Hardware implementation of functional neuronal circuits has rapidly become more feasible due to increasing reliability of memristor-CMOS integration at a scale necessitated by neuromorphic processes. Most neuromorphic implementations of the memristor treat it as a variable synaptic weight modulated by conductance. The work in this paper enhances biological plausibility of analog vision system circuits by mimicking the nonlinear dynamics of a network of receptive field that resembles those found in the lateral geniculate nucleus. The memristive circuit provides a biologically accurate response where a single cell behaves simultaneously as its own on-center receptive field, and as the off-surround receptive field of adjacent cells. It maximally responds to spatial variations of light. Each output is a fundamental unit of cortical visual information, and we show how the receptive field of each neuron can be superimposed to perceive edges and recognize objects when scaled to higher cortical areas. The functionality of the array is verified in SPICE simulations.