Background: Most of our social interactions involve perception of emotional information from the faces of other people. Furthermore,
such emotional processes are thought to be aberrant in a range of clinical disorders, including psychosis and depression. However, the
exact neurofunctional maps underlying emotional facial processing are not well defined. Methods: Two independent researchers conducted
separate comprehensive PubMed (1990 to May 2008) searches to find all functional magnetic resonance imaging (fMRI) studies
using a variant of the emotional faces paradigm in healthy participants. The search terms were: “fMRI AND happy faces,” “fMRI
AND sad faces,” “fMRI AND fearful faces,” “fMRI AND angry faces,” “fMRI AND disgusted faces” and “fMRI AND neutral faces.” We extracted
spatial coordinates and inserted them in an electronic database. We performed activation likelihood estimation analysis for
voxel-based meta-analyses. Results: Of the originally identified studies, 105 met our inclusion criteria. The overall database consisted
of 1785 brain coordinates that yielded an overall sample of 1600 healthy participants. Quantitative voxel-based meta-analysis of brain
activation provided neurofunctional maps for 1) main effect of human faces; 2) main effect of emotional valence; and 3) modulatory effect
of age, sex, explicit versus implicit processing and magnetic field strength. Processing of emotional faces was associated with increased
activation in a number of visual, limbic, temporoparietal and prefrontal areas; the putamen; and the cerebellum. Happy, fearful
and sad faces specifically activated the amygdala, whereas angry or disgusted faces had no effect on this brain region. Furthermore,
amygdala sensitivity was greater for fearful than for happy or sad faces. Insular activation was selectively reported during processing of
disgusted and angry faces. However, insular sensitivity was greater for disgusted than for angry faces. Conversely, neural response in
the visual cortex and cerebellum was observable across all emotional conditions. Limitations: Although the activation likelihood estimation
approach is currently one of the most powerful and reliable meta-analytical methods in neuroimaging research, it is insensitive
to effect sizes. Conclusion: Our study has detailed neurofunctional maps to use as normative references in future fMRI studies of
emotional facial processing in psychiatric populations. We found selective differences between neural networks underlying the basic emotions in limbic and insular brain regions