Alexander S. Weigard, Ph.D.

T-32 Post-Doctoral Fellow, U-M Addiction Center


Alexander Weigard is a Postdoctoral Research Fellow at the University of Michigan Addiction Center in the Department of Psychiatry. He is interested in using computational and network modeling methods to better characterize cognitive and neural risk factors for the development of attention problems and substance use disorders. He hopes to integrate this work with machine learning to enhance the real-world prediction of problematic substance use, psychopathology and associated outcomes.

Areas of Interest

  • Computational Psychiatry
  • Developmental Cognitive Neuroscience
  • Clinical Applications of Cognitive Modeling
  • Network Analyses
  • Substance Use Disorders
  • Attention Problems / ADHD


  • Penn State University, Ph.D. - Clinical Psychology, Specialization in Cognitive and Affective Neuroscience
  • Penn State University, M.S. - Psychology
  • Temple University, B.A. - Psychology, Minor in Cognitive Neuroscience

Select Publications

Weigard, A., Soules, M., Ferris, B., Zucker, R. A., Sripada, C., & Heitzeg, M. (2020). Cognitive modeling informs interpretation of go/no-go task-related neural activations and their links to externalizing psychopathologyBiological Psychiatry: Cognitive Neuroscience and Neuroimaging5(5), 530-541.

Weigard, A., Hardee, J. E., Zucker, R. A., Heitzeg, M. M., & Beltz, A. M. (2020). The role of pubertal timing in the link between family history of alcohol use disorder and late adolescent substance useDrug & Alcohol Dependence, 107955.

Weigard, A., Sathian, K., & Hampstead, B. M. (2020). Model-based assessment and neural correlates of spatial memory deficits in mild cognitive impairmentNeuropsychologia136, 107251.

Weigard, A., Heathcote, A., & Sripada, C. (2019). Modeling the effects of methylphenidate on interference and evidence accumulation processes using the conflict linear ballistic accumulatorPsychopharmacology236(8), 2501-2512.

Weigard, A., Heathcote, A., Matzke, D., & Huang-Pollock, C. (2019). Cognitive modeling suggests that attentional failures drive longer stop-signal reaction time estimates in attention deficit/hyperactivity disorderClinical Psychological Science7(4), 856-872.

Sripada, C., Rutherford, S., Angstadt, M., Thompson, W. K., Luciana, M., Weigard, A., Hyde, L., & Heitzeg, M. (2019). Prediction of neurocognition in youth from resting state fMRIMolecular Psychiatry, 1-9.

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