#	Pagina
attuale pagina	/open-h2020/projects/194926/index.html
-1	/open-h2020/per-country/es/fundacion+parque+cientifico+de+madrid-fpcm/index.html
-2	/open-h2020/projects/204390/index.html

Opendata, web and dolomites

DecoMP_ECoG SIGNED

Decoding memory processing from experimental and spontaneous human brain activity using intracranial electrophysiological recordings and machine learning based methods.

Total Cost €

EC-Contrib. €

Partnership

Views

Outcomes and
results

DecoMP_ECoG project word cloud

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

diseases stores parts electrocorticographic decode human software memory surface methodological recordings spontaneous retrieval maintains dysfunction little return experimental learning science computer stored society critical degenerative modern despite diagnostic stanford later secondly electrophysiological techniques encoding socialization host machine burden dementias acquired cognitive intracranial settings quality consolidation function source aided consists age category data tools first brain college university vigilance neurodegenerative ecog strategies london

Project "DecoMP_ECoG" data sheet

The following table provides information about the project.

Coordinator	UNIVERSITY COLLEGE LONDON Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT website: n.a. 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	United Kingdom [UK]
Project website	https://sites.google.com/site/decompecog/
Total cost	241˙169 €
EC max contribution	241˙169 € (100%)
Programme	1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
Code Call	H2020-MSCA-IF-2014
Funding Scheme	MSCA-IF-GF
Starting year	2015
Duration (year-month-day)	from 2015-07-01 to 2018-11-21

Partnership

Take a look of project's partnership.

#	participants	country	role	EC contrib. [€]
1	UNIVERSITY COLLEGE LONDON UNIVERSITY COLLEGE LONDON Organization address address: GOWER STREET city: LONDON postcode: WC1E 6BT website: n.a. contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	UK (LONDON)	coordinator	241˙169.00
2	BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY BOARD OF TRUSTEES OF THE LELAND STANFORD JUNIOR UNIVERSITY Organization address address: SERRA MALL 450 city: STANFORD postcode: 94305 2004 website: www.stanford.edu contact info title: n.a. name: n.a. surname: n.a. function: n.a. email: n.a. telephone: n.a. fax: n.a.	US (STANFORD)	partner	0.00

Map

Project objective

Despite the critical importance of memory for cognitive function and socialization, very little is known about how information is stored for later retrieval and use. Understanding how the human brain maintains and stores information would enhance research on memory dysfunction in degenerative diseases, such as the age-related dementias, which represent a large burden for European society, and could facilitate the development of strategies for improving memory. The current proposal will use intracranial electrophysiological recordings from the surface of the human brain to investigate encoding, retrieval and consolidation of category-specific information during experimental settings, as well as during spontaneous brain activity. The proposal consists in two parts: first, electrocorticographic (ECoG) data will be acquired at Stanford University, with access to high-quality recordings and modern tools for electrophysiological data analysis. Secondly, machine learning based methodologies will be developed at the Department of Computer Science, University College London (return host) to decode spontaneous brain activity in different vigilance states. Finally, all developed methods will be implemented in an open source software, ensuring the timely dissemination of state-of-the art techniques. The methodological developments considered in this project could provide means for developing computer-aided diagnostic tools for neurodegenerative diseases.

Publications

List of publications.
year	authors and title	journal	last update
2018	Aaron Kucyi, Jessica Schrouff, Stephan Bickel, Brett L. Foster, James M. Shine, Josef Parvizi Intracranial electrophysiology reveals reproducible intrinsic functional connectivity within human brain networks published pages: 0217-18, ISSN: 0270-6474, DOI: 10.1523/JNEUROSCI.0217-18.2018	The Journal of Neuroscience	2019-06-11
2018	Jessica Schrouff, J. M. Monteiro, L. Portugal, M. J. Rosa, C. Phillips, J. MourÃ£o-Miranda Embedding Anatomical or Functional Knowledge in Whole-Brain Multiple Kernel Learning Models published pages: 117-143, ISSN: 1539-2791, DOI: 10.1007/s12021-017-9347-8	Neuroinformatics 16/1	2019-06-11
2016	Jessica Schrouff, Janaina MourÃ£o-Miranda, Christophe Phillips, Josef Parvizi Decoding intracranial EEG data with multiple kernel learning method published pages: 19-28, ISSN: 0165-0270, DOI: 10.1016/j.jneumeth.2015.11.028	Journal of Neuroscience Methods 261	2019-06-11
2016	Amy L. Daitch, Brett L. Foster, Jessica Schrouff, Vinitha Rangarajan, ItÄ±r KaÅŸikÃ§i, Sandra Gattas, Josef Parvizi Mapping human temporal and parietal neuronal population activity and functional coupling during mathematical cognition published pages: E7277-E7286, ISSN: 0027-8424, DOI: 10.1073/pnas.1608434113	Proceedings of the National Academy of Sciences 113/46	2019-06-11

Are you the coordinator (or a participant) of this project? Plaese send me more information about the "DECOMP_ECOG" project.

For instance: the website url (it has not provided by EU-opendata yet), the logo, a more detailed description of the project (in plain text as a rtf file or a word file), some pictures (as picture files, not embedded into any word file), twitter account, linkedin page, etc.

Send me an email (fabio@fabiodisconzi.com) and I put them in your project's page as son as possible.

Thanks. And then put a link of this page into your project's website.

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