Michael Crawley Freund

The paper shows that multidimensional attentional control involves reactive suppression of distractor representations in human EEG, guided by a structured multivariate conflict signal.

This paper shows that combining hierarchical Bayesian modeling with multivariate decoding improves the reliability and precision of estimating individual differences in cognitive control from fMRI data.

The paper introduces the DMCC55B dataset, a collection of fMRI data from 55 healthy young adults performing cognitive control tasks, for benchmarking and analysis of task performance and individual differences.

The DMCC project investigates two cognitive control modes, proactive and reactive, using neuroimaging and behavioral tasks, finding a domain-general neural signature for reactive control.

This paper uses representational similarity analysis to test coding schemes in the Stroop task, finding incongruency coding in DMFC and target/incongruency coding in DLPFC.