Andrea Stocco

This study links individual differences in long-term memory forgetting to resting-state brain connectivity patterns, supporting storage degradation over retrieval failure.

This paper uses Dynamic Causal Modeling on fMRI data to compare three basal ganglia connectivity models across cognitive tasks and resting state, finding the Mixed model performs best.

The paper shows individual differences in decision-making strategies are linked to neural efficiency in memory or reinforcement systems.

The paper develops an autoencoder model to explain the complex relationship between hippocampal size and memory function in Alzheimer's Disease, Autism Spectrum Disorder, and PTSD by simulating experience-dependent encoding.

The paper correlates individual forgetting rates with resting-state EEG power in specific beta frequency bands, suggesting task-free neuroimaging can inform idiographic cognitive models.

The paper tests the Common Model of Cognition using fMRI data and finds it outperforms alternative architectures across multiple cognitive domains.

This paper introduces a method using effective connectivity analysis of fMRI data to distinguish between competing computational models of the Stroop task, showing that functional connectivity patterns can differentiate models with identical behavioral predictions.