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AXO-MATH SIGNED

Imaging and analyzing dynamics of reward-related long-range axons during decision-making in behaving mice

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 AXO-MATH project word cloud

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

original    final    axons    treatment    prevention    dynamically    learning    brain    viral    characterization    pfc    dorsal    neuroscience    participate    valuation    projections    preference    hypothesize    modulated    volumes    amygdala    maladaptive    images    behaviors    extraction    plasticity    combination    math    axonal    analytical    significantly    automatic    animal    schizophrenia    unprecedented    critical    host    encode    micrometer    mathematical    interdisciplinary    basolateral    handle    initial    diseases    behaving    multidisciplinary    switch    sensory    stage    receiving    autism    human    relationship    thanks    substrates    context    anatomical    axo    genetic    hub    disorders    image    mice    dynamics    abuse    nucleus    unknown    functional    tegmental    expertise    synaptic    expert    largely    precise    neuroeconomics    shape    microscopy    society    obsessive    regions    neuronal    seamless    decision    positively    data    investigates    network    accuracy    input    vivo    deciphering    ventral    function    modern    action    mechanisms    tools    lack    area    substance    neuropsychiatric    model   

Project "AXO-MATH" data sheet

The following table provides information about the project.

Coordinator
CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS 

Organization address
address: RUE MICHEL ANGE 3
city: PARIS
postcode: 75794
website: www.cnrs.fr

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 France [FR]
 Total cost 185˙076 €
 EC max contribution 185˙076 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2017
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2018
 Duration (year-month-day) from 2018-05-01   to  2020-04-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRS FR (PARIS) coordinator 185˙076.00

Map

Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

Decision-making is a crucial brain function which neuronal substrates are largely unknown. Deciphering those mechanisms is critical for the prevention and the treatment of brain diseases as decision-making is maladaptive in many neuropsychiatric disorders (obsessive behaviors, schizophrenia, autism, substance abuse); it would also significantly advance neuroeconomics and therefore positively impact society. AXO-MATH (MATHematical analysis of AXOnal projections) investigates the neuronal mechanisms involved in decision-making in behaving mice using interdisciplinary approaches and state-of-the-art methods. We hypothesize that a final step before the action is taken is implemented in the dorsal PFC as it is an anatomical hub receiving projections from both sensory areas and regions believed to participate in choice valuation, such as the ventral tegmental area and the basolateral nucleus of the amygdala. Using an original combination of advanced microscopy and genetic and viral tools, we will image the activity of those long-range axons in two conditions: while the expert animal is taking a choice, and during the stage of preference learning. Precise measures will allow us to test a model in which projections from the amygdala to the PFC encode choice values and can be dynamically modulated as a function of the context by the ventral tegmental area to switch preference. The characterization accuracy will be unprecedented thanks to the design of new analytical tools - the initial expertise of the applicant. We propose novel mathematical methods tailored to the automatic extraction of complex-shape and micrometer-scale features of synaptic activity in in vivo microscopy images; they lack human input and can handle large volumes of data. By a seamless combination of the host and applicant multidisciplinary expertise we will address the relationship between synaptic network dynamics and functional brain plasticity which is a major challenge in modern neuroscience.

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