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(Contact me if you do not have access to any publications!)
  1. "Cognitive signatures of depression, anhedonia, and affective states using computational modeling and neurocognitive testing." Ging-Jehli, N.R., Kuhn, M., Blank, J.M., Chanthrakumar, P., Steinberger, D.C., Yu, Z., Herrington, T.D., Dillon, D.G., Pizzagalli, D.A., Frank, M.J. (2024). Biological Psychiatry: Cognitive Neuroscience and Neuroimaging. In press.

  2. "Cognitive & attentional mechanisms of cooperation: implications for incentive designs and computational psychiatry." Ging-Jehli, N.R., Arnold, L.E., Van Zandt, T. (2023). Cognitive, Affective, & Behavioral Neuroscience. Link or Link to preprint

  3. "A Diffusion Decision Model Analysis of The Cognitive Effects of Neurofeedback for ADHD." Ging-Jehli, N.R., Painter, Q.A., Kraemer, H., Roley-Roberts, M.E., Panchyshyn, C.*, deBeus, R., Arnold,L.E. (2023). Neuropsychology. Link or Link to preprint

  4. “Latent cognitive components moderate neurofeedback response in ADHD – A computational modeling analysis of a randomized clinical trial” Ging-Jehli, N.R., Kraemer, H., Arnold, L.E., Roley Roberts, M.E., deBeus, R. (2023). Journal of Clinical and Experimental Neuropsychology. Link or Link to preprint

  5. "Comorbid anxiety and disruptive behavior disorders but not ADHD presentation moderate neurofeedback effect in children with ADHD" Roley-Robert, M.E., Bergman, R., Pan, X., Tan, Y., Hendrix, K., deBeus, R., Kerson, C., Arns, M., Ging-Jehli, N.R., Connor, S., Shrader, C., Arnold, L.E. (2022).  Applied Psychophysiology and Biofeedback. Link

  6. “Improving Neurocognitive Testing using Computational Psychiatry – A Systematic Review for ADHD” Ging-Jehli, N.R., Ratcliff, R., Arnold, L.E. (2021). Psychological Bulletin. Link or Link to preprint

  7. “Characterizing underlying cognitive components of ADHD presentations and co-morbid diagnoses – A diffusion decision model analysis” Ging-Jehli, N.R., Arnold, L.E., Roley-Roberts, M.E., deBeus, R. (2021). Journal of Attention Disorders. Link or Link to preprint 

  8. “Effects of aging in a task-switch paradigm with the diffusion decision model” Ging-Jehli, N.R., Ratcliff, R. (2020). Journal of Psychology and Aging. Link or Link to preprint

  9. “Exploring cholesterol supplementation for autistic symptoms in Children with Low Cholesterol” Ging-Jehli, N.R., Deepa, M., Hollway J., Hurt, E., Moone, S., Arnold, L.E. (2020). Journal of Developmental and Physical Disabilities. Link to preprint

  10. “On self-serving strategic beliefs” Ging-Jehli, N.R., Schneider, F.H., Weber, R.A. (2020). Journal of Games and Economic Behavior. Link 

  11. “Generosity across contexts” Davis, A. L., Jehli, N.R., Miller, J.H., & Weber, R.A. (2015). CESifo Working Paper, No. 5272, Center for Economic Studies and ifo Institute (CESifo), Munich.

  1. “Broader visual processing and distinct pupil dynamics facilitate resolving perceptual conflict and compensate for ADHD distractibility” Ging-Jehli, N.R., Arnold, L.E., Sellers J., Van Zandt, T. (submitted).
  2. "Distinct basal ganglia decision dynamics under conflict and uncertainty." Ging-Jehli, N.R., Cavanagh, J.F., Ahn, M., Segar, D.J., Asaad, W.F., Frank, M.J. (submitted).

  3. "A jsPsych Touchscreen Extension for Behavioral Research on Touch-Enabled Interfaces."  Strittmatter, Y., Spitzer, W.H., Ging-Jehli, N.R., Musslick, S. (submitted).


  1. Conflict-processing and intracranial EEG signatures of people with parkinson’s disease (PD)

  2. A unified modeling approach to characterize disorder-specific and transdiagnostic features across cognitive domains and over time

  3. Computational phenotyping of major depressive disorders (MDD) and obsessive compulsive disorders (OCD) within Approach-Avoidance-Conflict Processing

  4. Neuronal and attentional signatures of attention-deficit/hyperactivity disorder (ADHD) within a novel cognitive flexibility task

  5. Neurocognitive study using own developed cognitive flexibility paradigm and a new joint-modeling approach to integrate behavioral responses, eye tracking, and EEG

  6. Applying the Diffusion Decision Model and Machine Learning Algorithms to the Neuropsychological Test Performances and EEG resting state activity in an ADHD Sample from the MTA study

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