RT Journal Article SR Electronic T1 Evidence Integration in Natural Acoustic Textures during Active and Passive Listening JF eneuro JO eNeuro FD Society for Neuroscience SP ENEURO.0090-18.2018 DO 10.1523/ENEURO.0090-18.2018 VO 5 IS 2 A1 Górska, Urszula A1 Rupp, Andre A1 Boubenec, Yves A1 Celikel, Tansu A1 Englitz, Bernhard YR 2018 UL http://www.eneuro.org/content/5/2/ENEURO.0090-18.2018.abstract AB Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration.