Research

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. (in press). Integrating word embedding models with an instance memory model to explain false recognition. In M. Goldwater, F. Anggoro, B. Hayes, & D. Ong (Eds.), Proceedings of the 45th Annual Conference of the Cognitive Science Society. Sydney: Cognitive Science Society.

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

Chang, M., Brainerd, C. J., Toglia, M. P., & Schmidt, S. R. (2021). Norms for emotion-false memory lists. Behavior Research Methods, 53(1), 96-112. [DOI] [PDF]

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 metacognitive judgment and memory in terms of (a) what factors determine whether metamemory judgments track or deviate from actual memory; and (b) why and how making metamemory 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. [DOI] [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. [DOI] [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. [DOI] [PDF]

Many prior studies have demonstrated that the intensity of semantic attributes (e.g., M familiarity) in the to-be-remembered materials can influence the nature of encoding and thus the ultimate memory outcomes. Our research further reveals that not only the intensity but also the variability in semantic attributes (e.g., SD familiarity) affect recall accuracy. Recently, I have extended the memory effects of attribute ambiguity (indexed by SDs) from recall to recognition and from true memory to false memory.

Example publications:

Chang, M. & Brainerd, C. J. (in press). The recognition effects of attribute ambiguity.  Psychonomic Bulletin & Review.

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

Brainerd, C. J., Chang, M., & Bialer, D. M. (2021). Emotional ambiguity and memory. Journal of Experimental Psychology: General, 150(8), 1476-1499. [DOI] [PDF]

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. [DOI] [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. [DOI] [PDF]