individuals can help account for differences in how we act, think and look.
However, while neuroscientists in the past have been able to trace the basis of specific traits such as memory, researchers have failed to explain just how we are so cognitively and phenotypically diverse. New research conducted at the Beckman Institute for Advanced Science and Technology at the University of Illinois at Urbana-Champaign uncovered traits in the brain that may explain our cognitive and phenotypic diversity. It was published in NeuroImage.
The researchers began by using neuroimaging methods, such as Magnetic Resonance Imaging (MRI) and tests of memory, to assess several properties of the participants’ mental ability and brain structure. The use of MRI allowed Aron Barbey, the leader of the study and director of the Decision Neuroscience Laboratory at the Beckman Institute, and his team to examine different structures and characteristics of the brain, such as nerve fiber bundles, white-matter tracts, volume, cortical thickness and blood flow.
Cognitive testing also allowed them to assess participants’ working memory, executive memory, episodic memory and fluid intelligence, among other measures. In line with past studies, Barbey and his colleagues found a large variation in these measurements among individuals.
After plotting the correlation between each measurement, the team was able to divide its data into four large traits based on their level of relatedness using Independent Component Analysis (ICA). By doing this, Barbey and his colleagues found that their four groups of traits were able to account for 58 percent of the structural variation in the participants. This analysis, however, could not explain the cognitive differences between individuals.
The team then set out to account for differences in learning and memory between the study’s participants. By performing another ICA analysis that only considered the cognitive differences not explained by the four traits, the group was able to uncover specific anatomical characteristics that explained differences in learning and memory between participants. Specifically, Barbey found that gray matter regions, white matter fiber tracts and networks in the superior parietal and frontal regions of the brain are strongly related to cognitive variables such as episodic memory and executive function.
“A major focus of research in cognitive neuroscience is understanding how intelligence is shaped by individual differences in brain structure and function,” Aron Barbey told the Illinois News Bureau.
Barbey’s research represents the first successful effort at characterizing the individual variation among our brains. His work may allow scientists to explain the differences in intelligence among humans.
“Brains are as different as faces, and this study helped us understand what a ‘normal’ brain looks like,” Patrick Watson, a postdoctoral researcher at the Beckman Institute and primary author of the paper, said. “By looking for unexpected brain differences, we were able to home in on parts of the brain related to things like memory and intelligence.”
The researchers’ approach to studying the brain also represents a new data-driven era of neuroscience. By using computational and statistical tools such as ICA, scientists may be able to detect underlying sources of variation that are invisible to traditional neuroimaging methods. Integrating computers with neuroscience may lead to novel ways to study the brain, according to Stephen Koslow, former director of the Division of Basic and Clinical Neuroscience at the National Institute of Mental Health.
“What we are attempting to do is take advantage of the advances in computer and communications technologies to develop tools to study (the brain and nervous system) at different levels,” Koslow told The Scientist.
