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Physiologically relevant microfluidic neuro-engineering

Total Cost €


EC-Contrib. €






 CONNEXIO project word cloud

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

combining    labelling    transduce    reproduce    ways    circuitry    spiking    individual    vitro    neurons    experimental    deposition    incubo    microgrooves    tuned    populations    free    networks    drugs    chambers    physiological    lens    label    functional    connectivity    calcium    network    computational    resolution    compartmentalized    clinically    monitoring    platform    chip    lensfree    seeded    optical    neuroscience    fabricate    huntington    dimensions    manipulated    densities    electrical    stimulations    chips    differences    constantly    observing    neurites    engineering    biological    connectivities    observation    compare    decipher    answer    neural    connected    model    brain    parkinson    patterning    global    observe    developing    entire    loop    basic    view    fundamental    microfluidic    localized    diseases    external    implied    disruptive    neurodegenerative    neuron    grow    engineer    oscillators    microfluidics    types    minimalistic    primary    technique    neuro    pattern   

Project "CONNEXIO" data sheet

The following table provides information about the project.


Organization address
address: RUE MICHEL ANGE 3
city: PARIS
postcode: 75794

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 1˙727˙731 €
 EC max contribution 1˙727˙731 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2016-STG
 Funding Scheme ERC-STG
 Starting year 2016
 Duration (year-month-day) from 2016-11-01   to  2021-10-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 


 Project objective

Developing minimalistic biological neural networks and observing their functional activity is crucial to decipher the information processing in the brain. This project aims to address two major challenges: to design and fabricate in vitro biological neural networks that are organized in physiological relevant ways and to provide a label-free monitoring platform capable of observing neural activity both at the neuron resolution and at large fields of view. To do so, the project will develop a unique microfluidic compartmentalized chips where populations of primary neurons will be seeded in deposition chambers with physiological relevant number and densities. Chambers will be connected by microgrooves in which neurites only can grow and whose dimensions will be tuned according to the connectivity pattern to reproduce. To observe the activity of such complex neural networks, we will develop a disruptive observation technique that will transduce the electrical activity of spiking neurons into optical differences observed on a lens-free platform, without calcium labelling and constantly in-incubo. By combining neuro-engineering patterning and the lens-free platform, we will compare individual spiking to global oscillators in basic neural networks under localized external stimulations. Such results will provide experimental insight into computational neuroscience current approaches. Finally, we will design an in vitro network that will reproduce a neural loop implied in major neurodegenerative diseases with physiological relevant neural types, densities and connectivities. This circuitry will be manipulated in order to model Huntington and Parkinson diseases on the chip and assess the impact of known drugs on the functional activity of the entire network. This project will engineer microfluidics chips with physiological relevant neural network and a lensfree activity monitoring platform to answer fundamental and clinically relevant issues in neuroscience.

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

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