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Richard E. Carson

Richard E. Carson

· Professor

Yale University · Biological Engineering

Active 1931–2024

h-index106
Citations50.2k
Papers1.0k309 last 5y
Funding$63.1M1 active
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About

Richard Carson is a professor of Radiology and Biomedical Imaging and of Biomedical Engineering at Yale University. He serves as the Director of Graduate Studies in Biomedical Engineering. His research focuses on biomedical imaging, particularly in the context of PET and MR signals, with an emphasis on pharmacokinetic physiologic modeling in simultaneous PET/MR imaging. Carson's work involves developing novel quantitation approaches for PET and MR signals, contributing to advancements in imaging techniques and data analysis. His role includes leadership within the Center for Molecular Imaging Technology and Translation, where he collaborates on projects aimed at improving imaging methodologies and their applications in biomedical research.

Research topics

  • Medicine
  • Pathology
  • Biology
  • Neuroscience
  • Psychology
  • Internal medicine
  • Biochemistry
  • Chemistry
  • Nuclear medicine
  • Machine Learning
  • Computer Science
  • Oncology
  • Artificial Intelligence
  • Econometrics
  • Psychiatry
  • Data science
  • Theoretical computer science
  • Cell biology
  • Cancer research
  • Immunology
  • Nuclear magnetic resonance
  • Mathematics
  • Physics
  • Audiology

Selected publications

  • Preclinical evaluation of a brain penetrant PARP PET imaging probe in rat glioblastoma and nonhuman primates

    European Journal of Nuclear Medicine and Molecular Imaging · 2023 · 15 citations

    • Nuclear medicine
    • Medicine
    • Pathology
  • Anatomically interpretable deep learning of brain age captures domain-specific cognitive impairment

    Proceedings of the National Academy of Sciences · 2023 · 116 citations

    • Psychology
    • Audiology
    • Neuroscience

    = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.

  • Mapping neurotransmitter systems to the structural and functional organization of the human neocortex

    Nature Neuroscience · 2022 · 748 citations

    • Neuroscience
    • Biology
    • Psychology

    Neurotransmitter receptors support the propagation of signals in the human brain. How receptor systems are situated within macro-scale neuroanatomy and how they shape emergent function remain poorly understood, and there exists no comprehensive atlas of receptors. Here we collate positron emission tomography data from more than 1,200 healthy individuals to construct a whole-brain three-dimensional normative atlas of 19 receptors and transporters across nine different neurotransmitter systems. We found that receptor profiles align with structural connectivity and mediate function, including neurophysiological oscillatory dynamics and resting-state hemodynamic functional connectivity. Using the Neurosynth cognitive atlas, we uncovered a topographic gradient of overlapping receptor distributions that separates extrinsic and intrinsic psychological processes. Finally, we found both expected and novel associations between receptor distributions and cortical abnormality patterns across 13 disorders. We replicated all findings in an independently collected autoradiography dataset. This work demonstrates how chemoarchitecture shapes brain structure and function, providing a new direction for studying multi-scale brain organization.

  • Reversal of synapse loss in Alzheimer mouse models by targeting mGluR5 to prevent synaptic tagging by C1Q

    Science Translational Medicine · 2022 · 105 citations

    • Neuroscience
    • Biology
    • Cell biology

    F]SynVesT-1 PET for SV2A and by histology, and the therapeutic benefit persisted after drug washout. Phospho-TAU accumulation in double knock-in mice was also reduced by SAM treatment. Single-nuclei transcriptomics demonstrated that SAM treatment in both models normalized expression patterns to a far greater extent in neurons than glia. Last, treatment prevented synaptic localization of the complement component C1Q and synaptic engulfment in AD mice. Thus, selective modulation of mGluR5 reversed neuronal gene expression changes to protect synapses from damage by microglial mediators in rodents.

  • Staging tau pathology with tau PET in Alzheimer’s disease: a longitudinal study

    Translational Psychiatry · 2021 · 65 citations

    • Oncology
    • Psychology
    • Internal medicine

    F-AV-1451 tau PET (baseline age 73.9 ± 7.7 years, 375 female) were stratified into five stages by a topographic PET staging scheme. Cognitive trajectories and clinical progression were compared across stages with or without further dichotomy of amyloid status, using linear mixed-effect models and Cox proportional hazard models. Significant cognitive decline was first observed in stage 1 when tau levels only increased in transentorhinal regions. Rates of cognitive decline and clinical progression accelerated from stage 2 to stage 3 and stage 4. Higher stages were also associated with greater CSF phosphorylated tau and total tau concentrations from stage 1. Abnormal tau accumulation did not appear with normal β-amyloid in neocortical regions but prompt cognitive decline by interacting with β-amyloid in temporal regions. Highly accumulated tau in temporal regions independently led to cognitive deterioration. Topographic PET staging scheme have potentials in early diagnosis, predicting disease progression, and studying disease mechanism. Characteristic tau spreading pattern in Alzheimer's disease could be illustrated with biomarker measurement under NIA-AA framework. Clinical-neuroimaging-neuropathological studies in other cohorts are needed to validate these findings.

  • Plasma phosphorylated-tau181 as a predictive biomarker for Alzheimer’s amyloid, tau and FDG PET status

    Translational Psychiatry · 2021 · 68 citations

    • Medicine
    • Pathology
    • Oncology

    Plasma phosphorylated-tau181 (p-tau181) showed the potential for Alzheimer's diagnosis and prognosis, but its role in detecting cerebral pathologies is unclear. We aimed to evaluate whether it could serve as a marker for Alzheimer's pathology in the brain. A total of 1189 participants with plasma p-tau181 and PET data of amyloid, tau or FDG PET were included from ADNI. Cross-sectional relationships of plasma p-tau181 with PET biomarkers were tested. Longitudinally, we further investigated whether different p-tau181 levels at baseline predicted different progression of Alzheimer's pathological changes in the brain. We found plasma p-tau181 significantly correlated with brain amyloid (Spearman ρ = 0.45, P < 0.0001), tau (0.25, P = 0.0003), and FDG PET uptakes (-0.37, P < 0.0001), and increased along the Alzheimer's continuum. Individually, plasma p-tau181 could detect abnormal amyloid, tau pathologies and hypometabolism in the brain, similar with or even better than clinical indicators. The diagnostic accuracy of plasma p-tau181 elevated significantly when combined with clinical information (AUC = 0.814 for amyloid PET, 0.773 for tau PET, and 0.708 for FDG PET). Relationships of plasma p-tau181 with brain pathologies were partly or entirely mediated by the corresponding CSF biomarkers. Besides, individuals with abnormal plasma p-tau181 level (>18.85 pg/ml) at baseline had a higher risk of pathological progression in brain amyloid (HR: 2.32, 95%CI 1.32-4.08) and FDG PET (3.21, 95%CI 2.06-5.01) status. Plasma p-tau181 may be a sensitive screening test for detecting brain pathologies, and serve as a predictive biomarker for Alzheimer's pathophysiology.

  • First-in-Human Evaluation of <sup>18</sup>F-SynVesT-1, a Radioligand for PET Imaging of Synaptic Vesicle Glycoprotein 2A

    Journal of Nuclear Medicine · 2020 · 130 citations

    Senior authorCorresponding
    • Nuclear medicine
    • Chemistry
    • Nuclear magnetic resonance

    F-SynVesT-1, displays excellent kinetic and in vivo binding properties in humans and holds great potential for the imaging and quantification of synaptic density in neuropsychiatric disorders.

  • Functional brain architecture is associated with the rate of tau accumulation in Alzheimer’s disease

    Nature Communications · 2020 · 338 citations

    • Neuroscience
    • Medicine
    • Biology

    In Alzheimer's diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation.

  • Challenges and Opportunities with Causal Discovery Algorithms: Application to Alzheimer’s Pathophysiology

    Scientific Reports · 2020 · 133 citations

    • Computer Science
    • Machine Learning
    • Artificial Intelligence

    Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer's disease (AD), a complex progressive disease, as a model because the well-established evidence provides a "gold-standard" causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the "gold standard" graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible.

  • Spread of pathological tau proteins through communicating neurons in human Alzheimer’s disease

    Nature Communications · 2020 · 532 citations

    • Neuroscience
    • Biology
    • Psychology

    Tau is a hallmark pathology of Alzheimer's disease, and animal models have suggested that tau spreads from cell to cell through neuronal connections, facilitated by β-amyloid (Aβ). We test this hypothesis in humans using an epidemic spreading model (ESM) to simulate tau spread, and compare these simulations to observed patterns measured using tau-PET in 312 individuals along Alzheimer's disease continuum. Up to 70% of the variance in the overall spatial pattern of tau can be explained by our model. Surprisingly, the ESM predicts the spatial patterns of tau irrespective of whether brain Aβ is present, but regions with greater Aβ burden show greater tau than predicted by connectivity patterns, suggesting a role of Aβ in accelerating tau spread. Altogether, our results provide evidence in humans that tau spreads through neuronal communication pathways even in normal aging, and that this process is accelerated by the presence of brain Aβ.

Recent grants

Frequent coauthors

  • Yiyun Huang

    Yale University

    391 shared
  • Nabeel Nabulsi

    Yale University

    362 shared
  • Jim Ropchan

    Yale University

    238 shared
  • Jean‐Dominique Gallezot

    Yale University

    213 shared
  • Mika Naganawa

    Yale University

    192 shared
  • Pierre N. Tariot

    Banner Alzheimer’s Institute

    179 shared
  • John C. Morris

    Washington University in St. Louis

    179 shared
  • Jacobo Mintzer

    Medical University of South Carolina

    173 shared

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