Schizophrenia (SCZ) is a complex disorder in which various pathophysiological models have been postulated. Brain imaging studies using EEG/MEG and fMRI show altered amplitude and, more recently, decrease in phase coherence in response to external stimuli. What are the dynamic mechanisms of such phase incoherence, and can it serve as a differential-diagnostic marker? Addressing this gap in our knowledge, we uniquely combine a review of previous findings, novel empirical data, and computational-dynamic simulation. The main findings are: (i) the review shows decreased phase coherence in SCZ across a variety of different tasks and frequencies, e.g., task- and frequency-unspecific, which is further supported by our own novel data; (ii) our own data demonstrate diagnostic specificity of decreased phase coherence for SCZ as distinguished from major depressive disorder; (iii) simulation data exhibit increased phase offset in SCZ leading to a precision index, in the millisecond range, of the phase coherence relative to the timing of the external stimulus. Together, we demonstrate the key role of temporal imprecision in phase coherence of SCZ, including its mechanisms (phase offsets, precision index) on the basis of which we propose a phase-based temporal imprecision model of psychosis (PTP). The PTP targets a deeper dynamic layer of a basic disturbance. This converges well with other models of psychosis like the basic self-disturbance and time-space experience changes, as discussed in phenomenological and spatiotemporal psychopathology, as well as with the models of aberrant predictive coding and disconnection as in computational psychiatry. Finally, our results show that temporal imprecision as manifest in decreased phase coherence is a promising candidate biomarker for clinical differential diagnosis of SCZ, and more broadly, psychosis.