Visual receptive fields are characterised by their centre-surround organisation and are typically modelled by Difference-of-Gaussians (DoGs)1. The DoG captures the effect of surround modulation, where the central receptive field can be modulated by simultaneous stimulation of a surrounding area2–5. Although it is well-established that this centre-surround organisation is crucial for extracting spatial information from visual scenes, the underlying law binding the organisation has remained hidden. Indeed, previous studies have reported a wide range of size and gain ratios of the DoG used to model the receptive fields6–9. Here, we present an equation that describes a principle for receptive field organisation, and we demonstrate that functional Magnetic Resonance Imaging (fMRI) population Receptive Field (pRF) maps of human V1 adhere to this principle. We formulate and understand the equation through consideration of the concept of Direct-Current-free (DC-free) filtering from electrical engineering, and we show how this particular type of filtering effectively makes the DoG process frequencies of interest without misallocation of bandwidth to redundant frequencies. Taken together, our results reveal how this organisational principle enables the visual system to adapt its sampling strategy to optimally cover the stimulus-space relevant to the organism, restricted only by Heisenberg’s uncertainty principle that imposes a lower bound on the simultaneous precision in spatial position and frequency. Since surround modulation has been observed in all sensory modalities10, we expect these results will become a corner stone in our understanding of how biological systems in general achieve their high information processing capacity.