K
Karl Magnus Petersson
Researcher at Max Planck Society
Publications - 187
Citations - 15557
Karl Magnus Petersson is an academic researcher from Max Planck Society. The author has contributed to research in topics: Artificial grammar learning & Semantic memory. The author has an hindex of 63, co-authored 185 publications receiving 14441 citations. Previous affiliations of Karl Magnus Petersson include Chinese Academy of Sciences & Karolinska Institutet.
Papers
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Journal ArticleDOI
Disentangling stimulus plausibility and contextual congruency: Electro-physiological evidence for differential cognitive dynamics
Moreno I. Coco,Moreno I. Coco,Susana Araújo,Susana Araújo,Karl Magnus Petersson,Karl Magnus Petersson +5 more
TL;DR: The results suggest that the integration mechanisms are sensitive to both global and local effects of expectancy in a modality independent manner, and provide novel insights into the interdependence of expectancy during meaning integration of cross‐modal stimuli in a verification task.
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The neuropharmacology of implicit learning.
TL;DR: It is concluded that one can predict improved implicit acquisition by moderately elevated dopamine levels and impaired implicit Acquisition by moderately decreased dopamine levels, which are most prominent in the dorsal striatum.
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Visual naming deficits in dyslexia: An ERP investigation of different processing domains.
TL;DR: These findings suggest suboptimal processing in early stages of object processing in dyslexia, when integration and mapping of perceptual information to a more form-specific percept in memory take place.
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Distinguishing Syntactic Operations in the Brain: Dependency and Phrase-Structure Parsing
Alessandro Lopopolo,Alessandro Lopopolo,Antal van den Bosch,Karl Magnus Petersson,Roel M. Willems,Roel M. Willems +5 more
TL;DR: The hypothesis that different brain regions could be sensitive to different kinds of syntactic computations is investigated, and the fit of phrase-structure and dependency structure descriptors to activity in brain areas using fMRI is compared.
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Learning related modulation of functional retrieval networks in man
TL;DR: It appears necessary to develop elaborated and explicit computational models for prefrontal and medial temporal functions in order to derive detailed empirical predictions, and in combination with an efficient use and development of functional neuroimaging approaches, to further the understanding of the processing significance of these regions in memory.