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Journal articles on the topic 'Computational nerve model'

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Published: 4 June 2021
Last updated: 1 February 2022

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1

Helmers, S. L., J. Begnaud, A. Cowley, H. M. Corwin, J. C. Edwards, D. L. Holder, H. Kostov, et al. "Application of a computational model of vagus nerve stimulation." Acta Neurologica Scandinavica 126, no. 5 (February 24, 2012): 336–43. http://dx.doi.org/10.1111/j.1600-0404.2012.01656.x.

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2

Michalkova, A., and J. Leszczynski. "Interactions of nerve agents with model surfaces: Computational approach." Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films 28, no. 4 (July 2010): 1010–17. http://dx.doi.org/10.1116/1.3271148.

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3

Lubba, Carl H., Yann Le Guen, Sarah Jarvis, Nick S. Jones, Simon C. Cork, Amir Eftekhar, and Simon R. Schultz. "PyPNS: Multiscale Simulation of a Peripheral Nerve in Python." Neuroinformatics 17, no. 1 (June 15, 2018): 63–81. http://dx.doi.org/10.1007/s12021-018-9383-z.

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Abstract Bioelectronic Medicines that modulate the activity patterns on peripheral nerves have promise as a new way of treating diverse medical conditions from epilepsy to rheumatism. Progress in the field builds upon time consuming and expensive experiments in living organisms. To reduce experimentation load and allow for a faster, more detailed analysis of peripheral nerve stimulation and recording, computational models incorporating experimental insights will be of great help. We present a peripheral nerve simulator that combines biophysical axon models and numerically solved and idealised extracellular space models in one environment. We modelled the extracellular space as a three-dimensional resistive continuum governed by the electro-quasistatic approximation of the Maxwell equations. Potential distributions were precomputed in finite element models for different media (homogeneous, nerve in saline, nerve in cuff) and imported into our simulator. Axons, on the other hand, were modelled more abstractly as one-dimensional chains of compartments. Unmyelinated fibres were based on the Hodgkin-Huxley model; for myelinated fibres, we adapted the model proposed by McIntyre et al. in 2002 to smaller diameters. To obtain realistic axon shapes, an iterative algorithm positioned fibres along the nerve with a variable tortuosity fit to imaged trajectories. We validated our model with data from the stimulated rat vagus nerve. Simulation results predicted that tortuosity alters recorded signal shapes and increases stimulation thresholds. The model we developed can easily be adapted to different nerves, and may be of use for Bioelectronic Medicine research in the future.
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4

Beck, Jeremy M., and Christopher M. Hadad. "Hydrolysis of nerve agents by model nucleophiles: A computational study." Chemico-Biological Interactions 175, no. 1-3 (September 2008): 200–203. http://dx.doi.org/10.1016/j.cbi.2008.04.026.

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Giannessi, Elisabetta, Maria Rita Stornelli, and Pier Nicola Sergi. "A unified approach to model peripheral nerves across different animal species." PeerJ 5 (November 10, 2017): e4005. http://dx.doi.org/10.7717/peerj.4005.

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Peripheral nerves are extremely complex biological structures. The knowledge of their response to stretch is crucial to better understand physiological and pathological states (e.g., due to overstretch). Since their mechanical response is deterministically related to the nature of the external stimuli, theoretical and computational tools were used to investigate their behaviour. In this work, a Yeoh-like polynomial strain energy function was used to reproduce the response of in vitro porcine nerve. Moreover, this approach was applied to different nervous structures coming from different animal species (rabbit, lobster, Aplysia) and tested for different amount of stretch (up to extreme ones). Starting from this theoretical background, in silico models of both porcine nerves and cerebro-abdominal connective of Aplysia were built to reproduce experimental data (R2 > 0.9). Finally, bi-dimensional in silico models were provided to reduce computational time of more than 90% with respect to the performances of fully three-dimensional models.
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6

Sharma, G. C., and Madhu Jain. "A computational solution of mathematical model for oxygen transport in peripheral nerve." Computers in Biology and Medicine 34, no. 7 (October 2004): 633–45. http://dx.doi.org/10.1016/s0010-4825(03)00043-x.

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7

Yang, Changhui, Ruixia Yang, Tingting Xu, and Yinxia Li. "Computational model of enterprise cooperative technology innovation risk based on nerve network." Journal of Algorithms & Computational Technology 12, no. 2 (March 22, 2018): 177–84. http://dx.doi.org/10.1177/1748301818762527.

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Collaborative innovation has become the principal innovation method because of the puniness of the innovation strength of the enterprises. Due to the objective reality nature of the risk of enterprise collaborative technology innovation, it is necessary to take measures to prevent and indemnify the loss which the risk may bring. Because there is the complex nonlinear function mechanism between risk factors, the cooperative mode and control mechanism of enterprise collaborative innovation can be studied by nonlinear method. First, this paper analyzed the seeking method of enterprise collaborative innovation risk, and then the concept of controlling risk regulation gradient of the cooperating technological innovation under network environment was explained. And a complete controlling risk model of the cooperating technological innovation has been put forward, which is based on the wavelet and nerve network. Finally, the discussion about the conclusion of the research was given.
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8

Sachs, Murray B., Raimond L. Winslow, and Bernd H. A. Sokolowski. "A computational model for rate-level functions from cat auditory-nerve fibers." Hearing Research 41, no. 1 (August 1989): 61–69. http://dx.doi.org/10.1016/0378-5955(89)90179-2.

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9

Bacqué-Cazenave, Julien, Bryce Chung, David W. Cofer, Daniel Cattaert, and Donald H. Edwards. "The effect of sensory feedback on crayfish posture and locomotion: II. Neuromechanical simulation of closing the loop." Journal of Neurophysiology 113, no. 6 (March 15, 2015): 1772–83. http://dx.doi.org/10.1152/jn.00870.2014.

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Neuromechanical simulation was used to determine whether proposed thoracic circuit mechanisms for the control of leg elevation and depression in crayfish could account for the responses of an experimental hybrid neuromechanical preparation when the proprioceptive feedback loop was open and closed. The hybrid neuromechanical preparation consisted of a computational model of the fifth crayfish leg driven in real time by the experimentally recorded activity of the levator and depressor (Lev/Dep) nerves of an in vitro preparation of the crayfish thoracic nerve cord. Up and down movements of the model leg evoked by motor nerve activity released and stretched the model coxobasal chordotonal organ (CBCO); variations in the CBCO length were used to drive identical variations in the length of the live CBCO in the in vitro preparation. CBCO afferent responses provided proprioceptive feedback to affect the thoracic motor output. Experiments performed with this hybrid neuromechanical preparation were simulated with a neuromechanical model in which a computational circuit model represented the relevant thoracic circuitry. Model simulations were able to reproduce the hybrid neuromechanical experimental results to show that proposed circuit mechanisms with sensory feedback could account for resistance reflexes displayed in the quiescent state and for reflex reversal and spontaneous Lev/Dep bursting seen in the active state.
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10

Ge, Yimeng, Shuan Ye, Kaihua Zhu, Tianruo Guo, Diansan Su, Dingguo Zhang, Yao Chen, Xinyu Chai, and Xiaohong Sui. "Mediating different-diameter Aβ nerve fibers using a biomimetic 3D TENS computational model." Journal of Neuroscience Methods 346 (December 2020): 108891. http://dx.doi.org/10.1016/j.jneumeth.2020.108891.

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11

Mourdoukoutas, Antonios P., Dennis Q. Truong, Devin K. Adair, Bruce J. Simon, and Marom Bikson. "High-Resolution Multi-Scale Computational Model for Non-Invasive Cervical Vagus Nerve Stimulation." Neuromodulation: Technology at the Neural Interface 21, no. 3 (October 27, 2017): 261–68. http://dx.doi.org/10.1111/ner.12706.

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12

Ahmed, Sameed, and Anita T. Layton. "Sex-specific computational models for blood pressure regulation in the rat." American Journal of Physiology-Renal Physiology 318, no. 4 (April 1, 2020): F888—F900. http://dx.doi.org/10.1152/ajprenal.00376.2019.

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In the past decades, substantial effort has been devoted to the development of computational models of the cardiovascular system. Some of these models simulate blood pressure regulation in humans and include components of the circulatory, renal, and neurohormonal systems. Although such human models are intended to have clinical value in that they can be used to assess the effects and reveal mechanisms of hypertensive therapeutic treatments, rodent models would be more useful in assisting the interpretation of animal experiments. Also, despite well-known sexual dimorphism in blood pressure regulation, almost all published models are gender neutral. Given these observations, the goal of this project is to develop the first computational models of blood pressure regulation for male and female rats. The resulting sex-specific models represent the interplay among cardiovascular function, renal hemodynamics, and kidney function in the rat; they also include the actions of the renal sympathetic nerve activity and the renin-angiotensin-aldosterone system as well as physiological sex differences. We explore mechanisms responsible for blood pressure and renal autoregulation and notable sexual dimorphism. Model simulations suggest that fluid and sodium handling in the kidney of female rats, which differs significantly from males, may contribute to their observed lower salt sensitivity as compared with males. Additionally, model simulations highlight sodium handling in the kidney and renal sympathetic nerve activity sensitivity as key players in the increased resistance of females to angiotensin II-induced hypertension as compared with males.
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13

Lima, Pedro M., Neville J. Ford, and Patricia M. Lumb. "Computational methods for a mathematical model of propagation of nerve impulses in myelinated axons." Applied Numerical Mathematics 85 (November 2014): 38–53. http://dx.doi.org/10.1016/j.apnum.2014.06.004.

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14

Heinz, Michael G., H. Steven Colburn, and Laurel H. Carney. "Evaluating Auditory Performance Limits: I. One-Parameter Discrimination Using a Computational Model for the Auditory Nerve." Neural Computation 13, no. 10 (October 1, 2001): 2273–316. http://dx.doi.org/10.1162/089976601750541804.

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A method for calculating psychophysical performance limits based on stochastic neural responses is introduced and compared to previous analytical methods for evaluating auditory discrimination of tone frequency and level. The method uses signal detection theory and a computational model for a population of auditory nerve (AN) fiber responses. The use of computational models allows predictions to be made over a wider parameter range and with more complete descriptions of AN responses than in analytical models. Performance based on AN discharge times (all-information) is compared to performance based only on discharge counts (rate-place). After the method is verified over the range of parameters for which previous analytical models are applicable, the parameter space is then extended. For example, a computational model of AN activity that extends to high frequencies is used to explore the common belief that rate-place information is responsible for frequency encoding at high frequencies due to the rolloff in AN phase locking above 2 kHz. This rolloff is thought to eliminate temporal information at high frequencies. Contrary to this belief, results of this analysis show that rate-place predictions for frequency discrimination are inconsistent with human performance in the dependence on frequency for high frequencies and that there is significant temporal information in the AN up to at least 10 kHz. In fact, the all-information predictions match the functional dependence of human performance on frequency, although optimal performance is much better than human performance. The use of computational AN models in this study provides new constraints on hypotheses of neural encoding of frequency in the auditory system; however, the method is limited to simple tasks with deterministic stimuli. A companion article in this issue (“Evaluating Auditory Performance Limits: II”) describes an extension of this approach to more complex tasks that include random variation of one parameter, for example, random-level variation, which is often used in psychophysics to test neural encoding hypotheses.
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15

Johnson, Matthew D., Yazan M. Dweiri, Jason Cornelius, Kingman P. Strohl, Armin Steffen, Maria Suurna, Ryan J. Soose, et al. "Model-based analysis of implanted hypoglossal nerve stimulation for the treatment of obstructive sleep apnea." Sleep 44, Supplement_1 (February 27, 2021): S11—S19. http://dx.doi.org/10.1093/sleep/zsaa269.

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Abstract Study Objectives Individuals with obstructive sleep apnea (OSA), characterized by frequent sleep disruptions from tongue muscle relaxation and airway blockage, are known to benefit from on-demand electrical stimulation of the hypoglossal nerve. Hypoglossal nerve stimulation (HNS) therapy, which activates the protrusor muscles of the tongue during inspiration, has been established in multiple clinical studies as safe and effective, but the mechanistic understanding for why some stimulation parameters work better than others has not been thoroughly investigated. Methods In this study, we developed a detailed biophysical model that can predict the spatial recruitment of hypoglossal nerve fascicles and axons within these fascicles during stimulation through nerve cuff electrodes. Using this model, three HNS programming scenarios were investigated including grouped cathode (---), single cathode (o-o), and guarded cathode bipolar (+-+) electrode configurations. Results Regardless of electrode configuration, nearly all hypoglossal nerve axons circumscribed by the nerve cuff were recruited for stimulation amplitudes <3 V. Within this range, monopolar configurations required lower stimulation amplitudes than the guarded bipolar configuration to elicit action potentials within hypoglossal nerve axons. Further, the spatial distribution of the activated axons was more uniform for monopolar versus guarded bipolar configurations. Conclusions The computational models predicted that monopolar HNS provided the lowest threshold and the least sensitivity to rotational angle of the nerve cuff around the hypoglossal nerve; however, this setting also increased the likelihood for current leakage outside the nerve cuff, which could potentially activate axons in unintended branches of the hypoglossal nerve. Clinical Trial Registration NCT01161420.
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16

Novikov, Andrei, Ekaterina Blinova, Elena Semeleva, Karina Karakhanjan, Mikhail Mironov, Dmirty Blinov, Yuliya Krainova, Dmitry Pakhomov, Olga Vasilkina, and Elena Samishina. "On local anesthetic action of some dimethylacetamide compounds." Research Results in Pharmacology 4, no. 4 (December 2, 2018): 1–8. http://dx.doi.org/10.3897/rrpharmacology.4.31440.

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The study aim was to explore local anesthetic properties of some tertiary and quaternary derivatives of dimethylacetamide. Materials and methods. The study was performed on white laboratory mice and rats of both sexes, male Agouti guinea pigs, and isolated sciatic nerves of lake frog. In the focus of the study there were two quaternary and eight tertiary compounds of dimethylacetamide with substituted anion with some amino and carbonic acids residue. A local anesthetic property was predicted by computational analysis. Acute toxicity of the most promising substances was studied in mice through subcutaneous route. Local anesthetic activity of tertiary compounds LKhT-3-00, LKhT-4-00 and quaternary LKhT-12-02 was studied on models of terminal, infiltration and conduction anesthesia. The influence of substances on mixed nerve conduction was investigated on lake frog’s isolated sciatic nerves. Results and discussion. The greatest probability of the local anesthetic activity during computational analysis was estimated for the tertiary derivatives of dimethylacetamide LKhT-3-00 and LKhT-4-00 and for the quaternary compound LKhT-12-02. According to their toxicological profile, the compounds belong to moderately toxic substances (class 3). On the model of terminal and infiltration anesthesia, substances LKhT-3-00 and LKhT-4-00 at concentrations of 0.5-1% rapidly cause deep and prolonged anesthesia. On the models of conduction anesthesia, the quaternary derivative of dimethylacetamide LKhT-12-02 has the greatest analgesic effect. The duration of the effect of the substance is over 3 hours. All the investigated compounds block sciatic nerve conduction. The longest effect is registered for LKhT-12-02. Conclusions. Dimethylacetamide derivatives at concentrations of 0.5-1.0% exhibit a local anesthetic activity, and are effective for terminal, conduction and infiltration anesthesia. Their effect is due to blockade of nerve conduction.
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17

Szmurlo, Robert, Jacek Starzynski, Stanislaw Wincenciak, and Andrzej Rysz. "Numerical model of vagus nerve electrical stimulation." COMPEL - The international journal for computation and mathematics in electrical and electronic engineering 28, no. 1 (January 2, 2009): 211–20. http://dx.doi.org/10.1108/03321640910919002.

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18

Mandal, Debasish, Kaushik Sen, and Abhijit K. Das. "Aminolysis of a Model Nerve Agent: A Computational Reaction Mechanism Study ofO,S-Dimethyl Methylphosphonothiolate." Journal of Physical Chemistry A 116, no. 32 (August 8, 2012): 8382–96. http://dx.doi.org/10.1021/jp305994g.

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19

Kang, Soojin, Tanmoy Chwodhury, Il Joon Moon, Sung Hwa Hong, Hyejin Yang, Jong Ho Won, and Jihwan Woo. "Effects of Electrode Position on Spatiotemporal Auditory Nerve Fiber Responses: A 3D Computational Model Study." Computational and Mathematical Methods in Medicine 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/934382.

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A cochlear implant (CI) is an auditory prosthesis that enables hearing by providing electrical stimuli through an electrode array. It has been previously established that the electrode position can influence CI performance. Thus, electrode position should be considered in order to achieve better CI results. This paper describes how the electrode position influences the auditory nerve fiber (ANF) response to either a single pulse or low- (250 pulses/s) and high-rate (5,000 pulses/s) pulse-trains using a computational model. The field potential in the cochlea was calculated using a three-dimensional finite-element model, and the ANF response was simulated using a biophysical ANF model. The effects were evaluated in terms of the dynamic range, stochasticity, and spike excitation pattern. The relative spread, threshold, jitter, and initiated node were analyzed for single-pulse response; and the dynamic range, threshold, initiated node, and interspike interval were analyzed for pulse-train stimuli responses. Electrode position was found to significantly affect the spatiotemporal pattern of the ANF response, and this effect was significantly dependent on the stimulus rate. We believe that these modeling results can provide guidance regarding perimodiolar and lateral insertion of CIs in clinical settings and help understand CI performance.
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20

Ye, Shuan, Kaihua Zhu, Peng Li, and Xiaohong Sui. "Neural Firing Mechanism Underlying Two-Electrode Discrimination by 3D Transcutaneous Electrical Nerve Stimulation Computational Model." Journal of Shanghai Jiaotong University (Science) 24, no. 6 (December 2019): 716–22. http://dx.doi.org/10.1007/s12204-019-2134-y.

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21

Amoddeo, Antonino. "Mathematical Model and Numerical Simulation for Electric Field Induced Cancer Cell Migration." Mathematical and Computational Applications 26, no. 1 (December 31, 2020): 4. http://dx.doi.org/10.3390/mca26010004.

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A mathematical model describing the interaction of cancer cells with the urokinase plasminogen activation system is represented by a system of partial differential equations, in which cancer cell dynamics accounts for diffusion, chemotaxis, and haptotaxis contributions. The mutual relations between nerve fibers and tumors have been recently investigated, in particular, the role of nerves in the development of tumors, as well neurogenesis induced by cancer cells. Such mechanisms are mediated by neurotransmitters released by neurons as a consequence of electrical stimuli flowing along the nerves, and therefore electric fields can be present inside biological tissues, in particular, inside tumors. Considering cancer cells as negatively charged particles immersed in the correct biological environment and subjected to an external electric field, the effect of the latter on cancer cell dynamics is still unknown. Here, we implement a mathematical model that accounts for the interaction of cancer cells with the urokinase plasminogen activation system subjected to a uniform applied electric field, simulating the first stage of cancer cell dynamics in a three-dimensional axial symmetric domain. The obtained numerical results predict that cancer cells can be moved along a preferred direction by an applied electric field, suggesting new and interesting strategies in cancer therapy.
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22

Cosner, Chris. "Existence of Global Solutions to a Model of a Myelinated Nerve Axon." SIAM Journal on Mathematical Analysis 18, no. 3 (May 1987): 703–10. http://dx.doi.org/10.1137/0518053.

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23

Raspopovic, S., M. Capogrosso, and S. Micera. "A Computational Model for the Stimulation of Rat Sciatic Nerve Using a Transverse Intrafascicular Multichannel Electrode." IEEE Transactions on Neural Systems and Rehabilitation Engineering 19, no. 4 (August 2011): 333–44. http://dx.doi.org/10.1109/tnsre.2011.2151878.

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24

Denniss, Jonathan, Andrew Turpin, Fumi Tanabe, Chota Matsumoto, and Allison M. McKendrick. "Structure–Function Mapping: Variability andConvictionin Tracing Retinal Nerve Fiber Bundles and Comparison to a Computational Model." Investigative Opthalmology & Visual Science 55, no. 2 (February 4, 2014): 728. http://dx.doi.org/10.1167/iovs.13-13142.

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25

Chung, Bryce, Julien Bacqué-Cazenave, David W. Cofer, Daniel Cattaert, and Donald H. Edwards. "The effect of sensory feedback on crayfish posture and locomotion: I. Experimental analysis of closing the loop." Journal of Neurophysiology 113, no. 6 (March 15, 2015): 1763–71. http://dx.doi.org/10.1152/jn.00248.2014.

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The effect of proprioceptive feedback on the control of posture and locomotion was studied in the crayfish Procambarus clarkii (Girard). Sensory and motor nerves of an isolated crayfish thoracic nerve cord were connected to a computational neuromechanical model of the crayfish thorax and leg. Recorded levator (Lev) and depressor (Dep) nerve activity drove the model Lev and Dep muscles to move the leg up and down. These movements released and stretched a model stretch receptor, the coxobasal chordotonal organ (CBCO). Model CBCO length changes drove identical changes in the real CBCO; CBCO afferent responses completed the feedback loop. In a quiescent preparation, imposed model leg lifts evoked resistance reflexes in the Dep motor neurons that drove the leg back down. A muscarinic agonist, oxotremorine, induced an active state in which spontaneous Lev/Dep burst pairs occurred and an imposed leg lift excited a Lev assistance reflex followed by a Lev/Dep burst pair. When the feedback loop was intact, Lev/Dep burst pairs moved the leg up and down rhythmically at nearly three times the frequency of burst pairs when the feedback loop was open. The increased rate of rhythmic bursting appeared to result from the positive feedback produced by the assistance reflex.
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Yavuz, Mehmet, and Asıf Yokus. "Analytical and numerical approaches to nerve impulse model of fractional‐order." Numerical Methods for Partial Differential Equations 36, no. 6 (June 2, 2020): 1348–68. http://dx.doi.org/10.1002/num.22476.

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27

Thomas, E. A., H. Sjövall, and J. C. Bornstein. "Computational model of the migrating motor complex of the small intestine." American Journal of Physiology-Gastrointestinal and Liver Physiology 286, no. 4 (April 2004): G564—G572. http://dx.doi.org/10.1152/ajpgi.00369.2003.

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The migrating motor complex (MMC) is a cyclic motor pattern with several phases enacted over the entire length of the small intestine. This motor pattern is initiated and coordinated by the enteric nervous system and modulated by extrinsic factors. Because in vitro preparations of the MMC do not exist, it has not been possible to determine the intrinsic nerve circuits that manage this motor pattern. We have used computer simulation to explore the possibility that the controlling circuit is the network of AH/Dogiel type II (AH) neurons. The basis of the model is that recurrent connections between AH neurons cause local circuits to enter a high-firing-rate state that provides the maximal motor drive observed in phase III of the MMC. This also drives adjacent segments of the network causing slow migration. Delayed negative feedback within the circuit, provided by activity-dependent synaptic depression, forces the network to return to rest after passage of phase III. The anal direction of propagation is a result of slight anal bias observed in projections of AH neurons. The model relates properties of neurons to properties of the MMC cycle: phase III migration speed is governed by neuron excitability, MMC cycle length is governed by the rate of recovery of synaptic efficacy, and phase III duration is governed by duration of slow excitatory postsynaptic potentials in AH neurons. In addition, the model makes experimental predictions that can be tested using standard techniques.
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Winkelstein, Beth A., and Joyce A. DeLeo. "Mechanical Thresholds for Initiation and Persistence of Pain Following Nerve Root Injury: Mechanical and Chemical Contributions at Injury." Journal of Biomechanical Engineering 126, no. 2 (April 1, 2004): 258–63. http://dx.doi.org/10.1115/1.1695571.

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There is much evidence supporting the hypothesis that magnitude of nerve root mechanical injury affects the nature of the physiological responses which can contribute to pain in lumbar radiculopathy. Specifically, injury magnitude has been shown to modulate behavioral hypersensitivity responses in animal models of radiculopathy. However, no study has determined the mechanical deformation thresholds for initiation and maintenance of the behavioral sensitivity in these models. Therefore, it was the purpose of this study to quantify the effects of mechanical and chemical contributions at injury on behavioral outcomes and to determine mechanical thresholds for pain onset and persistence. Male Holtzman rats received either a silk or chromic gut ligation of the L5 nerve roots, a sham exposure of the nerve roots, or a chromic exposure in which no mechanical deformation was applied but chromic gut material was placed on the roots. Using image analysis, nerve root radial strains were estimated at the time of injury. Behavioral hypersensitivity was assessed by measuring mechanical allodynia continuously throughout the study. Chromic gut ligations produced allodynia responses for nerve root strains at two-thirds of the magnitudes of those strains which produced the corresponding behaviors for silk ligation. Thresholds for nerve root compression producing the onset (8.4%) and persistence of pain (17.4%–22.2%) were determined for silk ligation in this lumbar radiculopathy model. Such mechanical thresholds for behavioral sensitivity in a painful radiculopathy model begin to provide biomechanical data which may have utility in broader experimental and computational models for relating injury biomechanics and physiologic responses of pain.
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29

Hagen, David R., Jacob K. White, and Bruce Tidor. "Convergence in parameters and predictions using computational experimental design." Interface Focus 3, no. 4 (August 6, 2013): 20130008. http://dx.doi.org/10.1098/rsfs.2013.0008.

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Typically, biological models fitted to experimental data suffer from significant parameter uncertainty, which can lead to inaccurate or uncertain predictions. One school of thought holds that accurate estimation of the true parameters of a biological system is inherently problematic. Recent work, however, suggests that optimal experimental design techniques can select sets of experiments whose members probe complementary aspects of a biochemical network that together can account for its full behaviour. Here, we implemented an experimental design approach for selecting sets of experiments that constrain parameter uncertainty. We demonstrated with a model of the epidermal growth factor–nerve growth factor pathway that, after synthetically performing a handful of optimal experiments, the uncertainty in all 48 parameters converged below 10 per cent. Furthermore, the fitted parameters converged to their true values with a small error consistent with the residual uncertainty. When untested experimental conditions were simulated with the fitted models, the predicted species concentrations converged to their true values with errors that were consistent with the residual uncertainty. This paper suggests that accurate parameter estimation is achievable with complementary experiments specifically designed for the task, and that the resulting parametrized models are capable of accurate predictions.
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Rothman, J. S., E. D. Young, and P. B. Manis. "Convergence of auditory nerve fibers onto bushy cells in the ventral cochlear nucleus: implications of a computational model." Journal of Neurophysiology 70, no. 6 (December 1, 1993): 2562–83. http://dx.doi.org/10.1152/jn.1993.70.6.2562.

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1. Convergence of auditory nerve (AN) fibers onto bushy cells of the ventral cochlear nucleus (VCN) was investigated with a model that describes the electrical membrane properties of these cells. The model consists of a single compartment, representing the soma, and includes three voltage-sensitive ion channels (fast sodium, delayed-rectifier-like potassium, and low-threshold potassium). These three channels have characteristics derived from voltage clamp data of VCN bushy cells. The model also contains a leakage channel, membrane capacitance, and synaptic inputs. The model accurately reproduces the membrane rectification seen in current clamp studies of bushy cells, as well as their unique current clamp responses. 2. In this study, the number and synaptic strength of excitatory AN inputs to the model were varied to investigate the relationship between input convergence parameters and response characteristics. From 1 to 20 excitatory synaptic inputs were applied through channels in parallel with the voltage-gated channels. Each synapse was driven by an independent AN spike train; spike arrivals produced brief (approximately 0.5 ms) conductance increases. The number (NS) and conductance (AE) of these inputs were systematically varied. The input spike trains were generated as a renewal point process that accurately models characteristics of AN fibers (refractoriness, adaptation, onset latency, irregularity of discharge, and phase locking). Adaptation characteristics of both high and low spontaneous rate (SR) AN fibers were simulated. 3. As NS and AE vary over the ranges 1–20 and 3–80 nS, respectively, the full range of response types seen in VCN bushy cells are produced by the model, with AN inputs typical of high-SR AN fibers. These include primarylike (PL), primarylike-with-notch (Pri-N), and onset-L (On-L). In addition, Onset responses, whose association with bushy cells in uncertain, and “dip” responses, which are not seen in the VCN, are produced. Dip responses occur with large NS and/or AE, and are due to depolarization block. When the AN inputs have the adaptation characteristics of low-SR AN fibers, PL--but not Pri-N or On-L responses--are produced. This suggests that neurons showing Pri-N and On-L responses must receive high-SR AN inputs. 4. The regularity of discharge of the model is compared with that of VCN bushy cells, using a measure derived from the mean and standard deviation of interspike intervals. Regularity is an important constraint on the model because the regularity of VCN bushy cells is the same as that of their AN inputs.(ABSTRACT TRUNCATED AT 400 WORDS)
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31

Adams, Robert D., Rebecca K. Willits, and Amy B. Harkins. "Computational modeling of neurons: intensity-duration relationship of extracellular electrical stimulation for changes in intracellular calcium." Journal of Neurophysiology 115, no. 1 (January 1, 2016): 602–16. http://dx.doi.org/10.1152/jn.00571.2015.

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In many instances of extensive nerve damage, the injured nerve never adequately heals, leaving lack of nerve function. Electrical stimulation (ES) has been shown to increase the rate and orient the direction of neurite growth, and is a promising therapy. However, the mechanism in which ES affects neuronal growth is not understood, making it difficult to compare existing ES protocols or to design and optimize new protocols. We hypothesize that ES acts by elevating intracellular calcium concentration ([Ca2+]i) via opening voltage-dependent Ca2+ channels (VDCCs). In this work, we have created a computer model to estimate the ES Ca2+ relationship. Using COMSOL Multiphysics, we modeled a small dorsal root ganglion (DRG) neuron that includes one Na+ channel, two K+ channels, and three VDCCs to estimate [Ca2+]i in the soma and growth cone. As expected, the results show that an ES that generates action potentials (APs) can efficiently raise the [Ca2+]i of neurons. More interestingly, our simulation results show that sub-AP ES can efficiently raise neuronal [Ca2+]i and that specific high-voltage ES can preferentially raise [Ca2+]i in the growth cone. The intensities and durations of ES on modeled growth cone calcium rise are consistent with directionality and orientation of growth cones experimentally shown by others. Finally, this model provides a basis to design experimental ES pulse parameters, including duration, intensity, pulse-train frequency, and pulse-train duration to efficiently raise [Ca2+]i in neuronal somas or growth cones.
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LaTorre, Antonio, Man Ting Kwong, Julián A. García-Grajales, Riyi Shi, Antoine Jérusalem, and José-María Peña. "Model calibration using a parallel differential evolution algorithm in computational neuroscience: Simulation of stretch induced nerve deficit." Journal of Computational Science 39 (January 2020): 101053. http://dx.doi.org/10.1016/j.jocs.2019.101053.

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Denniss, Jonathan, Allison M. McKendrick, and Andrew Turpin. "An Anatomically Customizable Computational Model Relating the Visual Field to the Optic Nerve Head in Individual Eyes." Investigative Opthalmology & Visual Science 53, no. 11 (October 9, 2012): 6981. http://dx.doi.org/10.1167/iovs.12-9657.

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34

Nagaraj, Vivek, Andrew Lamperski, and Theoden I. Netoff. "Seizure Control in a Computational Model Using a Reinforcement Learning Stimulation Paradigm." International Journal of Neural Systems 27, no. 07 (August 28, 2017): 1750012. http://dx.doi.org/10.1142/s0129065717500125.

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Neuromodulation technologies such as vagus nerve stimulation and deep brain stimulation, have shown some efficacy in controlling seizures in medically intractable patients. However, inherent patient-to-patient variability of seizure disorders leads to a wide range of therapeutic efficacy. A patient specific approach to determining stimulation parameters may lead to increased therapeutic efficacy while minimizing stimulation energy and side effects. This paper presents a reinforcement learning algorithm that optimizes stimulation frequency for controlling seizures with minimum stimulation energy. We apply our method to a computational model called the epileptor. The epileptor model simulates inter-ictal and ictal local field potential data. In order to apply reinforcement learning to the Epileptor, we introduce a specialized reward function and state-space discretization. With the reward function and discretization fixed, we test the effectiveness of the temporal difference reinforcement learning algorithm (TD(0)). For periodic pulsatile stimulation, we derive a relation that describes, for any stimulation frequency, the minimal pulse amplitude required to suppress seizures. The TD(0) algorithm is able to identify parameters that control seizures quickly. Additionally, our results show that the TD(0) algorithm refines the stimulation frequency to minimize stimulation energy thereby converging to optimal parameters reliably. An advantage of the TD(0) algorithm is that it is adaptive so that the parameters necessary to control the seizures can change over time. We show that the algorithm can converge on the optimal solution in simulation with slow and fast inter-seizure intervals.
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Alam, Manjurul, and Padmanabhan Seshaiyer. "Impact of Contact Constraints on the Dynamics of Idealized Intracranial Saccular Aneurysms." Bioengineering 6, no. 3 (August 30, 2019): 77. http://dx.doi.org/10.3390/bioengineering6030077.

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The rupture potential of intracranial aneurysms is an important medical question for physicians. While most intracranial (brain) aneurysms are asymptomatic, the quantification of rupture potential of both symptomatic and asymptomatic lesions is an active area of research. Furthermore, an intracranial aneurysm constrained by an optic nerve tissue might be a scenario for a physician to deal with during the treatment process. In this work, we developed a computational model of an idealized intracranial saccular aneurysm constrained by a rigid nerve tissue to investigate the impact of constrained nerve tissues on the dynamics of aneurysms. A comparative parametric study for constraints of varying length on aneurysm surface was considered. Our computational results demonstrated the impact of contact constraints on the level of stress near the fundus and provided insight on when these constraints can be protective and when they can be destructive. The results show that lesions with long contact constraints generated higher stress (0.116 MPa), whereas lesions without constraints generated less stress (0.1 MPa) at the fundus, which indicated that lesions with nerve constraints can be protective and less likely to rupture than the lesions without constraints. Moreover, lesions with point load on the fundus generated the highest stress (18.15 MPa) and, hence, they can be destructive.
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Zanini, Chiara, and Fabio Zanolin. "Complex dynamics in a nerve fiber model with periodic coefficients." Nonlinear Analysis: Real World Applications 10, no. 3 (June 2009): 1381–400. http://dx.doi.org/10.1016/j.nonrwa.2008.01.024.

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37

Lai, Ying-Cheng, Raimond L. Winslow, and Murray B. Sachs. "The Functional Role of Excitatory and Inhibitory Interactions in Chopper Cells of the Anteroventral Cochlear Nucleus." Neural Computation 6, no. 6 (November 1994): 1127–40. http://dx.doi.org/10.1162/neco.1994.6.6.1127.

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Chopper cells in the anteroventral cochlear nucleus of the cat maintain a robust rate-place representation of vowel spectra over a broad range of stimulus levels. This representation resembles that of low threshold, high spontaneous rate primary auditory nerve fibers at low stimulus levels, and that of high threshold, low spontaneous rate auditory-nerve fibers at high stimulus levels. This has led to the hypothesis that chopper cells in the anteroventral cochlear nucleus selectively process inputs from different spontaneous rate populations of primary auditory-nerve fibers at different stimulus levels. We present a computational model, making use of shunting inhibition, for how this level dependent processing may be performed within the chopper cell dendritic tree. We show that this model (1) implements level-dependent selective processing, (2) reproduces detailed features of real chopper cell post-stimulus-time histograms, and (3) reproduces nonmonotonic rate versus level functions in response to single tones measured.
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Hamasaki, Toru, and Masami Iwamoto. "Computational analysis of the relationship between mechanical state and mechanoreceptor responses during scanning of a textured surface." Advances in Mechanical Engineering 11, no. 11 (November 2019): 168781401988526. http://dx.doi.org/10.1177/1687814019885263.

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Skin deformation caused by contact with an object is transduced into nerve signals by tactile mechanoreceptors, allowing humans to perceive tactile information. Previous research has revealed that the mechanical state associated with finger skin deformation at mechanoreceptor locations in a finite element model is correlated with the experimentally measured responses of slowly adapting type I mechanoreceptors. However, these findings were obtained under static contact conditions. Therefore, in this study, we calculated the von Mises stress at slowly adapting type I and rapidly adapting type I mechanoreceptor locations during dynamic scanning of a textured surface using a finite element model of the human finger. We then estimated the hypothetical responses of the mechanoreceptors and compared the estimated results with the nerve firing of the receptors in previous neurophysiological experiments. These comparisons demonstrated that the temporal history of von Mises stress at mechanoreceptor locations was more strongly correlated with the “number of” impulses (R2 = 0.93 for slowly adapting type I and R2 = 0.90 for rapidly adapting type I) than the impulse “rate” (R2 = 0.58 for slowly adapting type I and R2 = 0.53 for rapidly adapting type I). Our findings suggest that the temporal history of von Mises stress can be used to roughly estimate the number of impulses of mechanoreceptors during scanning of a textured surface.
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Schaette, Roland, and Richard Kempter. "Predicting Tinnitus Pitch From Patients' Audiograms With a Computational Model for the Development of Neuronal Hyperactivity." Journal of Neurophysiology 101, no. 6 (June 2009): 3042–52. http://dx.doi.org/10.1152/jn.91256.2008.

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Tinnitus is often related to hearing loss, but how hearing loss could lead to tinnitus has remained unclear. Animal studies show that the occurrence of tinnitus is correlated to increased spontaneous firing rates of central auditory neurons, but mechanisms that give rise to such hyperactivity have not been identified yet. Here we present a computational model that reproduces tinnitus-related hyperactivity and predicts tinnitus pitch from the audiograms of tinnitus patients with noise-induced hearing loss and tone-like tinnitus. Our key assumption is that the mean firing rates of central auditory neurons are controlled by homeostatic plasticity. Decreased auditory nerve activity after hearing loss is counteracted through an increase of the neuronal response gain, which restores the mean rate but can also lead to hyperactivity. Hyperactivity patterns calculated from patients' audiograms exhibit distinct peaks at frequencies close to the perceived tinnitus pitch, corroborating hyperactivity through homeostatic plasticity as a mechanism for the development of tinnitus after hearing loss. The model suggests that such hyperactivity, and thus also tinnitus caused by cochlear damage, could be alleviated through additional stimulation.
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40

Cang, Jianhua, and W. Otto Friesen. "Model for Intersegmental Coordination of Leech Swimming: Central and Sensory Mechanisms." Journal of Neurophysiology 87, no. 6 (June 1, 2002): 2760–69. http://dx.doi.org/10.1152/jn.2002.87.6.2760.

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Sensory feedback as well as the coupling signals within the CNS are essential for leeches to produce intersegmental phase relationships in body movements appropriate for swimming behavior. To study the interactions between the central pattern generator (CPG) and peripheral feedback in controlling intersegmental coordination, we have constructed a computational model for the leech swimming system with physiologically realistic parameters. First, the leech swimming CPG is simulated by a chain of phase oscillators coupled by three channels of coordinating signals. The activity phase, the projection direction, and the phase response curve (PRC) of each channel are based on the identified intersegmental interneuron network. Output of this largely constrained model produces stable coordination in the simulated CPG with average phase lags of 8–10°/segment in the period range from 0.5 to 1.5 s, similar to those observed in isolated nerve cords. The model also replicates the experimental finding that shorter chains of leech nerve cords have larger phase lags per segment. Sensory inputs, represented by stretch receptors, were subsequently incorporated into the CPG model. Each stretch receptor with its associated PRC, which was defined to mimic the experimental results of phase-dependent phase shifts of the central oscillator by the ventral stretch receptor, can alter the phase of the local central oscillator. Finally, mechanical interactions between the muscles from neighboring segments were simulated by PRCs linking adjacent stretch receptors. This model shows that interactions between neighboring muscles could globally increase the phase lags to the larger value required for the one-wavelength body form observed in freely swimming leeches. The full model also replicates the experimental observation that leeches with severed nerve cords have larger intersegmental phase lags than intact animals. The similarities between physiological and simulation results demonstrate that we have established a realistic model for the central and peripheral control of intersegmental coordination of leech swimming.
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41

Zarei, Vahhab, Sijia Zhang, Beth A. Winkelstein, and Victor H. Barocas. "Tissue loading and microstructure regulate the deformation of embedded nerve fibres: predictions from single-scale and multiscale simulations." Journal of The Royal Society Interface 14, no. 135 (October 2017): 20170326. http://dx.doi.org/10.1098/rsif.2017.0326.

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Excessive deformation of nerve fibres (axons) in the spinal facet capsular ligaments (FCLs) can be a cause of pain. The axons are embedded in the fibrous extracellular matrix (ECM) of FCLs, so understanding how local fibre organization and micromechanics modulate their mechanical behaviour is essential. We constructed a computational discrete-fibre model of an axon embedded in a collagen fibre network attached to the axon by distinct fibre–axon connections. This model was used to relate the axonal deformation to the fibre alignment and collagen volume concentration of the surrounding network during transverse, axial and shear deformations. Our results showed that fibre alignment affects axonal deformation only during transverse and axial loading, but higher collagen volume concentration results in larger overall axonal strains for all loading cases. Furthermore, axial loading leads to the largest stretch of axonal microtubules and induces the largest forces on axon's surface in most cases. Comparison between this model and a multiscale continuum model for a representative case showed that although both models predicted similar averaged axonal strains, strain was more heterogeneous in the discrete-fibre model.
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42

Coy, Rachel, Maxime Berg, James B. Phillips, and Rebecca J. Shipley. "Modelling-informed cell-seeded nerve repair construct designs for treating peripheral nerve injuries." PLOS Computational Biology 17, no. 7 (July 8, 2021): e1009142. http://dx.doi.org/10.1371/journal.pcbi.1009142.

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Millions of people worldwide are affected by peripheral nerve injuries (PNI), involving billions of dollars in healthcare costs. Common outcomes for patients include paralysis and loss of sensation, often leading to lifelong pain and disability. Engineered Neural Tissue (EngNT) is being developed as an alternative to the current treatments for large-gap PNIs that show underwhelming functional recovery in many cases. EngNT repair constructs are composed of a stabilised hydrogel cylinder, surrounded by a sheath of material, to mimic the properties of nerve tissue. The technology also enables the spatial seeding of therapeutic cells in the hydrogel to promote nerve regeneration. The identification of mechanisms leading to maximal nerve regeneration and to functional recovery is a central challenge in the design of EngNT repair constructs. Using in vivo experiments in isolation is costly and time-consuming, offering a limited insight on the mechanisms underlying the performance of a given repair construct. To bridge this gap, we derive a cell-solute model and apply it to the case of EngNT repair constructs seeded with therapeutic cells which produce vascular endothelial growth factor (VEGF) under low oxygen conditions to promote vascularisation in the construct. The model comprises a set of coupled non-linear diffusion-reaction equations describing the evolving cell population along with its interactions with oxygen and VEGF fields during the first 24h after transplant into the nerve injury site. This model allows us to evaluate a wide range of repair construct designs (e.g. cell-seeding strategy, sheath material, culture conditions), the idea being that designs performing well over a short timescale could be shortlisted for in vivo trials. In particular, our results suggest that seeding cells beyond a certain density threshold is detrimental regardless of the situation considered, opening new avenues for future nerve tissue engineering.
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43

LIN, M., Z. Y. LUO, B. F. BAI, F. XU, and T. J. LU. "FLUID DYNAMICS ANALYSIS OF SHEAR STRESS ON NERVE ENDINGS IN DENTINAL MICROTUBULE: A QUANTITATIVE INTERPRETATION OF HYDRODYNAMIC THEORY FOR DENTAL PAIN." Journal of Mechanics in Medicine and Biology 11, no. 01 (March 2011): 205–19. http://dx.doi.org/10.1142/s0219519411003983.

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Noxious thermal and/or mechanical stimuli applied to dentine can cause fluid flow in dentinal microtubules (DMTs). The fluid flow induces shear stress (SS) on intradental nerve endings and may excite pulpal mechanoreceptors to generate dental pain sensation. There exist numerous studies on dental thermal pain, but few are mathematical. For this, we developed a computational fluid dynamics (CFD) model of dentinal fluid flow (DFF) in innervated DMTs. Based on this model, we systematically investigated the effects of various parameters (e.g., biological structure, DFF velocity, and fluid properties) on the SS experienced by intradental nerve endings and thus provide a quantitative interpretation to the hydrodynamic theory. The dimensions of biological structures, odontoblastic process (OP) movement, dentinal fluid velocity, and viscosity were found to have significant influences on the SS while dentinal fluid density showed negligible influence under conditions studied. The results indicate that: (i) dental pain study of animal models may not be directly applied to human being and the results may even vary from one person to another and (ii) OP movement caused by DFF changes the dimension of the space for the fluid flow, affecting thus the SS on nerve endings. The present work enables better understanding of the mechanisms underlying dental pain sensation and quantification of dental pain intensity resulted from clinical procedures such as dentine sensitivity testing and dental restorative processes.
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44

Yang, Hyejin, Jong Ho Won, Inyong Choi, and Jihwan Woo. "A computational study to model the effect of electrode-to-auditory nerve fiber distance on spectral resolution in cochlear implant." PLOS ONE 15, no. 8 (August 3, 2020): e0236784. http://dx.doi.org/10.1371/journal.pone.0236784.

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45

Mandal, Debasish, Bhaskar Mondal, and Abhijit K. Das. "Isomerization and Decomposition of a Model Nerve Agent: A Computational Analysis of the Reaction Energetics and Kinetics of Dimethyl Ethylphosphonate." Journal of Physical Chemistry A 114, no. 39 (October 7, 2010): 10717–25. http://dx.doi.org/10.1021/jp106270d.

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46

Manakova, N. А., and O. V. Gavrilova. "About Nonuniqueness of Solutions of the Showalter-Sidorov Problem for One Mathematical Model of Nerve Impulse Spread in Membrane." Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software" 11, no. 4 (2018): 161–68. http://dx.doi.org/10.14529/mmp180413.

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47

Barnett, William H., Sarah E. M. Jenkin, William K. Milsom, Julian F. R. Paton, Ana P. Abdala, Yaroslav I. Molkov, and Daniel B. Zoccal. "The Kölliker-Fuse nucleus orchestrates the timing of expiratory abdominal nerve bursting." Journal of Neurophysiology 119, no. 2 (February 1, 2018): 401–12. http://dx.doi.org/10.1152/jn.00499.2017.

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Coordination of respiratory pump and valve muscle activity is essential for normal breathing. A hallmark respiratory response to hypercapnia and hypoxia is the emergence of active exhalation, characterized by abdominal muscle pumping during the late one-third of expiration (late-E phase). Late-E abdominal activity during hypercapnia has been attributed to the activation of expiratory neurons located within the parafacial respiratory group (pFRG). However, the mechanisms that control emergence of active exhalation, and its silencing in restful breathing, are not completely understood. We hypothesized that inputs from the Kölliker-Fuse nucleus (KF) control the emergence of late-E activity during hypercapnia. Previously, we reported that reversible inhibition of the KF reduced postinspiratory (post-I) motor output to laryngeal adductor muscles and brought forward the onset of hypercapnia-induced late-E abdominal activity. Here we explored the contribution of the KF for late-E abdominal recruitment during hypercapnia by pharmacologically disinhibiting the KF in in situ decerebrate arterially perfused rat preparations. These data were combined with previous results and incorporated into a computational model of the respiratory central pattern generator. Disinhibition of the KF through local parenchymal microinjections of gabazine (GABAA receptor antagonist) prolonged vagal post-I activity and inhibited late-E abdominal output during hypercapnia. In silico, we reproduced this behavior and predicted a mechanism in which the KF provides excitatory drive to post-I inhibitory neurons, which in turn inhibit late-E neurons of the pFRG. Although the exact mechanism proposed by the model requires testing, our data confirm that the KF modulates the formation of late-E abdominal activity during hypercapnia. NEW & NOTEWORTHY The pons is essential for the formation of the three-phase respiratory pattern, controlling the inspiratory-expiratory phase transition. We provide functional evidence of a novel role for the Kölliker-Fuse nucleus (KF) controlling the emergence of abdominal expiratory bursts during active expiration. A computational model of the respiratory central pattern generator predicts a possible mechanism by which the KF interacts indirectly with the parafacial respiratory group and exerts an inhibitory effect on the expiratory conditional oscillator.
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48

Dong, Yi, Stefan Mihalas, Sung Soo Kim, Takashi Yoshioka, Sliman Bensmaia, and Ernst Niebur. "A simple model of mechanotransduction in primate glabrous skin." Journal of Neurophysiology 109, no. 5 (March 1, 2013): 1350–59. http://dx.doi.org/10.1152/jn.00395.2012.

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Tactile stimulation of the hand evokes highly precise and repeatable patterns of activity in mechanoreceptive afferents; the strength (i.e., firing rate) and timing of these responses have been shown to convey stimulus information. To achieve an understanding of the mechanisms underlying the representation of tactile stimuli in the nerve, we developed a two-stage computational model consisting of a nonlinear mechanical transduction stage followed by a generalized integrate-and-fire mechanism. The model improves upon a recently published counterpart in two important ways. First, complexity is dramatically reduced (at least one order of magnitude fewer parameters). Second, the model comprises a saturating nonlinearity and therefore can be applied to a much wider range of stimuli. We show that both the rate and timing of afferent responses are predicted with remarkable precision and that observed adaptation patterns and threshold behavior are well captured. We conclude that the responses of mechanoreceptive afferents can be understood using a very parsimonious mechanistic model, which can then be used to accurately simulate the responses of afferent populations.
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Cantrell, Meredith B., Warren M. Grill, and Stephen M. Klein. "Computer-based Finite Element Modeling of Insulated Tuohy Needles Used in Regional Anesthesia." Anesthesiology 110, no. 6 (June 1, 2009): 1229–34. http://dx.doi.org/10.1097/aln.0b013e3181a16275.

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Background Differences in needle design may impact nerve localization. This study evaluates the electrical properties of two insulated Tuohy needles using computational finite element modeling. Methods Three-dimensional geometric computer-based models were created representing two 18-gauge, insulated Tuohy needles: (1) with an exposed metal tip and (2) with an insulated tip. The models were projected in simulated human tissue. Using finite element methodology, distributions of current-density were calculated. Voltages in the modeled medium were calculated, and activation patterns of a model nerve fiber around the tip of each needle were estimated using the activating function. Results Maximum current density on the exposed-tip needle occurred along the edge of the distal tip; the distal edge was 1.7 times larger than the side edges and 3.5 times larger than the proximal edge. Conversely, maximum current density occurred along the proximal edge of the insulated-tip Tuohy opening; the proximal edge was 1.9 times larger than the side edges of the opening and 3.5 times larger than the distal edge of the opening. Voltages generated by the exposed-tip needle were larger and had a wider spatial distribution than that of the insulated-tip needle, which restricted to the area immediately adjacent to the opening. Different changes in threshold were predicted to excite a nerve fiber as the needles were rotated or advanced toward the modeled nerve. Conclusions The needles displayed different asymmetric distributions of current density and positional effects on threshold. If this analysis is validated clinically, it may prove useful in testing stimulating needles before clinical application.
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Scoz, Alessia, Laura Bertazzi, and Eleuterio F. Toro. "On well-posedness of a mathematical model for cerebrospinal fluid in the optic nerve sheath and the spinal subarachnoid space." Applied Mathematics and Computation 413 (January 2022): 126625. http://dx.doi.org/10.1016/j.amc.2021.126625.

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