首页    期刊浏览 2024年10月07日 星期一
登录注册

文章基本信息

  • 标题:Common brain activations for painful and non-painful aversive stimuli
  • 本地全文:下载
  • 作者:Dave J Hayes ; Georg Northoff
  • 期刊名称:BMC Neuroscience
  • 印刷版ISSN:1471-2202
  • 电子版ISSN:1471-2202
  • 出版年度:2012
  • 卷号:13
  • 期号:1
  • 页码:60
  • DOI:10.1186/1471-2202-13-60
  • 语种:English
  • 出版社:BioMed Central
  • 摘要:Identification of potentially harmful stimuli is necessary for the well-being and self-preservation of all organisms. However, the neural substrates involved in the processing of aversive stimuli are not well understood. For instance, painful and non-painful aversive stimuli are largely thought to activate different neural networks. However, it is presently unclear whether there is a common aversion-related network of brain regions responsible for the basic processing of aversive stimuli. To help clarify this issue, this report used a cross-species translational approach in humans (i.e. meta-analysis) and rodents (i.e. systematic review of functional neuroanatomy). Animal and human data combined to show a core aversion-related network, consisting of similar cortical (i.e. MCC, PCC, AI, DMPFC, RTG, SMA, VLOFC; see results section or abbreviation section for full names) and subcortical (i.e. Amyg, BNST, DS, Hab, Hipp/Parahipp, Hyp, NAc, NTS, PAG, PBN, raphe, septal nuclei, Thal, LC, midbrain) regions. In addition, a number of regions appeared to be more involved in pain-related (e.g. sensory cortex) or non-pain-related (e.g. amygdala) aversive processing. This investigation suggests that aversive processing, at the most basic level, relies on similar neural substrates, and that differential responses may be due, in part, to the recruitment of additional structures as well as the spatio-temporal dynamic activity of the network. This network perspective may provide a clearer understanding of why components of this circuit appear dysfunctional in some psychiatric and pain-related disorders.
  • 关键词:Meta-analysis ; Translational ; Aversion ; Pain ; Neuroimaging ; Animal models
国家哲学社会科学文献中心版权所有