Emotional prediction: An ALE meta-analysis and MACM analysis

Conscious Cogn. 2018 Feb:58:158-169. doi: 10.1016/j.concog.2017.10.019. Epub 2017 Nov 8.

Abstract

The prediction of emotion has been explored in a variety of functional brain imaging and neurophysiological studies. However, an overall picture of the areas involved this process remains unexploited. Here, we quantitatively summarized the published literature on emotional prediction using activation likelihood estimation (ALE) in functional magnetic resonance imaging (fMRI). Furthermore, the current study employed a meta-analytic connectivity modeling (MACM) to map the meta-analytic coactivation maps of regions of interest (ROIs). Our ALE analysis revealed significant convergent activations in some vital brain areas involved in emotional prediction, including the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), orbitofrontal cortex (OFC) and medial prefrontal cortex (MPFC). For the MACM analysis, we identified that the DLPFC, VLPFC and OFC were the core areas in the coactivation network of emotional prediction. Overall, the results of ALE and MACM indicated that prefrontal brain areas play critical roles in emotional prediction.

Keywords: ALE; Dorsolateral prefrontal cortex; Emotional prediction; MACM; Orbitofrontal cortex; Ventrolateral prefrontal cortex.

Publication types

  • Meta-Analysis
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Emotions / physiology*
  • Functional Neuroimaging / statistics & numerical data*
  • Humans
  • Image Processing, Computer-Assisted / statistics & numerical data*
  • Prefrontal Cortex / diagnostic imaging
  • Prefrontal Cortex / physiology*