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Reshaping cortical circuits to decrease binge eating

Total Cost €


EC-Contrib. €






 ReCoDE project word cloud

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

brain    disorders    regulation    models    protocols    food    ravenous    edge    neurobiology    optogenetics    orchestrating    prefrontal    region    multiple    cutting    circuitry    moving    output    concurrent    sites    normalizing    little    combine    gap    unclear    vivo    diseases    plasticity    cope    neural    mouse    hindered    rodents    cortex    lha    limits    unknown    threefold    prominently    stress    humans    hypothalamus    patients    pathology    optogenetic    hypotheses    obesity    engenders    therapeutic    network    critical    urgently    unravel    limit    function    fiber    rebalances    reorganization    tracing    intake    lateral    maintains    normalized    dysfunction    recordings    feeding    predict    mice    electrophysiology    innervates    alters    eating    circuits    treatments    engage    restored    functional    gain    altered    disruptions    circuit    pfc    calcium    successful    strategy    synapses    society    functionally    binge    photometric    pathologies    combining    link    cortical   

Project "ReCoDE" data sheet

The following table provides information about the project.


Organization address
postcode: 3584 CX

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]
 Total cost 1˙499˙966 €
 EC max contribution 1˙499˙966 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-STG
 Funding Scheme ERC-STG
 Starting year 2019
 Duration (year-month-day) from 2019-07-01   to  2024-06-30


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Obesity and eating disorders are critical problems in society. Many patients with these brain diseases cope with stress by ravenous food intake (binge eating), which engenders new stress and maintains the pathology. Evidence-based treatments for this are urgently needed, but their implementation is hindered by a knowledge gap on: (i) which stress-driven neural disruptions cause binge eating, and (ii) whether these neural circuit changes can be normalized for therapeutic gain. Studies in humans and rodents link binge eating to dysfunction of the prefrontal cortex (PFC), a brain region orchestrating the stress response. However, it is unknown how effects of stress on PFC output cause binge eating. The PFC prominently innervates the lateral hypothalamus (LHA), a region with a crucial role in managing food intake, yet little is known about the function of PFC regulation of the LHA. I predict that stress-induced binge eating requires a functional reorganization of prefrontal cortical control over lateral hypothalamus feeding circuits, and that this control can be restored to limit binge eating.

I propose a cutting-edge threefold strategy to address these hypotheses in mouse models: 1. I will unravel the make-up of PFC-LHA circuitry, combining electrophysiology, optogenetics and neural tracing. I will assess how stress functionally alters this complex network.

2. I will determine the concurrent activity at multiple sites within PFC-LHA circuitry as mice engage in stress-driven binge eating, using fiber photometric calcium recordings.

3. I will assess if normalizing stress-altered PFC-LHA synapses rebalances this circuitry in vivo and limits binge eating. For this I will combine optogenetic plasticity protocols, with fiber photometric measurements in freely moving mice.

Overall, this challenging project aims to unravel the unclear neurobiology of stress-induced binge eating. If successful, this would provide a key advance in understanding binge eating pathologies.

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

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