Despite an extremely rich and complex auditory environment, human beings categorize sounds effortlessly. While it is now well-known that this ability is a result of complex interaction of bottom-up processing of low-level acoustic features and top-down influences like evolutionary relevance, it is yet unclear how these processes drive categorization. The objective of the current study was to use functional neuroimaging to investigate the contribution of these two processes for category selectivity in the cortex. We used a set of ecologically valid sounds that belonged to three different categories: animal vocalizations, environmental sounds and human non-speech sounds, all matched on acoustic structure attributes like harmonic-to-noise ratio to minimize differences in bottom-up processing as well as matched for familiarity to rule out other top-down influences. Participants performed a loudness judgment task in the scanner and data were acquired using a sparse-temporal sampling paradigm. Our functional imaging results show that there is category selectivity in the cortex only for species-specific vocalizations and this is revealed in six clusters in the right and left STG/STS. Category selectivity was not observed for any other category of sounds. Our findings suggest a potential role of evolutionary relevance for cortical processing of sounds. While this seems to be an appealing proposition, further studies are required to explore the role of top-down mechanisms arising from such features to drive category selectivity in the brain.
Pubmed ID: 22522473 RIS Download
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Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.
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