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Description: 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 of interest 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.

License: GNU General Public License (GPL) 3.0

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MATLAB source code for generating Stochastic figure-ground (SFG) acoustic stimulus

MATLAB source code for generating Stochastic figure-ground (SFG) acoustic stimulus

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NIH Cortex software based source code for fMRI data acquisition

NIH Cortex software based source code for fMRI data acquisition on SFG segregation

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SPM script for fMRI data processing

MATLAB based source code for fMRI data processing using SPM

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Schneider_Dheerendra (2017) Nat Sci Rep: Macaque SFG fMRI data

fMRI data on rhesus macaques passively listening to SFG stimulus

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Schneider_Dheerendra (2017) Nat Sci Rep: Macaque SFG behavioural data set

Go/No-Go figure detection task using Stochastic Figure-Ground stimuli (SFG) with varying target-to-masker ratios (figure coherence).

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