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Cong P, Long Y, Zhang X, Guo Y, Jiang Y. Elucidating the underlying components of metacognitive systematic bias in the human dorsolateral prefrontal cortex and inferior parietal cortex. Sci Rep 2024; 14:11380. [PMID: 38762635 PMCID: PMC11102512 DOI: 10.1038/s41598-024-62343-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 05/15/2024] [Indexed: 05/20/2024] Open
Abstract
Metacognitive systematic bias impairs human learning efficiency, which is characterized by the inconsistency between predicted and actual memory performance. However, the underlying mechanism of metacognitive systematic bias remains unclear in existing studies. In this study, we utilized judgments of learning task in human participants to compare the neural mechanism difference in metacognitive systematic bias. Participants encoded words in fMRI sessions that would be tested later. Immediately after encoding each item, participants predicted how likely they would remember it. Multivariate analyses on fMRI data demonstrated that working memory and uncertainty decisions are represented in patterns of neural activity in metacognitive systematic bias. The available information participants used led to overestimated bias and underestimated bias. Effective connectivity analyses further indicate that information about the metacognitive systematic bias is represented in the dorsolateral prefrontal cortex and inferior parietal cortex. Different neural patterns were found underlying overestimated bias and underestimated bias. Specifically, connectivity regions with the dorsolateral prefrontal cortex, anterior cingulate cortex, and supramarginal gyrus form overestimated bias, while less regional connectivity forms underestimated bias. These findings provide a mechanistic account for the construction of metacognitive systematic bias.
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Affiliation(s)
- Peiyao Cong
- School of Psychology, Northeast Normal University, 5268 Renmin Street, Changchun, Jilin, 130024, China
| | - Yiting Long
- School of Psychology, Northeast Normal University, 5268 Renmin Street, Changchun, Jilin, 130024, China
| | - Xiaojing Zhang
- School of Psychology, Northeast Normal University, 5268 Renmin Street, Changchun, Jilin, 130024, China
| | - Yanlin Guo
- School of Psychology, Northeast Normal University, 5268 Renmin Street, Changchun, Jilin, 130024, China
| | - Yingjie Jiang
- School of Psychology, Northeast Normal University, 5268 Renmin Street, Changchun, Jilin, 130024, China.
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Wang X, Liu X, Chen L, Feng K, Ye Q, Zhu H. The Forward Effect of Delayed Judgments of Learning Is Influenced by Difficulty in Memory and Category Learning. J Intell 2023; 11:101. [PMID: 37367503 DOI: 10.3390/jintelligence11060101] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 05/03/2023] [Accepted: 05/23/2023] [Indexed: 06/28/2023] Open
Abstract
Delayed judgment of learning (JOL) is a widely used metacognitive monitoring strategy that can also enhance learning outcomes. However, the potential benefits of delayed JOL on subsequent learning of new material, known as the forward effect of delayed JOL, and its stability and underlying mechanisms have yet to be fully explored. In this study, we investigated the forward effect of delayed JOL using previously unexamined word pair materials and explored the boundary conditions of this effect by manipulating the difficulty of the materials. We also examined this effect within the context of category learning. Our findings demonstrate that delayed JOL significantly enhanced the retention of new information (Experiment 1A), while the forward effect of the delayed JOL occurred only for material with a certain degree of difficulty rather than for easy material (Experiment 1B). These findings were extended and replicated using category learning (Experiment 2). These results suggest that delayed JOL can be used as a preparation strategy for subsequent learning, particularly when faced with challenging materials. Our study provides novel insights into the potential benefits and limitations of delayed JOL and contributes to our understanding of the underlying mechanisms that govern metacognitive monitoring and learning strategies.
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Affiliation(s)
- Xun Wang
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, School of Psychology, Zhejiang Normal University, Jinhua 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China
| | - Xinyue Liu
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, School of Psychology, Zhejiang Normal University, Jinhua 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China
| | - Luyao Chen
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, School of Psychology, Zhejiang Normal University, Jinhua 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China
| | - Kaiqi Feng
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, School of Psychology, Zhejiang Normal University, Jinhua 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China
| | - Qun Ye
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, School of Psychology, Zhejiang Normal University, Jinhua 321004, China
- Key Laboratory of Intelligent Education Technology and Application of Zhejiang Province, Zhejiang Normal University, Jinhua 321004, China
| | - Haoliang Zhu
- Intelligent Laboratory of Child and Adolescent Mental Health and Crisis Intervention of Zhejiang Province, School of Psychology, Zhejiang Normal University, Jinhua 321004, China
- Department of Psychology, Wenzhou University, Wenzhou 325035, China
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Cong P, Jia N. An Event-Related Potential Study on Differences Between Higher and Lower Easy of Learning Judgments: Evidence for the Ease-of-Processing Hypothesis. Front Psychol 2022; 13:779907. [PMID: 35369252 PMCID: PMC8972125 DOI: 10.3389/fpsyg.2022.779907] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 02/21/2022] [Indexed: 11/19/2022] Open
Abstract
Easy of learning (EOL) judgments occur before active learning begins, and it is a prediction of how difficult it will be to learn new material in future learning. This study compared the amplitude of event-related potential (ERP) components and brain activation regions between high and low EOL judgments by adopting ERPs with a classical EOL judgment paradigm, aiming to confirm the ease-of-processing hypothesis. The results showed that (1) the magnitudes of EOL judgments are affected by encoding fluency cues, and the judgment magnitude increases with encoding fluency; (2) low EOL judgments are associated with higher N400 amplitude at the left superior frontal gyrus (SFG) and left middle frontal gyrus (MFG). High EOL judgments showed enlarged slow-wave (600–1,000 ms) potentials than low EOL judgments at the left medial temporal lobe (MTL), right ventromedial prefrontal cortex (VMPFC), and dorsolateral prefrontal cortex (DLPFC). Our results support the ease-of-processing hypothesis, particularly, by affirming that EOL judgments are affected by encoding fluency in two processing stages. N400 reflects the process of acquiring encoding fluency cues, while slow-wave indicates that individuals use encoding fluency cues for metacognitive monitoring.
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