Episodic memory; fMRI; Temporal structure; Event segmentation; Scene construction
Abstract :
[en] The continuous flow of experience that characterizes real-life events is not recorded as such in episodic memory but is condensed as a succession of event segments separated by temporal discontinuities. To unravel the neural basis of this representational structure, we recorded real-life events using wearable camera technology and used fMRI to investigate brain activity during their temporal unfolding in memory. We found that, compared to the representation of static scenes in memory, dynamically unfolding memory representations were associated with greater activation of the posterior medial episodic network. Strikingly, by analyzing the autocorrelation of brain activity patterns at successive time points throughout the retrieval period, we found that this network showed higher temporal dynamics when recalling events that included a higher density of event segments. These results reveal the key role of the posterior medial network in representing the dynamic unfolding of the event segments that constitute real-world memories.
Research Center/Unit :
PsyNCog - Psychologie et Neuroscience Cognitives - ULiège
Jeunehomme, Olivier ✱; Université de Liège - ULiège > Département de Psychologie
Heinen, Rebekka ✱; Ruhr University Bochum > Faculty of Psychology > Department of Neuropsychology, Institute of Cognitive Neuroscience
Stawarczyk, David ; Université de Liège - ULiège > Département de Psychologie ; Université de Liège - ULiège > Psychologie et Neuroscience Cognitives (PsyNCog)
Axmacher, Nikolai; Ruhr University Bochum > Faculty of Psychology > Department of Neuropsychology, Institute of Cognitive Neuroscience
D'Argembeau, Arnaud ; Université de Liège - ULiège > Département de Psychologie ; Université de Liège - ULiège > Psychologie et Neuroscience Cognitives (PsyNCog)
✱ These authors have contributed equally to this work.
Language :
English
Title :
Representational dynamics of memories for real-life events
Publication date :
2022
Journal title :
iScience
eISSN :
2589-0042
Publisher :
Elsevier, Cambridge, United States - Massachusetts
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