Emotional prediction: An ALE meta-analysis and MACM analysis

Area of Science:

• Neuroscience
• Cognitive Neuroscience
• Neuroimaging

Background:

• Emotion prediction is vital for social interaction and decision-making.
• Previous studies used functional brain imaging and neurophysiology, but a comprehensive overview of involved brain areas is lacking.

Purpose of the Study:

• To quantitatively summarize the brain regions involved in emotional prediction.
• To identify the network of brain areas coactivating during emotional prediction.

Main Methods:

• Activation Likelihood Estimation (ALE) meta-analysis of functional magnetic resonance imaging (fMRI) studies.
• Meta-Analytic Connectivity Modeling (MACM) to map coactivation patterns of key brain regions.

Main Results:

• ALE analysis identified significant convergent activations in the dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), orbitofrontal cortex (OFC), and medial prefrontal cortex (MPFC).
• MACM analysis highlighted the DLPFC, VLPFC, and OFC as core components of the emotional prediction coactivation network.

Conclusions:

• Prefrontal cortex regions, including the DLPFC, VLPFC, OFC, and MPFC, play critical roles in the cognitive process of emotional prediction.
• The findings provide a synthesized understanding of the neural underpinnings of emotional prediction.