This provides the NIH Cortex software based source code for fMRI data acquisition on the auditory segregation experiment. A critical aspect of auditory scene analysis is the ability to extract a sound of relevance (figure) from a background of competing sounds (ground) such as when we hear a speaker in a cafe. This is formally known as auditory figure-ground segregation. This is colloquially known as "cocktail party problem". To understand how the brain segregates overlapping sounds, we need to record from neurons, i.e. single cells in the brain. Since systematic single cell brain recordings are not suitable to perform in humans, we need to use animals in this research. Monkeys are best suited as animal models of human auditory perception due to their similar auditory abilities and similar organization of their auditory brain as humans. However, before we generalize the findings from monkeys to humans, we need to establish that monkeys utilize similar brain regions as humans for auditory figure ground segregation. I employed non-invasive functional magnetic resonance imaging (fMRI) and presented stochastic figure ground (SFG) artificial sounds to awake passively listening rhesus macaques (macaca mulatta) that were trained to perform visual fixation for fluid reward. I showed that monkeys use similar regions of their auditory brain as humans to separate overlapping sounds. This has now paved the way for recording from single cells in the monkey brain which will enable us to understand how the brain solves the cocktail party problem. If you use this code **please cite the following paper**: [1] Felix Schneider*, Pradeep Dheerendra*, Fabien Balezeau, Michael Ortiz-Rios, Yukiko Kikuchi, Christopher I. Petkov, Alexander Thiele, and Timothy D. Griffiths. "Auditory figure-ground analysis in rostral belt and parabelt of the macaque monkey." Scientific reports 8, no. 1 (2018): 1-8. https://doi.org/10.1038/s41598-018-36903-1