DocumentCode
718387
Title
A scalable high performance client/server framework to manage and analyze high dimensional datasets recorded by 4096 CMOS-MEAs
Author
Zordan, Stefano ; Zanotto, Matteo ; Nieus, Thierry ; Di Marco, Stefano ; Amin, Hayder ; Maccione, Alessandro ; Berdondini, Luca
Author_Institution
Ist. Italiano di Tecnol., Genoa, Italy
fYear
2015
fDate
22-24 April 2015
Firstpage
968
Lastpage
971
Abstract
Large scale CMOS-MEAs are an emerging neurotechnology enabling extracellular recordings in-vitro and in-vivo with thousand´s electrodes simultaneously. This is on the way to provide the unprecedented capability of acquiring signals from several thousands of single-units, thus opening novel perspectives for electrophysiology, but also novel challenges for analysis and management of large datasets. Here, we propose an analysis platform designed for managing unprecedentedly large datasets of electrical recordings acquired with a 4096-electrode array platform. Furthermore it provides a computational framework to facilitate the development and integration of new analysis tools exploiting high-resolution electrical recordings.
Keywords
CMOS integrated circuits; bioelectric phenomena; biomedical electrodes; microelectrodes; neurophysiology; 4096-electrode array platform; CMOS based microelectrode array; electrophysiology; extracellular recordings; high-resolution electrical recordings; large scale CMOS-MEAs; neurotechnology; Arrays; Brain; Electrodes; Extracellular; Graphical user interfaces; Servers;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
Conference_Location
Montpellier
Type
conf
DOI
10.1109/NER.2015.7146787
Filename
7146787
Link To Document