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Positive behavioral traits and functional connections covary in HCP Subjects
A just released finding from HCP data reveals a strong link between patterns of functional connectivity in the brain’s default mode network and “positive” personal traits such as fluid intelligence (IQ), language skills, and life satisfaction. The study conducted by WU-Minn HCP consortium investigators was released in Nature Neuroscience this week.
Authors searched patterns of resting state functional connectivity in 461 subjects from the HCP 500 Subjects Release, looked for correlations between 158 out-of-scanner behavioral and demographic measures in the same set of subjects, then applied a canonical correlation analysis (CCA) to find maximal relationships between the two sets of data over the population. The analysis revealed “modes” of co-variation across the population between subjects’ functional connectivity patterns and the behavioral/demographic measures that could be compared.
What they found was remarkable. Over the population studied, only one CCA mode stood out significantly relating functional connectomes to subject measures. This mode is strongly associated with high subject scores in cognition, memory, years of education, income level, and other “positive” traits and negatively associated with “negative” traits such as substance use and high anger/aggression scores. Brain connectivity patterns most strongly associated with this mode include significantly higher connectivity in components of the default network, including medial frontal and parietal cortex, the temporo-parietal junction, the anterior insula, and the frontal operculum.
This finding resonates with the established finding that multiple cognitive measures are correlated in subjects as the general intelligence factor “g”, but in this case, the correlated attributes include a more general mode of positive life function that are tied to underlying brain function (in the form of strong functional connectivity between certain brain regions).
In the Nature News article that accompanies the study, Marcus Raichle and Deanna Barch, a neuroscientist and psychologist at Washington University and consortium members of the WU-Minn HCP, were interviewed:
[Raichle] is impressed that the activity and anatomy of the brains alone were enough to reveal this ‘positive-negative’ axis. “You can distinguish people with successful traits and successful lives versus those who are not so successful,” he says.
But Raichle says that it is impossible to determine from this study how different traits relate to one another and whether the weakened brain connections are the cause or effect of negative traits. And although the patterns are clear across the large group of HCP volunteers, it might be some time before these connectivity patterns could be used to predict risks and traits in a given individual. Deanna Barch, a psychologist at Washington University who co-authored the latest study, says that once these causal relationships are better understood, it might be possible to push brains toward the ‘good’ end of the axis.
As more subject-specific functional connectome data becomes available, more fine-grained studies will be possible to further understand how the interactions between brain networks can give rise to positive behavioral traits such as those measured by the HCP. In the near future, look for cutting-edge developments in interpreting individual structural connectivity based on diffusion MRI experiments by HCP to give our understanding of how underlying brain structure contributes to differences between individuals with different behavioral patterns a leap forward.
Check out the original article:
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A positive-negative mode of population covariation links brain connectivity, demographics and behavior.
- We investigated the relationship between individual subjects’ functional connectomes and 280 behavioral and demographic measures in a single holistic multivariate analysis relating imaging to non-imaging data from 461 subjects in the Human Connectome Project. We identified one strong mode of population co-variation: subjects were predominantly spread along a single ‘positive-negative’ axis linking lifestyle, demographic and psychometric measures to each other and to a specific pattern of brain connectivity.