Cognitive Neuroscience Research

The Division of Cognitive Neuroscience focuses on cognitive experimental and neuroimaging approaches to cognitive functioning across the life span. There is an emphasis on normal and abnormal aging and degenerative neurological disease.

Areas of Research

  • Brain imaging
  • Cognitive aging
  • Cognitive disparities
  • Cognitive experimental and neuroimaging studies in aging and dementia
  • Cultural and educational experience
  • Development of neuroimaging-based biomarkers for aging, psychiatric and degenerative disease
  • Lifestyle, social intellectual activities and cognition – dementia
  • Longitudinal methods
  • Mechanisms relating nutrition, lifestyle, cognitive reserve factors with cognition - dementia
  • Multimodal imaging of age-related decline, such as fMRI and DTI
  • Multivariate analysis of clinical and basic neuroimaging data
  • Neuropsychology
  • Nutrition, diet and cognition - dementia
  • Physical activities, exercise and cognition dementia
  • Positive psychosocial factors
  • Robustness analysis of pre-processing in functional MRI

Studies

Current Cognitive Experimental Studies

  • Cognitive experimental and traditional neuropsychological battery-based studies of cognition in normal aging and our diseases of interest, including Alzheimer's, Parkinson's, and Huntington's disease.
  • Metacognition and cognitive control processes
  • Effects of literacy, education, ethnicity, and acculturation on cognition
  • Cognitive and exercise interventions for cognition
  • Cognition and functional capacity in Parkinson's and Huntington's diseases
  • Cognitive reserve
  • Social determinants of brain health including social isolation and loneliness, sleep hygiene, and sedentary behaviors / physical activity
  • Attentional bias in multiple sclerosis
  • Impact of diagnosis concealment vs. disclosure on neuropsychological function (cognition, mood) in multiple sclerosis

Current Cognitive Neuroimaging Studies

  • Networks underlying recognition and working memory in young adults, normal aging and Alzheimer's disease
  • Correlates of cognitive improvement in intervention studies
  • Correlates of aging and Alzheimer's disease in structural and resting CBF scans
  • Improved analytic methods for functional imaging
  • Developing a fMRI biomarker to predict memory impairment in adults with multiple sclerosis
  • Utilizing machine learning approaches to identify cognitive phenotypes in multiple sclerosis