The Formation Mechanism of False Memory

One line of my research focuses on understanding the formation mechanism of false memory using the framework of fuzzy-trace theory (FTT; Brainerd & Reyna, 1995). I have used hypothesis-driven behavioral experimentation and mathematical modeling to investigate the unique role of "gist" in false memory formation. Recently, I have been conducting computational implementations of FTT to formulate the episodic representation and processing mechanism that give rise to false memories.

Example publications:

Chang, M., Johns, B. T. & Brainerd, C. J. (under review). True and false recognition in MINERVA2: A computational implementation of fuzzy-trace theory. 

Chang, M., & Brainerd, C. J. (2021). Semantic and phonological false memory: A review of theory and data. Journal of Memory and Language, 119, 104210. [PDF]

Brainerd, C. J., Chang, M., & Bialer, D. M. (2020). From association to gist. Journal of Experimental Psychology: Learning, Memory and Cognition, 46(11), 2106-2127. [PDF]

The Interplay between Metamemory and Memory

People often regulate their learning based on metacognitive judgments, which refer to people's self-monitoring of their learning. My research aims at unveiling the complex interplay between metamemory and memory in terms of (a) what factors determine whether metacognitive judgments track or deviate from actual memory, and (b) why and how making metacognitive judgments can sometimes directly modify memory performance.  

Example publications:

Chang, M. & Brainerd, C. J. (2023). The font size effect depends on list relatedness. Memory & Cognition. [PDF] 

Chang, M. & Brainerd, C. J. (2022). Changed-goal or cue-strengthening? Examining the reactivity of judgments of learning with the dual-retrieval model. Metacognition and Learning. [PDF] 

Chang, M. & Brainerd, C. J. (2022). Association and dissociation between judgments of learning and memory: A meta-analysis of the font size effect. Metacognition and Learning, 17, 443-476. [PDF]

The Memory Effects of Semantic and Contextual Factors

Semantic attributes are building blocks of meanings (e.g., valence indicates how pleasant an item is), and the intensity of semantic attributes (e.g., M valence ratings) is often found to impact memory. Our research further reveals that not only the intensity but also the variability in semantic attributes (e.g., valence rating SD) affect memory. Recently, I have also been examining the memory effects of contextual diversity (i.e., the number of distinct contexts where an item occurs) as opposed to the number of sheer item repetitions.

Example publications:

Chang, M., Jones, M. N. & Johns, B. T. (2023). Comparing word frequency, semantic diversity, and semantic distinctiveness in lexical organization. Journal of Experimental Psychology: General. [PDF] 

Chang, M. & Brainerd, C. J. (2023). The recognition effects of attribute ambiguity.  Psychonomic Bulletin & Review. [PDF] 

Brainerd, C. J., Chang, M., Bialer, D. M., & Toglia, M. P. (2021). Semantic ambiguity and memory. Journal of Memory and Language, 121, 104286. [PDF]

The Age-Related and Disease-Related Changes in Cognition

To expand the scope of my research on memory and metacognition and to develop a larger theoretical backdrop for understanding these cognitive functions, I have also used behavioral experimentation and large-scale analyses of existing datasets to examine how cognitive functions change with healthy aging, mild cognitive impairment (MCI), and Alzheimer's disease (AD). 

Example publications:

Chang, M. & Brainerd, C. J. (2022). Predicting conversion from mild cognitive impairment to Alzheimer’s disease with multimodal factor scores. Journal of Clinical and Experimental Neuropsychology, 44(4), 316-335. [PDF]

Chang, M., & Brainerd, C. J. (2021). Factor analyses of the ADNI neuropsychological battery: An examination of diagnostic and longitudinal invariance. Neuropsychology, 35(4), 434-450. [PDF]