Modeling of Pain Using Artificial Neural Networks

Haeri, ءMohammad; Asemani, Davud; Gharibzadeh, Shahriar

doi:10.1006/jtbi.2003.3130

Cited by 36 publications

(22 citation statements)

References 22 publications

(27 reference statements)

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“…1). This so-called three-layer neural network has been shown to be sufficient to model problems of any degree of complexity (Haeri et al, 2003). The transfer function between neurons across layer was a…”

Section: Ann Modelmentioning

confidence: 99%

Lower extremity joint torque predicted by using artificial neural network during vertical jump

Liu

Shih

Tian

et al. 2009

Journal of Biomechanics

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Section: Ann Modelmentioning

confidence: 99%

Lower extremity joint torque predicted by using artificial neural network during vertical jump

Liu

Shih

Tian

et al. 2009

Journal of Biomechanics

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“…The vigorous increase of the number of action potentials fired by the P-Neuroid as a response to repetitive stimulation at frequencies greater than 2 Hz (Figure 6a), resembled a potentiation that can be assumed as wind-up, a frequency-dependent increase of the DH neurons excitability evoked by recurrent stimulation of nociceptive primary afferents (Herrero et al, 2000) which has been successfully reproduced by computational models at the level of artificial neural networks (Haeri et al, 2003) as well as at the cellular and molecular level (Britton et al, 1996;Farajidavar et al, 2008). Nevertheless, wind-up only occurs within a narrow band of frequencies of stimulation and it reaches its maximum around 1-2 Hz (Schouenborg, 1984) (see Figure 6b).…”

Section: Non-linearities In Noxious Stimuli Processingmentioning

confidence: 79%

Lamina specific loss of inhibition may lead to distinct neuropathic manifestations: a computational modeling approach

et al. 2015

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Introduction: It has been reported that inhibitory control at the superficial dorsal horn (SDH) can act in a regionally distinct manner, which suggests that regionally specific subpopulations of SDH inhibitory neurons may prevent one specific neuropathic condition. Methods: In an attempt to address this issue, we provide an alternative approach by integrating neuroanatomical information provided by different studies to construct a network-model of the SDH. We use Neuroids to simulate each neuron included in that model by adapting available experimental evidence. Results: Simulations suggest that the maintenance of the proper level of pain sensitivity may be attributed to lamina II inhibitory neurons and, therefore, hyperalgesia may be elicited by suppression of the inhibitory tone at that lamina. In contrast, lamina III inhibitory neurons are more likely to be responsible for keeping the nociceptive pathway from the mechanoreceptive pathway, so loss of inhibitory control in that region may result in allodynia. The SDH network-model is also able to replicate non-linearities associated to pain processing, such as Aβ-fiber mediated analgesia and frequency-dependent increase of the neural response. Discussion: By incorporating biophysical accuracy and newer experimental evidence, the SDH network-model may become a valuable tool for assessing the contribution of specific SDH connectivity patterns to noxious transmission in both physiological and pathological conditions.

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“…Owing to the extreme complexity of protein structures, statistical and empirical prediction approaches are widely used to study this kind of relationship (Bokma, 2006;Cai et al, 2003;Chou, 2001aChou, , b, 2004Chou, , 2005Shen, 2007a, 2008;Jahandideh et al, 2007;Haeri et al, 2003;Kurgan et al, 2008;.…”

Section: Introductionmentioning

confidence: 99%

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design

Huang

Wei

et al. 2009

Journal of Theoretical Biology

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Modeling of Pain Using Artificial Neural Networks

Cited by 36 publications

References 22 publications

Lower extremity joint torque predicted by using artificial neural network during vertical jump

Lower extremity joint torque predicted by using artificial neural network during vertical jump

Lamina specific loss of inhibition may lead to distinct neuropathic manifestations: a computational modeling approach

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design

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