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  3. Predictable and unpredictable deviance detection in the human hippocampus and amygdala.
 

Predictable and unpredictable deviance detection in the human hippocampus and amygdala.

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BORIS DOI
10.48350/191607
Publisher DOI
10.1093/cercor/bhad532
PubMed ID
38216528
Description
Our brains extract structure from the environment and form predictions given past experience. Predictive circuits have been identified in wide-spread cortical regions. However, the contribution of medial temporal structures in predictions remains under-explored. The hippocampus underlies sequence detection and is sensitive to novel stimuli, sufficient to gain access to memory, while the amygdala to novelty. Yet, their electrophysiological profiles in detecting predictable and unpredictable deviant auditory events remain unknown. Here, we hypothesized that the hippocampus would be sensitive to predictability, while the amygdala to unexpected deviance. We presented epileptic patients undergoing presurgical monitoring with standard and deviant sounds, in predictable or unpredictable contexts. Onsets of auditory responses and unpredictable deviance effects were detected earlier in the temporal cortex compared with the amygdala and hippocampus. Deviance effects in 1-20 Hz local field potentials were detected in the lateral temporal cortex, irrespective of predictability. The amygdala showed stronger deviance in the unpredictable context. Low-frequency deviance responses in the hippocampus (1-8 Hz) were observed in the predictable but not in the unpredictable context. Our results reveal a distributed network underlying the generation of auditory predictions and suggest that the neural basis of sensory predictions and prediction error signals needs to be extended.
Date of Publication
2024-01-31
Publication Type
Article
Subject(s)
000 Computer science, knowledge & systems
600 Technology > 610 Medicine & health
500 Science > 510 Mathematics
Keyword(s)
amygdala auditory predictions deviance hippocampus intracranial EEG
Language(s)
en
Contributor(s)
Tzovara, Athinaorcid-logo
Universitätsklinik für Neurologie
Institut für Informatik (INF)
Fedele, Tommaso
Sarnthein, Johannes
Ledergerber, Debora
Lin, Jack J
Knight, Robert T
Additional Credits
Universitätsklinik für Neurologie
Series
Cerebral cortex
Publisher
Oxford University Press
ISSN
1460-2199
Access(Rights)
restricted
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