• DocumentCode
    1476983
  • Title

    Brain Enabled by Next-Generation Neurotechnology: Using Multiscale and Multimodal Models

  • Author

    Shenoy, Krishna V. ; Nurmikko, Arto V.

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
  • Volume
    3
  • Issue
    2
  • fYear
    2012
  • fDate
    3/1/2012 12:00:00 AM
  • Firstpage
    31
  • Lastpage
    36
  • Abstract
    The ultimate goal is to understand how the information in the distributed neural circuits of the brain reorganizes and plastically adapts to laboratory disruptions designed to reversibly mimic brain injury. Our approach involves a new generation of data- driven mathematical models of brain circuits and their connection with complex behavioral tasks in primates that are enabled with a suite of novel experimental tools .In the following article, we illustrate a few of these methods, which include projecting input directly onto specifically targeted brain microcircuits and thus writing in neuromodulatory signals. These methods also enable the simultaneous read out and write in of real-time neural responses across multiple spatial and temporal scales of network activity.
  • Keywords
    brain; integrated circuits; neurophysiology; brain circuits; brain injury; brain microcircuits; brain models; brain reorganisation; data driven mathematical models; distributed neural circuits; network activity; next generation neurotechnology; real time neural responses; Biomedical optical imaging; Brain models; Mathematical model; Neuroscience; Optical pulses; Optical sensors; Animals; Behavior, Animal; Bioengineering; Brain; Electrodes, Implanted; Genetic Engineering; Macaca mulatta; Microelectrodes; Models, Neurological; Neurosciences; Opsins; Rats; Task Performance and Analysis;
  • fLanguage
    English
  • Journal_Title
    Pulse, IEEE
  • Publisher
    ieee
  • ISSN
    2154-2287
  • Type

    jour

  • DOI
    10.1109/MPUL.2011.2181021
  • Filename
    6173095