Past, Present and Future of Brain Stimulation
J. Modolo; R. Edwards; J. Campagnaud; B. Bhattacharya; A. Beuter
Mathematical Modelling of Natural Phenomena (2010)
- Volume: 5, Issue: 2, page 185-207
- ISSN: 0973-5348
Access Full Article
topAbstract
topHow to cite
topModolo, J., et al. "Past, Present and Future of Brain Stimulation." Mathematical Modelling of Natural Phenomena 5.2 (2010): 185-207. <http://eudml.org/doc/197691>.
@article{Modolo2010,
abstract = {Recent technological advances including brain imaging (higher resolution in space and
time), miniaturization of integrated circuits (nanotechnologies), and acceleration of
computation speed (Moore’s Law), combined with interpenetration between neuroscience,
mathematics, and physics have led to the development of more biologically plausible
computational models and novel therapeutic strategies. Today, mathematical models of
irreversible medical conditions such as Parkinson’s disease (PD) are developed and
parameterised based on clinical data. How do these evolutions have a bearing on deep brain
stimulation (DBS) of patients with PD? We review how the idea of DBS, a standard
therapeutic strategy used to attenuate neurological symptoms (motor, psychiatric), has
emerged from past experimental and clinical observations, and present how, over the last
decade, computational models based on different approaches (phase oscillator models,
spiking neuron network models, population-based models) have started to shed light onto
DBS mechanisms. Finally, we explore a new mathematical modelling approach based on neural
field equations to optimize mechanisms of brain stimulation and achieve finer control of
targeted neuronal populations. We conclude that neuroscience and mathematics are crucial
partners in exploring brain stimulation and this partnership should also include other
domains such as signal processing, control theory and ethics.},
author = {Modolo, J., Edwards, R., Campagnaud, J., Bhattacharya, B., Beuter, A.},
journal = {Mathematical Modelling of Natural Phenomena},
keywords = {brain stimulation; spiking neurons; neural field models},
language = {eng},
month = {3},
number = {2},
pages = {185-207},
publisher = {EDP Sciences},
title = {Past, Present and Future of Brain Stimulation},
url = {http://eudml.org/doc/197691},
volume = {5},
year = {2010},
}
TY - JOUR
AU - Modolo, J.
AU - Edwards, R.
AU - Campagnaud, J.
AU - Bhattacharya, B.
AU - Beuter, A.
TI - Past, Present and Future of Brain Stimulation
JO - Mathematical Modelling of Natural Phenomena
DA - 2010/3//
PB - EDP Sciences
VL - 5
IS - 2
SP - 185
EP - 207
AB - Recent technological advances including brain imaging (higher resolution in space and
time), miniaturization of integrated circuits (nanotechnologies), and acceleration of
computation speed (Moore’s Law), combined with interpenetration between neuroscience,
mathematics, and physics have led to the development of more biologically plausible
computational models and novel therapeutic strategies. Today, mathematical models of
irreversible medical conditions such as Parkinson’s disease (PD) are developed and
parameterised based on clinical data. How do these evolutions have a bearing on deep brain
stimulation (DBS) of patients with PD? We review how the idea of DBS, a standard
therapeutic strategy used to attenuate neurological symptoms (motor, psychiatric), has
emerged from past experimental and clinical observations, and present how, over the last
decade, computational models based on different approaches (phase oscillator models,
spiking neuron network models, population-based models) have started to shed light onto
DBS mechanisms. Finally, we explore a new mathematical modelling approach based on neural
field equations to optimize mechanisms of brain stimulation and achieve finer control of
targeted neuronal populations. We conclude that neuroscience and mathematics are crucial
partners in exploring brain stimulation and this partnership should also include other
domains such as signal processing, control theory and ethics.
LA - eng
KW - brain stimulation; spiking neurons; neural field models
UR - http://eudml.org/doc/197691
ER -
References
top- C. Ajmone Marsan. Focal electrical stimulation. In: Experimental Models of Epilepsy: A manual for the laboratory worker. Eds D. P. Purpura, J. K. Penry, D. Tower, D. M. Woodbury and R. Walter, Raven Press, New York, 1972.
- S. Amari. Dynamics of pattern formation in lateral-inhibition type neural fields. Biol. Cybern., 27 (1977), No. 2, 77–87.
- F. Atay A. Hutt. Stability and bifurcations in neural fields with finite propagation speed and general connectivity. SIAM J. Appl. Math., 65 (2005), No. 2, 644–666.
- U. B. Barnikol, O. V. Popovych, C. Hauptmann, V. Sturm, H. J. Freund P. A. Tass. Tremor entrainment by patterned low-frequency stimulation. Philos. Transact. A Math. Phys. Eng. Sci., 366 (2008), No. 1880, 3543–3573.
- R. Bartolow. Experimental investigations into the functions of the human brain. AM. J. Med. Sci., 1874, 305–313.
- N. P. Bechtereva, A. N. Bondarchuk V. M. Smirnov. Therapeutic electrostimulations of deep brain structures. Vopr Neirokhir, 1 (1972), 115–120.
- A. L. Benabid, P. Pollak, A. Louveau, S. Henry J. de Rougemont. Combined (thalamotomy and stimulation) stereotactic surgery of the Vim thalamic nucleus for bilateral Parkinson disease. Appl. Neurophysiol., 50 (1987), No. 1-6, 344–346.
- A. L. Benabid, W. Bradley, J. Mitrofanis, C. Xia, B. Piallat, V. Fraix, A. Batir, P. Krack, P. Pollak F. Berger. Therapeutic electrical stimulation of the central nervous system. C. R. Biologies, 328 (2005), 177–186.
- S. A. Chkhenkeli. Direct deep brain stimulation: first steps toward the feedback control of seizures. In: Epilepsy as a dynamical disease, p. 249-262. Eds J. Milton and P. Jung, Springer-Verlag, New York, 2003.
- J. Echauz, H. Firpi, G. Georgoulas. Intelligent control strategies for neurostimulation. In: Applications of intelligent control of engineering systems. Ed P. K. Valavanis, Springer, 2009.
- R. Edwards. Approximation of neural network dynamics by reaction-diffusion equations. Math. Meth. App. Sci., 19 (1996), 651–677.
- G. B. Ermentrout J. D. Cowan. A mathematical theory of visual hallucination patterns. Biol. Cybern., 34 (1979), No. 3, 137–150.
- A. Eusebio, A. Pogosyan, S. Wang, B. Averbeck, L. D. Gaynor, S. Cantiniaux, T. Witjas, P. Limousin, J. P. Azulay P. Brown. Resonance in subthalamo-cortical circuits in Parkinson’s disease. Brain, 132 (2009), No. 8, 2139–2150.
- W. Gerstner, R. Kempter, J. L. van Hemmen H. Wagner. A neuronal learning rule for sub-millisecond temporal coding. Nature, 383 (1996), 76–81.
- F. A. Gibbs, E. L. Gibbs W. G. Lennox. The likeness of the cortical dysrhythmias of schizophrenia and psychomotor epilepsy. Am. J. Psychiatry, 95 (1938), 255–269.
- P. L. Gildenberg. History of electrical neuromodulation for chronic pain. Pain Medicine, 7 (2006), S7–S13.
- B. J. Gluckman, E. J. Neel, T. I. Neto, W. L. Ditto, M. L. Spano S. J. Schiff. Electric field suppression of epileptiform activity in hippocampal slices. J. Neurophysiol., 6 (1996), 4202–4205.
- B. J. Gluckman, H. Nguyen, S. L. Weinstein S. J. Schiff. Adaptive electric field control of epileptic seizures. J. Neurosci., 21 (2001), No. 2, 290–600.
- S. Grillner, A. Kozlov J. H. Kotaleski. Integrative neuroscience: linking levels of analyses. Curr. Opin. Neurobiol., 15 (2005), No. 5, 614–621.
- R. Hassler, F. Mundiger T. Riechert. Correlations between clinical and autoptic findings in stereotaxic operations in parkinsonism. Confin. Neurol., 26 (1965), 282–290.
- A. L. Hodgkin A. F. Huxley. A quantitative description of membrane current and its application to conduction and excitation in nerve. J. Physiol., 117 (1952), No. 4, 500–544.
- J. C. Horton, D. L. Adams. The cortical column: a structure without a function. Phil. Trans. of the Royal Soc. B, 360 (2005), No. 1456, 837–862.
- X. Huang, W. C. Troy, Q. Yang, H. Ma, C. R. Laing, S. J. Schiff J. Y. Wu. Spiral waves in disinhibited mammalian neocortex. J. Neurosci., 24 (2004), 9897–9902.
- E. M. Izhikevich. Simple model of spiking neurons. Transactions on Neural Networks, 14 (2003), 1569–1572.
- E. M. Izhikevich. Polychronization: computation with spikes. Neural Computation, 18 (2006), 245–282.
- H. H. Jasper. Recording from microelectrodes in stereotactic surgery for Parkinson’s disease. J. Neurosurg., 24 (1966), 219–221.
- E. I. Kandel. Functional and stereotactic neurosurgery. Plenum Medical Book Co, New York, 1966.
- R. R. Llinas, U. Ribary, D. Jeanmonod, E. Kronberg, P. P. Mitra. Thalamocortical dysrhythmia: a neurological and neuropsychiatric syndrome characterized by magnetoencephalography. Proc. Natl. Acad. Sci. USA, 96 (1999), No 26, 15222–15227.
- H. O. Lüders. Deep brain stimulation and epilepsy. Martin Dunitz, New York, 2004.
- C. C. McIntyre, S. Mori, D. L. Sherman, N. V. Thakor J. L. Vitek. Electric field and stimulating influence generated by deep brain stimulation of the subthalamic nucleus. Clin. Neurophysiol., 115 (2004), No. 3, 589–595.
- W. Meissner, A. Leblois, D. Hansel, B. Bioulac, C. E. Gross, A. Benazzouz T. Boraud. Subthalamic high frequency stimulation resets subthalamic firing and reduces abnormal oscillations. Brain, 128 (2005), No. 10, 2372–2382.
- JMilton, P. Jung. Epilepsy as a dynamical disease. Springer-Verlag, New York, 2003.
- J. Modolo, J. Henry A. Beuter. Dynamics of the subthalamo-pallidal complex in Parkinson’s disease during deep brain stimulation. J. Biol. Phys., 34 (2008), No. 3-4, 351–366.
- J. Modolo, A. Beuter. Contribution of cortical inputs to subthalamic activity during deep brain stimulation. Proceedings of the Neurocomp 2008 conference, Marseille, France (2008).
- J. Modolo A. Beuter. Linking brain dynamics, neural mechanisms and deep brain stimulation in Parkinson’s disease: an integrated perspective. Med. Eng. Phys., 31 (2009), 615–623.
- D. Q. Nykamp D. Tranchina. A population density approach that facilitates largescale modeling of neural networks : analysis and an application to orientation tuning. J. Comput. Neurosci., 8 (2000), No. 1, 19–50.
- J. Olszewski. The thalamus of the Macaca Mulatta. An atlas for use with the stereotactic instrument. Basel Karger, 1952.
- A. Omurtag, B. W. Knight, L. Sirovich. On the simulation of large populations of neurons. J. Comput. Neurosci., 8 (2000), No. 5, 51–63.
- A. Pascual, J. Modolo, A. Beuter. Is a computational model useful to understand the effect of deep brain stimulation in Parkinson’s disease?J. Integr. Neurosci., 5 (2006), No. 4, 541–559.
- J. Richmond. The 3Rs-Past, present and future. Scand. J. Lab. Anim. Sci., 27 (2000), 84–92.
- J. E. Rubin D. Terman. High frequency stimulation of the subthalamic nucleus eliminates pathological thalamic rhythmicity in a computational model. J. Comput. Neurosci., 16 (2004), No. 3, 211–235.
- D. Rubino, K. A. Robbins N. G. Hatsopoulos. Propagating waves mediate information transfer in the motor cortex. Nature Neurosci., 9 (2006), No. 12, 1549–1557.
- J. D. Speelman D. A. Bosch. Resurgence of functional neurosurgery for Parkinson’s disease: a historical perspective. Mov. Disord., 13 (1998), No. 3, 582–588.
- E. A. Spiegel, H. T. Wycis, M. Marks A. S. Lee. Stereotaxic apparatus for operations on the human brain. Science, 106 (1947), 349–350.
- A. A. Spiegel, H. T. Wycis. Stereoencephalotomy (thalamic related procedures) part 1: Methods and atlas for the human brain. Grune and Stratton, New York, 1952.
- P. A. Tass. Phase Resetting in Medicine and Biology. Stochastic Modelling and Data Analysis. Series: Springer Series in Synergetics, 1999.
- D. Terman, J. E. Rubin, A. C. Yew C. J. Wilson. Activity patterns in a model for the subthalamopallidal network of the basal ganglia. J. Neurosci., 22 (2002), No. 7, 2963–2976.
- L. Timmermann, J. Gross, M. Dirks, J. Volkmann, H. J. Freund A. Schnitzler. The cerebral oscillatory network of parkinsonian resting tremor. Brain, 126 (2003), No. 1, 199–212.
- L. Timmermann, E. Florin, C. Reck. Pathological cerebral oscillatory activity in Parkinson’s disease: a critical review on methods, data and hypotheses. Expert Rev. Med. Dev., 4 (2007), No 5,651–61.
- M. S. Titcombe, L. Glass, D. Guehl A. Beuter. Dynamics of Parkinsonian tremor during deep brain stimulation. Chaos, 11 (2001), No. 4, 766–773.
- J. L. P. Velazquez. Brain, behaviour and mathematics: Are we using the right approaches?Physica D, 212 (2005), 161–182.
- J. A. Vilensky S. Gilman. Horsley was the first to use electrical stimulation of the human cerebral cortex intraoperatively. Surg. Neurol., 58 (2002), 425–426.
- H. R. Wilson J. D. Cowan. A mathematical theory of the functional dynamics of cortical and thalamic nervous tissue. Kybernetik, 13 (1973), No. 2, 55–80.
- T. Wichmann M. R. Delong. Deep brain stimulation for neurologic and neuropsychiatric disorders. Neuron, 52 (2006), No. 1, 197–204.
- A. Winfree. Are cardiac waves relevant to epileptic waves propagation? In: Epilepsy as a dynamical disease, p. 165-188. Eds J. Milton and P. Jung, Springer-Verlag, New York, 2003.
- J. S. Yeomans. Principles of Brain Stimulation. Oxford University Press, New York, 1990.
Citations in EuDML Documents
topNotesEmbed ?
topTo embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.