AgingLab.github.io/research.html at main · AgingLab/AgingLab.github.io · GitHub

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    <h3 style="text-align: left;">Brain age</h3>
    <p> Our lab studies brain aging by leveraging neuroimaging and machine learning to investigate individual
      variability in the aging trajectory. We focus on developing predictive models of brain age using MRI data and
      analyzing how deviations from normative aging relate to cognitive decline and other risk factors. A key aspect of
      our research involves examining the issue of residual correlations in brain age prediction models, recognizing
      their implications for bias and interpretability. By refining predictive models and incorporating multimodal
      imaging approaches, our lab aims to improve the accuracy and interpretability of brain age predictions, ultimately
      contributing to a deeper understanding of the mechanisms underlying brain aging.</p>

    <h3 style="text-align: left;">Parkinson's disease</h3>
    <p> Our lab investigates the neural mechanisms underlying Parkinson’s disease, with a focus on structural and
      functional brain changes from the earliest stages of the disease. Using advanced neuroimaging techniques, we
      analyze patterns of atrophy and altered connectivity in patients with Parkinson’s to better understand disease
      progression. A key aspect of our research involves network-based analyses, which have revealed distinct structural
      connectivity alterations associated with early-stage Parkinson’s. Additionally, our work explores the relationship
      between brain network integrity and cognitive decline, aiming to identify neuroimaging biomarkers that could
      improve early diagnosis and prognosis. By refining predictive models and integrating multimodal imaging
      approaches, we seek to enhance our understanding of Parkinson’s disease and contribute to the development of
      targeted interventions.</p>

    <h3 style="text-align: left;">Postmortem neuroimaging</h3>
    <p> Text to be added.</p>

    <h3 style="text-align: left;">Neurobiology of obesity</h3>
    <p> Using longitudinal data from an obesity cohort undergoing bariatric surgery, We identified brain-wide structural
      changes and activation patterns related to obesity that could be recovered after weight loss due to bariatric
      surgery. Finally, We applied the previous model of healthy brain age prediction and found an older brain age for
      individuals with obesity compared to individuals with normal weight. The results suggest that obesity-related
      brain health abnormalities might be reversed by significant and sustained weight loss and improvements in
      cardiometabolic health.
      <li>Zeighami Y, et al "Impact of weight loss on brain age: Improved brain health following bariatric surgery"
        NeuroImage 2022; 259: 119415 </li>
      <li> Zeighami Y, et al “Spontaneous Neural Activity Changes after Bariatric Surgery: a resting-state fMRI study”.
        Neuroimage 2021; 241, 118419 </li>

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