Predictive Modelling in Audition
Zusammenfassung der Projektergebnisse
How do we make sense of the perceptual (auditory) world? Predictive modeling theories claim that perception results from the interaction between the sensory input and our internal model of the world, which contains inferred causes of the sensorial input (i.e. the representation or belief of what in the outer world has generated the input). To verify the validity of the brain’s inference and to decide which of the concurrently active models applies, the inferred causes are used to formulate predictions about the sensory input. The predictions are compared with sensory input and the difference expresses prediction error, which, in turn, is used to improve the model. Once the input is explained by the prediction, the perceptual problem is solved and we “perceive” our respective internal model. Our experiments support this predictive view on (auditory) perception. For example, we were able to make predictions “visible” by generating predictions without corresponding sensory input so that the prediction error, which can be measured by brain activity recordings, is only driven be the top-down prediction. We could show that internal models exploit information from the recent history of the auditory stimulation, but also from long-term memory, from visual stimulation, and from our motor acts. We proposed a psychological conceptual framework called the Auditory Event Representation System (AERS), which is based on the assumption that auditory regularity violation detection and the formation of auditory perceptual objects are based on the same predictive regularity representations; thus, the internal models do not only help to understand the continuation of existing auditory streams, but they are also in the service of segregating the auditory streams. We established the important distinction between prediction and attention, and investigated how they are related. Our experiments revealed the (specific and unspecific) impact of our actions on the processing of the events we (believe to) generate. We conclude that this kind of predictive processing is a general operating principle of our brain. For psychological theories this predictive view mainly becomes helpful, when applied to particular content areas such as auditory pattern processing, sentence processing, novelty detection, voluntary spatial attention, processing of visuo-auditory emotion expressions, and action-hearing cycles.
Projektbezogene Publikationen (Auswahl)
- (2010). Is My Mobile Ringing? Evidence for Rapid Processing of a Personally Significant Sound in Humans. Journal of Neuroscience, 30, 7310-7313
Roye, A., Schröger, E., Jacobsen, T., & Gruber, T.
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.1113-10.2010) - (2011). Selective suppression of self-initiated sounds in an auditory stream: An ERP study. Psychophysiology, 48, 1276-1283
Baess, P., Horvath, J., Jacobsen, T., & Schröger, E.
(Siehe online unter https://doi.org/10.1111/j.1469-8986.2011.01196.x) - (2012). Early electrophysiological indicators for predictive processing in audition: A review. International Journal of Psychophysiology, 83, 120-131
Bendixen, A., SanMiguel, I., & Schröger, E.
(Siehe online unter https://doi.org/10.1016/j.ijpsycho.2011.08.003) - (2012). Predictive information processing in the brain: Principles, neural mechanisms and models. International. International Journal of Psychophysiology, 83 (21 contributions; 130 pp)
Todd, J., Schröger, E., & Winkler, I. (Eds.)
(Siehe online unter https://doi.org/10.1016/j.ijpsycho.2012.01.015) - (2013). Hearing silences: Human auditory processing relies on pre-activation of sound-specific brain activity patterns. Journal of Neuroscience, 33, 8633-8639
SanMiguel, I., Widmann, A., Bendixen, A., Trujillo-Barreto, N., & Schröger, E.
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.5821-12.2013) - (2013). The human brain maintains contradictory and redundant auditory sensory predictions. PLoS One, 8, e53634
Pieszek, M., Widmann, A., Gruber, T., & Schröger, E.
(Siehe online unter https://doi.org/10.1371/journal.pone.0053634) - (2014). Microsaccadic responses indicate fast categorization of sounds: a novel approach to study auditory cognition. Journal of Neuroscience, 34, 11152-11158
Widmann, A., Engbert, R., & Schröger, E.
(Siehe online unter https://doi.org/10.1523/JNEUROSCI.1568-14.2014) - (2014). Predictive Regularity Representations in Violation Detection and Auditory Stream Segregation: From Conceptual to Computational Models. Brain Topography, 27, 565-577
Schröger, E., Bendixen, A., Denham, S. L., Mill, R. W., Böhm, T. M., & Winkler, I.
(Siehe online unter https://doi.org/10.1007/s10548-013-0334-6) - (2015). Attention and prediction in human audition: a lesson from cognitive psychophysiology. European Journal of Neuroscience, 41, 641-664
Schröger, E., Marzecova, A., & SanMiguel, I.
(Siehe online unter https://doi.org/10.1111/ejn.12816) - (2015). Auditory perceptual objects as generative models: setting the stage for communication by sound. Brain and Language, 148, 1-22
Winkler, I., & Schröger, E.
(Siehe online unter https://doi.org/10.1016/j.bandl.2015.05.003) - (2015). Special issue: Bridging prediction and attention in current research on perception and action. Brain Research, 1626 (23 contributions; 280 pp)
Schröger, E., Kotz, S. A., & SanMiguel, I. (Eds.)
(Siehe online unter https://doi.org/10.1016/j.brainres.2015.08.037) - (2015). Special issue: Prediction in speech and language processing. Cortex, 68 (16 contributions; 182 pp)
Tavano, A. & Scharinger, M. (Eds.)
(Siehe online unter https://doi.org/10.1016/j.cortex.2015.05.001) - (2016). Implicit expectations influence target detection in children and adults. Developmental Science
Ruhnau, P., Schröger, E., & Sussman, E. S.
(Siehe online unter https://doi.org/10.1111/desc.12402) - (2016). Sensory suppression of brain responses to self-generated sounds is observed with and without the perception of agency. Cortex, 80, 5–20
Timm, J., Schönwiesner, M., Schröger, E., & SanMiguel, I.
(Siehe online unter https://doi.org/10.1016/j.cortex.2016.03.018)
