Spike ripples in striatum correlate with seizure risk in two mouse models.

6-OHDA, 6-hydroxydopamine Basal ganglia EEG biomarker EEG, electroencephalogram Epilepsy HFO, high frequency oscillation HFOs IEDs LFP, local field potential Spike-ripple

Journal

Epilepsy & behavior reports
ISSN: 2589-9864
Titre abrégé: Epilepsy Behav Rep
Pays: United States
ID NLM: 101750909

Informations de publication

Date de publication:
2022
Historique:
received: 06 12 2021
revised: 21 01 2022
accepted: 05 02 2022
entrez: 11 3 2022
pubmed: 12 3 2022
medline: 12 3 2022
Statut: epublish

Résumé

Epilepsy biomarkers from electroencephalogram recordings are routinely used to assess seizure risk and localization. Two widely adopted biomarkers include: (i) interictal spikes, and (ii) high frequency ripple oscillations. The combination of these two biomarkers, ripples co-occurring with spikes (spike ripples), has been proposed as an improved biomarker for the epileptogenic zone and epileptogenicity in humans and rodent models. Whether spike ripples translate to predict seizure risk in rodent seizure models is unknown. Further, recent evidence suggests ictal networks can include deep gray nuclei in humans. Whether pathologic spike ripples and seizures are also observed in the basal ganglia in rodent models has not been explored. We addressed these questions using local field potential recordings from mice with and without striatal seizures after carbachol or 6-hydroxydopamine infusions into the striatum. We found increased spike ripples in the interictal and ictal periods in mice with seizures compared to pre-infusion and post-infusion seizure-free recordings. These data provide evidence of electrographic seizures involving the striatum in mice and support the candidacy of spike ripples as a translational biomarker for seizure risk in mouse models.

Identifiants

pubmed: 35274094
doi: 10.1016/j.ebr.2022.100529
pii: S2589-9864(22)00006-5
pmc: PMC8902602
doi:

Types de publication

Journal Article

Langues

eng

Pagination

100529

Subventions

Organisme : NINDS NIH HHS
ID : R01 NS115797
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS119483
Pays : United States

Informations de copyright

© 2022 The Authors.

Déclaration de conflit d'intérêts

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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Auteurs

Wen Shi (W)

Department of Neurology, Massachusetts General Hospital, Boston, MA, United States.
Harvard Medical School, Boston, MA, United States.

Dana Zemel (D)

Department of Biomedical Engineering, Boston University, Boston, MA, United States.

Sudiksha Sridhar (S)

Department of Biomedical Engineering, Boston University, Boston, MA, United States.

Rebecca A Mount (RA)

Department of Biomedical Engineering, Boston University, Boston, MA, United States.

R Mark Richardson (RM)

Harvard Medical School, Boston, MA, United States.
Department of Neurosurgery, Massachusetts General Hospital, Boston, MA, United States.

Uri T Eden (UT)

Department of Mathematics and Statistics, Boston University, Boston, MA, United States.

Xue Han (X)

Department of Biomedical Engineering, Boston University, Boston, MA, United States.

Mark A Kramer (MA)

Department of Mathematics and Statistics, Boston University, Boston, MA, United States.

Catherine J Chu (CJ)

Department of Neurology, Massachusetts General Hospital, Boston, MA, United States.
Harvard Medical School, Boston, MA, United States.

Classifications MeSH