About

Brandon Gavett, Ph.D., ABPP-CN, is an Associate Professor of Neurology at the UC Davis School of Medicine. He is a board-certified clinical neuropsychologist whose work employs advanced psychometric methods such as latent variable modeling and item response theory, along with machine learning techniques, to enhance understanding of how cognitive abilities change during late life as a result of aging and neurodegenerative diseases. His research interests focus on risk and resilience factors—including cognitive reserve, brain reserve, and brain maintenance—and how these traits are established and maintained throughout the lifespan. His work integrates data related to cognitive functioning, neuroimaging, biomarkers, personality, and lifestyle variables, with an emphasis on understanding, characterizing, and addressing health disparities in cognitive aging that impact different racial and ethnic groups. Dr. Gavett conducts his research as part of the UC Davis Alzheimer’s Disease Research Center, one of approximately 30 NIH-funded ADRCs nationwide. The UC Davis ADRC has been following study participants for over 20 years in some cases, collecting clinical, neuroimaging, and biomarker data relevant to Alzheimer’s disease and related dementias.

Research topics

• Psychology
• Medicine
• Developmental psychology
• Neuroscience
• Cognitive psychology
• Biology
• Audiology
• Demography
• Pathology
• Psychiatry

Selected publications

• Association of apolipoprotein E genotype with cognitive performance: findings from the University of California, Davis Alzheimer's Disease Research Center longitudinal diversity cohort

  Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · 2026-01-01

  articleOpen access

  Abstract INTRODUCTION The apolipoprotein E (ApoE) ε4 allele is a key genetic risk for Alzheimer's disease, but its effects may differ by heritage. We examined how ApoE4 influences hippocampal volume, episodic memory, and clinical syndrome across race and ethnicity (ethnoracial) groups. METHODS We analyzed 946 participants with the ApoE genotype, clinical diagnosis, and magnetic resonance imaging scans. Regression and structural equation modeling tested ApoE4's impact on cognition and whether an ethnoracial group consisting of 486 White, 234 Black/African American, or 226 Hispanic/Latino individuals moderated these effects. RESULTS ApoE4 prevalence increased with the clinical syndrome (odds ratio [OR] = 3.0, p < 0.0001). It correlated with lower hippocampal volume ( ß = −0.14, p < 0.001) and weaker memory performance ( ß = −0.21, p < 0.001). The indirect effect of ApoE4 via hippocampal volume was largest among White participants. DISCUSSION ApoE4's influence on hippocampal volume, episodic memory and clinical syndrome varies by ethnoracial group, with the strongest effects among White individuals. Our findings necessitate further AD biomarker research, as standard markers may not apply universally.

  PublisherDOI

• Domain-specific changes in everyday cognition: Associations with diagnosis change and gray matter volume change.

  Neuropsychology · 2025-10-23 · 1 citations

  articleOpen access1st authorCorresponding

  OBJECTIVE: Declines in everyday cognitive functioning are a common occurrence in late life. The present study sought to understand how informant-rated everyday cognitive abilities related to memory, language, spatial skills, planning, organization, and divided attention-as measured by the Everyday Cognition (ECog) scale-change over time in a diverse sample of older adults. METHOD: = 264)-cross-sectional and longitudinal total gray matter and hippocampus volume. RESULTS: ECog domains changed at different rates when modeled as a function of diagnosis change; differences in domain were most apparent in the stable mild cognitive impairment (MCI)-to-MCI and MCI-to-dementia conversion groups. By contrast, ECog domains changed at the same rate when modeled as a function of baseline gray matter volume and longitudinal gray matter volume change, corresponding to other research suggesting that cognitive domains change at relatively uniform rates over time. In separate models, total gray matter and hippocampus atrophy were salient predictors of ECog score changes. At baseline, hippocampus volume was the strongest predictor of ECog intercepts. CONCLUSIONS: Although some caution is warranted interpreting score changes due to floor and ceiling effects, the ECog appears sensitive to underlying gray matter atrophy and change in clinical disease severity when used longitudinally. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

  PublisherDOI

• Harmonized cognitive performance in an older adult cohort of Vietnamese American immigrants: The VIP study

  Alzheimer s & Dementia · 2025-05-01 · 2 citations

  articleOpen access1st authorCorresponding

  INTRODUCTION: Vietnamese Americans represent an understudied population with unique risk factors relevant to cognitive aging. The current study sought to model global cognition in the Vietnamese Insights into Cognitive Aging Program (VIP) study and harmonize ability estimates with the National Alzheimer's Coordinating Center (NACC) Uniform Data Set. METHODS: Cognitive data from VIP (N = 548) and NACC (N = 15,923) were analyzed using item response theory. Seven common items were assessed for differential item functioning (DIF); items without salient DIF were used to harmonize the cognitive composite score across the two cohorts. RESULTS: Although five of the seven common items showed evidence of DIF, the magnitude of this DIF was negligible, affecting the factor score estimates of only 12 (2.19%) VIP participants by more than one standard error. DISCUSSION: Global cognitive functioning can be estimated in Vietnamese American immigrants with minimal bias and psychometrically matched to one of the largest studies of cognitive aging and dementia worldwide. HIGHLIGHTS: This is the first known study to model cognition in older Vietnamese Americans. Global cognition was harmonized with minimal bias across two diverse cohorts. Differential item functioning was found in five of seven items, but the impact was not salient. Results create new opportunities to study health disparities in an underrepresented group.

  PublisherOA PDFDOI

• Sex/gender differences in domain‐specific cognitive decline by mid‐ and late‐life body mass index

  Alzheimer s & Dementia · 2025-12-01

  articleOpen access

  BACKGROUND: ) with cognition, but whether the association between BMI and cognitive decline varies by gender among racially-diverse older adults remains less understood. METHOD: Analyses used data from 1,711 participants in a harmonized cohort of racially/ethnically diverse older adults (LifeAfter90, KHANDLE, STAR) with BMI measured during mid- (ages 40-60) and late-life (≥65). Verbal episodic memory (VEM) and executive function (EF) were measured using z-standardized Spanish and English Neuropsychological Assessment Scales. Mid- and late-life BMI were obtained from the first available health records at each life stage and categorized into normal, overweight, and obese using race-specific cutoffs. Separate linear mixed models explored sex/gender differences in mid- and late-life BMI effects on cognitive decline using three-way interaction (sex/gender*BMI category*time) and sex/gender-stratified analyses. Models were adjusted for demographics, assessment-mode (in-person vs phone), and visit 1(Y/N) to account for practice-effects. RESULT: Participants were 62% women and had a mean age of 79±9.7 at first cognitive assessment (Table 1). At mid-life (mean BMI age=48±6.8), 22% of participants had obesity, 37% had overweight, and 41% had normal BMI. At late-life (mean BMI age=71±6.8), 36% of participants had obesity, 42% had overweight, and 21% had normal BMI. Neither mid- nor late-life BMI category were associated with EF decline, regardless of sex/gender (interaction p >0.10). Associations of mid-life obese BMI, mid-life overweight BMI, and late-life overweight BMI on VEM decline differed by gender (p <0.10). Stratified analyses found that among women, those with higher mid-life BMI had slower decline in VEM, though the difference was not significantly different than women with normal midlife BMI (overweight: (β(95%CI):0.03(-0.03,0.08); obese:0.01(-0.02,0.05)). Among men, those with obese BMI at mid-life had faster decline (-0.07(-0.14,-0.001)) than those with normal BMI. In late-life, women with higher BMI (obese: -0.03(-0.09,0.02), overweight:-0.05(-0.10,0.01)) trended towards a faster decline in VEM, whereas men with higher BMI at late-life (obese: 0.01(-0.05,0.08), overweight: (0.05(-0.01,0.11)) trended towards less decline (Figure 1). CONCLUSION: These findings suggests that mid-life and late-life BMI may have differential associations with VEM in men and women. This may suggest differences in underlying mechanisms of cognitive decline between sex/gender.

  PublisherOA PDFDOI

• Translation with ongoing adaptation and improvement (ToAI) framework: A community‐informed, structured, iterative approach to culturally adapting cognitive assessment tools

  Alzheimer s & Dementia Translational Research & Clinical Interventions · 2025-04-01 · 1 citations

  articleOpen access

  INTRODUCTION: Alzheimer's disease (AD) and related dementias (ADRD) are increasing globally, including in the United States, but the fast-growing Vietnamese American population remains understudied, with a significant lack of culturally adapted neuropsychological assessment tools. The Vietnamese Insights into Cognitive Aging Program (VIP) addresses this gap as the first longitudinal cohort study focused on this community. METHODS: This paper (1) describes the assessment instruments, including a neuropsychological battery selected for the VIP, and (2) introduces the Translation with Ongoing Adaptation and Improvement (ToAI) framework, an innovative and practical method for culturally informed translation and adaptation. RESULTS: The ToAI framework followed a nine-step process: preparation, translation, native-speaker review, VIP team review, external panel review, pilot testing, proofreading, final formatting, and ongoing review and improvement. DISCUSSION: The ToAI framework was efficient, and the ongoing improvement component was particularly beneficial. It is recommended for inclusion in future cross-cultural research involving translation and adaptation processes. Highlights: The Translation with Ongoing Adaptation and Improvement (ToAI) framework.Cross-cultural translation and adaptation of psychological assessment instruments.Neuropsychological assessment for Vietnamese American older adults.The Vietnamese Insights into Cognitive Aging Program (VIP).

  PublisherOA PDFDOI

• The consequences of changes to neuropsychological test batteries on measuring cognitive decline in long‐running studies of cognitive aging and dementia

  Alzheimer s & Dementia · 2025-12-01

  articleOpen access

  BACKGROUND: Several large, representative studies of older adults, like the US Health and Retirement Study (HRS), have collected longitudinal cognitive data on their participants; however, the cognitive batteries used by the HRS have changed over time, including the introduction of the Harmonized Cognitive Assessment Protocol (HCAP) battery for a subset of HRS participants. When cognitive batteries change over time, changes in measurement properties might result in misleading findings about cognitive trajectories. The aim of this study was to use simulation methods to assess the magnitude of bias in estimating cognitive decline that is induced by test batteries that changed over time. METHOD: We simulated true cognition using non-linear models of cognitive change derived from four harmonized longitudinal cognitive aging studies (UC Davis Alzheimer' Disease Research Center longitudinal cohort, Kaiser Healthy Aging and Diverse Life Experiences study, Kaiser Study of Healthy Aging in African Americans, Kaiser Life After 90 Study). Empirical HRS-HCAP item parameters were used as true item parameters, and item response theory methods were used to simulate measured test results for different batteries of cognitive tests in HRS and HRS-HCAP. We estimated "blended" cognitive trajectories, artificially introducing mid-course changes of the simulated test used to measure cognition. To illustrate the impact of these changes, we then used linear mixed-effects models to estimate 11-year cognitive trajectories, overall and by quartile of true decline. RESULT: Using instruments with the highest measurement precision led to estimated cognitive trajectories that best matched the truth. At the same time, estimated trajectories using less informative test versions were very closely related (Figure 1), such that blended trajectories did not deviate from the truth substantially (Figure 2). CONCLUSION: Our results support the use of high-quality instruments, like the HCAP battery, for optimally studying cognitive trajectories. However, differences between estimated HCAP and HRS-TICS trajectories were small, suggesting that, in practice, changes in test batteries over time may not meaningfully affect estimates of cognitive decline.

  PublisherOA PDFDOI

• A cognitive ability profile can provide a valid phenotype for future cognitive resilience to brain aging

  Alzheimer s & Dementia · 2025-12-01

  articleOpen access1st authorCorresponding

  BACKGROUND: Individual differences have been observed in the association between neurodegenerative brain changes and rates of cognitive decline. People who experience less rapid decline than expected based on neurodegeneration are described as being cognitively resilient to brain aging. We hypothesized that patterns of cognitive strengths and weaknesses (certain cognitive profiles) can provide a valid phenotype of prospective resilience. METHOD: Participants (N = 2432) were from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study (1/2/3/GO). There were three analytic phases: 1) generate an estimate of prospective resilience; 2) use that resilience estimate to develop a baseline cognitive resilience phenotype; 3) validate the phenotype longitudinally. In the first phase, prospective resilience was defined as the discrepancy between rates of future cognitive and brain change (cognitive slope minus brain slope). In the second phase, a bifactor confirmatory factor analysis model defined the cognitive resilience phenotype as a latent variable representing the variance that the observed cognitive test scores shared with the prospective resilience estimate from phase 1. In the third phase, we used regression in a held-out sample to test the hypothesized interaction between the resilience phenotype and brain volume change when predicting longitudinal cognitive decline (i.e., does the phenotype modify the association between brain atrophy and rate of cognitive decline?). RESULT: The cognitive performance indicators that most strongly contributed to the resilience phenotype were Trail Making Test B (loading = .73), animal fluency (loading = .67), and Boston Naming Test (loading = .67; Table 1). The cognitive resilience phenotype moderated the regression of cognitive slope on brain slope in the held-out sample (B=-0.043, SE=0.016; Table 2, Figure 1). CONCLUSION: A cross-sectional estimate of prospective cognitive resilience against brain atrophy can be constructed from the ADNI neuropsychological test battery. This phenotype, which draws heavily upon measures of processing speed/executive functioning, category fluency, verbal naming, and immediate recall, can predict the extent to which future brain atrophy will impact rates of cognitive decline. Examining cognitive phenotypes associated with more resilient cognitive aging may help to understand neural systems that underpin resilience, potentially leading to resilience-promoting interventions and new opportunities to efficiently monitor changes in resilience over time.

  PublisherOA PDFDOI

• Sex differences in the association between episodic memory residual reserve index and change in executive function

  Aging Brain · 2025-01-01 · 1 citations

  articleOpen access

  ε4 alleles). A three-way interaction was observed between cognitive reserve, brain integrity, and sex on the EF slope. Females benefitted more than males from the protective effects of cognitive reserve at low levels of brain integrity. Sex differences in the protective effect of cognitive reserve were not moderated by brain beta-amyloid burden.

  PublisherDOI

• Machine learning diagnosis of cognitive impairment and dementia in harmonized older adult cohorts

  Alzheimer s & Dementia · 2025-08-01 · 1 citations

  articleOpen access

  INTRODUCTION: Clinical diagnosis (normal cognition, mild cognitive impairment [MCI], dementia) is critical for understanding cognitive impairment and dementia but can be resource intensive and subject to inconsistencies due to complex clinical judgments that are required. Machine learning approaches might provide meaningful additions and/or alternatives to traditional clinical diagnosis. METHODS: The study sample was composed of three harmonized longitudinal cohorts of demographically diverse older adults. We used the XGBoost extreme gradient boosting platform to predict clinical diagnosis using different feature sets. RESULTS: Measures of cognition were especially important predictive features of clinical diagnosis. Prediction accuracy was higher in a sample that had longer follow-up, better balance across diagnostic outcomes, and both self- and informant-report independent function measures. DISCUSSION: Algorithmic diagnosis might be a meaningful substitute for clinical diagnosis in studies in which clinical evaluation and diagnosis are not feasible for all participants and may provide a standardized alternative when clinical diagnosis is available. HIGHLIGHTS: A machine learning algorithm was used to diagnose cognitive impairment and dementia. Measures of cognition were strongest predictive features for clinical diagnosis. Algorithm accuracy was improved by informant-report independent function measures. Algorithmic diagnosis might be an alternative if clinical diagnosis is not feasible. Standardization is an important advantage of algorithmic diagnosis.

  PublisherOA PDFDOI

• Examining the Consequences of Neuropsychological Test Battery Changes on Measuring Cognitive Decline

  Innovation in Aging · 2025-12-01

  articleOpen access

  Abstract Large, representative studies of older adults have collected longitudinal cognitive data, but cognitive batteries often change over time. When cognitive batteries change, changes in measurement properties may result in misleading findings about cognitive trajectories. Using the Health and Retirement Study (HRS) as an example, we used simulation methods to assess the magnitude of bias in estimating cognitive decline induced by changing test batteries over time. We first simulated true cognition values using non-linear models of cognitive change derived from four harmonized longitudinal cognitive aging studies. We then used item response theory (IRT) methods to simulate measured test results for different cognitive testing batteries, including the introduction of the Harmonized Cognitive Assessment Protocol (HCAP) for a subset of HRS participants. We then estimated blended cognitive trajectories, artificially introducing changes of the simulated test to measure cognition. To illustrate the impact of these changes, we used linear mixed-effects models to estimate 11-year cognitive trajectories, overall and by quartile of true decline. Using instruments with the highest measurement precision led to estimated cognitive trajectories that best matched the truth; however, estimated trajectories using less informative test versions did not deviate from the truth by an appreciable amount. As such, we conclude that in practice, changes in test batteries over time may not meaningfully affect estimates of cognitive decline when IRT scoring is used.

  PublisherOA PDFDOI

Frequent coauthors

• Robert A. Stern

  Boston University

  118 shared

• C Golden

  84 shared

• Ann C. McKee

  United States Department of Veterans Affairs

  67 shared

• Robert C. Cantu

  Emerson Hospital

  66 shared

• Christopher J. Nowinski

  Boston University

  64 shared

• Daniel H. Daneshvar

  Harvard University

  56 shared

• Neil W. Kowall

  University of California, San Francisco

  53 shared

• Andrew E. Budson

  VA Boston Healthcare System

  51 shared

Education

• Postdoctoral Resident, Alzheimer's Disease Center

  Boston University School of Medicine

  2009

• Psychology Intern

  VA Connecticut Health System West Haven Campus

  2007

• Ph.D.

  University at Albany Department of Psychology

  2007