Models of attention often distinguish between attention subtypes, with classic models separating orienting, switching, and sustaining functions. Compared to other forms of attention, the neurophysiological basis of sustaining attention has received far less attention yet it is known that momentary failures of sustained attention can have far ranging negative impacts in healthy individuals and lasting sustained attention deficits are pervasive in clinical populations. In recent years, however, there has been increased interest in characterizing moment-to-moment fluctuations in sustained attention in addition to the overall vigilance decrement and understanding how these neurocognitive systems change over the lifespan and across various clinical populations. The use of novel neuroimaging paradigms and statistical approaches has allowed for better characterization of the neural networks supporting sustained attention, and highlighted dynamic interactions within and across multiple distributed networks that predict behavioral performance. These advances have also provided potential biomarkers to identify individuals with sustained attention deficits. These findings have led to new theoretical models of why sustaining focused attention is a challenge for individuals and form the basis for the next generation of sustained attention research, which seeks to accurately diagnose and develop theoretically-driven treatments for sustained attention deficits that affect a variety of clinical populations.