Download PDF
Methods Inf Med 2007; 46(02): 142-146
DOI: 10.1055/s-0038-1625395
Original Article
Schattauer GmbH

Neural Engineering

A New Discipline for Analyzing and Interacting with the Nervous System
D. M. Durand
1   Neural Engineering Center, Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio, USA
› Author Affiliations
Further Information

Publication History

Publication Date:
11 January 2018 (online)

    Permissions and Reprints

Summary

Objectives : The field of neural engineering focuses on an area of research at the interface between neuroscience and engineering. The area of neural engineering was first associated with the brain machine interface but is much broader and encompasses experimental, computational, and theoretical aspects of neural interfacing, neuroelectronics, neuromechanical systems, neuroinformatics, neuroimaging, neural prostheses, artificial and biological neural circuits, neural control, neural tissue regeneration, neural signal processing, neural modelling and neuro-computation. One of the goals of neural engineering is to develop a selective interface for the peripheral nervous system.

Methods : Nerve cuffs electrodes have been developed to either reshape or maintain the nerve into an elongated shape in order to increase the circumference to cross sectional ratio. It is then possible to place many electrodes around the nerve to achieve selectivity. This new cuff (flat interface nerve electrode: FINE) was applied to the hypoglossal nerve and the sciatic nerve in dogs and cats to estimate the selectivity of the interface.

Results : By placing many contacts close to the axons, three different types of selectivity were achieved: 1) The FINE could generate a high degree of stimulation selectivity as estimated by the individual fascicle recording. 2) Similarly, recording selectivity was also demonstrated and blind source algorithms were applied to recover the signals. 3) Finally, by placing arrays of electrodes along the nerve, small fiber diameters could be excited before large fibers thereby reversing the recruitment order.

Conclusion : Taking advantage of the fact that nerves are not round but oblong or flat allows a novel design for selective nerve interface with the peripheral nervous system. This new design has found applications in many disorders of the nervous system such as bladder incontinence, obstructive sleep apnea and stroke.

Keywords

Neural prostheses - recruitment order - selective nerve stimulation
 

  • References

  • 1. Tasaki I. Nervous Transmission. Springfield, IL: Charles C Thomas; 1953
    PubMedGoogle Scholar
  • 2. Solomonow M. External control of the neuromuscular system. IEEE Trans Biomed Eng 1984; 31 (12) 752-763.
    PubMedGoogle Scholar
  • 3. Fang ZP, Mortimer JT. A method to effect physiological recruitment order in electrically activated muscle. IEEE Trans Biomed Eng 1991; 38 (02) 175-179.
    CrossrefPubMedGoogle Scholar
  • 4. Tai C, Jiang D. Selective stimulation of smaller fibers in a compound nerve trunk with single cathode by rectangular current pulses. IEEE Trans Biomed Eng 1994; 41 (03) 286-291.
    CrossrefPubMedGoogle Scholar
  • 5. Grill WM, Mortimer JT. Stimulus waveforms for selective neural stimulation. 1995
    PubMedGoogle Scholar
  • 6. Robblee LS, Rose TL. Electrochemical guidelines for selection of protocols and electrode materials for neural stimulation. 1990
    PubMedGoogle Scholar
  • 7. Tyler DJ, Durand DM. Alteration of Neural Geometry of Selective Nerve Stimulation. 1997
    PubMedGoogle Scholar
  • 8. Tyler DJ, Durand DM. Functionally selective peripheral nerve stimulation with a flat interface nerve electrode. IEEE Trans Neural Syst Rehabil Eng 2002; 10 (04) 294-303.
    CrossrefPubMedGoogle Scholar
  • 9. Leventhal DK, Durand DM. Subfascicle stimulation selectivity with the flat interface nerve electrode. Ann Biomed Eng 2003; 31 (06) 643-52.
    CrossrefPubMedGoogle Scholar
  • 10. Tyler DJ, Durand DM. Chronic response of the rat sciatic nerve to the flat interface nerve electrode. Ann Biomed Eng 2003; 31 (06) 633-642.
    CrossrefPubMedGoogle Scholar
  • 11. Leventhal DK, Durand DM. Chronic Measurement of the Stimulation Selectivity of the Flat Interface Nerve Electrode. IEEE Transactions on Biomedical Engineering 2004; 51 (09) 1649-1658.
    CrossrefPubMedGoogle Scholar
  • 12. Yoo PB, Sahin M, Durand DM. Selective stimulation of the canine hypoglossal nerve using a multicontact cuff electrode. Ann Biomed Eng 2004; 32 (04) 511-519.
    CrossrefPubMedGoogle Scholar
  • 13. Perez-Orive J, Durand DM. Modeling study of peripheral nerve recording selectivity. IEEE Trans Rehabil Eng 2000; 8 (03) 320-329.
    CrossrefPubMedGoogle Scholar
  • 14. Sahin M, Durand DM, Haxhiu MA. Chronic recordings of hypoglossal nerve activity in a dog model of upper airway obstruction. J Appl Physiol 1999; 87 (06) 2197-2206.
    CrossrefPubMedGoogle Scholar
  • 15. Yoo PB., Durand DM. Selective Fascicular Recording of the Hypoglossal Nerve Using a MultiContact Nerve Cuff Electrode. 2003
    PubMedGoogle Scholar
  • 16. Tesfayesus W, Yoo P, Moffitt M, Durand DM. Blind Source Separtation of nerve Cuff Recordings. Recordings Proceedings of the 25th International Conference of the IEEE/EMBS, Cancun, Mexico, 2003
    PubMedGoogle Scholar
  • 17. Lertmanorat Z, Durand DM. A novel electrode array for diameter-dependent control of axonal excitability: a simulation study. IEEE Trans Biomed Eng 2004; 51 (07) 1242-1250.
    CrossrefPubMedGoogle Scholar
  • 18. Lertmanorat Z, Gustafson KJ, Durand DM. Electrode array for reversing the recruitment order of peripheral nerve stimulation: experimental studies. Ann Biomed Eng 2006; 34 (01) 152-160.
    CrossrefPubMedGoogle Scholar
  • 19. Caparso AV, Durand DM. A Nerve CuffElectrode for Controlled Reshaping of Neural Geometry. In: The 2nd Joint meeting of the IEEE/EMBS and BMES. Houston, TX; 2002
    PubMedGoogle Scholar