Neuromorphic neural interfaces: from neurophysiological inspiration to biohybrid coupling with nervous systems.

Journal: Journal of neural engineering
Published Date:

Abstract

OBJECTIVE: Computation in nervous systems operates with different computational primitives, and on different hardware, than traditional digital computation and is thus subjected to different constraints from its digital counterpart regarding the use of physical resources such as time, space and energy. In an effort to better understand neural computation on a physical medium with similar spatiotemporal and energetic constraints, the field of neuromorphic engineering aims to design and implement electronic systems that emulate in very large-scale integration (VLSI) hardware the organization and functions of neural systems at multiple levels of biological organization, from individual neurons up to large circuits and networks. Mixed analog/digital neuromorphic VLSI systems are compact, consume little power and operate in real time independently of the size and complexity of the model.

Authors

  • Frédéric D Broccard
    Institute for Neural Computation, UC San Diego, United States of America. Department of Bioengineering, UC San Diego, United States of America.
  • Siddharth Joshi
  • Jun Wang
    Department of Speech, Language, and Hearing Sciences and the Department of Neurology, The University of Texas at Austin, Austin, TX 78712, USA.
  • Gert Cauwenberghs