This paper presents a complex preference framework of integrating pulsed neural networks into neural/symbolic hybrid approaches. In particular, we introduce an interpretation of neural codes as multidimensional complex neural preferences and preference classes, which allow the integration of knowledge from different neural and symbolic models. We define some basic operations on complex preferences and preference classes that allow them to be directly integrated in to symbolic models. Furthermore, we show the interpretation of mean firing rate, time-to-first-spike, synchrony and phase codes as complex neural preferences and the interpretation of the operations on preference classes of these codes. T o the best of our knowledge this is the first work that addresses the integration of pulsed neural networks in to hybrid approaches, in particular the symbolic interpretation and simultaneous processing of mean firing rate and pulse coding schemes in a preferences framework.