The ability to make accurate and timely decisions, such as judging when it is safe to cross the road, is the foundation of adaptive behaviour. While the computational and neural processes supporting simple decisions on isolated stimuli have been well characterised, in the real world decision-making often requires integration of discrete sensory events over time and space. When crossing the road, for example, the locations and speeds of several cars must be considered. It remains unclear how such integrative perceptual decisions are regulated computationally. Here we used psychophysics, electroencephalography and computational modelling to understand how the human brain combines visual motion signals across space. We directly tested competing predictions arising from influential serial and parallel accounts of visual processing. Using a biologically plausible model of motion filtering, we find evidence in favour of parallel integration as the fundamental computational mechanism regulating integrated perceptual decisions.