• J. Neurophysiol. · Feb 2012

    Sound-identity processing in early areas of the auditory ventral stream in the macaque.

    • Paweł Kuśmierek, Michael Ortiz, and Josef P Rauschecker.
    • Department of Neuroscience, Georgetown University Medical Center, Washington, District of Columbia 20057, USA. pk83@georgetown.edu
    • J. Neurophysiol. 2012 Feb 1; 107 (4): 1123-41.

    AbstractAuditory cortical processing is thought to be accomplished along two processing streams. The existence of a posterior/dorsal stream dealing, among others, with the processing of spatial aspects of sound has been corroborated by numerous studies in several species. An anterior/ventral stream for the processing of nonspatial sound qualities, including the identification of sounds such as species-specific vocalizations, has also received much support. Originally discovered in anterolateral belt cortex, most recent work on the anterior/ventral pathway has been performed on far anterior superior temporal (ST) areas and on ventrolateral prefrontal cortex (VLPFC). Regions of the anterior/ventral stream near its origin in early auditory areas have been less explored. In the present study, we examined three early auditory regions with different anteroposterior locations (caudal, middle, and rostral) in awake rhesus macaques. We analyzed how well classification based on sound-evoked activity patterns of neuronal populations replicates the original stimulus categories. Of the three regions, the rostral region (rR), which included core area R and medial belt area RM, yielded the greatest classification success across all stimulus classes or between classes of natural sounds. Starting from ∼80 ms past stimulus onset, clustering based on the population response in rR became clearly more successful than clustering based on responses from any other region. Our study demonstrates that specialization for sound-identity processing can be found very early in the auditory ventral stream. Furthermore, the fact that this processing develops over time can shed light on underlying mechanisms. Finally, we show that population analysis is a more sensitive method for revealing functional specialization than conventional types of analysis.

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