| Paper: | PS-2A.30 |
| Session: | Poster Session 2A |
| Location: | Symphony/Overture |
| Session Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation Time: | Friday, September 7, 17:15 - 19:15 |
| Presentation: |
Poster
|
| Publication: |
2018 Conference on Cognitive Computational Neuroscience, 5-8 September 2018, Philadelphia, Pennsylvania |
| Paper Title: |
Natural Sound Statistics Predict Auditory Grouping Principles |
| Manuscript: |
Click here to view manuscript |
| DOI: |
https://doi.org/10.32470/CCN.2018.1135-0 |
| Authors: |
Wiktor Mlynarski, Josh McDermott, Massachusetts Institute of Technology, United States |
| Abstract: |
Events and objects in the world must be inferred from sensory signals to support behavior. Because sensory signals are transduced with measurements that are temporally and spatially local, the estimation of a particular object or event can be viewed as the result of grouping these local measurements into representations of their common causes. In the auditory system, perceptual grouping is believed to exploit acoustic regularities of natural sounds, such as the tendency of frequencies to be harmonically related or to share a common onset. However, acoustic grouping cues have traditionally been identified using intuitions and informal observation, and investigated using simple, artificial stimuli. As a result, the relevance of known grouping cues to real-world auditory scene analysis remains unclear, and additional or alternative cues remain a possibility. Here we derive auditory grouping cues from co-occurrence statistics of local acoustic features in natural sounds. This process recovers established cues but also reveals previously unappreciated aspects of grouping. The results provide confirmation that auditory grouping is adapted to natural stimulus statistics, and show how these statistics can be harnessed to reveal novel grouping phenomena. |
