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A neural index reflecting the amount of cognitive resources available during memory encoding: A model-based approach
Si Ma1, Vencislav Popov2, Qiong Zhang1
1Department of Psychology, Rutgers University.
Abstract:
Humans have a limited amount of cognitive resources to process various cognitive operations at a given moment. The Source of Activation Confusion model of episodic memory proposes that resources are consumed during each processing, and once depleted, they need time to recover gradually. This has been supported by a series of behavioral findings in the past. However, the neural substrate of the resources is not known. In the present study, over an existing electroencephalogram data set of a free recall task (Kahana et al., 2022), we provided a neural index reflecting the amount of cognitive resources available for forming new memory traces. Unique to our approach, we obtained the neural index not through correlating neural patterns with behavior outcomes or experimental conditions, but by demonstrating its alignment with a latent quantity of cognitive resources inferred from the Source of Activation Confusion model. In addition, we showed that the identified neural index can be used to propose novel hypothesis regarding other long-term memory phenomena. Specifically, we found that according to the neural index, neural encoding patterns for subsequently recalled items correspond to greater available cognitive resources compared with those for subsequently unrecalled items. This provides a mechanistic account for the long-established subsequent memory effects (i.e., differential neural encoding patterns between subsequently recalled vs. subsequently unrecalled items), which has been previously associated with attention, fatigue, and properties of the stimuli. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
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