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This provides the MATLAB source code for generating "Stochastic figure-ground (SFG) acoustic stimulus" 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 have created artificial sounds known as Stochastic figure-ground stimulus which allows us to examine the fundamental brain mechanisms underlying auditory figure ground segregation. Here an auditory object made of temporally coherent tones repeating in time ("figure") overlap in time and frequency with background made of randomly varying tones ("ground"). So extraction of this auditory object requires integration across both time and frequency - a form of sequential grouping of spectral patterns which is similar to extraction of a voice in a noisy party. Thus, these synthetic stimuli simulate the challenges faced in real-world listening yet are devoid of semantic confounds. Stochastic figure-ground stimulus are made of 5-15 randomly chosen pure tone components (ground) that change for every chord. This ground segment is overlaid with certain additional tonal components that are either coherent ("figure") or incoherent ("control"), presented at the middle segment of a sound. 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.