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 (Brainerd & Reyna, 1995). I have used hypothesis-driven behavioral experimentation and mathematical modeling to investigate the process-level explanation of false memories.  Recently, I have been using computational modeling to gain a more comprehensive understanding of the cognitive processes that give rise to false memories.

Example publications:

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]

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. [DOI] [PDF]

The Interplay between Metacognition 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 metacognitive judgment and memory in terms of (a) what factors determine whether JOLs track or deviate from actual memory; and (b) why and how making JOLs can sometimes directly modify memory performance.  

Example publications:

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]

Chang, M. & Brainerd, C. J. (under revision). The font size effect depends on list relatedness. 

The Cognitive Effects of Semantic Attribute and Contextual Variability

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. My research further reveals that not only the intensity but also the variability in semantic attributes (e.g., SD familiarity) affect memory accuracy. More recently, I have also been investigating how variability in contextual repetitions (e.g., occurrence in the same versus distinct contexts) affects cognition.

Example publications:

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

Chang, M. & Brainerd, C. J. (under review). The recognition effects of attribute ambiguity. 

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]

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. [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]