Micropatterned surface electrode for massive selective stimulation of intraepidermal nociceptive fibres.


BACKGROUND:No satisfactory neurophysiological test for nociceptive afferents is available to date. Laser stimuli present risks of skin damage, whilst electrical stimulation through specially designed electrodes is not selective enough. NEW METHOD:We present a new electrode designed according to critical issues identified in preliminary computer simulations concerning electric field gradient through the skin. To provide selective stimulation the activating electric field must be limited to intraepidermal free nerve endings. To this end, a new interdigitated electrode (IDE) was made of conductive rails arranged in a comb-like micropattern, situated only 150μm apart from each other (150 IDE) and alternately connected to the opposite poles of the stimulator. RESULTS:Evoked potentials recorded from the scalp were obtained after stimulation with the 150 IDE and with a similarly designed, but more widely spaced electrode (1000μm, or 1000 IDE). Small amplitude early and medium latency components were recorded with the 1000 IDE, suggesting activation of Aβ fibres. On the other hand, the 150 IDE only evoked late responses, confirming sufficient selectivity in small fibre activation. COMPARISON WITH EXISTING METHOD(S):The main differences with existing electrodes are: 1) Microspaced interdigitated conductive rails. 2) The potentially unlimited surface of stimulation and high efficiency per surface unit, resulting in large numbers of activated nociceptors. CONCLUSIONS:A new electrode providing selective stimulation of nociceptive nerve free endings is presented. It is non-invasive, and its surface can be enlarged at will. It is expected that it may greatly help in neurophysiological assessment of conditions affecting the nociceptive pathway.


J Neurosci Methods


Leandri M,Marinelli L,Siri A,Pellegrino L




Has Abstract


2018-01-01 00:00:00












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    journal_title:Journal of neuroscience methods

    pub_type: 杂志文章


    authors: Hirata Y,Aihara K

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  • Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.

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    authors: Donnelly-Kehoe PA,Pascariello GO,Gómez JC,Alzheimers Disease Neuroimaging Initiative.

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    journal_title:Journal of neuroscience methods

    pub_type: 杂志文章


    authors: Feinerman O,Moses E

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    journal_title:Journal of neuroscience methods

    pub_type: 杂志文章


    authors: Hodos W,Bobko P

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    journal_title:Journal of neuroscience methods

    pub_type: 杂志文章


    authors: Hamada T

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    authors: Safiulina D,Kaasik A,Seppet E,Peet N,Zharkovsky A,Seppet E

    更新日期:2004-08-15 00:00:00

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    authors: Prime D,Woolfe M,Rowlands D,O'Keefe S,Dionisio S

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    journal_title:Journal of neuroscience methods

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    authors: Bhattacharjee J,Nunes Cardozo B,Kamphuis W,Kamermans M,Vrensen GF

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    journal_title:Journal of neuroscience methods

    pub_type: 杂志文章


    authors: Claverol-Tinture E,Pine J

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    journal_title:Journal of neuroscience methods

    pub_type: 杂志文章


    authors: Weenink RP,Hollmann MW,Stevens MF,Kager J,van Gulik TM,van Hulst RA

    更新日期:2014-05-15 00:00:00