Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Randomization tests: application to single-cell and other single-unit neuroscience experiments

E S Edgington1, B H Bland

  • 1Department of Psychology, University of Calgary, Alberta, Canada.

Journal of Neuroscience Methods
|May 1, 1993
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Posterior hypothalamic nucleus deep brain stimulation restores locomotion in rats with haloperidol-induced akinesia but not skilled forelimb use in pellet reaching and lever pressing.

Neuroscience·2011
Same author

Deep brain stimulation of the posterior hypothalamic nucleus reverses akinesia in bilaterally 6-hydroxydopamine-lesioned rats.

Neuroscience·2009
Same author

To move or not: previous experience in a runway avoidance task determines the appearance of hippocampal Type 2 sensory processing theta.

Behavioural brain research·2007
Same author

Theta band oscillation and synchrony in the hippocampal formation and associated structures: the case for its role in sensorimotor integration.

Behavioural brain research·2001
Same author

[Basic micro-electrophysiologic techniques used in neurobiology].

Postepy higieny i medycyny doswiadczalnej·2000
Same author

Hippocampal theta-related cellular activity in the superior colliculus of the urethane-anesthetized rat.

Hippocampus·1999

Randomization tests offer a valid statistical approach for neuroscience single-unit data, overcoming limitations of traditional parametric tests. These computer-aided methods are now accessible and crucial for accurate experimental significance determination.

Area of Science:

  • Neuroscience
  • Statistics
  • Computational Biology

Background:

  • Parametric statistical tests like ANOVA and t-tests face validity criticisms when applied to single-unit neuroscience data.
  • These criticisms extend to parametric tests used for single-subject and other single-unit experimental data.
  • Randomization tests provide a statistically sound alternative, free from these validity concerns.

Purpose of the Study:

  • To describe the application of randomization tests for determining the statistical significance of experimental manipulations in neuroscience.
  • To highlight the advantages of randomization tests over traditional parametric tests for single-unit data.
  • To provide information on accessing readily available computer programs for randomization tests.

Main Methods:

Related Experiment Videos

  • Utilizing randomization tests for statistical analysis of single-unit data in neuroscience.
  • Addressing the computational demands of randomization tests through modern computer programs.
  • Demonstrating the application of these tests to various single-unit experimental designs.

    • Main Results:

    • Randomization tests have proven valuable and valid for analyzing single-unit neuroscience data, especially when random sampling is absent.
    • The computational barriers to using randomization tests have been overcome with the availability of computer programs.
    • Public domain programs for randomization tests are now accessible, facilitating their widespread adoption.

    Conclusions:

    • Randomization tests are a robust and valid statistical methodology for neuroscience research involving single-unit data.
    • The accessibility of computational tools makes randomization tests a practical choice for researchers.
    • Adopting randomization tests enhances the reliability of statistical significance determination in neuroscience experiments.