About

Cassie Mogilner Holmes is a professor of marketing and behavioral decision making at UCLA Anderson School of Management, holding the Bud Knapp Marketing Professorship. Her research focuses on happiness, emphasizing the role of time in well-being. She studies how focusing on time rather than money can increase happiness, how the meaning of happiness evolves over a lifetime, and the happiness derived from ordinary and extraordinary experiences. Her findings highlight the importance of personal connections and being present in the moment for overall happiness. Holmes has published her research in top academic journals such as Psychological Science and the Journal of Consumer Research. Her work has been featured in prominent media outlets including NPR, The Economist, The New York Times, the Wall Street Journal, Scientific American, and the Boston Globe. She developed and teaches a popular course on applying the science of happiness to life design, which informs her book, 'Happier Hour,' a Wall Street Journal bestseller and Amazon Best Book of 2022. Prior to UCLA, she was a tenured faculty member at the Wharton School at the University of Pennsylvania, where she taught strategic brand management. Holmes earned her Ph.D. in marketing from Stanford and her B.A. in psychology from Columbia University.

Research topics

• Computer science
• Neuroscience
• Artificial intelligence
• Anatomy
• Biology

Selected publications

• The General Linear Model

  Elsevier eBooks · 2007-01-01 · 35 citations

  book-chapterSenior author
  PublisherDOI

• A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM)

  Philosophical Transactions of the Royal Society B Biological Sciences · 2001-08-29 · 2397 citations

  articleOpen access

  Motivated by the vast amount of information that is rapidly accumulating about the human brain in digital form, we embarked upon a program in 1992 to develop a four-dimensional probabilistic atlas and reference system for the human brain. Through an International Consortium for Brain Mapping (ICBM) a dataset is being collected that includes 7000 subjects between the ages of eighteen and ninety years and including 342 mono- and dizygotic twins. Data on each subject includes detailed demographic, clinical, behavioural and imaging information. DNA has been collected for genotyping from 5800 subjects. A component of the programme uses post-mortem tissue to determine the probabilistic distribution of microscopic cyto- and chemoarchitectural regions in the human brain. This, combined with macroscopic information about structure and function derived from subjects in vivo, provides the first large scale opportunity to gain meaningful insights into the concordance or discordance in micro- and macroscopic structure and function. The philosophy, strategy, algorithm development, data acquisition techniques and validation methods are described in this report along with database structures. Examples of results are described for the normal adult human brain as well as examples in patients with Alzheimer's disease and multiple sclerosis. The ability to quantify the variance of the human brain as a function of age in a large population of subjects for whom data is also available about their genetic composition and behaviour will allow for the first assessment of cerebral genotype-phenotype-behavioural correlations in humans to take place in a population this large. This approach and its application should provide new insights and opportunities for investigators interested in basic neuroscience, clinical diagnostics and the evaluation of neuropsychiatric disorders in patients.

  PublisherOA PDFDOI

• Cortical Change in Alzheimer's Disease Detected with a Disease-specific Population-based Brain Atlas

  Cerebral Cortex · 2001-01-01 · 446 citations

  article

  We report the first detailed population-based maps of cortical gray matter loss in Alzheimer's disease (AD), revealing prominent features of early structural change. New computational approaches were used to: (i) distinguish variations in gray matter distribution from variations in gyral patterns; (ii) encode these variations in a brain atlas (n = 46); (iii) create detailed maps localizing gray matter differences across groups. High resolution 3D magnetic resonance imaging (MRI) volumes were acquired from 26 subjects with mild to moderate AD (age 75.8+/-1.7 years, MMSE score 20.0+/-0.9) and 20 normal elderly controls (72.4+/-1.3 years) matched for age, sex, handedness and educational level. Image data were aligned into a standardized coordinate space specifically developed for an elderly population. Eighty-four anatomical models per brain, based on parametric surface meshes, were created for all 46 subjects. Structures modeled included: cortical surfaces, all major superficial and deep cortical sulci, callosal and hippocampal surfaces, 14 ventricular regions and 36 gyral boundaries. An elastic warping approach, driven by anatomical features, was then used to measure gyral pattern variations. Measures of gray matter distribution were made in corresponding regions of cortex across all 46 subjects. Statistical variations in cortical patterning, asymmetry, gray matter distribution and average gray matter loss were then encoded locally across the cortex. Maps of group differences were generated. Average maps revealed complex profiles of gray matter loss in disease. Greatest deficits (20-30% loss, P<0.001-0.0001) were mapped in the temporo-parietal cortices. The sensorimotor and occipital cortices were comparatively spared (0-5% loss, P>0.05). Gray matter loss was greater in the left hemisphere, with different patterns in the heteromodal and idiotypic cortex. Gyral pattern variability also differed in cortical regions appearing at different embryonic phases. 3D mapping revealed profiles of structural deficits consistent with the cognitive, metabolic and histological changes in early AD. These deficits can therefore be (i) charted in a living population and (ii) compared across individuals and groups, facilitating longitudinal, genetic and interventional studies of dementia.

  PublisherDOI

• High-resolution cerebellar anatomy

  Cambridge University Press eBooks · 2001-11-15 · 1 citations

  book-chapterSenior author

  Jansen and Brodal began their treatise on the cerebellum by pointing out its great morphological diversity across species, which appeared striking even within the mammals (Jansen and Brodal, 1954). While intriguing the early anatomists, this fascinating anatomy presents considerable challenges to current methods for imaging, mapping, and measuring morphology. These tasks are further complicated by today's focus on functional imaging, which requires that the brain be mapped in vivo. The cerebellum's gross features and major landmarks are easily distinguished with non-invasive techniques such as conventional magnetic resonance imaging (MRI), but novel techniques are required to discern its individual folia and deep nuclei. While the creation of stereotaxic atlas systems for the cerebral hemispheres has greatly facilitated the exchange and comparison of structural and functional data, the most ubiquitous stereotaxic systems and atlas spaces fail to define the cerebellum sufficiently in terms of its placement or delineation. This chapter describes progress in each of these problem areas. Specifically, it describes the use of a high-resolution cryosectioning approach that produces full-color, three-dimensional image volumes of in-situ anatomy and a multi-scan MRI approach to achieve superior in-vivo image volumes of cerebellar anatomy. It also describes efforts to rectify the standard cerebral atlases with multisubject mappings of this structure by use of informatics techniques and a deformable brain atlas.

  PublisherDOI

• Brain Abnormalities in Early-Onset Schizophrenia Spectrum Disorder Observed With Statistical Parametric Mapping of Structural Magnetic Resonance Images

  American Journal of Psychiatry · 2000-09-01 · 128 citations

  article

  OBJECTIVE: The purpose of this study was to assess neuroanatomic abnormalities in children and adolescents with childhood-onset schizophrenia by using whole-brain voxel-based morphometric analyses. Previous volumetric studies of brain abnormalities in childhood-onset schizophrenia have revealed anomalies similar to those in subjects with adult-onset schizophrenia. Specifically, low cerebral volume, high ventricular volume, and thalamic, basal ganglia, callosal, and temporal lobe abnormalities have been observed in childhood-onset schizophrenia. Relatively few anatomical structures have been delineated and measured in this rare population, partly because of the labor involved in the slice-by-slice region definition required of conventional volumetric image analyses. METHOD: The subjects were 10 normal children and adolescents and nine children and adolescents with early-onset schizophrenia (mean age at diagnosis, 11.0 years; range, 7-16 years). The authors conducted voxel-by-voxel and volumetric statistical analyses of high-resolution structural magnetic resonance images. RESULTS: Statistical parametric maps of gray matter, white matter, and CSF differences between the groups revealed that the subjects with early-onset schizophrenia had larger ventricles, predominantly in the posterior horns of the lateral ventricles, and midcallosal, posterior cingulate, caudate, and thalamic abnormalities. Volumetric analyses of the lateral ventricles in native image data space confirmed significantly higher volume in posterior, but not anterior, regions. Randomization tests confirmed the overall statistical significance of the group differences and validity of the parametric maps. CONCLUSIONS: These findings are generally consistent with the findings of other research groups, but localization of enlarged ventricles specific to the posterior region may be a new finding in the literature on childhood-onset schizophrenia.

  PublisherDOI

• Estimation of Brain Compartment Volume from MR Cavalieri Slices

  Journal of Computer Assisted Tomography · 2000-05-01 · 40 citations

  articleCorresponding

  PURPOSE: Recent theory has been developed to estimate volume from a systematic sample of tissue slices of a given thickness and to predict the corresponding error. Our goal was to check the error prediction formulas by resampling and to determine the minimum number of MR slices required to estimate the volumes of the cerebrum and of the compartments of gray matter (GM) and white matter (WM) with prescribed errors. METHOD: Our working data set comprised the GM and WM segmentations obtained from a paradigmatic high signal-to-noise ratio 3D spoiled GRASS MR volume data set for a single healthy human subject. The data were classified using a fuzzy clustering minimum distance algorithm. We thereby obtained a stack of 183 serial coronal slices of 1 mm thickness encompassing the whole cerebrum. Empirical resampling was carried out using the corresponding data vectors, and the theoretical error predictors were thereby checked for slice thicknesses of 1, 3, 9, and 27 mm, with a distance of 45 mm between slice midplanes. RESULTS: Irrespective of slice thickness, a minimum of 3, 5, and 10 slices provided estimates of the true total volume of GM and WM in the cerebrum with coefficients of error (CEs) of 10, 5, and 3%, respectively, where CE(V)% = 100 x SE(V)/V. For the cerebrum, a minimum of two, three, and four slices were required for CEs of the same precision. CONCLUSION: In combination with high signal-to-noise ratio and enhanced tissue contrast, Cavalieri slices are the most appropriate for MRI, they supply unbiased and highly efficient volume estimates of brain compartments. For a given number of slices, CE(V) decreases rapidly when the slices are thicker than the gaps between them; when the slices are thinner than the gaps, then CE(V) is similar to that in the situation when the slice thickness is zero.

  PublisherDOI

• Analyzing Functional Brain Images in a Probabilistic Atlas: A Validation of Subvolume Thresholding

  Journal of Computer Assisted Tomography · 2000-01-01 · 47 citations

  articleCorresponding

  PURPOSE: The development of structural probabilistic brain atlases provides the framework for new analytic methods capable of combining anatomic information with the statistical mapping of functional brain data. Approaches for statistical mapping that utilize information about the anatomic variability and registration errors of a population within the Talairach atlas space will enhance our understanding of the interplay between human brain structure and function. METHOD: We present a subvolume thresholding (SVT) method for analyzing positron emission tomography (PET) and single photon emission CT data and determining separately the statistical significance of the effects of motor stimulation on brain perfusion. Incorporation of a priori anatomical information into the functional SVT model is achieved by selecting a proper anatomically partitioned probabilistic atlas for the data. We use a general Gaussian random field model to account for the intrinsic differences in intensity distribution across brain regions related to the physiology of brain activation, attenuation effects, dead time, and other corrections in PET imaging and data reconstruction. RESULTS: H2(15)O PET scans were acquired from six normal subjects under two different activation paradigms: left-hand and right-hand finger-tracking task with visual stimulus. Regional region-of-interest and local (voxel) group differences between the left and right motor tasks were obtained using nonparametric stochastic variance estimates. As expected from our simple finger movement paradigm, significant activation (z = 6.7) was identified in the left motor cortex for the right movement task and significant activation (z = 6.3) for the left movement task in the right motor cortex. CONCLUSION: We propose, test, and validate a probabilistic SVT method for mapping statistical variability between groups in subtraction paradigm studies of functional brain data. This method incorporates knowledge of, and controls for, anatomic variability contained in modern human brain probabilistic atlases in functional statistical mapping of the brain.

  PublisherDOI

• Early cortical change in Alzheimer's disease detected using cortical pattern matching and a disease-specific population-based brain atlas

  NeuroImage · 2000-05-01 · 4 citations

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• Localizing Age-Related Changes in Brain Structure between Childhood and Adolescence Using Statistical Parametric Mapping

  NeuroImage · 1999-06-01 · 555 citations

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• In vivo evidence for post-adolescent brain maturation in frontal and striatal regions

  Nature Neuroscience · 1999-10-01 · 1439 citations

  letter
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Frequent coauthors

• Alan C. Evans

  Montreal Neurological Institute and Hospital

  27 shared

• D. Louis Collins

  Rutgers, The State University of New Jersey

  15 shared

• Lynda Mainville

  McGill University

  14 shared

• Arthur W. Toga

  14 shared

• Barbara E. Jones

  12 shared

• David MacDonald

  Minneapolis VA Medical Center

  11 shared

• Noor Jehan Kabani

  Sunnybrook Health Science Centre

  11 shared

• Paul M. Thompson

  University of Southern California

  10 shared

Awards & honors

• Early Career Award from the Association of Consumer Research
• Early Career Award from the Society of Consumer Psychology
• Best 40 Business Professors Under 40 by Poets & Quants