Abstract rules drive adaptation in the subcortical sensory pathway
Abstract
The subcortical sensory pathways are the fundamental channels for mapping the outside world to our minds. Sensory pathways efficiently transmit information by adapting neural responses to the local statistics of the sensory input. The longstanding mechanistic explanation for this adaptive behaviour is that neural activity decreases with increasing regularities in the local statistics of the stimuli. An alternative account is that neural coding is directly driven by expectations of the sensory input. Here we used abstract rules to manipulate expectations independently of local stimulus statistics. The ultra-high-field functional-MRI data show that abstract expectations can drive the response amplitude to tones in the human auditory pathway. These results provide first unambiguous evidence of abstract processing in a subcortical sensory pathway. They indicate that the neural representation of the outside world is altered by our prior beliefs even at initial points of the processing hierarchy.
Data availability
Derivatives (beta maps and log-likelihood maps, computed with SPM) and all code used for data processing and analysis are publicly available in https://osf.io/f5tsy/.
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Predictive processing in the human subcortical auditory pathwayOSF, 10.17605/OSF.IO/F5TSY.
Article and author information
Author details
Funding
H2020 European Research Council (SENSOCOM (647051))
- Katharina von Kriegstein
Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg
- Alejandro Tabas
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: This study was approved by the Ethics committee of the Medical Faculty of the University of Leipzig, Germany (ethics approval number 273/14-ff). All listeners provided written informed consent and received monetary compensation for their participation.
Copyright
© 2020, Tabas et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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