Over the past decade, mice have emerged as a useful model for studying vision, owing in large part to their genetic tractability. Such studies have also yielded the unexpected and fascinating finding that movement, particularly locomotion, has a striking effect on cortical visual activity in mice. The discovery of so-called state-dependent visual processing suggested that the role of even primary sensory areas is not as simple as previously thought. Many studies showed that locomotion enhances visual neural activity, but few directly examined whether it actually improved sensory perception in a behavioral task. For my dissertation project I addressed this by examining the interactions between locomotion-dependent modulation of brain state and different goal-directed sensory selection brain states. Two groups of mice were trained to visually monitor either one of two locations (selective) or both (non-selective) for a contrast change, and this simple difference produced a spatially selective and non-selective brain state in primary visual cortex (V1), respectively. Locomotion affected the two groups of mice differently, impairing performance and neural representations of visual information of selective mice, while having no effect on non-selective mice. These and other results suggest that these two groups of mice use local versus global mechanisms to perform their respective tasks, and in the case of selective mice, the global influence of locomotion disrupts their locally modulated brain state and impairs performance. Locomotion influences brain state differently, depending on the whether the animal employs a spatially selective state to perform its task. Thus, state-dependence is state-dependent. These findings demonstrate the importance of studying complex interactions, and argue for reducing reductionism in neuroscience as we gain the necessary technology to carry out such studies. Moving forward, this mouse model will do just that, and enable investigation into the cell type and circuit mechanisms underlying these phenomena. Wading into the enormous complexity of the brain may ultimately be the only way to understand how it works as a whole.