Literature DB >> 27562603

Quantifying antiepileptic drug effects using intrinsic excitability measures.

Christian Meisel1,2, Dietmar Plenz1, Andreas Schulze-Bonhage3, Heinz Reichmann2.   

Abstract

Pathologic increases in excitability levels of cortical tissue commonly underlie the initiation and spread of seizure activity in patients with epilepsy. By reducing the excitability levels in neural tissue, antiepileptic drug (AED) pharmacotherapy aims to reduce seizure severity and frequency. However, AEDs may also bring about adverse effects, which have been reported to increase with higher AED load. Measures that monitor the dose-dependent effects of AEDs on cortical tissue and quantify its excitability level are therefore of prime importance for efficient clinical care and treatment but have been difficult to identify. Here, we systematically analyze continuous multiday electrocorticography (ECoG) data from 10 patients under different levels of AED load and derive the recently proposed intrinsic excitability measures (IEMs) from different brain regions and across different frequency bands. We find that IEMs are significantly negatively correlated with AED load (prescribed daily dose/defined daily dose). Furthermore, we demonstrate that IEMs derived from different brain regions can robustly capture global changes in the degree of excitability. These results provide a step toward the ultimate goal of developing a reliable quantitative measure of central physiologic effects of AEDs in patients with epilepsy. Wiley Periodicals, Inc.
© 2016 International League Against Epilepsy.

Entities:  

Keywords:  Antiepileptic drug; Biomarker; Epilepsy; Excitability

Mesh:

Substances:

Year:  2016        PMID: 27562603     DOI: 10.1111/epi.13517

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  7 in total

1.  Playing soft, with tough players: Controlling adverse drug effects while tuning antiepileptic drugs, epilepsy & the person.

Authors:  Dejan Stevanovic
Journal:  Indian J Med Res       Date:  2017-03       Impact factor: 2.375

2.  Seizure pathways change on circadian and slower timescales in individual patients with focal epilepsy.

Authors:  Gabrielle M Schroeder; Beate Diehl; Fahmida A Chowdhury; John S Duncan; Jane de Tisi; Andrew J Trevelyan; Rob Forsyth; Andrew Jackson; Peter N Taylor; Yujiang Wang
Journal:  Proc Natl Acad Sci U S A       Date:  2020-05-04       Impact factor: 11.205

3.  Early detection rate changes from a brain-responsive neurostimulation system predict efficacy of newly added antiseizure drugs.

Authors:  Imran H Quraishi; Michael R Mercier; Tara L Skarpaas; Lawrence J Hirsch
Journal:  Epilepsia       Date:  2019-12-17       Impact factor: 5.864

Review 4.  Criticality, Connectivity, and Neural Disorder: A Multifaceted Approach to Neural Computation.

Authors:  Kristine Heiney; Ola Huse Ramstad; Vegard Fiskum; Nicholas Christiansen; Axel Sandvig; Stefano Nichele; Ioanna Sandvig
Journal:  Front Comput Neurosci       Date:  2021-02-10       Impact factor: 2.380

5.  Critical dynamics in the spread of focal epileptic seizures: Network connectivity, neural excitability and phase transitions.

Authors:  S Amin Moosavi; Viktor K Jirsa; Wilson Truccolo
Journal:  PLoS One       Date:  2022-08-23       Impact factor: 3.752

6.  Maintained avalanche dynamics during task-induced changes of neuronal activity in nonhuman primates.

Authors:  Shan Yu; Tiago L Ribeiro; Christian Meisel; Samantha Chou; Andrew Mitz; Richard Saunders; Dietmar Plenz
Journal:  Elife       Date:  2017-11-08       Impact factor: 8.140

7.  Seizure pathways: A model-based investigation.

Authors:  Philippa J Karoly; Levin Kuhlmann; Daniel Soudry; David B Grayden; Mark J Cook; Dean R Freestone
Journal:  PLoS Comput Biol       Date:  2018-10-11       Impact factor: 4.475

  7 in total

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