Opendata, web and dolomites

ViMoAct SIGNED

Modelling cortical information flow during visuomotor adaptation as active inference in the human brain

Total Cost €

0

EC-Contrib. €

0

Partnership

0

Views

0

 ViMoAct project word cloud

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

multiple    tracking    belief    error    interdisciplinary    experiment    appeals    assumption    environment    causal    hemodynamic    delayed    endogenous    precision    dynamic    previously    tested    spectral    models    perform    movements    weighting    sensory    feedback    self    flow    gap    free    modelled    allocation    movement    optimal    determines    filtering    cortical    bodily    compatible    conflicts    actions    updating    hierarchy    fmri    experimentally    levels    errors    hierarchical    either    suppression    manipulated    manual    attentional    function    suggests    relative    active    bayesian    mr    thereby    stimulus    explains    photorealistic    lacks    relies    follows    prediction    predictions    contribution    predicted    move    visuoproprioceptive    inference    visuomotor    recent    instructed    formal    glove    updated    predictive    noise    requiring    experiments    cognitive    model    optimise    bayes    public    virtual    motor    generalised    generative    investigation    world    close    coding    principles    empirical    brain    exchange    energy    representation    visual    data    proprioceptive    meg   

Project "ViMoAct" data sheet

The following table provides information about the project.

Coordinator
UNIVERSITY COLLEGE LONDON 

Organization address
address: GOWER STREET
city: LONDON
postcode: WC1E 6BT
website: n.a.

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 United Kingdom [UK]
 Total cost 183˙454 €
 EC max contribution 183˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-11-01   to  2020-05-02

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITY COLLEGE LONDON UK (LONDON) coordinator 183˙454.00

Map

 Project objective

Recent research suggests that to control bodily movements the brain relies on Bayes-optimal predictive models that are updated by sensory prediction error. This assumption may be generalised within a new formal account of motor control as active (Bayesian) inference. Active inference explains motor control in terms of hierarchical Bayesian filtering or predictive coding, i.e., as belief updating and suppression of prediction error to optimise a hierarchical generative model in the brain; thereby the weighting of prediction errors by their predicted precision determines their relative impact on hierarchical inference. This novel proposal still lacks concrete empirical investigation. The proposed project will close this research gap by testing whether cortical information flow during manual actions, requiring visuomotor adaptation and cognitive control of attention, follows the principles of active inference. In two fMRI experiments and one MEG experiment, participants will move a photorealistic virtual hand model via an MR-compatible data glove to perform simple manual tracking tasks in a virtual reality environment. The precision of prediction errors at multiple levels of a previously established cortical motor control hierarchy will be experimentally manipulated via visuoproprioceptive conflicts (introduced by delayed visual movement feedback) and via attentional allocation – either stimulus-driven (via increased sensory noise) or endogenous (instructed) – to visual or proprioceptive movement feedback. Active inference’s specific predictions about information flow between and within cortical areas will be tested with recently established dynamic causal modelling of the modelled hemodynamic (fMRI) or spectral (MEG) responses. Active inference appeals to a general free-energy principle of brain function; this contribution will thus promote interdisciplinary exchange of knowledge about self- and world-representation in the brain and will be of general public interest.

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "VIMOACT" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an  email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

The information about "VIMOACT" are provided by the European Opendata Portal: CORDIS opendata.

More projects from the same programme (H2020-EU.1.3.2.)

DEAP (2019)

Development of Epithelium Apical Polarity: Does the mechanical cell-cell adhesions play a role?

Read More  

Mel.Photo.Protect (2019)

Unraveling the Photoprotecting Mechanism of Melanin - From a Library of Fragments to Simulation of Spectra and Function

Read More  

ORIGIN (2019)

Origin: reconstructing African prehistory using ancient DNA

Read More