About
Ian H. Gotlib is the Marjorie Mhoon Fair Professor and Director of the Stanford Neurodevelopment, Affect, and Psychopathology (SNAP) Laboratory at Stanford University. His research examines psychobiological factors that increase the risk of developing depression and engaging in suicidal behaviors, focusing on neural, cognitive, social, endocrinological, and genetic influences in depressed individuals. He applies these findings to study predictors of depression in children at risk for the disorder and investigates the effects of early life stress on neurodevelopmental trajectories in boys and girls through puberty, aiming to explain the increased prevalence of depression and suicidal behaviors in adolescent girls. Additionally, Dr. Gotlib extends his research to the study of brain function, structure, endocrine function, and behaviors in neonates and infants raised in suboptimal environments. His work is supported primarily by grants from the National Institutes of Health, and he has received numerous awards for his contributions to psychopathology and depression research. Dr. Gotlib is a highly published scientist with over 500 articles, and he has authored or edited several books in his field. He holds a Ph.D. in Clinical Psychology from the University of Waterloo and is a fellow of several professional associations, including the American Psychological Association and the Association for Psychological Science.
Research topics
- Psychology
- Medicine
- Psychiatry
- Neuroscience
- Clinical psychology
- Gerontology
- Cognitive psychology
- Medical emergency
- Audiology
- Cardiology
- Developmental psychology
- Internal medicine
Selected publications
Scientific Reports · 2022 · 49 citations
- Medicine
- Clinical psychology
- Psychology
The impact of COVID-19-related stress on perinatal women is of heightened public health concern given the established intergenerational impact of maternal stress-exposure on infants and fetuses. There is urgent need to characterize the coping styles associated with adverse psychosocial outcomes in perinatal women during the COVID-19 pandemic to help mitigate the potential for lasting sequelae on both mothers and infants. This study uses a data-driven approach to identify the patterns of behavioral coping strategies that associate with maternal psychosocial distress during the COVID-19 pandemic in a large multicenter sample of pregnant women (N = 2876) and postpartum women (N = 1536). Data was collected from 9 states across the United States from March to October 2020. Women reported behaviors they were engaging in to manage pandemic-related stress, symptoms of depression, anxiety and global psychological distress, as well as changes in energy levels, sleep quality and stress levels. Using latent profile analysis, we identified four behavioral phenotypes of coping strategies. Critically, phenotypes with high levels of passive coping strategies (increased screen time, social media, and intake of comfort foods) were associated with elevated symptoms of depression, anxiety, and global psychological distress, as well as worsening stress and energy levels, relative to other coping phenotypes. In contrast, phenotypes with high levels of active coping strategies (social support, and self-care) were associated with greater resiliency relative to other phenotypes. The identification of these widespread coping phenotypes reveals novel behavioral patterns associated with risk and resiliency to pandemic-related stress in perinatal women. These findings may contribute to early identification of women at risk for poor long-term outcomes and indicate malleable targets for interventions aimed at mitigating lasting sequelae on women and children during the COVID-19 pandemic.
Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years
Human Brain Mapping · 2021 · 289 citations
- Psychology
- Neuroscience
- Developmental psychology
Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3–90 years
Human Brain Mapping · 2021 · 161 citations
- Psychology
- Neuroscience
- Gerontology
Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
NeuroImage · 2020 · 52 citations
- Psychology
- Cognitive psychology
- Neuroscience
Through the Human Connectome Project (HCP) our understanding of the functional connectome of the healthy brain has been dramatically accelerated. Given the pressing public health need, we must increase our understanding of how connectome dysfunctions give rise to disordered mental states. Mental disorders arising from high levels of negative emotion or from the loss of positive emotional experience affect over 400 million people globally. Such states of disordered emotion cut across multiple diagnostic categories of mood and anxiety disorders and are compounded by accompanying disruptions in cognitive function. Not surprisingly, these forms of psychopathology are the leading cause of disability worldwide. The Research Domain Criteria (RDoC) initiative spearheaded by NIMH offers a framework for characterizing the relations among connectome dysfunctions, anchored in neural circuits and phenotypic profiles of behavior and self-reported symptoms. Here, we report on our Connectomes Related to Human Disease protocol for integrating an RDoC framework with HCP protocols to characterize connectome dysfunctions in disordered emotional states, and present quality control data from a representative sample of participants. We focus on three RDoC domains and constructs most relevant to depression and anxiety: 1) loss and acute threat within the Negative Valence System (NVS) domain; 2) reward valuation and responsiveness within the Positive Valence System (PVS) domain; and 3) working memory and cognitive control within the Cognitive System (CS) domain. For 29 healthy controls, we present preliminary imaging data: functional magnetic resonance imaging collected in the resting state and in tasks matching our constructs of interest ("Emotion", "Gambling" and "Continuous Performance" tasks), as well as diffusion-weighted imaging. All functional scans demonstrated good signal-to-noise ratio. Established neural networks were robustly identified in the resting state condition by independent component analysis. Processing of negative emotional faces significantly activated the bilateral dorsolateral prefrontal and occipital cortices, fusiform gyrus and amygdalae. Reward elicited a response in the bilateral dorsolateral prefrontal, parietal and occipital cortices, and in the striatum. Working memory was associated with activation in the dorsolateral prefrontal, parietal, motor, temporal and insular cortices, in the striatum and cerebellum. Diffusion tractography showed consistent profiles of fractional anisotropy along known white matter tracts. We also show that results are comparable to those in a matched sample from the HCP Healthy Young Adult data release. These preliminary data provide the foundation for acquisition of 250 subjects who are experiencing disordered emotional states. When complete, these data will be used to develop a neurobiological model that maps connectome dysfunctions to specific behaviors and symptoms.
Molecular Psychiatry · 2020 · 299 citations
- Internal medicine
- Psychology
- Medicine
Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
Child Abuse & Neglect · 2020 · 528 citations
Senior authorCorresponding- Clinical psychology
- Psychology
- Psychiatry
Recent grants
NIH · $6.2M · 2012
NIH · $6.2M · 2017
NIH · $432k · 2016
NIH · $2.5M · 2015
NIH · $6.6M · 2023–2028
Frequent coauthors
- 198 shared
Tiffany C. Ho
University of California, Los Angeles
- 162 shared
Matthew D. Sacchet
Massachusetts General Hospital
- 100 shared
Anthony J. Gifuni
McGill University
- 94 shared
Jutta Joormann
- 92 shared
Lianne Schmaal
University of Melbourne
- 91 shared
Dick J. Veltman
- 84 shared
Paul M. Thompson
University of Southern California
- 83 shared
Henrik Walter
Humboldt-Universität zu Berlin
Labs
Education
- 1981
Ph.D., Clinical Psychology
University of Waterloo
Awards & honors
- Distinguished Investigator Award from the National Alliance…
- Joseph Zubin Award for lifetime research contributions to th…
- APA Award for Distinguished Scientific Contribution
- APS Distinguished Scientist Award
- MERIT award from NIMH
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