Antiepileptic Therapy Reduces Coupling Strength Among Brain Cortical Regions in Patients with Unverricht–Lundborg Disease: A Pilot Study

  • Chang-Chia Liu
  • Petros Xanthopoulos
  • Vera Tomaino
  • Kazutaka Kobayashi
  • Basim M. Uthman
  • Panos M. Pardalos
Part of the Springer Optimization and Its Applications book series (SOIA, volume 38)


The unified myoclonus rating scale (UMRS) has been utilized to assess the severity of myoclonus and the efficacy of antiepileptic drug (AED) treatment in patients with Unverricht–Lundborg disease (ULD). Electroencephalographic (EEG) recordings are normally used as a supplemental tool for the diagnosis of epilepsy disorders. In this study, mutual information and nonlinear interdependence measures were applied to the EEG recordings in an attempt to identify the effect of treatment on the coupling strength and directionality of mutual information and nonlinear interdependences between different brain cortical regions. Two 1-h EEG recordings were acquired from four ULD subjects; one prior and one after a minimum of 2 months treatment with an add-on AED. Subjects in this study were siblings of same parents and suffered from ULD for approximately 37 years. Our results indicated that the coupling strength was low between different brain cortical regions in the patients with disease of less severity. Adjunctive AED treatment was associated with significant decrease of the coupling strength in all subjects. The mutual information between different brain cortical regions was also reduced after treatment. These findings could provide a new insight for developing a novel surrogate outcome measure for patients with epilepsy when clinical tools or observations could potentially fail to detect a significant difference.


Nonlinear interdependence Mutual information Electroencephalogram epilepsy Unverricht–Lundborg disease Progressive myoclonic epilepsy 



This work was partially supported by North Florida Foundation for Research and Education, Inc. North Florida/South Georgia Veterans Health System 1601 SW Archer Rd. (151), Gainesville, FL 32608.


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© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.J. Crayton Pruitt Family Department of Biomedical EngineeringUniversity of FloridaGainesvilleUSA
  2. 2.Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA
  3. 3.Bioinformatics Laboratory, Experimental and Clinical Medicine DepartmentMagna Graecia UniversityCatanzaroItaly
  4. 4.Department of Industrial and Systems EngineeringUniversity of Florida, Center for Applied OptimizationGainesvilleUSA
  5. 5.Department of Neurological SurgeryNihon University School of MedicineTokyoJapan
  6. 6.Division of Applied System Neuroscience, Department of Advanced Medical ScienceNihon University School of MedicineTokyoJapan
  7. 7.Department of NeurologyUniversity of FloridaGainesvilleUSA
  8. 8.Department of NeuroscienceUniversity of FloridaGainesvilleUSA
  9. 9.The Evelyn F. and William L. McKnight Brain InstituteUniversity of FloridaGainesvilleUSA
  10. 10.Neurology Services, North Florida/South Georgia Veterans Health SystemGainesvilleUSA
  11. 11.Department of Industrial and Systems EngineeringUniversity of FloridaGainesvilleUSA
  12. 12.J. Crayton Pruitt Family Department of Biomedical EngineeringUniversity of FloridaGainesvilleUSA
  13. 13.The Evelyn F. and William L. McKnight Brain InstituteUniversity of FloridaGainesvilleUSA

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