Differentiable contributions of human amygdalar subregions in the computations underlying reward and avoidance learning
Charlotte Prevost, Jonathan A McCabe, Ryan K Jessup, Peter Bossaerts, John P O'Doherty
European Journal of Neuroscience | WILEY | Published : 2011
To understand how the human amygdala contributes to associative learning, it is necessary to differentiate the contributions of its subregions. However, major limitations in the techniques used for the acquisition and analysis of functional magnetic resonance imaging (fMRI) data have hitherto precluded segregation of function with the amygdala in humans. Here, we used high-resolution fMRI in combination with a region-of-interest-based normalization method to differentiate functionally the contributions of distinct subregions within the human amygdala during two different types of instrumental conditioning: reward and avoidance learning. Through the application of a computational-model-based ..View full abstract
Awarded by Science Foundation Ireland
We thank Christian Kerskens and Mimi Liljeholm for helpful discussions. This work was funded by Science Foundation Ireland grant 08/IN.1/B1844 to J.O.D.