Mouse strain variation in maximal electroshock seizure threshold

Thomas N. Ferraro, Gregory T. Golden, George G. Smith, Denis DeMuth, Russell J. Buono, Wade H. Berrettini

Research output: Contribution to journalArticlepeer-review

48 Scopus citations

Abstract

Maximal electroshock seizure threshold (MEST) is a classical measure of seizure sensitivity with a wide range of experimental applications. We determined MEST in nine inbred mouse strains and one congenic strain using a procedure in which mice are given one shock per day with an incremental (1 mA) current increase in each successive trial until a maximal seizure (tonic hindlimb extension) is elicited. C57BL/6J and DBA/2J mice exhibited the highest and lowest MEST, respectively, with the values of other strains falling between these two extremes. The relative rank order of MEST values by inbred strain (highest to lowest) is as follows: C57BL/6J>CBA/J=C3H/HeJ>A/J>Balb/cJ=129/SvIMJ=129/SvJ>AKR/ J>DBA/2J. Results of experiments involving a single electroconvulsive shock given to separate groups of mice at different current intensities suggest that determination of MEST by the method used is not affected by repeated sub-maximal seizures. Overall, results document a distinctive mouse strain distribution pattern for MEST. Additionally, low within strain variability suggests that environmental factors which affect quantification of MEST are readily controlled under the conditions of this study. We conclude that MEST represents a useful tool for dissecting the multifactorial nature of seizure sensitivity in mice.

Original languageEnglish (US)
Pages (from-to)82-86
Number of pages5
JournalBrain Research
Volume936
Issue number1-2
DOIs
StatePublished - May 17 2002
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Neuroscience(all)
  • Molecular Biology
  • Clinical Neurology
  • Developmental Biology

Fingerprint

Dive into the research topics of 'Mouse strain variation in maximal electroshock seizure threshold'. Together they form a unique fingerprint.

Cite this