Determining the receptive field of a visual sensory neuron is crucial to characterize the region of the visual field and the stimuli this neuron is sensitive to. We propose a new method to estimate receptive fields by a nonconvex variational approach, thus relaxing the simplifying and unrealistic assumption of convexity made by standard approaches. The method consists of solving a relaxed discrete energy minimization problem using a proximal alternating algorithm. We compare our approach with the classical spike-triggered-average technique on simulated data, considering a typical retinal ganglion cell as ground truth. Results show a high improvement in terms of accuracy and convergence with respect to the duration of the experiment.