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  • 标题:Blueprints for measuring natural behavior
  • 本地全文:下载
  • 作者:Alicja Puścian ; Ewelina Knapska
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2022
  • 卷号:25
  • 期号:7
  • 页码:1-13
  • DOI:10.1016/j.isci.2022.104635
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryUntil recently laboratory tasks for studying behavior were highly artificial, simplified, and designed without consideration for the environmental or social context. Although such an approach offers good control over behavior, it does not allow for researching either voluntary responses or individual differences. Importantly for neuroscience studies, the activity of the neural circuits involved in producing unnatural, artificial behavior is variable and hard to predict. In addition, different ensembles may be activated depending on the strategy the animal adopts to deal with the spurious problem. Thus, artificial and simplified tasks based on responses, which do not occur spontaneously entail problems with modeling behavioral impairments and underlying brain deficits. To develop valid models of human disorders we need to test spontaneous behaviors consistently engaging well-defined, evolutionarily conserved neuronal circuits. Such research focuses on behavioral patterns relevant for surviving and thriving under varying environmental conditions, which also enable high reproducibility across different testing settings.Graphical abstractDisplay OmittedBiological sciences; Neuroscience; Behavioral neuroscience
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