Universität zu Köln

Kluger, Daniel S., Broers, Nico, Roehe, Marlen A., Wurm, Moritz F., Busch, Niko A. and Schubotz, Ricarda, I (2020). Exploitation of local and global information in predictive processing. PLoS One, 15 (4). SAN FRANCISCO: PUBLIC LIBRARY SCIENCE. ISSN 1932-6203

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Abstract

While prediction errors have been established to instigate learning through model adaptation, recent studies have stressed the role of model-compliant events in predictive processing. Specifically, probabilistic information at critical points in time (so-called checkpoints) has been suggested to be sampled in order to evaluate the internal model, particularly in uncertain contexts. This way, initial model-based expectations are iteratively reaffirmed under uncertainty, even in the absence of prediction errors. Using electroencephalography (EEG), the present study aimed to investigate the interplay of such global uncertainty information and local adjustment cues prompting on-line adjustments of expectations. Within a stream of single digits, participants were to detect ordered sequences (i.e., 3-4-5-6-7) that had a regular length of five digits and were occasionally extended to seven digits. Over time, these extensions were either rare (low irreducible uncertainty) or frequent (high uncertainty) and could be unexpected or indicated by incidental colour cues. Accounting for cue information, an N400 component was revealed as the correlate of locally unexpected (vs expected) outcomes, reflecting effortful integration of incongruous information. As for model-compliant information, multivariate pattern decoding within the P3b time frame demonstrated effective exploitation of local (adjustment cues vs non-informative analogues) and global information (high vs low uncertainty regular endings) sampled from probabilistic events. Finally, superior fit of a global model (disregarding local adjustments) compared to a local model (including local adjustments) in a representational similarity analysis underscored the precedence of global reference frames in hierarchical predictive processing. Overall, results suggest that just like error-induced model adaptation, model evaluation is not limited to either local or global information. Following the hierarchical organisation of predictive processing, model evaluation too can occur at several levels of the processing hierarchy.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Kluger, Daniel S. UNSPECIFIED UNSPECIFIED UNSPECIFIED Broers, Nico UNSPECIFIED UNSPECIFIED UNSPECIFIED Roehe, Marlen A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Wurm, Moritz F. UNSPECIFIED UNSPECIFIED UNSPECIFIED Busch, Niko A. UNSPECIFIED UNSPECIFIED UNSPECIFIED Schubotz, Ricarda, I UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-337249
DOI:	10.1371/journal.pone.0231021
Journal or Publication Title:	PLoS One
Volume:	15
Number:	4
Date:	2020
Publisher:	PUBLIC LIBRARY SCIENCE
Place of Publication:	SAN FRANCISCO
ISSN:	1932-6203
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language CONTEXT; COMPONENT; N400; ELECTROENCEPHALOGRAM; RECOGNITION; UNCERTAINTY; RESPONSES; TUTORIAL; DYNAMICS; MEMORY Multiple languages Multidisciplinary Sciences Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/33724