  Generative models of brain activity have been instrumental in testing
hypothesized mechanisms underlying brain dynamics against experimental
datasets. Beyond capturing the key mechanisms underlying spontaneous brain
dynamics, these models hold an exciting potential for understanding the
mechanisms underlying the dynamics evoked by targeted brain-stimulation
techniques. This paper delves into this emerging application, using concepts
from dynamical systems theory to argue that the stimulus-evoked dynamics in
such experiments may be shaped by new types of mechanisms distinct from those
that dominate spontaneous dynamics. We review and discuss: (i) the targeted
experimental techniques across spatial scales that can both perturb the brain
to novel states and resolve its relaxation trajectory back to spontaneous
dynamics; and (ii) how we can understand these dynamics in terms of mechanisms
using physiological, phenomenological, and data-driven models. A tight
integration of targeted stimulation experiments with generative quantitative
modeling provides an important opportunity to uncover novel mechanisms of brain
dynamics that are difficult to detect in spontaneous settings.
