Animal models of maternal immune activation (MIA) are widely used as experimental tools to study neurobehavioral and molecular dysfunctions in relation to immune-mediated neurodevelopmental disorders and mental illnesses. Both planned or intended (‘a-priori variability’) and unplanned or unintended (‘a-posteriori variability’) sources of variability exist in and are relevant to these models. The design, implementation, and interpretation of MIA models, thus, require adequate time considering both types of variability and developing appropriate strategies to handle them. While there are multiple strategies for minimizing variability in MIA models, variability per se is not an undermining characteristic of MIA models or any other model system applied to psychoneuroimmunological research. In fact, it offers unique opportunities for new (and sometimes unexpected) discoveries, granted that researchers are aware of the potential sources of variability and are open to novel methodological approaches and ways of data analysis.
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Weber‐Stadlbauer et al. (2019) studied this question.
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