Brain connectomes are insightful models that describe the connectivity of different regions throughout the brain. These connectomes are traditionally generated through correlation of oxygen data from Functional magnetic resonance imaging (fMRI) scans. Photoacoustic ultrasound (PAU) can also detect oxygenation levels while being more accessible and cost effective than fMRI. We propose the use of PAU to generate brain connectomes as an alternative to fMRI. In this study we successfully developed a pipeline for processing PAU data from whole brain scans of mice models and found that the connectomes it produced were comparable to those generated by fMRI, particularly in detecting connections previously documented in the literature. Our findings suggest that PAU is a promising alternative to fMRI for brain connectome analysis, offering advantages in sensitivity and spatial coverage, making it a valuable tool for future research on brain connectivity.