Echo Planar Imaging (EPI) is a neuroimaging tool for clinical practice and research investigation. Due to odd-even echo phase inconsistencies, however, EPI suffers from Nyquist N/2 ghost artifacts. In standard neuroimaging protocols, EPI artifacts are suppressed using phase correction techniques that require reference data collected from a reference scan. Because reference-scan based techniques are sensitive to subject motion, EPI performance is sub-optimal in neuroimaging applications. In this technical note, we present a novel EPI data processing technique which we call Parallel EPI Artifact Correction (PEAC). By introducing an implicit data constraint associated with multi-coil sensitivity in parallel imaging, PEAC converts phase correction into a constrained problem that can be resolved using an iterative algorithm. This enables "reference-less" EPI that can improve neuroimaging performance. In the presented work, PEAC is investigated using a standard functional magnetic resonance imaging (fMRI) protocol with multi-slice 2D EPI. It is demonstrated that PEAC can suppress ghost artifacts as effectively as the standard reference-scan based phase correction technique used on a clinical MRI system. We also found that PEAC can achieve dynamic phase correction when motion occurs.