• 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