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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.

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

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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lastchecktime (2021-09-20 8:58:34) correctly updated