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This project was led by the AWESOME @Hardigirl (post doc in @THinC_Lab) but benefited from collaborations with @MilhamMichael @TingsterX @sofievalk @leechbrain @borisberhardt @DanielMargulies and others.

The good news is that we can optimise task contexts to maximise their sensitivity to specific relationships, reducing the cost of future BWAS. See work by @leechbrain @romy_lorenz to see how this could work.

So the take home is that BWAS studies that use only 1 situation (often rest) require large sample sizes because any single situation may not be suited to detect brain-trait associations for all trait dimensions. See this nice review by @GrattonCaterina

Importantly we looked at how many people you would need to show the relations in the best tasks for capturing a specific trait. Our estimates suggest hundreds (not thousands) of people would be needed to show the brain-trait relationship seen in the whole sample.

These relations were clear for #gradients 3 (task positive-task negative) and 2 (vision-motor). Tasks with a strong response for one trait were different to those for other traits. This suggests there is likely no -one-size-fits-all situation for all brain-trait associations

We examined if location of any of the tasks in the state-space varied with traits using Linear Mixed Models in R. We found little evidence that traits uniformly impact on brain activity in all tasks. Instead brain-trait association were often stronger in some tasks than others 👇

To this end we took the task data from the Human Connectome Project and examined how brain activity in each situation vary with the Big-5 Personality traits. We built a 3d state-space using the first three #gradients from the work by @margulies and projected task data into it 👇

Brain Wide Association Studies (BWAS) often make an assumption: Traits are expressed equally in a situation e.g. rest. However, psychology know some traits are expressed more in some situations than others. this contextually-bound view of personality help improve BWAS?.