In Vivo Neuroscience Toolkit

This toolkit gives in vivo neuroscientists practical steps for strengthening credibility before, during and after a study. It focuses on actions that improve study design, reduce bias, support animal welfare and make methods and data easier for others to understand. 
Planning your study

Study design and power 

A correctly powered study is essential for a credible project and ethically important when using animals. The NC3Rs Experimental Design Assistant is a useful starting point because it helps researchers build an experimental plan, consider statistical analysis, randomisation and blinding, and produce a shareable plan that can support transparency and preregistration. 

Where possible, build blinding into both data collection and analysis, particularly when the experimenter is involved in judging an endpoint. Consider power alongside the groups required for the experiment, including sex, litters, controls and age.

Use male and female animals where possible 

Studies should use both sexes wherever possible unless there is a robust justification not to do so. Including both sexes gives a fuller view of biology and can reduce the waste of animals. When female animals are used, the stage of cycle should be considered and reported where relevant, with assessment made on the day of testing after the experiment has concluded. 

Use animals from several litters 

Experimental cohorts should be derived from a variety of litters and randomised appropriately. This helps control for environmental or genetic factors within individual litters that may affect outcomes. In some studies, litter should also be included as a factor in the analysis. Block designs can be useful where variation needs to be introduced in a controlled way to improve generalisability. 

Use the correct control groups

Control groups are especially important when working with genetically modified animals. Knock-out studies should use the corresponding wild-type littermate control. Conditional knock-out studies should also consider the LoxP-ready line alone and the Cre-driver line alone, because a Cre line may already have a phenotype. 

Consider animal age 

Brain and behaviour change with age, as do other aspects of physiology. Design long-term experiments with this in mind and report accurately the age at which each test was conducted. 

Preregister the study 

Preregistering a time-stamped research plan before starting the study can reduce bias and build confidence in the work. The preregistration should clearly state the rationale, hypotheses, methods and intended statistical analysis. All-purpose registries such as OSF can be used, and in vivo researchers may also consider the Animal Study Registry. 

These videos are taken from BNA webinars on credibility and will explain these processes in more detail.

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During your study:

Manage data consistently 

A data management plan should describe how raw data, processed data, notes and analysis files will be stored, named and protected. Retain raw data so that future errors in processing or analysis can be traced back to source. A lab-wide approach to data gathering can improve continuity when staff move on and can make data easier to share later. 

Know and report genetic background 

The genetic background of rodents can affect phenotype and should be known, maintained and reported. When starting a new colony, source animals from a trusted supplier. For established in-house colonies, routine genotyping can help identify drift from the original background over successive breeding generations. 

Handle rodents carefully 

Handling can affect animal welfare and scientific outcomes, especially in behavioural studies. Non-stressful handling methods should be used. Researchers should also minimise day-to-day experimenter differences, including differences in glove type, deodorant, perfume and other olfactory cues. 

Consider circadian rhythms and light 

Rodent physiology and behaviour are guided by circadian rhythms. Experiments should be conducted at similar and well-considered times of day, and studies should avoid spanning a light change where possible. Data collected during the dark phase, when animals are naturally awake, may be more robust for some outcomes. 

After data collection:

Use ARRIVE when reporting 

The ARRIVE guidelines are designed to improve reporting of research involving animals. The updated guidance includes the Essential 10, a core set of information needed to help readers and reviewers assess reliability, methods and findings. 

Share data where appropriate 

Sharing in vivo data through an online repository can make datasets secure, citable and accessible in the long term. It can also support future meta-analysis and secondary use. Suitable repositories may include NeuroMorpho, figshare, Dryad or another repository appropriate to the data type and funder requirements. 

These videos are taken from BNA webinars on credibility and will explain these processes in more detail.

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References and links 
  • NC3Rs Experimental Design Assistant: https://eda.nc3rs.org.uk/ 
  • ARRIVE guidelines: https://arriveguidelines.org/ 
  • Animal Study Registry: https://www.animalstudyregistry.org/ 
  • Menke J et al. The Rigor and Transparency Index Quality Metric for Assessing Biological and Medical Science Methods. iScience, 2020. doi.org/10.1016/j.isci.2020.101698 
  • Becker JB, Prendergast BJ and Liang JW. Female rats are not more variable than male rats: a meta-analysis of neuroscience studies. Biology of Sex Differences, 2016. doi.org/10.1186/s13293-016-0087-5 
  • Giusti SA et al. Behavioral phenotyping of Nestin-Cre mice: implications for genetic mouse models of psychiatric disorders. Journal of Psychiatric Research, 2014. doi.org/10.1016/j.jpsychires.2014.04.002 
  • Higgins SG, Nogiwa-Valdez AA and Stevens MM. Considerations for implementing electronic laboratory notebooks in an academic research environment. Nature Protocols, 2022. doi.org/10.1038/s41596-021-00645-8 
  • Gerlai R. Gene-targeting studies of mammalian behavior: is it the mutation or the background genotype? Trends in Neurosciences, 1996. doi.org/10.1016/s0166-2236(96)20020-7 

This toolkit was originally produced with guidance from Anthony Isles.