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Shared neural codes of recognition memory.

Ambrus, G. G., 2024. Shared neural codes of recognition memory. Scientific Reports, 14, 15846.

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Ambrus-2024-Scientific_Reports.pdf - Published Version
Available under License Creative Commons Attribution.


DOI: 10.1038/s41598-024-66158-y


Recognition memory research has identified several electrophysiological indicators of successful memory retrieval, known as old-new effects. These effects have been observed in different sensory domains using various stimulus types, but little attention has been given to their similarity or distinctiveness and the underlying processes they may share. Here, a data-driven approach was taken to investigate the temporal evolution of shared information content between different memory conditions using openly available EEG data from healthy human participants of both sexes, taken from six experiments. A test dataset involving personally highly familiar and unfamiliar faces was used. The results show that neural signals of recognition memory for face stimuli were highly generalized starting from around 200 ms following stimulus onset. When training was performed on non-face datasets, an early (around 200–300 ms) to late (post-400 ms) differentiation was observed over most regions of interest. Successful cross-classification for non-face stimuli (music and object/scene associations) was most pronounced in late period. Additionally, a striking dissociation was observed between familiar and remembered objects, with shared signals present only in the late window for correctly remembered objects, while cross-classification for familiar objects was successful in the early period as well. These findings suggest that late neural signals of memory retrieval generalize across sensory modalities and stimulus types, and the dissociation between familiar and remembered objects may provide insight into the underlying processes.

Item Type:Article
Uncontrolled Keywords:Multivariate pattern analysis; EEG; Memory; Familiarity; Recollection
Group:Faculty of Science & Technology
ID Code:40139
Deposited By: Symplectic RT2
Deposited On:10 Jul 2024 12:45
Last Modified:10 Jul 2024 12:45


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