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The neural basis of judgments-of-lea...

Kao, Yun-Ching.

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The neural basis of judgments-of-learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	The neural basis of judgments-of-learning./
Author:	Kao, Yun-Ching.
Description:	102 p.
Notes:	Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5435.
Contained By:	Dissertation Abstracts International67-09B.
Subject:	Biology, Neuroscience. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3235247
ISBN:	9780542894565

The neural basis of judgments-of-learning.
Kao, Yun-Ching.

The neural basis of judgments-of-learning. - 102 p.

Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5435.

Thesis (Ph.D.)--Stanford University, 2006.

A critical aspect of learning is the ability to self-evaluate whether that learning was successful. Such judgments-of-learning (JOLs) are of particular interest because these processes can enhance the effectiveness of learning by guiding the allocation of resources at a time when information remains available for learning. JOL paradigms require participants to predict during encoding whether stimuli have been successfully learned (i.e., are likely to be remembered or forgotten in a later test of retention). Although research on JOLs has spanned the last three decades, little is known about the neural mechanisms underlying JOLs. Using functional magnetic resonance imaging (fMRI), the studies in this dissertation are the first to examine the neural basis of JOLs in healthy adults. The first study identified brain regions supporting JOLs (predictions of encoding success) and examined whether these regions are the same as or different from those supporting learning itself (actual encoding success). The results demonstrated that the ventromedial prefrontal cortex (VMPFC) supported predictions of encoding success but not actual encoding success. In contrast, the medial temporal lobes supported actual encoding success but not predicted encoding success. Furthermore, activations in VMPFC correlated with individual differences in the accuracy of JOLs, which points to the importance of VMPFC in JOL accuracy. The second study examined JOL strategies that differ in effectiveness to address the hypothesis that VMPFC supports accurate JOLs by integrating converging signals from subordinate neural systems. This study also explored behavioral and neural differences amongst individuals in their utilization of JOL strategies. We found that VMPFC activations varied with the effectiveness of JOL strategies. In addition, good predictors adaptively changed their JOL strategies and showed greater VMPFC activations than poor predictors. These studies are the first to explore the neural basis of JOLs and are part of a handful of studies that examined individual differences in JOL. Results from the present studies provide hypotheses that will motivate future cognitive and neuroscience research on JOLs, and have implications for research in neuroeconomics, affective neuroscience, developmental neuroscience, and neuropsychology.

ISBN: 9780542894565Subjects--Topical Terms:

1017680
Biology, Neuroscience.

The neural basis of judgments-of-learning.
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100 1 $a Kao, Yun-Ching. $3 1924089
245 1 4 $a The neural basis of judgments-of-learning.
300 $a 102 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-09, Section: B, page: 5435.
500 $a Adviser: Anthony D. Wagner.
502 $a Thesis (Ph.D.)--Stanford University, 2006.
520 $a A critical aspect of learning is the ability to self-evaluate whether that learning was successful. Such judgments-of-learning (JOLs) are of particular interest because these processes can enhance the effectiveness of learning by guiding the allocation of resources at a time when information remains available for learning. JOL paradigms require participants to predict during encoding whether stimuli have been successfully learned (i.e., are likely to be remembered or forgotten in a later test of retention). Although research on JOLs has spanned the last three decades, little is known about the neural mechanisms underlying JOLs. Using functional magnetic resonance imaging (fMRI), the studies in this dissertation are the first to examine the neural basis of JOLs in healthy adults. The first study identified brain regions supporting JOLs (predictions of encoding success) and examined whether these regions are the same as or different from those supporting learning itself (actual encoding success). The results demonstrated that the ventromedial prefrontal cortex (VMPFC) supported predictions of encoding success but not actual encoding success. In contrast, the medial temporal lobes supported actual encoding success but not predicted encoding success. Furthermore, activations in VMPFC correlated with individual differences in the accuracy of JOLs, which points to the importance of VMPFC in JOL accuracy. The second study examined JOL strategies that differ in effectiveness to address the hypothesis that VMPFC supports accurate JOLs by integrating converging signals from subordinate neural systems. This study also explored behavioral and neural differences amongst individuals in their utilization of JOL strategies. We found that VMPFC activations varied with the effectiveness of JOL strategies. In addition, good predictors adaptively changed their JOL strategies and showed greater VMPFC activations than poor predictors. These studies are the first to explore the neural basis of JOLs and are part of a handful of studies that examined individual differences in JOL. Results from the present studies provide hypotheses that will motivate future cognitive and neuroscience research on JOLs, and have implications for research in neuroeconomics, affective neuroscience, developmental neuroscience, and neuropsychology.
590 $a School code: 0212.
650 4 $a Biology, Neuroscience. $3 1017680
650 4 $a Psychology, Psychobiology. $3 1017821
650 4 $a Psychology, Cognitive. $3 1017810
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773 0 $t Dissertation Abstracts International $g 67-09B.
790 1 0 $a Wagner, Anthony D., $e advisor
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791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3235247