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.
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A PET activation study of dynamic mechanical allodynia in patients with mononeuropathy.
TL;DR: A bilateral activation of the lateral pain system as well as involvement of the medial pain system during dynamic mechanical allodynia in patients with mononeuropathy is revealed.
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Fear and the amygdala: manipulation of awareness generates differential cerebral responses to phobic and fear-relevant (but nonfeared) stimuli.
Katrina Carlsson,Karl Magnus Petersson,Daniel Lundqvist,Andreas Karlsson,Martin Ingvar,Arne Öhman +5 more
TL;DR: A shift from top-down control to an affectively driven system optimized for speed was observed in phobic relative to fear-relevant aware processing.
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What artificial grammar learning reveals about the neurobiology of syntax
TL;DR: It is argued that the left inferior frontal region is a generic on-line sequence processor that unifies information from various sources in an incremental and recursive manner, independent of whether there are any processing requirements related to syntactic movement or hierarchically nested structures.
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A prefrontal non-opioid mechanism in placebo analgesia
Predrag Petrovic,Eija Kalso,Karl Magnus Petersson,Karl Magnus Petersson,Karl Magnus Petersson,Jesper L. R. Andersson,Peter Fransson,Martin Ingvar +7 more
TL;DR: The results support that placebo is different from specific treatment with a prefrontal top‐down influence on rACC, and show that the opioid‐receptor‐rich rostral anterior cingulate cortex is activated in both placebo and opioid analgesia.
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Neural mechanisms for voice recognition
Attila Andics,Attila Andics,James M. McQueen,Karl Magnus Petersson,Viktor Gál,Viktor Gál,Gábor Rudas,Zoltán Vidnyánszky,Zoltán Vidnyánszky +8 more
TL;DR: Voice recognition is supported by neural voice spaces that are organized around flexible 'mean voice' representations, which are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values.