The Poor, Unhappy, Chain-smoking Brain

A thought-provoking new paper from Oxford neuroscientists Stephen Smith and colleagues reports a correlation between a certain pattern of brain activity and, well, a great many things. The researchers took 461 resting state fMRI scans from the open Human Connectome Project (HCP) database. Associated with each scan is a set of 'meta-data' about the volunteer who had the scan. These 158 variables (listed here) cover everything from age and gender, to mental health status, income, and 'times used tobacco today'. Using the technique of Canonical Correlation Analysis (CCA), Smith et al. discovered that many of the meta-data variables were correlated with each other. In fact, there seemed to be a single axis (or factor) underlying the different measures. This axis was essentially "good vs. bad". So, for instance, performing well on intelligence tests, having a high income, and 'life satisfaction' were correlated with each other, while these were negatively correlated with "bad" things such as currently smoking, self-reported anger problems, and 'testing positive for THC' (cannabis). In other words, poor, unhappy, chain smokers tend to score poorly on IQ tests, and vice versa. You might call this the "It never rains but it pours" principle. Having established this rather depressing (if unsurprising) fact, Smith et al. then found that the 'positive-negative' axis has neural correlates in the fMRI data. Specifically, people with "good" characteristics tended to show more resting state connectivity between most brain areas (see below, red), especially in the default mode network (DMN). "Bad" brains had less connectivity overall, but in a few pathways they had more (blue).