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[NEWS] Scientists can monitor brain activity to predict epileptic seizures few minutes in advance

 

Elizabeth Delacruz can’t crawl or toddle around like most youngsters nearing their second birthday.

A rare metabolic disorder that decimated her mobility has also led to cortical blindness – her brain is unable to process images received from an otherwise healthy set of brown eyes. And multiple times a day Elizabeth suffers seizures that continually reduce her brain function. She can only offer an occasional smile or make soft bubbly sounds to communicate her mood.

“But a few months ago I heard her say, ‘Mama,’ and I started to cry,” said Carmen Mejia, a subtle quaver in her voice as she recalled the joy of hearing her daughter. “That’s the first time she said something.”

Ms. Mejia realizes it may also be the last, unless doctors can find a way to detect and prevent the epileptic seizures stemming from a terminal disease called pyruvate dehydrogenase deficiency (PDHD) – which occurs when mitochondria don’t provide enough energy for the cells.

A UT Southwestern study gives parents like Ms. Mejia renewed hope for their children: By monitoring the brain activity of a specific cell type responsible for seizures, scientists can predict convulsions at least four minutes in advance in both humans and mice. The research further shows that an edible acid called acetate may effectively prevent seizures if they are detected with enough notice.

Although the prediction strategy cannot yet be used clinically – a mobile technology for measuring brain activity would have to be developed – it signifies a potential breakthrough in a field that had only been able to forecast seizures a few seconds ahead.

“Many of the families I meet with are not just bothered by the seizures. The problem is the unpredictability, the not knowing when and where a seizure might occur,” said Dr. Juan Pascual, a pediatric neurologist with UT Southwestern’s O’Donnell Brain Institute who led the study published in Science Translational Medicine. “We’ve found a new approach that may one day solve this issue and hopefully help other scientists track down the root of seizures for many kinds of epilepsy.”

Debunked theory

The critical difference between the study and previous efforts was debunking the long-held belief among researchers that most cells in epilepsy patients have malfunctioning mitochondria. In fact, Dr. Pascual’s team spent a decade developing a PDHD mouse model that enabled them to first discover the key metabolic defect in the brain and then determine only a single neuron type was responsible for seizures as the result of the metabolic defect. They honed in on these neurons’ electrical activity with an electroencephalogram (EEG) to detect which brainwave readings signaled an upcoming seizure.

“It’s much more difficult to predict seizures if you don’t know the cell type and what its activity looks like on the EEG,” Dr. Pascual said. “Until this finding, we thought it was a global deficiency in the cells and so we didn’t even know to look for a specific type.”

Predicting seizures

The study shows how a PDHD mouse model helped scientists trace the seizures to inhibitory neurons near the cortex that normally keep the brain’s electrical activity in check.

Scientists then tested a method of calculating when seizures would occur in mice and humans by reviewing EEG files and looking for decreased activity in energy-deficient neurons. Their calculations enabled them to forecast 98 percent of the convulsions at least four minutes in advance.

Dr. Pascual is hopeful his lab can refine EEG analyses to extend the warning window by several more minutes. Even then, live, clinical predictions won’t be feasible unless scientists develop technology to automatically interpret the brain activity and calculate when a seizure is imminent.

Still, he said, the discovery that a single cell type can be used to forecast seizures is a paradigm-shifting finding that may apply to all mitochondrial diseases and related epilepsies.

Potential therapy

Dr. Pascual’s ongoing efforts to extend the prediction time may be a crucial step in utilizing the other intriguing finding from the study: the use of acetate to prevent seizures.

The study showed that delivering acetate into the blood stream of PDHD mice gave their neurons enough energy to normalize their activity and decrease seizures for as long as the acetate was in the brain. However, Dr. Pascual said the acetate would probably need more time – perhaps 10 minutes or more – to take effect in humans if taken by mouth.

Acetate, which naturally occurs in some foods, has been used in patients for decades – including newborns needing intravenous nutrition or patients whose metabolism has shut down. But it had not yet been established as an effective treatment for mitochondrial diseases that underlie epilepsy.

Among the reasons, Dr. Pascual said, is that labs have struggled to create an animal model of such diseases to study its effects; his own lab spent about a decade doing so. Another is the widespread acceptance of the ketogenic diet to reduce the frequency of seizures.

But amid a growing concern about potentially unhealthy side effects of ketogenic diets, Dr. Pascual has been researching alternatives that may refuel the brain more safely and improve cognition.

Frequent seizures

Elizabeth, among a handful of patients whose EEG data were used in the new study, has been prescribed a ketogenic diet and some vitamins to control the seizures. Her family has seen little improvement. Elizabeth often has more than a dozen seizures a day and her muscles and cognition continue to decline. She can’t hold her head up and her mother wonders how many more seizures her brain can take.

Elizabeth was only a few months old when she was diagnosed with PDHD, which occurs when cells lack certain enzymes to efficiently convert food into energy. Patients who show such early signs often don’t survive beyond a few years.

Ms. Mejia does what she can to comfort her daughter, with the hope that Dr. Pascual’s work can someday change the prognosis for PDHD. Ms. Mejia sings, talks, and offers stuffed animals and other toys to her daughter. Although her little girl can’t see, the objects offer a degree of mental stimulation, she said.

“It’s so hard to see her go through this,” Ms. Mejia said. “Every time she has a seizure, her brain is getting worse. I still hope one day she can get a treatment that could stop all this and make her life better.”

‘Big questions’

Dr. Pascual is already conducting further research into acetate treatments, with the goal of launching a clinical trial for patients like Elizabeth in the coming years.

His lab is also researching other epilepsy conditions – such as glucose transporter type I (Glut1) deficiency – to determine if inhibitory neurons in other parts of the brain are responsible for seizures. If so, the findings could provide strong evidence for where scientists should look in the brain to detect and prevent misfiring neurons.

“It’s an exciting time, but there is much that needs to happen to make this research helpful to patients,” Dr. Pascual said. “How do we find an automated way of detecting neuron activity when patients are away from the lab? What are the best ways to intervene when we know a seizure is coming? These are big questions the field still needs to answer.”

via Scientists can monitor brain activity to predict epileptic seizures few minutes in advance

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[Abstract + References] Neuron–glia interactions in the pathophysiology of epilepsy

Abstract

Epilepsy is a neurological disorder afflicting ~65 million people worldwide. It is caused by aberrant synchronized firing of populations of neurons primarily due to imbalance between excitatory and inhibitory neurotransmission. Hence, the historical focus of epilepsy research has been neurocentric. However, the past two decades have enjoyed an explosion of research into the role of glia in supporting and modulating neuronal activity, providing compelling evidence of glial involvement in the pathophysiology of epilepsy. The mechanisms by which glia, particularly astrocytes and microglia, may contribute to epilepsy and consequently could be harnessed therapeutically are discussed in this Review.

References

  1. 1.

    Sontheimer, H. Diseases of the Nervous System 61–95 (Elsevier, 2015).

  2. 2.

    Fisher, R. S. et al. ILAE official report: a practical clinical definition of epilepsy. Epilepsia 55, 475–482 (2014).

  3. 3.

    Kaplan, D. I., Isom, L. L. & Petrou, S. Role of sodium channels in epilepsy. Cold Spring Harb. Perspect. Med. 6, a022814 (2016).

  4. 4.

    Loscher, W., Hirsch, L. J. & Schmidt, D. The enigma of the latent period in the development of symptomatic acquired epilepsy – traditional view versus new concepts. Epilepsy Behav. 52, 78–92 (2015).

  5. 5.

    Sofroniew, M. V. Astrogliosis. Cold Spring Harb. Perspect. Biol. 7, a020420 (2014).

  6. 6.

    Vezzani, A., French, J., Bartfai, T. & Baram, T. Z. The role of inflammation in epilepsy. Nat. Rev. Neurol. 7, 31–40 (2011).

  7. 7.

    van Vliet, E. A. et al. Blood-brain barrier leakage may lead to progression of temporal lobe epilepsy. Brain130, 521–534 (2007).

  8. 8.

    Dingledine, R., Varvel, N. H. & Dudek, F. E. When and how do seizures kill neurons, and is cell death relevant to epileptogenesis? Adv. Exp. Med. Biol. 813, 109–122 (2014).

  9. 9.

    Jessberger, S. & Parent, J. M. Epilepsy and adult neurogenesis. Cold Spring Harb. Perspect. Biol. 7, a020677 (2015).

  10. 10.

    Goldberg, E. M. & Coulter, D. A. Mechanisms of epileptogenesis: a convergence on neural circuit dysfunction. Nat. Rev. Neurosci. 14, 337–349 (2013).

  11. 11.

    Devinsky, O., Vezzani, A., Najjar, S., De Lanerolle, N. C. & Rogawski, M. A. Glia and epilepsy: excitability and inflammation. Trends Neurosci. 36, 174–184 (2013).

  12. 12.

    Kim, S. Y., Porter, B. E., Friedman, A. & Kaufer, D. A potential role for glia-derived extracellular matrix remodeling in postinjury epilepsy. J. Neurosci. Res.94, 794–803 (2016).

  13. 13.

    Hauser, R. M., Henshall, D. C. & Lubin, F. D. The epigenetics of epilepsy and its progression. Neuroscientist 24, 186–200 (2018).

  14. 14.

    Silver, J. & Miller, J. H. Regeneration beyond the glial scar. Nat. Rev. Neurosci. 5, 146–156 (2004).

  15. 15.

    Liddelow, S. A. et al. Neurotoxic reactive astrocytes are induced by activated microglia. Nature 541, 481–487 (2017).

  16. 16.

    Robel, S. et al. Reactive astrogliosis causes the development of spontaneous seizures. J. Neurosci.35, 3330–3345 (2015).This study shows that genetically induced astrogliosis is sufficient to cause epileptic seizures in mice without any other CNS pathologies.

  17. 17.

    Ortinski, P. I. et al. Selective induction of astrocytic gliosis generates deficits in neuronal inhibition. Nat. Neurosci. 13, 584–591 (2010).This study demonstrates that selective induction of astrogliosis in mice using a virus is sufficient to cause network hyperexcitability by impairing neuronal inhibition.

  18. 18.

    Uhlmann, E. J. et al. Astrocyte-specific TSC1 conditional knockout mice exhibit abnormal neuronal organization and seizures. Ann. Neurol. 52, 285–296 (2002).

  19. 19.

    Sosunov, A. A. et al. Phenotypic conversions of “protoplasmic” to “reactive” astrocytes in Alexander disease. J. Neurosci. 33, 7439–7450 (2013).

  20. 20.

    Messing, A., Brenner, M., Feany, M. B., Nedergaard, M. & Goldman, J. E. Alexander disease. J. Neurosci.32, 5017–5023 (2012).

  21. 21.

    Rossini, L. et al. Seizure activity per se does not induce tissue damage markers in human neocortical focal epilepsy. Ann. Neurol. 82, 331–341 (2017).

  22. 22.

    Buckmaster, P. S., Abrams, E. & Wen, X. Seizure frequency correlates with loss of dentate gyrus GABAergic neurons in a mouse model of temporal lobe epilepsy. J. Comp. Neurol. 525, 2592–2610 (2017).

  23. 23.

    Moody, W. J., Futamachi, K. J. & Prince, D. A. Extracellular potassium activity during epileptogenesis. Exp. Neurol. 42, 248–263 (1974).

  24. 24.

    Heinemann, U. & Lux, H. D. Ceiling of stimulus induced rises in extracellular potassium concentration in the cerebral cortex of cat. Brain Res. 120, 231–249 (1977).

  25. 25.

    Coulter, D. A. & Steinhauser, C. Role of astrocytes in epilepsy. Cold Spring Harb. Perspect. Med. 5, a022434 (2015).

  26. 26.

    Traynelis, S. F. & Dingledine, R. Potassium-induced spontaneous electrographic seizures in the rat hippocampal slice. J. Neurophysiol. 59, 259–276 (1988).

  27. 27.

    Gabriel, S. et al. Stimulus and potassium-induced epileptiform activity in the human dentate gyrus from patients with and without hippocampal sclerosis. J. Neurosci. 24, 10416–10430 (2004).

  28. 28.

    Olsen, M. L. & Sontheimer, H. Functional implications for Kir4.1 channels in glial biology: from K+ buffering to cell differentiation. J. Neurochem.107, 589–601 (2008).

  29. 29.

    Steinhauser, C., Seifert, G. & Bedner, P. Astrocyte dysfunction in temporal lobe epilepsy: K+ channels and gap junction coupling. Glia 60, 1192–1202 (2012).

  30. 30.

    Heuser, K. et al. Loss of perivascular Kir4.1 potassium channels in the sclerotic hippocampus of patients with mesial temporal lobe epilepsy. J. Neuropathol. Exp. Neurol. 71, 814–825 (2012).

  31. 31.

    Hinterkeuser, S. et al. Astrocytes in the hippocampus of patients with temporal lobe epilepsy display changes in potassium conductances. Eur. J. Neurosci. 12, 2087–2096 (2000).

  32. 32.

    Djukic, B., Casper, K. B., Philpot, B. D., Chin, L. S. & McCarthy, K. D. Conditional knock-out of Kir4.1 leads to glial membrane depolarization, inhibition of potassium and glutamate uptake, and enhanced short-term synaptic potentiation. J. Neurosci. 27, 11354–11365 (2007).

  33. 33.

    Buono, R. J. et al. Association between variation in the human KCNJ10 potassium ion channel gene and seizure susceptibility. Epilepsy Res. 58, 175–183 (2004).

  34. 34.

    Ferraro, T. N. et al. Fine mapping of a seizure susceptibility locus on mouse chromosome 1: nomination of Kcnj10 as a causative gene. Mamm. Genome 15, 239–251 (2004).

  35. 35.

    Kucheryavykh, Y. V. et al. Downregulation of Kir4.1 inward rectifying potassium channel subunits by RNAi impairs potassium transfer and glutamate uptake by cultured cortical astrocytes. Glia 55, 274–281 (2007).

  36. 36.

    Doyon, N., Vinay, L., Prescott, S. A. & De Koninck, Y. Chloride regulation: a dynamic equilibrium crucial for synaptic inhibition. Neuron 89, 1157–1172 (2016).

  37. 37.

    Moore, Y. E., Kelley, M. R., Brandon, N. J., Deeb, T. Z. & Moss, S. J. Seizing control of KCC2: a new therapeutic target for epilepsy. Trends Neurosci. 40, 555–571 (2017).

  38. 38.

    Lee, H. H., Deeb, T. Z., Walker, J. A., Davies, P. A. & Moss, S. J. NMDA receptor activity downregulates KCC2 resulting in depolarizing GABAA receptor-mediated currents. Nat. Neurosci. 14, 736–743 (2011).

  39. 39.

    Rivera, C. et al. BDNF-induced TrkB activation down-regulates the K+-Cl cotransporter KCC2 and impairs neuronal Cl extrusion. J. Cell Biol. 159, 747–752 (2002).

  40. 40.

    Papadopoulos, M. C. & Verkman, A. S. Aquaporin water channels in the nervous system. Nat. Rev.: Neurosci. 14, 265–277 (2013).

  41. 41.

    Binder, D. K., Nagelhus, E. A. & Ottersen, O. P. Aquaporin-4 and epilepsy. Glia 60, 1203–1214 (2012).

  42. 42.

    Solenov, E., Watanabe, H., Manley, G. T. & Verkman, A. S. Sevenfold-reduced osmotic water permeability in primary astrocyte cultures from AQP-4-deficient mice, measured by a fluorescence quenching method. Am. J. Physiol. 286, C426–C432 (2004).

  43. 43.

    Nicchia, G. P., Frigeri, A., Liuzzi, G. M. & Svelto, M. Inhibition of aquaporin-4 expression in astrocytes by RNAi determines alteration in cell morphology, growth, and water transport and induces changes in ischemia-related genes. FASEB J. 17, 1508–1510 (2003).

  44. 44.

    Vajda, Z. et al. Delayed onset of brain edema and mislocalization of aquaporin-4 in dystrophin-null transgenic mice. Proc. Natl Acad. Sci. USA 99, 13131–13136 (2002).

  45. 45.

    Neely, J. D. et al. Syntrophin-dependent expression and localization of Aquaporin-4 water channel protein. Proc. Natl Acad. Sci. USA 98, 14108–14113 (2001).

  46. 46.

    Nagelhus, E. A., Mathiisen, T. M. & Ottersen, O. P. Aquaporin-4 in the central nervous system: cellular and subcellular distribution and coexpression with KIR4.1. Neuroscience 129, 905–913 (2004).

  47. 47.

    Hochman, D. W. The extracellular space and epileptic activity in the adult brain: explaining the antiepileptic effects of furosemide and bumetanide. Epilepsia 53 (Suppl. 1), 18–25 (2012).

  48. 48.

    Amiry-Moghaddam, M. et al. Delayed K+ clearance associated with aquaporin-4 mislocalization: phenotypic defects in brains of alpha-syntrophin-null mice. Proc. Natl Acad. Sci. USA 100, 13615–13620 (2003).

  49. 49.

    Binder, D. K. et al. Increased seizure duration and slowed potassium kinetics in mice lacking aquaporin-4 water channels. Glia 53, 631–636 (2006).

  50. 50.

    Giaume, C., Koulakoff, A., Roux, L., Holcman, D. & Rouach, N. Astroglial networks: a step further in neuroglial and gliovascular interactions. Nat. Rev. Neurosci. 11, 87–99 (2010).

  51. 51.

    Mylvaganam, S., Ramani, M., Krawczyk, M. & Carlen, P. L. Roles of gap junctions, connexins, and pannexins in epilepsy. Frontiers Physiol. 5, 172 (2014).

  52. 52.

    Deshpande, T. et al. Subcellular reorganization and altered phosphorylation of the astrocytic gap junction protein connexin43 in human and experimental temporal lobe epilepsy. Glia 65, 1809–1820 (2017).

  53. 53.

    Bedner, P. et al. Astrocyte uncoupling as a cause of human temporal lobe epilepsy. Brain 138, 1208–1222 (2015).

  54. 54.

    Voss, L. J., Jacobson, G., Sleigh, J. W., Steyn-Ross, A. & Steyn-Ross, M. Excitatory effects of gap junction blockers on cerebral cortex seizure-like activity in rats and mice. Epilepsia 50, 1971–1978 (2009).

  55. 55.

    During, M. J. & Spencer, D. D. Extracellular hippocampal glutamate and spontaneous seizure in the conscious human brain. Lancet 341, 1607–1610 (1993).

  56. 56.

    Eid, T., Williamson, A., Lee, T. S., Petroff, O. A. & de Lanerolle, N. C. Glutamate and astrocytes—key players in human mesial temporal lobe epilepsy? Epilepsia 49 (Suppl. 2), 42–52 (2008).

  57. 57.

    Schousboe, A., Scafidi, S., Bak, L. K., Waagepetersen, H. S. & McKenna, M. C. Glutamate metabolism in the brain focusing on astrocytes. Adv. Neurobiol. 11, 13–30 (2014).

  58. 58.

    Vandenberg, R. J. & Ryan, R. M. Mechanisms of glutamate transport. Physiol. Rev. 93, 1621–1657 (2013).

  59. 59.

    Tanaka, K. et al. Epilepsy and exacerbation of brain injury in mice lacking the glutamate transporter GLT-1. Science 276, 1699–1702 (1997).This is the first study to show that the homozygous knockout of GLT1 in mice causes lethal spontaneous seizures.

  60. 60.

    Kong, Q. et al. Increased glial glutamate transporter EAAT2 expression reduces epileptogenic processes following pilocarpine-induced status epilepticus. Neurobiol. Dis. 47, 145–154 (2012).

  61. 61.

    Rothstein, J. D. et al. Beta-lactam antibiotics offer neuroprotection by increasing glutamate transporter expression. Nature 433, 73–77 (2005).

  62. 62.

    Zeng, L. H., Bero, A. W., Zhang, B., Holtzman, D. M. & Wong, M. Modulation of astrocyte glutamate transporters decreases seizures in a mouse model of tuberous sclerosis complex. Neurobiol. Dis. 37, 764–771 (2010).

  63. 63.

    Sha, L. et al. Pharmacologic inhibition of Hsp90 to prevent GLT-1 degradation as an effective therapy for epilepsy. J. Exp. Med. 214, 547–563 (2017).

  64. 64.

    Campbell, S. L., Hablitz, J. J. & Olsen, M. L. Functional changes in glutamate transporters and astrocyte biophysical properties in a rodent model of focal cortical dysplasia. Front. Cell. Neurosci. 8, 425 (2014).

  65. 65.

    Campbell, S. L. & Hablitz, J. J. Decreased glutamate transport enhances excitability in a rat model of cortical dysplasia. Neurobiol. Dis. 32, 254–261 (2008).

  66. 66.

    Eid, T. et al. Loss of glutamine synthetase in the human epileptogenic hippocampus: possible mechanism for raised extracellular glutamate in mesial temporal lobe epilepsy. Lancet 363, 28–37 (2004).This study establishes a key role of GS in astrocytes for maintaining an optimal level of extracellular glutamate through the glutamate–glutamine cycle.

  67. 67.

    van der Hel, W. S. et al. Reduced glutamine synthetase in hippocampal areas with neuron loss in temporal lobe epilepsy. Neurology 64, 326–333 (2005).

  68. 68.

    Eid, T. et al. Recurrent seizures and brain pathology after inhibition of glutamine synthetase in the hippocampus in rats. Brain 131, 2061–2070 (2008).

  69. 69.

    Jiang, E., Yan, X. & Weng, H. R. Glial glutamate transporter and glutamine synthetase regulate GABAergic synaptic strength in the spinal dorsal horn. J. Neurochem. 121, 526–536 (2012).

  70. 70.

    Kaczor, P., Rakus, D. & Mozrzymas, J. W. Neuron-astrocyte interaction enhance GABAergic synaptic transmission in a manner dependent on key metabolic enzymes. Front. Cell. Neurosci. 9, 120 (2015).

  71. 71.

    Magistretti, P. J. & Allaman, I. A cellular perspective on brain energy metabolism and functional imaging. Neuron 86, 883–901 (2015).

  72. 72.

    Pellerin, L. & Magistretti, P. J. Sweet sixteen for ANLS. J. Cereb. Blood Flow Metab. 32, 1152–1166 (2012).

  73. 73.

    Gano, L. B., Patel, M. & Rho, J. M. Ketogenic diets, mitochondria, and neurological diseases. J. Lipid Res.55, 2211–2228 (2014).

  74. 74.

    Sada, N., Lee, S., Katsu, T., Otsuki, T. & Inoue, T. Epilepsy treatment. Targeting LDH enzymes with a stiripentol analog to treat epilepsy. Science 347, 1362–1367 (2015).

  75. 75.

    Verkhratsky, A. & Nedergaard, M. Physiology of astroglia. Physiol. Rev. 98, 239–389 (2017).

  76. 76.

    Tyzack, G. E. et al. Astrocyte response to motor neuron injury promotes structural synaptic plasticity via STAT3-regulated TSP-1 expression. Nat. Commun. 5, 4294 (2014).

  77. 77.

    Andresen, L. et al. Gabapentin attenuates hyperexcitability in the freeze-lesion model of developmental cortical malformation. Neurobiol. Dis.71, 305–316 (2014).

  78. 78.

    Neniskyte, U. & Gross, C. T. Errant gardeners: glial-cell-dependent synaptic pruning and neurodevelopmental disorders. Nat. Rev. Neurosci.18, 658 (2017).

  79. 79.

    Stevens, B. et al. The classical complement cascade mediates CNS synapse elimination. Cell 131, 1164–1178 (2007).This study demonstrates that astrocytes regulate complement-mediated synaptic pruning by phagocytic microglia.

  80. 80.

    Chu, Y. et al. Enhanced synaptic connectivity and epilepsy in C1q knockout mice. Proc. Natl Acad. Sci. USA 107, 7975–7980 (2010).

  81. 81.

    Clarke, L. E. & Barres, B. A. Emerging roles of astrocytes in neural circuit development. Nat. Rev. Neurosci. 14, 311–321 (2013).

  82. 82.

    Aronica, E. et al. Complement activation in experimental and human temporal lobe epilepsy. Neurobiol. Dis. 26, 497–511 (2007).

  83. 83.

    Hughes, E. G., Elmariah, S. B. & Balice-Gordon, R. J. Astrocyte secreted proteins selectively increase hippocampal GABAergic axon length, branching, and synaptogenesis. Mol. Cell. Neurosci. 43, 136–145 (2010).

  84. 84.

    Eroglu, C. & Barres, B. A. Regulation of synaptic connectivity by glia. Nature 468, 223–231 (2010).

  85. 85.

    Schafer, D. P. et al. Microglia contribute to circuit defects in Mecp2 null mice independent of microglia-specific loss of Mecp2 expression. eLife 5, e15224 (2016).

  86. 86.

    Tian, G.-F. et al. An astrocytic basis of epilepsy. Nat. Med. 11, 973 (2005).This is the first study to show that glutamate released from astrocytes induces neuronal firing and seizure activity.

  87. 87.

    Clasadonte, J. & Haydon, P. G. in Jasper’s Basic Mechanisms of the Epilepsies (eds Noebels, J. L., Avoli, M., Rogawski, M. A., Olsen, R. W. & Delgado-Escueta, A. V.) (National Center for Biotechnology Information (US), 2012).

  88. 88.

    Kang, N., Xu, J., Xu, Q., Nedergaard, M. & Kang, J. Astrocytic glutamate release-induced transient depolarization and epileptiform discharges in hippocampal CA1 pyramidal neurons. J. Neurophysiol.94, 4121–4130 (2005).

  89. 89.

    Fellin, T., Gomez-Gonzalo, M., Gobbo, S., Carmignoto, G. & Haydon, P. G. Astrocytic glutamate is not necessary for the generation of epileptiform neuronal activity in hippocampal slices. J. Neurosci.26, 9312–9322 (2006).

  90. 90.

    Robert, S. M. et al. SLC7A11 expression is associated with seizures and predicts poor survival in patients with malignant glioma. Sci. Transl Med. 7, 289ra86 (2015).

  91. 91.

    Buckingham, S. C. et al. Glutamate release by primary brain tumors induces epileptic activity. Nat. Med. 17, 1269–1274 (2011).

  92. 92.

    Tewari, B. P. et al. Perineuronal nets decrease membrane capacitance of peritumoral fast spiking interneurons in a model of epilepsy. Nat. Commun.9, 4724 (2018).

  93. 93.

    Campbell, S. L. et al. GABAergic disinhibition and impaired KCC2 cotransporter activity underlie tumor-associated epilepsy. Glia 63, 23–36 (2015).

  94. 94.

    Pallud, J. et al. Cortical GABAergic excitation contributes to epileptic activities around human glioma. Sci. Transl Med. 6, 244ra89 (2014).

  95. 95.

    Boison, D. Adenosinergic signaling in epilepsy. Neuropharmacology 104, 131–139 (2016).

  96. 96.

    Bowser, D. N. & Khakh, B. S. ATP excites interneurons and astrocytes to increase synaptic inhibition in neuronal networks. J. Neurosci. 24, 8606 (2004).

  97. 97.

    Zhang, J.-M. et al. ATP released by astrocytes mediates glutamatergic activity-dependent heterosynaptic suppression. Neuron 40, 971–982 (2003).

  98. 98.

    Gomes, C. V., Kaster, M. P., Tomé, A. R., Agostinho, P. M. & Cunha, R. A. Adenosine receptors and brain diseases: neuroprotection and neurodegeneration. Biochim. Biophys. Acta 1808, 1380–1399 (2011).

  99. 99.

    During, M. J. & Spencer, D. D. Adenosine: a potential mediator of seizure arrest and postictal refractoriness. Ann. Neurol. 32, 618–624 (1992).

  100. 100.

    Aronica, E. et al. Upregulation of adenosine kinase in astrocytes in experimental and human temporal lobe epilepsy. Epilepsia 52, 1645–1655 (2011).

  101. 101.

    Lau, L. W., Cua, R., Keough, M. B., Haylock-Jacobs, S. & Yong, V. W. Pathophysiology of the brain extracellular matrix: a new target for remyelination. Nat. Rev. Neurosci. 14, 722–729 (2013).

  102. 102.

    McRae, P. A., Baranov, E., Rogers, S. L. & Porter, B. E. Persistent decrease in multiple components of the perineuronal net following status epilepticus. Eur. J. Neurosci. 36, 3471–3482 (2012).

  103. 103.

    Dityatev, A. & Fellin, T. Extracellular matrix in plasticity and epileptogenesis. Neuron Glia Biol. 4, 235–247 (2008).

  104. 104.

    Dityatev, A. Remodeling of extracellular matrix and epileptogenesis. Epilepsia 51, 61–65 (2010).

  105. 105.

    Dubey, D. et al. Increased metalloproteinase activity in the hippocampus following status epilepticus. Epilepsy Res. 132, 50–58 (2017).

  106. 106.

    Mizoguchi, H. & Yamada, K. Roles of matrix metalloproteinases and their targets in epileptogenesis and seizures. Clin. Psychopharmacol. Neurosci. 11, 45 (2013).

  107. 107.

    Pollock, E., Everest, M., Brown, A. & Poulter, M. O. Metalloproteinase inhibition prevents inhibitory synapse reorganization and seizure genesis. Neurobiol. Dis. 70, 21–31 (2014).

  108. 108.

    Arranz, A. M. et al. Hyaluronan deficiency due to Has3 knock-out causes altered neuronal activity and seizures via reduction in brain extracellular space. J. Neurosci. 34, 6164–6176 (2014).This study reports the first direct evidence for the development of seizures due to degradation of the ECM.

  109. 109.

    Rempe, R. G. et al. Matrix metalloproteinase-mediated blood-brain barrier dysfunction in epilepsy. J. Neurosci. 38, 4301–4315 (2018).

  110. 110.

    Rankin-Gee, E. K. et al. Perineuronal net degradation in epilepsy. Epilepsia 56, 1124–1133 (2015).

  111. 111.

    Kochlamazashvili, G. et al. The extracellular matrix molecule hyaluronic acid regulates hippocampal synaptic plasticity by modulating postsynaptic L-type Ca2+ channels. Neuron 67, 116–128 (2010).

  112. 112.

    Favuzzi, E. et al. Activity-dependent gating of parvalbumin interneuron function by the perineuronal net protein brevican. Neuron 95, 639–655 (2017).

  113. 113.

    Srinivasan, J., Schachner, M. & Catterall, W. A. Interaction of voltage-gated sodium channels with the extracellular matrix molecules tenascin-C and tenascin-R. Proc. Natl Acad. Sci. USA 95, 15753–15757 (1998).

  114. 114.

    Frischknecht, R. et al. Brain extracellular matrix affects AMPA receptor lateral mobility and short-term synaptic plasticity. Nat. Neurosci. 12, 897–904 (2009).This is one of the first studies to explain the molecular mechanism of ECM-regulated synaptic plasticity.

  115. 115.

    Balmer, T. S. Perineuronal nets enhance the excitability of fast-spiking neurons. eNeurohttps://doi.org/10.1523/ENEURO.0112-16.2016(2016).

  116. 116.

    Morawski, M. et al. Ion exchanger in the brain: quantitative analysis of perineuronally fixed anionic binding sites suggests diffusion barriers with ion sorting properties. Sci. Rep. 5, 16471 (2015).

  117. 117.

    Härtig, W. et al. Cortical neurons immunoreactive for the potassium channel Kv3. 1b subunit are predominantly surrounded by perineuronal nets presumed as a buffering system for cations. Brain Res. 842, 15–29 (1999).

  118. 118.

    Glykys, J. et al. Local impermeant anions establish the neuronal chloride concentration. Science 343, 670–675 (2014).This is one of the first studies to show the regulation of neuronal chloride homeostasis by the ECM.

  119. 119.

    Zamanian, J. L. et al. Genomic analysis of reactive astrogliosis. J. Neurosci. 32, 6391–6410 (2012).

  120. 120.

    Struve, J. et al. Disruption of the hyaluronan-based extracellular matrix in spinal cord promotes astrocyte proliferation. Glia 52, 16–24 (2005).

  121. 121.

    Ye, Z.-C. & Sontheimer, H. Modulation of glial glutamate transport through cell interactions with the extracellular matrix. Int. J. Dev. Neurosci. 20, 209–217 (2002).

  122. 122.

    Guadagno, E. & Moukhles, H. Laminin-induced aggregation of the inwardly rectifying potassium channel, Kir4. 1, and the water-permeable channel, AQP4, via a dystroglycan-containing complex in astrocytes. Glia 47, 138–149 (2004).

  123. 123.

    Seiffert, E. et al. Lasting blood-brain barrier disruption induces epileptic focus in the rat somatosensory cortex. J. Neurosci. 24, 7829–7836 (2004).This study provides the first direct evidence that BBB disruption contributes to epileptogenesis.

  124. 124.

    Ivens, S. et al. TGF-β receptor-mediated albumin uptake into astrocytes is involved in neocortical epileptogenesis. Brain 130, 535–547 (2007).This study demonstrates the epileptogenic role of serum albumin and the TGFβ signalling in astrocytes following BBB disruption.

  125. 125.

    Kim, S. Y., Buckwalter, M., Soreq, H., Vezzani, A. & Kaufer, D. Blood-brain barrier dysfunction-induced inflammatory signaling in brain pathology and epileptogenesis. Epilepsia 53 (Suppl. 6), 37–44 (2012).

  126. 126.

    Weissberg, I. et al. Albumin induces excitatory synaptogenesis through astrocytic TGF-β/ALK5 signaling in a model of acquired epilepsy following blood-brain barrier dysfunction. Neurobiol. Dis. 78, 115–125 (2015).

  127. 127.

    Salar, S. et al. Blood-brain barrier dysfunction can contribute to pharmacoresistance of seizures. Epilepsia 55, 1255–1263 (2014).

  128. 128.

    Kim, S. Y. et al. TGFβ signaling is associated with changes in inflammatory gene expression and perineuronal net degradation around inhibitory neurons following various neurological insults. Sci. Rep. 7, 7711 (2017).

  129. 129.

    Bar-Klein, G. et al. Losartan prevents acquired epilepsy via TGF-β signaling suppression. Ann. Neurol. 75, 864–875 (2014).

  130. 130.

    Yang, Y., Estrada, E. Y., Thompson, J. F., Liu, W. & Rosenberg, G. A. Matrix metalloproteinase-mediated disruption of tight junction proteins in cerebral vessels is reversed by synthetic matrix metalloproteinase inhibitor in focal ischemia in rat. J. Cereb. Blood Flow Metab. 27, 697–709 (2007).This study provides direct evidence that MMPs impair the integrity of the BBB by degrading tight junction proteins.

  131. 131.

    Feng, S. et al. Matrix metalloproteinase-2 and -9 secreted by leukemic cells increase the permeability of blood-brain barrier by disrupting tight junction proteins. PLOS ONE 6, e20599 (2011).

  132. 132.

    Djerbal, L., Lortat-Jacob, H. & Kwok, J. Chondroitin sulfates and their binding molecules in the central nervous system. Glycoconj. J. 34, 363–376 (2017).

  133. 133.

    Pizzorusso, T. et al. Reactivation of ocular dominance plasticity in the adult visual cortex. Science 298, 1248–1251 (2002).This is the first study to demonstrate the functional role of PNNs in the visual cortex as a determinant of experience-dependent plasticity.

  134. 134.

    Engel, T., Alves, M., Sheedy, C. & Henshall, D. C. ATPergic signalling during seizures and epilepsy. Neuropharmacology 104, 140–153 (2016).

  135. 135.

    Cacheaux, L. P. et al. Transcriptome profiling reveals TGF-β signaling involvement in epileptogenesis. J. Neurosci. 29, 8927–8935 (2009).

  136. 136.

    Dzyubenko, E., Gottschling, C. & Faissner, A. Neuron-glia interactions in neural plasticity: contributions of neural extracellular matrix and perineuronal nets. Neural Plast. 2016, 5214961 (2016).

  137. 137.

    Naffah-Mazzacoratti, M. et al. Selective alterations of glycosaminoglycans synthesis and proteoglycan expression in rat cortex and hippocampus in pilocarpine-induced epilepsy. Brain Res. Bull. 50, 229–239 (1999).

  138. 138.

    Gottschall, P. E. & Howell, M. D. ADAMTS expression and function in central nervous system injury and disorders. Matrix Biol. 44, 70–76 (2015).

  139. 139.

    Mataga, N., Mizuguchi, Y. & Hensch, T. K. Experience-dependent pruning of dendritic spines in visual cortex by tissue plasminogen activator. Neuron 44, 1031–1041 (2004).

  140. 140.

    Bast, T., Ramantani, G., Seitz, A. & Rating, D. Focal cortical dysplasia: prevalence, clinical presentation and epilepsy in children and adults. Acta Neurol. Scand. 113, 72–81 (2006).

  141. 141.

    Iseki, K. et al. Increased syndecan expression by pleiotrophin and FGF receptor-expressing astrocytes in injured brain tissue. Glia 39, 1–9 (2002).

  142. 142.

    Hoffmann, K. et al. Retarded kindling progression in mice deficient in the extracellular matrix glycoprotein tenascin-R. Epilepsia 50, 859–869 (2009).

  143. 143.

    Muir, E. et al. Matrix metalloproteases and their inhibitors are produced by overlapping populations of activated astrocytes. Mol. Brain Res. 100, 103–117 (2002).

  144. 144.

    Wilczynski, G. M. et al. Important role of matrix metalloproteinase 9 in epileptogenesis. J. Cell Biol.180, 1021–1035 (2008).

  145. 145.

    Kochlamazashvili, G. et al. The extracellular matrix molecule hyaluronic acid regulates hippocampal synaptic plasticity by modulating postsynaptic L-type Ca 2+ channels. Neuron 67, 116–128 (2010).

  146. 146.

    Evers, M. R. et al. Impairment of L-type Ca2+channel-dependent forms of hippocampal synaptic plasticity in mice deficient in the extracellular matrix glycoprotein tenascin-C. J. Neurosci. 22, 7177–7194 (2002).

  147. 147.

    Konopka, A. et al. Cleavage of hyaluronan and CD44 adhesion molecule regulate astrocyte morphology via Rac1 signalling. PLOS ONE 11, e0155053 (2016).

  148. 148.

    Perosa, S. et al. Glycosaminoglycan levels and proteoglycan expression are altered in the hippocampus of patients with mesial temporal lobe epilepsy. Brain Res. Bull. 58, 509–516 (2002).

  149. 149.

    Jones, E. V. & Bouvier, D. S. Astrocyte-secreted matricellular proteins in CNS remodelling during development and disease. Neural Plast. 2014, 321209 (2014).

  150. 150.

    Lu, P., Takai, K., Weaver, V. M. & Werb, Z. Extracellular matrix degradation and remodeling in development and disease. Cold Spring Harb. Perspect. Biol. 3, a005058 (2011).

via Neuron–glia interactions in the pathophysiology of epilepsy | Nature Reviews Neuroscience

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[Abstract + References] The Reverse Wrist Hinge to improve wrist range of motion

Abstract

The wrist is often immobilized after trauma, potentially leading to subsequent stiffness.1 Static progressive wrist orthoses are sometimes used in rehabilitation when stiffness does not resolve with other techniques such as passive stretching, active exercise, and functional rehabilitation. Once the end-feel status of the wrist and the surrounding soft tissues is assessed,2 a low-load, prolonged stretch is an important factor to consider when attempting to regain wrist range of motion (ROM).3

References

  1. Lucado, A.M., Li, Z. Static progressive splinting to improve wrist stiffness after distal radius fracture: a prospective, case series study. Physiother Theory Pract2009;25:297–309.
  2. Porretto-Loehrke, A., Schuh, C., Szekeres, M. Clinical manual assessment of the wrist. J Hand Ther2016;29:123–135.
  3. Flowers, K.R., LaStayo, P. Effect of total end range time on improving passive range of motion.J Hand Ther1994;7:150–157.
  4. Schultz-Johnson, K. Static progressive splinting. J Hand Ther2002;15:163–178.
  5. Sueoka, S.S., Detemple, K. Static-progressive splinting in under 25 minutes and 25 dollars. J Hand Ther2011;24:280–286.
  6. Szekeres, M., Chinchalkar, S., LeBlanc, M. A low-tech alternative to static progressive wrist extension splinting: the wrist extension strap. J Hand Ther2002;15:375–376.

via The Reverse Wrist Hinge to improve wrist range of motion – Journal of Hand Therapy

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[ARTICLE] The validity of spatiotemporal gait analysis using dual laser range sensors: a cross-sectional study – Full Text

Abstract

Background

The spatiotemporal parameters were used for sophisticated gait analysis in widespread clinical use. Recently, a laser range sensor has been proposed as a new device for the spatiotemporal gait measurement. However, measurement using a single laser range sensor can only be used for short-range gait measurements because the device irradiates participants with lasers in a radial manner. For long-range gait measurement, the present study uses a modified method using dual laser range sensors installed at opposite ends of the walking path. The aim of present study was to investigate the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a computer-based instrumented walkway system.

Methods

Ten healthy participants were enrolled in this study. Ten-meter walking tests at 100, 75, and 50% of the comfortable speed were conducted to determine the concurrent validity of the proposed method compared to instrumented walkway measurements. Frequency distributions of errors for foot-contact (FC) and foot-off (FO) estimated times between the two systems were also calculated to determine the adequacy of estimation of FC and FO from three perspectives: accuracy (smallness of mean error), precision (smallness of variability), and unambiguity (monomodality of histogram). Intra-class correlation coefficient (2,1) was used to determine the concurrent validity of spatiotemporal parameters between the two systems.

Result

The results indicate that the detection times for FC and FO estimated by the proposed method did not differ from those measured by the instrumented walkway reference system. In addition, histogram for FC and FO showed monomodality. Intra-class correlation coefficients of the spatiotemporal parameters (stance time: 0.74; double support time: 0.56; stride time: 0.89; stride length: 0.83; step length: 0.71; swing time: 0.23) were not high enough. The mean errors of all spatiotemporal parameters were small.

Conclusions

These results suggest that the proposed lacks sufficient concurrent validity for spatiotemporal gait measurement. Further improvement of this proposed system seems necessary.

Background

In gait disorder rehabilitation, gait analysis plays an important role in optimizing treatment for each patient [1234]. Conventionally, visual observation of gait analysis is easy and low cost and is commonly used in rehabilitation facilities. However, previous studies report that visual observation gait analysis has low inter-rater and test-retest reliability as well as low criterion concurrent validity in contrast to kinematic analyses using various instruments [45]. For highly accurate measurements with good inter-rater and test-retest reliability, a three-dimensional motion analysis system has been used. Although this system is able to measure whole-body joint motions, it has high costs and is time- and labor-intensive to set up [6].

Spatiotemporal gait measurement is another valuable method to identify gait deviations, make diagnoses, determine appropriate therapy, and monitor patient progress [23]. Frequently, parameters such stance time, swing time, double support time, stride time, stride length, and step length are evaluated [78910]. To calculate these spatiotemporal parameters, accurate detection of two events for switching between the stance and swing phases is essential: foot contact (FC) and foot off (FO). FC is defined as when any point of the foot first contacts and is the starting point of the stance phase. FO is when the sole is raised completely from the floor and is the onset of the swing phase. A measurement system for detection of FC and FO is a computer-based instrumented walkway system with pressure sensors and produces high inter-rater and test-retest reliability [278910]. Although this system has a relatively reasonable price as compared with a three-dimensional motion analysis system, it is still considerably expensive to become widely used. In addition, it occupies a large amount of floor space and greatly limits effective use of the exercise room. While this system is placed on the floor, the place is not able to be used for other purposes even though the exercise room has limited floor space.

Recently, spatiotemporal gait measurement using a laser range scanner has been proposed as easy to install and remove [11121314]. With a laser range scanner, both lower legs are measured using two best-fitting circles whose contours are defined by laser points. Although this method is useful for easy measurement of gait parameters in a clinical setting, the raw contour of the leg is incomplete because the sensor provides only one-sided information [11]. In addition, the number of laser points comprising the spheres decreases with long-range gait measurements because the lasers irradiate participants in a radial manner. Since the radial range decreases with increasing distance from the laser, this causes larger measurement errors.

For eliminating problems in long-range gait measurement, we proposed a method of spatiotemporal gait analysis using dual laser range sensors installed at opposite ends of the walking path. Because the measurement using laser range sensor is quick and easy method, this proposed method has a high degree of usability for clinical practice. However, it is not clear whether the proposed method has concurrent validity, which is defined as evaluation of an instrument against an already validated measure [15], for spatiotemporal gait measurement by comparison to a computer based instrumented walkway system (reference system) that was widely used for criterion-related validity. The aim of present study was to investigate the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a reference system.

Methods

Participants

Ten healthy participants (7 males and 3 females, 20–24 years of age, 154-184 cm in height, 49-70 kg in weight) were enrolled in the present study. All participants have no history of orthopedic, neurophysiologic, and cardiovascular diseases. Informed consent was obtained from each participant before the experiments. The present study was approved by the ethics committee and was conducted according to the Declaration of Helsinki for human experiments.

Experimental procedures

This study used a cross-sectional design to assess the concurrent validity of the proposed method for spatiotemporal gait measurement by comparison to a reference system.

Participants wearing short pants were asked to get on a walking path and walk barefoot along a 12 m straight line including 3.5 m in front of the measured walking path and 3.5 m beyond the end of walking path. Each participant performed one trial at each speed: 100, 75, and 50% of the comfortable speed in a subjective manner. Before measurement, the order of the speed conditions was randomized for each participant. During the gait test, spatiotemporal measurements were carried out simultaneously using both the proposed method and the reference system. The inter-trial interval was set to 2 minutes to prevent fatigue.

Proposed method using laser range sensors

A two-dimensional radial scanning laser range sensor (UTM-30LX, Hokuyo Automatic Co., Ltd., Osaka, Japan) was used (Fig. 1a). The device has a scanning range from − 135° to 135° in steps of 0.25° (total of 1080 data points measuring the distance from the sensor to the target), and one scan is completed in 0.025 s (i.e., the sampling frequency is 40 Hz). In addition, the device exhibits very small test-retest variability and the relative error of a distance (0.1 to 10 m, σ < 0.01 m and ± 0.01 m, white Kent paper, respectively) in the repeated measurements using same laser range sensor unit (i.e. unit testing). Two devices were installed at opposite ends of a five-meter walking path at the level of the average shin height (0.25 m above the floor) [16] (Fig. 1b).

[…]

Continue —>  The validity of spatiotemporal gait analysis using dual laser range sensors: a cross-sectional study | Archives of Physiotherapy | Full Text

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[Abstract] Effectiveness of botulinum toxin treatment for upper limb spasticity after stroke over different ICF domains: a systematic review and meta-analysis.

Abstract

Objective

To provide a comprehensive overview of reported effects and scientific robustness of botulinum toxin (BoNT) treatment regarding the main clinical goals related to post-stroke upper limb spasticity, using the ICF classification.

Data sources

Embase.com, PubMed, Wiley/Cochrane Library, and Ebsco/CINAHL were searched from inception up to 16 May 2018.

Study Selection

Randomized controlled trials comparing upper limb BoNT injections with a control intervention in stroke patients were included. A total of 1212 unique records were screened by two independent reviewers. Forty trials were identified, including 2718 stroke patients.

Data Extraction

Outcome data were pooled according to assessment timing (i.e. 4-8 and 12 weeks after injection), and categorized into six main clinical goals (i.e. spasticity-related pain, involuntary movements, passive joint motion, care ability, arm and hand use, and standing and walking performance). Sensitivity analyses were performed for the influence of study and intervention characteristics, involvement of pharmaceutical industry, and publication bias.

Data Synthesis

Robust evidence is shown for the effectiveness of BoNT in reducing resistance to passive movement, as measured with the (Modified) Ashworth Score, and improving self-care ability for the affected hand and arm after intervention (p<0.005) and at follow-up (p<0.005). In addition, robust evidence is shown for the absence of effect on ‘arm-hand capacity’ at follow-up. BoNT significantly reduced ‘involuntary movements’, ‘spasticity-related pain’, and ‘carer burden’, and improved ‘passive range of motion’, while no evidence was found for ‘arm and hand use’ after intervention.

Conclusions

In view of the robustness of current evidence, no further trials are needed to investigate BoNT for its favourable effects on resistance to passive movement of the spastic wrist and fingers, and on self-care. No trials are needed to further confirm the lack of effects of BoNT on arm-hand capacity, whereas additional trials are needed to establish the suggested favourable effects of BoNT on other ‘body functions’ which may result in clinically meaningful outcomes at ‘activity’ and ‘participation’ levels.

via Effectiveness of botulinum toxin treatment for upper limb spasticity after stroke over different ICF domains: a systematic review and meta-analysis – Archives of Physical Medicine and Rehabilitation

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[WEB SITE] How to stretch your hands and wrists – Videos

Wrist pain can be frustrating and inconvenient. It can also make work or basic day-to-day activities, such as using a computer or cooking a meal, more difficult.

Exercises can improve mobility and decrease the chance of injury or reinjury. Wrist stretches are easy to do at home or at the office. When done properly, they can benefit a person’s overall wrist and hand health.

Anyone experiencing chronic pain or pain with numbness should visit a doctor for a thorough diagnosis.

The following stretches can help improve strength and mobility:

Wrist and hand stretches

A person should do the exercises below slowly and gently, focusing on stretching and strengthening. If the stretch hurts, stop.

The following wrist and hand stretches may improve strength and mobility:

1. Raised fist stretch

Raised fist stretch

To do this stretch:

  1. Start with your arm up beside your head, with your hand open.
  2. Make a fist, keeping your thumb outside of it.
  3. Slide your fingers toward your wrist until you feel a stretch.

2. Wrist rotations

Wrist rotations

To do this stretch:

  1. Stretch your arm out in front of you.
  2. Slowly, point the fingers down until you feel a stretch. Use the other hand to gently pull the raised hand toward the body. Hold this position for 3–5 seconds.
  3. Point the fingers toward the ceiling until you feel a stretch. Use the other hand to gently pull the raised hand toward the body. Hold this position for 3–5 seconds.
  4. Repeat this three times.

3. Prayer position

Prayer position

To do this stretch:

  1. Sit with your palms together and your elbows on the table in a prayer position.
  2. Lower the sides of the hands toward the table until you feel a stretch. Keep your palms together. Hold this position for 5–7 seconds.
  3. Relax.
  4. Repeat this three times.

4. Hooked stretch

Hooked stretch

To do this stretch:

  1. Hook one elbow under the other and pull both arms towards the center of the torso. You should feel a stretch in your shoulders.
  2. Wrap one arm around the other so that the palms are touching.
  3. Hold the position for 25 seconds.
  4. Switch arms and repeat it on the other side.

5. Finger stretch

finger stretch

To do this stretch:

  1. Bring the pinky and ring fingers together.
  2. Separate the middle and index fingers from the ring finger.
  3. Repeat the stretch 10 times.

6. Fist-opener

Fist opener

To do this stretch:

  1. Make a fist and hold it in front of you.
  2. Stretch your fingers until your hand is flat and open, with the fingers together.
  3. Repeat the movements 10 times.

7. Sponge-squeeze

Sponge squeeze

To do this stretch:

  1. Squeeze a sponge or stress ball, making a fist.
  2. Hold the position for 10 seconds.
  3. Relax.
  4. Repeat this 10 times.

8. Windshield wiper wrist movement

To do this stretch:

  1. Start with your hand face down on a table.
  2. Gently, point the hand to one side as far as it can go without moving the wrist. Hold it there for 3–5 seconds.
  3. Do the same on the other side.
  4. Repeat the movement three times on each side.

9. Thumb pull

To do this stretch:

  1. Grab your thumb with the other hand.
  2. Gently pull the thumb backward, away from the hand.
  3. Hold the stretch for 25 seconds.
  4. Repeat it on the other thumb.

10. Flower stretch

To do this stretch:

  1. Stretch the arms in front of you, with the backs of the hands and wrists touching.
  2. Imagine an invisible force pulling the fingers further from the body. Feel the stretch.
  3. Hold it for 25 seconds.

11. Finger fan

To do this stretch:

  1. Make a fist.
  2. Stretch your fingers outwards as far as they can go, like a fan.
  3. Repeat the movements 10 times.

12. Imaginary piano

To do this stretch:

  1. Pretend to play a piano.
  2. Flip your hands over and play an upside-down piano.

13. Finger pulls

To do this stretch:

  1. Lay your hand flat on a table.
  2. Gently pull a finger upward so that it points toward the ceiling.
  3. Hold the position for 5 seconds.
  4. Release the finger.
  5. Repeat this on all the other fingers.

14. Alternate finger stretch

To do this stretch:

  1. Bring the middle and ring fingers together.
  2. Separate the pinky and index fingers from them.
  3. Repeat the stretch 10 times.

15. Wrist-strengthener

To do this stretch:

  1. Get into position on your hands and knees, with the fingers pointing toward the body.
  2. Slowly lean forward, keeping your elbows straight.
  3. Hold the position for 20 seconds.
  4. Relax, then repeat the stretch.

Takeaway

Working with computers, writing, and doing manual labor put strain on the hands and wrists and can cause problems over time, such as tendonitis and carpal tunnel syndrome.

Taking frequent breaks and stretching before and while using the hands and wrists can help prevent strain. Improving flexibility and strength gradually can help people avoid wrist and hand injuries.

via Medical News Today: How to stretch your hands and wrists

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[Abstract] Investigation of multi-joint coordinated upper limb rehabilitation assisted with electromyography (EMG)-driven neuromuscular electrical stimulation (NMES)-robot after stroke

Abstract

More than 80% of stroke survivors worldwide suffer from permanent upper limb motor deficits. Restoration of upper limb motor functions in conventional rehabilitation remains challenging; the main difficulties are as follows: 1) lack of intensive, repetitive practice in manually delivered treatment; 2) lack of coordination management of upper limb motor tasks, particularly those involving the distal joints, e.g., the wrist and the hand; and 3) lack of understanding of the optimal joint supportive scheme in task-oriented upper limb training. More effective training strategies are necessary for upper limb rehabilitation following stroke. Robots have proved to be valuable assistants in labour-demanding post-stroke rehabilitation, with a controllable mechanical design and repeatable dynamic support in physical training. A series of rehabilitation robots for multi-joint practices were successfully designed in our previous works. In this work, we proposed a device-assisted multi-joint coordinated strategy for post-stroke upper limb training. The objectives of the study were as follows: 1) To evaluate the rehabilitation effectiveness of multi-joint coordinated upper limb practice assisted by an electromyography (EMG)-driven neuromuscular electric stimulation (NMES)-robot for stroke survivors in both the subacute and chronic stages. 2) To compare different joint supportive schemes using NMES-robots and identify the optimized scheme for upper limb rehabilitation. The objectives were achieved through three independent clinical trials using common clinical assessments, namely, the Fugl-Meyer Assessment (FMA), Modified Ashworth Scales (MAS), Action Research Arm Test (ARAT), and Functional Independence Measurement (FIM), and cross-session EMG evaluations to trace the recovery progress of individual muscle activities (i.e. EMG activation level) and muscular coordination (i.e. Co-contraction Index, CI) between a pair of muscles.
The first clinical randomized controlled trial (RCT) was conducted to investigate the clinical effects and rehabilitation effectiveness of the new training strategy in the subacute stroke period. Subjects were randomly assigned to two groups and received either 20 sessions of NMES-robot-assisted training (NMES-robot group, n=14) or time-matched conventional treatments (control group, n=10). Significant improvements were achieved in FMA (full score and shoulder/elbow), ARAT, and FIM for both groups [P<0.001, effect sizes (EFs)>0.279], whereas significant improvements in FMA (wrist/hand) and MAS (wrist) after treatment were only observed in the NMES-robot group (P<0.05, EFs>0.145), with the outcomes maintained for 3 months. In the NMES-robot group, CIs of the muscle pairs of biceps brachii and flexor carpi radialis (BIC&FCR) and biceps brachii and triceps brachii (BIC&TRI) were significantly reduced and the EMG activation level of the FCR decreased significantly. The result indicated comparable proximal motor improvements in both groups and better distal motor outcomes and more effective release of muscle spasticity across the whole upper limb in the NMES-robot group. The second part of the work was a clinical trial with a single-group design. Recruited chronic stroke patients (n=17) received 20 sessions of NMES-robot-assisted multi-joint coordinated upper limb training. Significant improvements were observed in FMA (full score and shoulder/elbow), ARAT, and FIM (P<0.05, EFs>0.157) and maintained for 3 months. CIs of the FCR&TRI and BIC&TRI muscle pairs and EMG activation levels of the FCR and BIC significantly decreased. The results indicated that the new training strategy was effective for upper limb recovery in the chronic stroke, with the long sustainability of the motor outcomes. In the third trial, another clinical RCT was conducted to investigate the training effects of different joint supportive schemes. The recruited chronic subjects were randomly assigned to receive task-oriented multi-joint practices with NMES-robotic support either to the finger-palm (hand group, n=15) or to the wrist-elbow (sleeve group, n=15). Significant improvements in FMA (full score and shoulder/elbow) and ARAT (P<0.05, EFs>0.147) were observed in both groups, whereas significant improvements in FMA (wrist/hand) and MAS (finger, wrist, and elbow) (P<0.05, EFs>0.149) were only observed in the hand group. These results indicated that the distal supportive scheme was more effective in distal motor recovery and whole arm spasticity control than the proximal supportive one under the same training strategy. In conclusion, NME-robot-assisted multi-joint coordinated training was able to achieve significant motor outcomes and effective muscle spasticity control in the entire upper limb, especially at the distal segments, i.e., the wrist and the fingers, in both subacute and chronic stroke patients. Moreover, the distal supportive scheme proved more effective than the proximal supportive scheme in multi-joint coordinated upper limb training.

via Investigation of multi-joint coordinated upper limb rehabilitation assisted with electromyography (EMG)-driven neuromuscular electrical stimulation (NMES)-robot after stroke | PolyU Institutional Research Archive

 

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[ARTICLE] Effectiveness of Robot-Assisted Upper Limb Training on Spasticity, Function and Muscle Activity in Chronic Stroke Patients Treated With Botulinum Toxin: A Randomized Single-Blinded Controlled Trial

Abstract

Background: The combined use of Robot-assisted UL training and Botulinum toxin (BoNT) appear to be a promising therapeutic synergism to improve UL function in chronic stroke patients.

Objective: To evaluate the effects of Robot-assisted UL training on UL spasticity, function, muscle strength and the electromyographic UL muscles activity in chronic stroke patients treated with Botulinum toxin.

Methods: This single-blind, randomized, controlled trial involved 32 chronic stroke outpatients with UL spastic hemiparesis. The experimental group (n = 16) received robot-assisted UL training and BoNT treatment. The control group (n = 16) received conventional treatment combined with BoNT treatment. Training protocols lasted for 5 weeks (45 min/session, two sessions/week). Before and after rehabilitation, a blinded rater evaluated patients. The primary outcome was the Modified Ashworth Scale (MAS). Secondary outcomes were the Fugl-Meyer Assessment Scale (FMA) and the Medical Research Council Scale (MRC). The electromyographic activity of 5 UL muscles during the “hand-to-mouth” task was explored only in the experimental group and 14 healthy age-matched controls using a surface Electromyography (EMGs).

Results: No significant between-group differences on the MAS and FMA were measured. The experimental group reported significantly greater improvements on UL muscle strength (p = 0.004; Cohen’s d = 0.49), shoulder abduction (p = 0.039; Cohen’s d = 0.42), external rotation (p = 0.019; Cohen’s d = 0.72), and elbow flexion (p = 0.043; Cohen’s d = 1.15) than the control group. Preliminary observation of muscular activity showed a different enhancement of the biceps brachii activation after the robot-assisted training.

Conclusions: Robot-assisted training is as effective as conventional training on muscle tone reduction when combined with Botulinum toxin in chronic stroke patients with UL spasticity. However, only the robot-assisted UL training contributed to improving muscle strength. The single-group analysis and the qualitative inspection of sEMG data performed in the experimental group showed improvement in the agonist muscles activity during the hand-to-mouth task.

Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03590314

Introduction

Upper limb (UL) sensorimotor impairments are one of the major determinants of long-term disability in stroke survivors (). Several disturbances are the manifestation of UL impairments after stroke (i.e., muscle weakness, changes in muscle tone, joint disturbances, impaired motor control). However, spasticity and weakness are the primary reason for rehabilitative intervention in the chronic stages (). Historically, spasticity refers to a velocity-dependent increase in tonic stretch reflexes with exaggerated tendon jerks resulting from hyperexcitability of the stretch reflex () while weakness is the loss of the ability to generate the normal amount of force.

From 7 to 38% of post-stroke patients complain of UL spasticity in the first year (). The pathophysiology of spasticity is complicated, and new knowledge has progressively challenged this definition. Processes involving central and peripheral mechanisms contribute to the spastic movement disorder resulting in abnormal regulation of tonic stretch reflex and increased muscle resistance of the passively stretched muscle and deficits in agonist and antagonist coactivation (). The resulting immobilization of the muscle at a fixed length for a prolonged time induces secondary biomechanical and viscoelastic properties changes in muscles and soft tissues, and pain (). These peripheral mechanisms, in turn, leads to further stiffness, and viscoelastic muscle changes (). Whether the muscular properties changes may be adaptive and secondary to paresis are uncertain. However, the management of UL spasticity should combine treatment of both the neurogenic and peripheral components of spasticity ().

UL weakness after stroke is prevalent in both acute and chronic phases of recovery (). It is a determinant of UL function in ADLs and other negative consequences such as bone mineral content (), atrophy and altered muscle pattern of activation. Literature supports UL strengthening training effectiveness for all levels of impairment and in all stages of recovery (). However, a small number of trials have been performed in chronic subgroup patients, and there is still controversy in including this procedure in UL rehabilitation ().

Botulinum toxin (BoNT) injection in carefully selected muscles is a valuable treatment for spastic muscles in stroke patients improving deficits in agonist and antagonist coactivation, facilitating agonist recruitment and increasing active range of motion (). However, improvements in UL activity or performance is modest (). With a view of improving UL function after stroke, moderate to high-quality evidence support combining BoNT treatment with other rehabilitation procedures (). Specifically, the integration of robotics in the UL rehabilitation holds promise for developing high-intensity, repetitive, task-specific, interactive treatment of upper limb (). The combined use of these procedures to compensate for their limitations has been studied in only one pilot RCT reporting positive results in UL function (Fugl-Meyer UL Assessment scale) and muscular activation pattern (). With the limits of the small sample, the results support the value of combining high-intensity UL training by robotics and BoNT treatment in patients with UL spastic paresis.

Clinical scales are currently used to assess the rehabilitation treatment effects, but these outcome measures may suffer from some drawbacks that can be overcome by instrumental assessment as subjectivity, limited sensitivity, and the lack of information on the underlying training effects on motor control (). Instrumental assessment, such as surface electromyography (sEMG) during a functional task execution allows assessing abnormal activation of spastic muscles and deficits of voluntary movements in patients with stroke.

Moreover, the hand-to-mouth task is representative of Activities of Daily Life (ADL) such as eating and drinking. Kinematic analysis of the hand-to-mouth task has been widely used to assess UL functions in individuals affected by neurological diseases showing adequate to more than adequate test-retest reliability in healthy subjects (). The task involves flexing the elbow a slightly flexing the shoulder against gravity, and it is considered to be a paradigmatic functional task for the assessment of spasticity and strength deficits on the elbow muscles (). Although sEMG has been reported to be a useful assessment procedure to detect muscle activity improvement after rehabilitation, limited results have been reported ().

The primary aim of this study was to explore the therapeutic synergisms of combined robot-assisted upper limb training and BoNT treatment on upper limb spasticity. The secondary aim was to evaluate the treatment effects on UL function, muscle strength, and the electromyographic activity of UL muscles during a functional task.

The combined treatment would contribute to decrease UL spasticity and improve function through a combination of training effects between BoNT neurolysis and the robotic treatment. A reduction of muscle tone would parallel improvement in muscle strength ought to the high-intensity, repetitive and task-specific robotic training. Since spasticity is associated with abnormal activation of shortening muscles and deficits in voluntary movement of the UL, the sEMG assessment would target these impairments ().

Materials and Methods

Trial Design

A single-blind RCT with two parallel group is reported. The primary endpoint was the changes in UL spasticity while the secondary endpoints were changes in UL function, muscle strength and the electromyographic activity of UL muscles during a functional task. The study was conducted according to the tenets of the Declaration of Helsinki, the guidelines for Good Clinical Practice, and the Consolidated Standards of Reporting Trials (CONSORT), approved by the local Ethics Committee “Nucleo ricerca clinica–Research and Biostatistic Support Unit” (prog n.2366), and registered at clinical trial (NCT03590314).

Patients

Chronic post-stroke patients with upper-limb spasticity referred to the Neurorehabilitation Unit (AOUI Verona) and the Physical Medicine and Rehabilitation Section, “OORR” Hospital (University of Foggia) were assessed for eligibility.

Inclusion criteria were: age > 18 years, diagnosis of ischemic or hemorrhagic first-ever stroke as documented by a computerized tomography scan or magnetic resonance imaging, at least 6 months since stroke, Modified Ashworth Scale (MAS) score (shoulder and elbow) ≤ 3 and ≥1+ (), BoNT injection within the previous 12 weeks of at least one of muscles of the affected upper limb, Mini-Mental State Examination (MMSE) score ≥24 () and Trunk Control Test score = 100/100 ().

Exclusion criteria were: any rehabilitation intervention in the 3 months before recruitment, bilateral cerebrovascular lesion, severe neuropsychologic impairment (global aphasia, severe attention deficit or neglect), joint orthopedic disorders.

All participants were informed regarding the experimental nature of the study. Informed consent was obtained from all subjects. The local ethics committee approved the study.

Interventions

Each patient underwent a BoNT injection in the paretic limb. The dose of BoNT injected into the target muscle was based on the severity of spasticity in each case. Different commercial formulations of BoNT were used according to the pharmaceutical portfolio contracts of our Hospitals (Onabotulinumtoxin A, Abobotulinumtoxin A, and Incobotulinumtoxin A). The dose, volume and number of injection sites were set accordingly. A Logiq ® Book XP portable ultrasound system (GE Healthcare; Chalfont St. Giles, UK) was used to inject BoNT into the target muscle.

Before the start of the study authors designed the experimental (EG) and the control group (CG) protocols. Two physiotherapists, one for each group, carried out the rehabilitation procedures. Patients of both groups received ten individual sessions (45 min/session, two sessions/week, five consecutive weeks). Treatments were performed in the rehabilitative gym of the G. B. Rossi University Hospital Neurological Rehabilitation Unit, or “OORR” Hospital.

Robot-Assisted UL Training

The Robot-assisted UL Training group was treated using the electromechanical device Armotion (Reha Technology, Olten, Switzerland). It is an end-effector device that allows goal-directed arm movements in a bi-dimensional space with visual feedback. It offers different training modalities such as passive, active, passive-active, perturbative, and assistive modes. The robot can move, drive or oppose the patient’s movement and allows creating a personalized treatment, varying parameters such as some repetitions, execution speed, resistance degree of motion. The exercises available from the software are supported by games that facilitate the functional use of the paretic arm (). The robot is equipped with a control system called “impedance control” that modulates the robot movements for adapting to the motor behavior of the patient’s upper limb. The joints involved in the exercises were the shoulder and the elbow, is the wrist fixed to the device.

The Robot-assisted UL Training consisted of passive mobilization and stretching exercises for affected UL (10 min) followed by robot-assisted exercises (35 min). Four types of exercises contained within the Armotion software and amount of repetitions were selected as follows: (i) “Collect the coins” (45–75 coins/10 min), (ii) “Drive the car” (15–25 laps/10 min), (iii) “Wash the dishes” (40–60 repetitions/10 min), and (iv) “Burst the balloons” (100–150 balloons/5 min) (Figure 1). All exercises were oriented to achieving several goals in various directions, emphasizing the elbow flexion-extension and reaching movement. The robot allows participants to execute the exercises through an “assisted as needed” control strategy. For increment the difficulty, we have varied the assisted and non-assisted modality, increasing the number of repetitions over the study period.

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Figure 1
The upper limb robot-assisted training setting.

Conventional Training

The conventional training consisted of UL passive mobilization and stretching (10 min) followed by UL exercises (35 min) that incorporated single or multi-joint movements for the scapula, shoulder, and elbow, performed in different positions (i.e., supine and standing position). The increase of difficulty and progression of intensity were obtained by increasing ROM, repetitions and performing movements against gravity or slight resistance (). Training parameters were recorded on the patient’s log. […]

 

Continue —>  Effectiveness of Robot-Assisted Upper Limb Training on Spasticity, Function and Muscle Activity in Chronic Stroke Patients Treated With Botulinum Toxin: A Randomized Single-Blinded Controlled Trial

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[Abstract + References] Synergy-Based FES for Post-Stroke Rehabilitation of Upper-Limb Motor Functions

Abstract

Functional electrical stimulation (FES) is capable of activating muscles that are under-recruited in neurological diseases, such as stroke. Therefore, FES provides a promising technology for assisting upper-limb motor functions in rehabilitation following stroke. However, the full benefits of FES may be limited due to lack of a systematic approach to formulate the pattern of stimulation. Our preliminary work demonstrated that it is feasible to use muscle synergy to guide the generation of FES patterns.In this paper, we present a methodology of formulating FES patterns based on muscle synergies of a normal subject using a programmable multi-channel FES device. The effectiveness of the synergy-based FES was tested in two sets of experiments. In experiment one, the instantaneous effects of FES to improve movement kinematics were tested in three patients post ischemic stroke. Patients performed frontal reaching and lateral reaching tasks, which involved coordinated movements in the elbow and shoulder joints. The FES pattern was adjusted in amplitude and time profile for each subject in each task. In experiment two, a 5-day session of intervention using synergy-based FES was delivered to another three patients, in which patients performed task-oriented training in the same reaching movements in one-hour-per-day dose. The outcome of the short-term intervention was measured by changes in Fugl–Meyer scores and movement kinematics. Results on instantaneous effects showed that FES assistance was effective to increase the peak hand velocity in both or one of the tasks. In short-term intervention, evaluations prior to and post intervention showed improvements in both Fugl–Meyer scores and movement kinematics. The muscle synergy of patients also tended to evolve towards that of the normal subject. These results provide promising evidence of benefits using synergy-based FES for upper-limb rehabilitation following stroke. This is the first step towards a clinical protocol of applying FES as therapeutic intervention in stroke rehabilitation.

I. Introduction

Muscle activation during movement is commonly disrupted due to neural injuries from stroke. A major challenge for stroke rehabilitation is to re-establish the normal ways of muscle activation through a general restoration of motor control, otherwise impairments may be compensated by the motor system through a substitution strategy of task control [1]. In post-stroke intervention, new technologies such as neuromuscular electrical stimulation (NMES) or functional electrical stimulation (FES) offer advantages for non-invasively targeting specific groups of muscles [2]–[4] to restore the pattern of muscle activation. Nevertheless, their effectiveness is limited by lack of a systematic methodology to optimize the stimulation pattern, to implement the optimal strategy in clinical settings, and to design a protocol of training towards the goal of restoring motor functions. This pioneer study addresses these issues in clinical application with a non-invasive FES technology.

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1. M. F. Levin, J. A. Kleim, and S. L. Wolf, “What do motor ‘recovery’ and ‘compensation’ mean in patients following stroke?” Neurorehabilitation Neural Repair, vol. 23, no. 4, pp. 313–319, 2008.

2. G. Alon, A. F. Levitt, and P. A. McCarthy, “Functional electrical stimulation (FES) may modify the poor prognosis of stroke survivors with severe motor loss of the upper extremity: A preliminary study,” Amer. J. Phys. Med. Rehabil., vol. 87, no. 8, pp. 627–636, 2008.

3. W. Rong, “A neuromuscular electrical stimulation (NMES) and robot hybrid system for multi-joint coordinated upper limb rehabilitation after stroke,” J. Neuroeng. Rehabil., vol. 14, no. 1, p. 34, Dec. 2017.

4. J. J. Daly, “Recovery of coordinated gait: Randomized controlled stroke trial of functional electrical stimulation (FES) versus no FES, with weight-supported treadmill and over-ground training,” Neurorehabilitation Neural Repair, vol. 25, no. 7, pp. 588–596, Sep. 2011.

5. R. Nataraj, M. L. Audu, R. F. Kirsch, and R. J. Triolo, “Comprehensive joint feedback control for standing by functional neuromuscular stimulation—A simulation study,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 18, no. 6, pp. 646–657, Dec. 2010.

6. R. Nataraj, M. L. Audu, and R. J. Triolo, “Restoring standing capabilities with feedback control of functional neuromuscular stimulation following spinal cord injury,” Med. Eng. Phys., vol. 42, pp. 13–25, Apr. 2017.

7. H. Rouhani, M. Same, K. Masani, Y. Q. Li, and M. R. Popovic, “PID controller design for FES applied to ankle muscles in neuroprosthesis for standing balance,” Frontiers Neurosci., vol. 11, p. 347, Jun. 2017.

8. V. K. Mushahwar, P. L. Jacobs, R. A. Normann, R. J. Triolo, and N. Kleitman, “New functional electrical stimulation approaches to standing and walking,” J. Neural Eng., vol. 4, no. 3, pp. S181–S197, Sep. 2007.

9. B. J. Holinski, “Intraspinal microstimulation produces over-ground walking in anesthetized cats,” J. Neural Eng., vol. 13, no. 5, p. 056016, Oct. 2016.

10. M. B. Popovic, D. B. Popovic, T. Sinkjær, A. Stefanovic, and L. Schwirtlich, “Restitution of reaching and grasping promoted by functional electrical therapy,” Artif. Organs, vol. 26, no. 3, pp. 271–275, Mar. 2002.

11. A. B. Ajiboye, “Restoration of reaching and grasping movements through brain-controlled muscle stimulation in a person with tetraplegia: A proof-of-concept demonstration,” Lancet Lond. Engl., vol. 389, no. 10081, pp. 1821–1830, May 2017.

12. J. H. Grill and P. H. Peckham, “Functional neuromuscular stimulation for combined control of elbow extension and hand grasp in C5 and C6 quadriplegics,” IEEE Trans. Rehabil. Eng., vol. 6, no. 2, pp. 190–199, Jun. 1998.

13. M. R. Popovic, T. A. Thrasher, M. E. Adams, V. Takes, V. Zivanovic, and M. I. Tonack, “Functional electrical therapy: Retraining grasping in spinal cord injury,” Spinal Cord, vol. 44, no. 3, pp. 143–151, Mar. 2006.

14. C. Ethier, E. R. Oby, M. J. Bauman, and L. E. Miller, “Restoration of grasp following paralysis through brain-controlled stimulation of muscles,” Nature, vol. 485, no. 7398, pp. 368–371, May 2012.

15. G. Alon, “Use of neuromuscular electrical stimulation in neureorehabilitation: A challenge to all,” J. Rehabil. Res. Develop., vol. 40, no. 6, pp. 9–12, Dec. 2003.

16. G. Alon, A. F. Levitt, and P. A. McCarthy, “Functional electrical stimulation enhancement of upper extremity functional recovery during stroke rehabilitation: A pilot study,” Neurorehabilitation Neural Repair, vol. 21, no. 3, pp. 207–215, Jun. 2007.

17. C. Church, C. Price, A. D. Pandyan, S. Huntley, R. Curless, and H. Rodgers, “Randomized controlled trial to evaluate the effect of surface neuromuscular electrical stimulation to the shoulder after acute stroke,” Stroke, vol. 37, no. 12, pp. 2995–3001, Dec. 2006.

18. J. H. Cauraugh and S. B. Kim, “Chronic stroke motor recovery: Duration of active neuromuscular stimulation,” J. Neurolog. Sci., vol. 215, nos. 1–2, pp. 13–19, Nov. 2003.

19. S. Ferrante, T. Schauer, G. Ferrigno, J. Raisch, and F. Molteni, “The effect of using variable frequency trains during functional electrical stimulation cycling,” Neuromodulation, Technol. Neural Interface, vol. 11, no. 3, pp. 216–226, Jul. 2008.

20. R. W. Fields, “Electromyographically triggered electric muscle stimulation for chronic hemiplegia,” Arch. Phys. Med. Rehabil., vol. 68, no. 7, pp. 407–414, Jul. 1987.

21. G. H. Kraft, S. S. Fitts, and M. C. Hammond, “Techniques to improve function of the arm and hand in chronic hemiplegia,” Arch. Phys. Med. Rehabil., vol. 73, no. 3, pp. 220–227, Mar. 1992.

22. G. van Overeem Hansen, “EMG-controlled functional electrical stimulation of the paretic hand,” Scand. J. Rehabil. Med., vol. 11, no. 4, pp. 189–193, 1979.

23. J. H. Cauraugh, S. B. Kim, and A. Duley, “Coupled bilateral movements and active neuromuscular stimulation: Intralimb transfer evidence during bimanual aiming,” Neurosci. Lett., vol. 382, nos. 1–2, pp. 39–44, Jul. 2005.

24. J. S. Knutson, D. D. Gunzler, R. D. Wilson, and J. Chae, “Contralaterally controlled functional electrical stimulation improves hand dexterity in chronic hemiparesis: A randomized trial,” Stroke, vol. 47, no. 10, pp. 2596–2602, Oct. 2016.

25. D. A. E. Bolton, J. H. Cauraugh, and H. A. Hausenblas, “Electromyogram-triggered neuromuscular stimulation and stroke motor recovery of arm/hand functions: A meta-analysis,” J. Neurol. Sci., vol. 223, no. 2, pp. 121–127, Aug. 2004.

26. M. K.-L. Chan, R. K.-Y. Tong, and K. Y.-W. Chung, “Bilateral upper limb training with functional electric stimulation in patients with chronic stroke,” Neurorehabilitation Neural Repair, vol. 23, no. 4, pp. 357–365, May 2009.

27. J. B. Manigandan, G. S. Ganesh, M. Pattnaik, and P. Mohanty, “Effect of electrical stimulation to long head of biceps in reducing gleno humeral subluxation after stroke,” Neuro Rehabil., vol. 34, no. 2, pp. 245–252, 2014.

28. S. Li, C. Zhuang, C. M. Niu, Y. Bao, Q. Xie, and N. Lan, “Evaluation of functional correlation of task-specific muscle synergies with motor performance in patients poststroke,” Frontiers Neurol., vol. 8, p. 337, Jul. 2017.

29. A. d’Avella, P. Saltiel, and E. Bizzi, “Combinations of muscle synergies in the construction of a natural motor behavior,” Nature Neurosci., vol. 6, no. 3, pp. 300–308, Mar. 2003.

30. V. C. K. Cheung, “Muscle synergy patterns as physiological markers of motor cortical damage,” Proc. Nat. Acad. Sci. USA, vol. 109, no. 36, pp. 14652–14656, Sep. 2012.

31. D. J. Clark, L. H. Ting, F. E. Zajac, R. R. Neptune, and S. A. Kautz, “Merging of healthy motor modules predicts reduced locomotor performance and muscle coordination complexity post-stroke,” J. Neurophysiol., vol. 103, no. 2, pp. 844–857, Feb. 2010.

32. E. Ambrosini, “Neuro-mechanics of recumbent leg cycling in post-acute stroke patients,” Ann. Biomed. Eng., vol. 44, pp. 3238–3251, Jun. 2016.

33. C. Zhuang, J. C. Marquez, H. E. Qu, X. He, and N. Lan, “A neuromuscular electrical stimulation strategy based on muscle synergy for stroke rehabilitation,” in Proc. IEEE 7th Int./EMBS Conf. Neural Eng. (NER), vol. 15, Apr. 2015, pp. 816–819.

34. R. S. Razavian, B. Ghannadi, N. Mehrabi, M. Charlet, and J. McPhee, “Feedback control of functional electrical stimulation for 2-D arm reaching movements,” IEEE Trans. Neural Syst. Rehabil. Eng., vol. 26, no. 10, pp. 2033–2043, Oct. 2018.

35. C. M. Niu, C. Zhuang, Y. Bao, S. Li, N. Lan, and Q. Xie, “Synergy-based NMES intervention accelerated rehabilitation of post-stroke hemiparesis,” in Proc. Assoc. Acad. Physiatrists Annu. Conf., Las Vegas, NV, USA, 2017.

36. H. Qu, “Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation,” J. Rehabil. Res. Develop., vol. 52, no. 3, pp. 263–278, 2016.

37. C. M. Niu, “Effectiveness of short-term training with a synergy-based FES paradigm on motor function recovery post stroke,” in Proc. 12th Int. Soc. Phys. Rehabil. Med. World Congr., Paris, France, 2018.

38. T. Wang, “Customization of synergy-based FES for post-stroke rehabilitation of upper-limb motor functions,” in Proc. IEEE 40th Annu. Int. Conf. Eng. Med. Biol. Soc. (EMBS), Jul. 2018, 3541–3544.

39. L. L. Baker, D. R. McNeal, L. A. Benton, B. R. Bowman, and R. L. Waters, Ed., Neuromuscular Electrical Stimulation a Practical Guide, 4th ed. Downey, CA, USA: Los Amigos Research & Education Institute, 2000.

40. A. d’Avella, A. Portone, L. Fernandez, and F. Lacquaniti, “Control of fast-reaching movements by muscle synergy combinations.,” J. Neurosci., vol. 26, no. 30, pp. 7791–7810, Jul. 2006.

41. R. D. Wilson, “Upper-limb recovery after stroke: A randomized controlled trial comparing EMG-triggered, cyclic, and sensory electrical stimulation,” Neurorehabilitation Neural Repair, vol. 30, no. 10, pp. 978–987, Nov. 2016.

42. A. J. Levine, “Identification of a cellular node for motor control pathways,” Nature Neurosci., vol. 17, no. 4, pp. 586–593, Apr. 2014.

43. S. B. Frost, S. Barbay, K. M. Friel, E. J. Plautz, and R. J. Nudo, “Reorganization of remote cortical regions after ischemic brain injury: A potential substrate for stroke recovery,” J. Neurophysiol., vol. 89, no. 6, pp. 3205–3214, Jun. 2003.

44. P. Langhorne, J. Bernhardt, and G. Kwakkel, “Stroke rehabilitation,” Lancet, vol. 377, no. 9778, pp. 1693–1702, May 2011.

45. M. D. Ellis, B. G. Holubar, A. M. Acosta, R. F. Beer, and J. P. A. Dewald, “Modifiability of abnormal isometric elbow and shoulder joint torque coupling after stroke,” Muscle Nerve, vol. 32, pp. 170–178, Aug. 2005.

46. J. P. A. Dewald, P. S. Pope, J. D. Given, T. S. Buchanan, and W. Z. Rymer, “Abnormal muscle coactivation patterns during isometric torque generation at the elbow and shoulder in hemiparetic subjects,” Brain, vol. 118, no. 2, pp. 495–510, 1995.

47. D. G. Kamper, A. N. McKenna-Cole, L. E. Kahn, and D. J. Reinkensmeyer, “Alterations in reaching after stroke and their relation to movement direction and impairment severity,” Arch. Phys. Med. Rehabil., vol. 83, no. 5, pp. 702–707, May 2002.

48. C. L. Massie, S. Fritz, and M. P. Malcolm, “Elbow extension predicts motor impairment and performance after stroke,” Rehabil. Res. Pract., vol. 2011, pp. 1–7, 2011.

49. V. C. K. Cheung, L. Piron, M. Agostini, S. Silvoni, A. Turolla, and E. Bizzi, “Stability of muscle synergies for voluntary actions after cortical stroke in humans,” Proc. Nat. Acad. Sci. USA, vol. 106, no. 46, pp. 19563–19568, Nov. 2009.

50. J. Roh, W. Z. Rymer, and R. F. Beer, “Robustness of muscle synergies underlying three-dimensional force generation at the hand in healthy humans,” J. Neurophysiol., vol. 107, no. 8, pp. 2123–2142, Apr. 2012.

51. J. Roh, W. Z. Rymer, and R. F. Beer, “Evidence for altered upper extremity muscle synergies in chronic stroke survivors with mild and moderate impairment,” Frontiers Hum. Neurosci., vol. 9, p. 6, Feb. 2015.

52. J. Roh, W. Z. Rymer, E. J. Perreault, S. B. Yoo, and R. F. Beer, “Alterations in upper limb muscle synergy structure in chronic stroke survivors,” J. Neurophysiol., vol. 109, no. 3, pp. 768–781, Feb. 2013.

53. W. H. Backes, W. H. Mess, V. van Kranen-Mastenbroek, and J. P. H. Reulen, “Somatosensory cortex responses to median nerve stimulation: fMRI effects of current amplitude and selective attention,” Clin. Neurophysiol., vol. 111, no. 10, pp. 1738–1744, Oct. 2000.

54. G. Francisco, “Electromyogram-triggered neuromuscular stimulation for improving the arm function of acute stroke survivors: A randomized pilot study,” Arch. Phys. Med. Rehabil., vol. 79, no. 5, pp. 570–575, May 1998.

55. S. K. Sabut, C. Sikdar, R. Kumar, and M. Mahadevappa, “Functional electrical stimulation of dorsiflexor muscle: Effects on dorsiflexor strength, plantarflexor spasticity, and motor recovery in stroke patients,” Neurorehabilitation, vol. 29, no. 4, pp. 393–400, 2011.

56. Y.-H. Wang, F. Meng, Y. Zhang, M.-Y. Xu, and S.-W. Yue, “Full-movement neuromuscular electrical stimulation improves plantar flexor spasticity and ankle active dorsiflexion in stroke patients: A randomized controlled study,” Clin. Rehabil., vol. 30, no. 6, pp. 577–586, Jun. 2016.

57. W. H. Chang and Y.-H. Kim, “Robot-assisted therapy in stroke rehabilitation,” J. Stroke, vol. 15, no. 3, p. 174, 2013.

58. H. G. Wu, Y. R. Miyamoto, L. N. G. Castro, B. P. Ölveczky, and M. A. Smith, “Temporal structure of motor variability is dynamically regulated and predicts motor learning ability,” Nature Neurosci., vol. 17, no. 2, pp. 312–321, Jan. 2014.

59. J. Frère and F. Hug, “Between-subject variability of muscle synergies during a complex motor skill,” Frontiers Comput. Neurosci., vol. 6, p. 99, Dec. 2012.

60. S. Muceli, A. T. Boye, A. d’Avella, and D. Farina, “Identifying representative synergy matrices for describing muscular activation patterns during multidirectional reaching in the horizontal plane,” J. Neurophysiol., vol. 103, no. 3, pp. 1532–1542, Mar. 2010.

61. J. F. Soechting and F. Lacquaniti, “Invariant characteristics of a pointing movement in man,” J. Neurosci., vol. 1, no. 7, pp. 710–720, Jul. 1981.

62. B. Cesqui, A. d’Avella, A. Portone, and F. Lacquaniti, “Catching a ball at the right time and place: Individual factors matter,” PLoS ONE, vol. 7, no. 2, p. e31770, Feb. 2012.

 

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[Abstract] How effective is physical therapy for gait muscle activity in hemiparetic patients who receive botulinum toxin injections?

Abstract

BACKGROUND: Administration of botulinum neurotoxin A (BoNT-A) to the ankle plantar flexors in patients with hemiplegia reduces the strength of knee extension, which may decrease their walking ability. Studies have reported improvements in walking ability with physical therapy following BoNT-A administration. However, no previous studies have evaluated from an exercise physiology perspective the efficacy of physical therapy after BoNT-A administration for adult patients with hemiplegia.

AIM: To investigate the effects of physical therapy following BoNT-A administration on gait electromyography for patients with hemiparesis secondary to stroke.

DESIGN: Non-randomized controlled trial.

SETTING: Single center.

POPULATION: Thirty-five patients with chronic stroke with spasticity were assigned to BoNT-A monotherapy (N.=18) or BoNT-A plus physical therapy (PT) (N.=17).

METHODS: On the paralyzed side of the body, 300 single doses of BoNT-A were administered intramuscularly to the ankle plantar flexors. Physical therapy was performed for 2 weeks, starting from the day after administration. Gait electromyography was performed and gait parameters were measured immediately before and 2 weeks after BoNT-A administration. Relative muscle activity, coactivation indices, and walking time/distance were calculated for each phase.

RESULTS: For patients who received BoNT-A monotherapy, soleus activity during the loading response decreased 2 weeks after the intervention (P<0.01). For those who received BoNT-A+PT, biceps femoris activity and knee coactivation index during the loading response and tibialis anterior activity during the pre-swing phases increased, whereas soleus and rectus femoris activities during the swing phase decreased 2 weeks after the intervention (P<0.05). These rates of change were significantly greater than those for patients who received BoNT-A monotherapy (P<0.05).
CONCLUSIONS: Following BoNT-A monotherapy, soleus activity during the stance phase decreased and walking ability either remained unchanged or deteriorated. Following BoNT-A+PT, muscle activity and knee joint stability increased during the stance phase, and abnormal muscle activity during the swing phase was suppressed.

CLINICAL REHABILITATION IMPACT: If botulinum treatment of the ankle plantar flexors in stroke patients is targeted to those with low knee extension strength, or if it aims to improve leg swing on the paralyzed side of the body, then physical therapy following BoNT-A administration could be an essential part of the treatment strategy.

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via How effective is physical therapy for gait muscle activity in hemiparetic patients who receive botulinum toxin injections? – European Journal of Physical and Rehabilitation Medicine 2019 February;55(1):8-18 – Minerva Medica – Journals

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