Eliana Vassena

This study uses meta-analysis to show that mPFC/dACC processes task demand and reward separately, with caudal regions integrating them to reflect cost-benefit trade-offs in effort investment.

This paper proposes a meta-Reinforcement Learning framework to unify theories of anterior cingulate cortex function in cognitive control and surprise monitoring, showing it explains neuroimaging data better than previous models.

The paper investigates how acute systemic inflammation affects mental effort allocation and decision-making, finding reduced acceptance of medium-effort tasks with preserved accuracy.

The paper links changes in large-scale neural networks during lab stress to real-life affective reactivity.

This study uses multi-level MVPA with fMRI to investigate how task sets are represented in the brain, finding co-activation in prefrontal cortex and conjunctive representation in visual cortex.

This paper introduces a computational model of the dorsal anterior cingulate cortex (dACC) and midbrain circuitry that explains how dACC functions as a reinforcement meta-learner.

This study uses fNIRS to show increased DLPFC activity during anticipation of mental effort, replicating fMRI findings and demonstrating fNIRS's utility for studying effort preparation.

The paper tests three theoretical models of dorsal anterior cingulate cortex using a value-based decision-making task and finds the Predicted Response-Outcome model best explains the results.

This paper applies computational models of prediction and error to explain neural coding of motivation and effort-based decision-making in prefrontal cortex across health and disease.