TY - JOUR
T1 - Computational models of auditory perception from feature extraction to stream segregation and behavior
AU - Rankin, James
AU - Rinzel, John
N1 - Funding Information:
Rankin acknowledges support from an Engineering and Physical Sciences Research Council (EPSRC) New Investigator Award ( EP/R03124X/1 ) and from the EPSRC Centre for Predictive Modelling in Healthcare ( EP/N014391/1 ). This is a review study, and as such did not generate any new data.
Publisher Copyright:
© 2019 The Authors
PY - 2019/10
Y1 - 2019/10
N2 - Audition is by nature dynamic, from brainstem processing on sub-millisecond time scales, to segregating and tracking sound sources with changing features, to the pleasure of listening to music and the satisfaction of getting the beat. We review recent advances from computational models of sound localization, of auditory stream segregation and of beat perception/generation. A wealth of behavioral, electrophysiological and imaging studies shed light on these processes, typically with synthesized sounds having regular temporal structure. Computational models integrate knowledge from different experimental fields and at different levels of description. We advocate a neuromechanistic modeling approach that incorporates knowledge of the auditory system from various fields, that utilizes plausible neural mechanisms, and that bridges our understanding across disciplines.
AB - Audition is by nature dynamic, from brainstem processing on sub-millisecond time scales, to segregating and tracking sound sources with changing features, to the pleasure of listening to music and the satisfaction of getting the beat. We review recent advances from computational models of sound localization, of auditory stream segregation and of beat perception/generation. A wealth of behavioral, electrophysiological and imaging studies shed light on these processes, typically with synthesized sounds having regular temporal structure. Computational models integrate knowledge from different experimental fields and at different levels of description. We advocate a neuromechanistic modeling approach that incorporates knowledge of the auditory system from various fields, that utilizes plausible neural mechanisms, and that bridges our understanding across disciplines.
UR - http://www.scopus.com/inward/record.url?scp=85069587285&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069587285&partnerID=8YFLogxK
U2 - 10.1016/j.conb.2019.06.009
DO - 10.1016/j.conb.2019.06.009
M3 - Review article
C2 - 31326723
AN - SCOPUS:85069587285
VL - 58
SP - 46
EP - 53
JO - Current Opinion in Neurobiology
JF - Current Opinion in Neurobiology
SN - 0959-4388
ER -