Exploitation of local and global information in predictive processing

Autor: Nico Broers, Moritz F. Wurm, Niko A. Busch, Ricarda Ines Schubotz, Marlen A. Roehe, Daniel S. Kluger
Přispěvatelé: Universitäts- und Landesbibliothek Münster
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Male
Computer science
Physiology
Event-Related Potentials
Social Sciences
Electroencephalography
Diagnostic Radiology
Thinking
Database and Informatics Methods
Learning and Memory
Mathematical and Statistical Techniques
ddc:150
Functional Magnetic Resonance Imaging
Medicine and Health Sciences
Psychology
Evoked Potentials
Clinical Neurophysiology
Brain Mapping
medicine.diagnostic_test
Radiology and Imaging
Statistics
Uncertainty
Event-related potentials
Behavior
Learning
Functional magnetic resonance imaging
Forecasting
Electrophysiology
Sensory perception
Magnetic Resonance Imaging
Bioassays and Physiological Analysis
Brain Electrophysiology
Pattern Recognition
Visual

Physical Sciences
Medicine
Female
Sequence Analysis
Reference frame
Research Article
Imaging Techniques
Permutation
Bioinformatics
Science
Models
Neurological

Neurophysiology
Adaptation (eye)
Neuroimaging
Research and Analysis Methods
Young Adult
Diagnostic Medicine
P3b
medicine
Humans
Statistical Methods
Probability
business.industry
Discrete Mathematics
Electrophysiological Techniques
Cognitive Psychology
Biology and Life Sciences
Pattern recognition
N400
Combinatorics
Cognitive Science
Artificial intelligence
Clinical Medicine
business
150 Psychology
Mathematics
Photic Stimulation
Neuroscience
Zdroj: PLoS ONE
PLoS ONE, Vol 15, Iss 4, p e0231021 (2020)
ISSN: 1932-6203
Popis: 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.
Finanziert durch den Open-Access-Publikationsfonds der Westfälischen Wilhelms-Universität Münster (WWU Münster).
Databáze: OpenAIRE
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