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Beyond the blob: characterizing Prefrontal Cortex networks in prediction and motivation with simultaneous EEG-fMRI recordings

Total Cost €


EC-Contrib. €






 PreMotive project word cloud

Explore the words cloud of the PreMotive project. It provides you a very rough idea of what is the project "PreMotive" about.

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Project "PreMotive" data sheet

The following table provides information about the project.


Organization address
postcode: 6525 EZ

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Netherlands [NL]
 Project website
 Total cost 165˙598 €
 EC max contribution 165˙598 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2016
 Duration (year-month-day) from 2016-08-01   to  2019-02-21


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Neural correlates of goal-directed behavior have been extensively studied with functional Magnetic Resonance Imaging (fMRI). This has allowed identifying the functional specialization of subregions in prefrontal cortex (PFC). In particular, medial PFC (MPFC) is involved in error monitoring, cognitive control, reward prediction and motivation, while dorsolateral PFC (DLPFC) supports working memory and goal-maintenance. Though useful, such characterization has neglected one fundamental aspect: network interactions. A mechanistic understanding of how MPFC and DLPFC interact in orchestrating goal-directed behavior is still lacking. Both regions seem to be involved in both prediction and error signalling mechanism, and in motivation-driven task-preparation. To date, no theoretical account has reconciled these findings, nor explained how MPFC and DLPFC interact in producing such effects. Here we propose a novel framework, where error signals generated by MPFC train error representations in DLPFC. These representations are reactivated when the same circumstance recurs and drive proportional MPFC involvement to prevent the error from happening again (by deploying adequate neural resources). The goal of the project is to test this theory by combining the excellent spatial resolution of fMRI with the excellent temporal precision of EEG in conjunction with precise quantitative predictions based on computational models of PFC. Simultaneous EEG-fMRI recordings will allow testing PFC network dynamics, both in a simple sensory prediction paradigm, and in a paradigm modulating motivation, aiming at demonstrating a shared underlying principle. This research programme will provide a neurofunctional characterization of how PFC network interactions drive goal-directed behaviour in both prediction and motivated task engagement. This work has important implications for future studies on PFC both in healthy subjects and in patients with motivation disorders.


year authors and title journal last update
List of publications.
2017 William H. Alexander, Joshua W. Brown, Anne G. E. Collins, Benjamin Y. Hayden, Eliana Vassena
Prefrontal Cortex in Control: Broadening the Scope to Identify Mechanisms
published pages: 1-5, ISSN: 0898-929X, DOI: 10.1162/jocn_a_01154
Journal of Cognitive Neuroscience 2019-10-15
2017 Eliana Vassena, James Deraeve, William H. Alexander
Predicting Motivation: Computational Models of PFC Can Explain Neural Coding of Motivation and Effort-based Decision-making in Health and Disease
published pages: 1633-1645, ISSN: 0898-929X, DOI: 10.1162/jocn_a_01160
Journal of Cognitive Neuroscience 29/10 2019-10-15
2017 William H. Alexander, Eliana Vassena, James Deraeve, Zachary D. Langford
Integrative Modeling of Prefrontal Cortex
published pages: 1674-1683, ISSN: 0898-929X, DOI: 10.1162/jocn_a_01138
Journal of Cognitive Neuroscience 29/10 2019-10-15
2017 Eliana Vassena, Clay B. Holroyd, William H. Alexander
Computational Models of Anterior Cingulate Cortex: At the Crossroads between Prediction and Effort
published pages: , ISSN: 1662-453X, DOI: 10.3389/fnins.2017.00316
Frontiers in Neuroscience 11 2019-10-15
2019 Jessica Schrouff, Doris Pischedda, Sarah Genon, Gregory Fryns, Ana Luísa Pinho, Eliana Vassena, Antonietta G. Liuzzi, Fabio S. Ferreira
Gender bias in (neuro)science: Facts, consequences, and solutions
published pages: , ISSN: 0953-816X, DOI: 10.1111/ejn.14397
European Journal of Neuroscience 2019-10-15
2018 Massimo Silvetti, Eliana Vassena, Elger Abrahamse, Tom Verguts
Dorsal anterior cingulate-brainstem ensemble as a reinforcement meta-learner
published pages: e1006370, ISSN: 1553-7358, DOI: 10.1371/journal.pcbi.1006370
PLOS Computational Biology 14/8 2019-10-15
2019 Eliana Vassena, Robin Gerrits, Jelle Demanet, Tom Verguts, Roma Siugzdaite
Anticipation of a mentally effortful task recruits Dorsolateral Prefrontal Cortex: An fNIRS validation study
published pages: 106-115, ISSN: 0028-3932, DOI: 10.1016/j.neuropsychologia.2018.04.033
Neuropsychologia 123 2019-10-15
2019 Eliana Vassena, James Deraeve, William H. Alexander
Task-specific prioritization of reward and effort information: Novel insights from behavior and computational modeling
published pages: , ISSN: 1530-7026, DOI: 10.3758/s13415-018-00685-w
Cognitive, Affective, & Behavioral Neuroscience 2019-10-15

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