Cross-modal effects provide a model framework for investigating hierarchical inter-areal processing, particularly, under conditions where unimodal cortical areas receive contextual feedback from other modalities. Here, using complementary behavioral and brain imaging techniques, we investigated the functional networks participating in face and voice processing during gender perception, a high-level feature of voice and face perception. Within the framework of a signal detection decision model, Maximum likelihood conjoint measurement (MLCM) was used to estimate the contributions of the face and voice to gender comparisons between pairs of audio-visual stimuli in which the face and voice were independently modulated. Top–down contributions were varied by instructing participants to make judgments based on the gender of either the face, the voice or both modalities (N = 12 for each task). Estimated face and voice contributions to the judgments of the stimulus pairs were not independent; both contributed to all tasks, but their respective weights varied over a 40-fold range due to top–down influences. Models that best described the modal contributions required the inclusion of two different top–down interactions: (i) an interaction that depended on gender congruence across modalities (i.e., difference between face and voice modalities for each stimulus); (ii) an interaction that depended on the within modalities’ gender magnitude. The significance of these interactions was task dependent. Specifically, gender congruence interaction was significant for the face and voice tasks while the gender magnitude interaction was significant for the face and stimulus tasks. Subsequently, we used the same stimuli and related tasks in a functional magnetic resonance imaging (fMRI) paradigm (N = 12) to explore the neural correlates of these perceptual processes, analyzed with Dynamic Causal Modeling (DCM) and Bayesian Model Selection. Results revealed changes in effective connectivity between the unimodal Fusiform Face Area (FFA) and Temporal Voice Area (TVA) in a fashion that paralleled the face and voice behavioral interactions observed in the psychophysical data. These findings explore the role in perception of multiple unimodal parallel feedback pathways.