The advancement of neuroscience depends on continued improvement in methods and models. Here, we present novel techniques for the use of awake functional magnetic resonance imaging (fMRI) in the prairie vole (Microtus ochrogaster) — an important step forward in minimally-invasive measurement of neural activity in a non-traditional animal model. Imaging neural responses in prairie voles, a species studied for its propensity to form strong and selective social bonds, is expected to greatly advance our mechanistic understanding of complex social and affective processes. The use of ultra-high-field fMRI allows for recording changes in region-specific activity throughout the entire brain simultaneously and with high temporal and spatial resolutions. By imaging neural responses in awake animals, with minimal invasiveness, we are able to avoid the confound of anesthesia, broaden the scope of possible stimuli, and potentially make use of repeated scans from the same animals. These methods are made possible by the development of an annotated and segmented 3D vole brain atlas and software for image analysis. The use of these methods in the prairie vole provides an opportunity to broaden neuroscientific investigation of behavior via a comparative approach, which highlights the ethological relevance of pro-social behaviors shared between voles and humans, such as communal breeding, selective social bonds, social buffering of stress, and caregiving behaviors. Results using these methods show that fMRI in the prairie vole is capable of yielding robust blood oxygen level dependent (BOLD) signal changes in response to hypercapnic challenge (inhaled 5% CO2), region-specific physical challenge (unilateral whisker stimulation), and presentation of a set of novel odors. Complementary analyses of repeated restraint sessions in the imaging hardware suggest that voles do not require acclimation to this procedure. Taken together, awake vole fMRI represents a new arena of neurobiological study outside the realm of traditional rodent models.