MICRONANO

Modeling Brain Circuitry using Scales Ranging from Micrometer to Nanometer

 Coordinatore  

Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.

 Nazionalità Coordinatore Non specificata
 Totale costo 2˙495˙982 €
 EC contributo 2 €
 Programma FP7-IDEAS-ERC
Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
 Anno di inizio 2010
 Periodo (anno-mese-giorno) 2010-04-01   -   2016-03-31

 Partecipanti

# participant  country  role  EC contrib. [€] 
1    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

 Organization address address: BATIMENT CE 3316 STATION 1
city: LAUSANNE
postcode: 1015

contact info
Titolo: Dr.
Nome: Caroline
Cognome: Vandevyver
Email: send email
Telefono: +41 21 693 4977
Fax: +41 21 693 5585

CH (LAUSANNE) hostInstitution 2˙495˙982.00
2    ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE

 Organization address address: BATIMENT CE 3316 STATION 1
city: LAUSANNE
postcode: 1015

contact info
Titolo: Prof.
Nome: Pascal
Cognome: Fua
Email: send email
Telefono: +41 21 693 66 47
Fax: +41 21 693 75 20

CH (LAUSANNE) hostInstitution 2˙495˙982.00

Mappa


 Word cloud

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brain    computer    vision    microscopes    connections    interpretation    resolution    data    full    automated    modalities   

 Obiettivo del progetto (Objective)

'If we are ever to unravel the mysteries of brain function at its most fundamental level, we will need a precise understanding of how its component neurons connect to each other. Furthermore, given the many recent advances in genetic engineering, viral targeting, and immunohistochemical labeling of specific cellular structures, there is a growing need for automated quantitative assessment of neuron morphology and connectivity. Electron microscopes can now provide the nanometer resolution that is needed to image synapses, and therefore connections, while Light Microscopes see at the micrometer resolution required to model the 3D structure of the dendritic network. Since both the arborescence and the connections are integral parts of the brain's wiring diagram, combining these two modalities is critically important. In fact, these microscopes now routinely produce high-resolution imagery in such large quantities that the bottleneck becomes automated processing and interpretation, which is needed for such data to be exploited to its full potential. We will therefore use our Computer Vision expertise to provide not only the necessary tools to process images acquired using a specific modality but also those required to create an integrated representation using all available modalities. This is a radical departure from earlier approaches to applying Computer Vision techniques in this field, which have tended to focus on narrow problems. State-of-the-art methods have not reached the level of reliability and integration that would allow automated processing and interpretation of the massive amounts of data that are required for a true leap of our understanding of how the brain works. In other words, we cannot yet exploit the full potential of our imaging technology and that is what we intend to change.'

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