Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation

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Abstract

Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data.
Original languageUndefined
Pages (from-to)479-491
Number of pages13
JournalBiological cybernetics
Volume109
Issue number4
DOIs
Publication statusPublished - Oct 2015

Keywords

  • EWI-26275
  • IR-97117
  • METIS-312712
  • BSS-Central mechanisms underlying chronic pain

Cite this

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title = "Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation",
abstract = "Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data.",
keywords = "EWI-26275, IR-97117, METIS-312712, BSS-Central mechanisms underlying chronic pain",
author = "H. Yang and Meijer, {Hil Ga{\'e}tan Ellart} and Robert Doll and Buitenweg, {Jan R.} and {van Gils}, {Stephanus A.}",
note = "eemcs-eprint-26275",
year = "2015",
month = "10",
doi = "10.1007/s00422-015-0656-4",
language = "Undefined",
volume = "109",
pages = "479--491",
journal = "Biological cybernetics",
issn = "0340-1200",
publisher = "Springer",
number = "4",

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Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation. / Yang, H.; Meijer, Hil Gaétan Ellart; Doll, Robert; Buitenweg, Jan R.; van Gils, Stephanus A.

In: Biological cybernetics, Vol. 109, No. 4, 10.2015, p. 479-491.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Computational modeling of Adelta-fiber-mediated nociceptive detection of electrocutaneous stimulation

AU - Yang, H.

AU - Meijer, Hil Gaétan Ellart

AU - Doll, Robert

AU - Buitenweg, Jan R.

AU - van Gils, Stephanus A.

N1 - eemcs-eprint-26275

PY - 2015/10

Y1 - 2015/10

N2 - Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data.

AB - Sensitization is an example of malfunctioning of the nociceptive pathway in either the peripheral or central nervous system. Using quantitative sensory testing, one can only infer sensitization, but not determine the defective subsystem. The states of the subsystems may be characterized using computational modeling together with experimental data. Here, we develop a neurophysiologically plausible model replicating experimental observations from a psychophysical human subject study. We study the effects of single temporal stimulus parameters on detection thresholds corresponding to a 0.5 detection probability. To model peripheral activation and central processing, we adapt a stochastic drift-diffusion model and a probabilistic hazard model to our experimental setting without reaction times. We retain six lumped parameters in both models characterizing peripheral and central mechanisms. Both models have similar psychophysical functions, but the hazard model is computationally more efficient. The model-based effects of temporal stimulus parameters on detection thresholds are consistent with those from human subject data.

KW - EWI-26275

KW - IR-97117

KW - METIS-312712

KW - BSS-Central mechanisms underlying chronic pain

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JO - Biological cybernetics

JF - Biological cybernetics

SN - 0340-1200

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