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Clinical neuroscience and psychiatric research increasingly acknowledge the important roles of prediction in psychopathology including anxiety, hallucination and apathy. Currently, transdiagnostic neuroimaging studies have found that common disruption of key large-scale brain networks including the frontoparietal network (FPN), the default mode network (DMN) and the salience network (SN) were manifested widely across autism, anxiety disorders, and schizophrenia. However, it still remains unsolved whether there are common cognitive mechanisms in relation to these shared alterations of large-scale brain networks. This thesis exploited functional Magnetic Resonance Imaging (fMRI) measures including brain activation, functional connectivity and dynamic brain networks to examine putative common neurocognitive mechanisms across the prevalent symptoms of anxiety, apathy, and hallucinations, with an emphasis on the role of prediction. Based on our findings, I propose a hypothesis of a common neurocognitive mechanism across anxiety, hallucination and apathy was proposed: the predicting brain model. Core brain networks, including the SN, FPN and DMN and peripheral regions involved in specific cognitive elements, underlie the common prediction of uncertain threats in anxiety, auditory stimuli in hallucinations and motivational drive in apathy. Our studies provide enhanced understanding of brain network organization during predictive processing underlying symptoms in psychiatric disorders may aid the development of more effective diagnostic and treatment strategies.