Action-value signals previously found in many brain areas can be accounted for neither by concurrent serial correlations in neural activity and action value nor by signals for other decision variables.
A novel method and software provides researchers with the capability to rapidly, flexibly, and robustly perform Bayesian parameter estimation of theoretically meaningful models in cognitive neuroscience that were heretofore intractable.
An analysis of recent literature advances novel hypotheses and suggests new experimental approaches in order to build an integrated understanding of prefrontal neural architecture and behavioral repertoires during development.
Response inhibition is initiated by the right inferior frontal gyrus (rIFG), and stopping performance is predicted by beta-band power as well as beta-band connectivity between rIFG and pre-supplementary motor area.
Manifold learning of longitudinal brain network data provides novel insights into adolescent structural connectome maturation, and how multiple scales of cortical and subcortical organization interact in typical neurodevelopment.