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Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F23%3A00573600" target="_blank" >RIV/67985807:_____/23:00573600 - isvavai.cz</a>

  • Alternative codes found

    RIV/00023752:_____/23:43921110 RIV/00216208:11130/23:10465216

  • Result on the web

    <a href="https://doi.org/10.1111/epi.17690" target="_blank" >https://doi.org/10.1111/epi.17690</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1111/epi.17690" target="_blank" >10.1111/epi.17690</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Personalized dynamic network models of the human brain as a future tool for planning and optimizing epilepsy therapy

  • Original language description

    Epilepsy is a common neurological disorder, with one third of patients not responding to currently available antiepileptic drugs. The proportion of pharmacoresistant epilepsies has remained unchanged for many decades. To cure epilepsy and control seizures requires a paradigm shift in the development of new approaches to epilepsy diagnosis and treatment. Contemporary medicine has benefited from the exponential growth of computational modeling, and the application of network dynamics theory to understanding and treating human brain disorders. In epilepsy, the introduction of these approaches has led to personalized epileptic network modeling that can explore the patient's seizure genesis and predict the functional impact of resection on its individual network's propensity to seize. The application of the dynamic systems approach to neurostimulation therapy of epilepsy allows designing stimulation strategies that consider the patient's seizure dynamics and long-term fluctuations in the stability of their epileptic networks. In this article, we review, in a nontechnical fashion suitable for a broad neuroscientific audience, recent progress in personalized dynamic brain network modeling that is shaping the future approach to the diagnosis and treatment of epilepsy.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    30103 - Neurosciences (including psychophysiology)

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2023

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Epilepsia

  • ISSN

    0013-9580

  • e-ISSN

    1528-1167

  • Volume of the periodical

    64

  • Issue of the periodical within the volume

    9

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    18

  • Pages from-to

    2221-2238

  • UT code for WoS article

    001024598000001

  • EID of the result in the Scopus database

    2-s2.0-85164598407