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Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks.

ABSTRACT: Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highlight how major advances in neuroscience tool development now enable multi-scale investigation of fundamental questions to resolve the currently controversial understanding of seizure networks. These findings will provide essential insight into what has emerged as a disconnect between the different levels of investigation and identify new targets and treatment options.

SUBMITTER: Farrell JS

PROVIDER: S-EPMC6430140 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks.

Farrell Jordan S JS Nguyen Quynh-Anh QA Soltesz Ivan I

Neuron 20190301 6

Current drug treatments for epilepsy attempt to broadly restrict excitability to mask a symptom, seizures, with little regard for the heterogeneous mechanisms that underlie disease manifestation across individuals. Here, we discuss the need for a more complete view of epilepsy, outlining how key features at the cellular and microcircuit level can significantly impact disease mechanisms that are not captured by the most common methodology to study epilepsy, electroencephalography (EEG). We highli ...[more]

PMID: 30897354

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Project description:The application of non-linear signal analysis techniques to biomedical data is key to improve our knowledge about complex physiological and pathological processes. In particular, the use of non-linear techniques to study electroencephalographic (EEG) recordings can provide an advanced characterization of brain dynamics. In epilepsy these dynamics are altered at different spatial scales of neuronal organization. We therefore apply non-linear signal analysis to EEG recordings from epilepsy patients derived with intracranial hybrid electrodes, which are composed of classical macro contacts and micro wires. Thereby, these electrodes record EEG at two different spatial scales. Our aim is to test the degree to which the analysis of the EEG recorded at these different scales allows us to characterize the neuronal dynamics affected by epilepsy. For this purpose, we retrospectively analyzed long-term recordings performed during five nights in three patients during which no seizures took place. As a benchmark we used the accuracy with which this analysis allows determining the hemisphere that contains the seizure onset zone, which is the brain area where clinical seizures originate. We applied the surrogate-corrected non-linear predictability score (ψ), a non-linear signal analysis technique which was shown previously to be useful for the lateralization of the seizure onset zone from classical intracranial EEG macro contact recordings. Higher values of ψ were found predominantly for signals recorded from the hemisphere containing the seizure onset zone as compared to signals recorded from the opposite hemisphere. These differences were found not only for the EEG signals recorded with macro contacts, but also for those recorded with micro wires. In conclusion, the information obtained from the analysis of classical macro EEG contacts can be complemented by the one of micro wire EEG recordings. This combined approach may therefore help to further improve the degree to which quantitative EEG analysis can contribute to the diagnostics in epilepsy patients.

Dataset Information

Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks.

Publications

Resolving the Micro-Macro Disconnect to Address Core Features of Seizure Networks.

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