The brain is the body’s largest energy consumer, even in the absence of demanding tasks. Moreover, electrophysiologists report on-going neuronal firing during stimulation or task in regions beyond those with a primary functional relationship to the perturbation. Despite converging evidence suggesting the whole brain is continuously working and adapting to anticipate and actuate in response to the environment, over the last 20 years, task-based functional MRI (fMRI) has emphasized a localizationist view of brain function, with fMRI showing only a handful of activated regions in response to task/stimulation. Here, we will discuss evidence challenging that view, and showing how under very low noise conditions, fMRI activations extend well beyond areas of primary relationship to the task; and blood-oxygen level-dependent (BOLD) signal changes correlated with task-timing can appear in large portions of the brain (sometimes over 90%; Figure 1) even for simple tasks (Gonzalez-Castillo et al., 2012). More importantly, these widespread activations vary substantially in shape across regions. We will discuss how such inter-regional variability can be exploited to parcellate the whole brain in action (Gonzalez-Castillo et al., 2012; Orban et al., 2015) using different clustering algorithms; and how such parcellations relate to intrinsic connectivity networks identified with resting-state scans. The relationship of excessively strict predictive response models during the analysis of fMRI data and the sparseness of fMRI activation maps will also be discussed. When more versatile models are in place, activation maps change drastically (Gonzalez-Castillo et al., 2015, 2012; Uludağ, 2008). In particular we will focus our attention to the contribution of transient (i.e., short responses at the beginning and the end of task epochs) and negatively sustained (i.e., negative deflections in BOLD signal that last the entire task epoch) responses to fMRI activation maps. We will discuss how positively sustained responses (those most commonly reported in the literature) may account for only one-third to one-fifth of voxels with hemodynamic responses time-locked with the experimental paradigm; and how inclusion of additional response models may help get a more accurate picture of brain functioning during task performance or external stimulation. Overall, the studies and methods discussed in this session will highlight the detail lying in fMRI signals beyond what is normally examined, and will emphasize both the pervasiveness of false negatives, and how the sparseness of fMRI maps is not a result of localized brain function, but a consequence of high noise and overly strict predictive response models.