Now out in @pnasnexus.org@bsky.com :
“Deconstructing neural predictors of risky choice”!
Take-home point :
At least two systems (not one) predict risky choice — but both are affective! ( #neuroscience )
https://academic.oup.com/pnasnexus/advance-article/doi/10.1093/pnasnexus/pgaf204/8168828
Other key points :
• Neural predictors of risky choice can be triply dissociated from neural correlates of sensory input and motor output.
• Predictors generalize across samples, tasks, and analyses (a priori and post-hoc)
• Predictors also account for individual differences in risky choice within the lab, as well as debt beyond the lab.
• Findings robustly support a #BrainAsPredictor account of risky choice of gambles (if you don't blow out your signal in the middle of the brain with #multiband#FMRI acquisition, see Study 4)
Spearheaded by the unstoppable Leili Mortazavi with Elnaz Ghasemi and Charlene C. Wu , this culminates > 15 years of work!
The findings imply that some #FMRI findings are more robust than commonly thought (with respect to reliability, validity, and generalizability).
Special thanks to the editors and reviewers at PNAS Nexus and for support from Stanford University 's #Neurochoice Initiative and the #ToyotaResearchInstitute ! (#AffectiveNeuroscience , #Neuroeconomics )
This is a bonfire demo instance for testing purposes
