Academic Appointments

  • Consulting Associate Professor, Psychiatry and Behavioral Sciences


All Publications

  • The National Consortium on Alcohol and Neuro-Development in Adolescence (NCANDA): A Multisite Study of Adolescent Development and Substance Use JOURNAL OF STUDIES ON ALCOHOL AND DRUGS Brown, S. A., Brumback, T. Y., Tomlinson, K., Cummins, K., Thompson, W. K., Nagel, B. J., De Bellis, M. D., Hooper, S. R., Clark, D. B., Chung, T., Hasler, B. P., Colrain, I. M., Baker, F. C., Prouty, D., Pfefferbaum, A., Sullivan, E. V., Pohl, K. M., Rohlfing, T., Nichols, B. N., Chu, W., Tapert, S. F. 2015; 76 (6): 895-908
  • Neuroinformatics Software Applications Supporting Electronic Data Capture, Management, and Sharing for the Neuroimaging Community NEUROPSYCHOLOGY REVIEW Nichols, B. N., Pohl, K. M. 2015; 25 (3): 356-368


    Accelerating insight into the relation between brain and behavior entails conducting small and large-scale research endeavors that lead to reproducible results. Consensus is emerging between funding agencies, publishers, and the research community that data sharing is a fundamental requirement to ensure all such endeavors foster data reuse and fuel reproducible discoveries. Funding agency and publisher mandates to share data are bolstered by a growing number of data sharing efforts that demonstrate how information technologies can enable meaningful data reuse. Neuroinformatics evaluates scientific needs and develops solutions to facilitate the use of data across the cognitive and neurosciences. For example, electronic data capture and management tools designed to facilitate human neurocognitive research can decrease the setup time of studies, improve quality control, and streamline the process of harmonizing, curating, and sharing data across data repositories. In this article we outline the advantages and disadvantages of adopting software applications that support these features by reviewing the tools available and then presenting two contrasting neuroimaging study scenarios in the context of conducting a cross-sectional and a multisite longitudinal study.

    View details for DOI 10.1007/s11065-015-9293-x

    View details for Web of Science ID 000360912800010

    View details for PubMedID 26267019

  • White matter microstructural recovery with abstinence and decline with relapse in alcohol dependence interacts with normal ageing: a controlled longitudinal DTI study LANCET PSYCHIATRY Pfefferbaum, A., Rosenbloom, M. J., Chu, W., Sassoon, S. A., Rohlfing, T., Pohl, K. M., Zahr, N. M., Sullivan, E. V. 2014; 1 (3): 202-212
  • Regional Manifold Learning for Disease Classification IEEE TRANSACTIONS ON MEDICAL IMAGING Ye, D. H., Desjardins, B., Hamm, J., Litt, H., Pohl, K. M. 2014; 33 (6): 1236-1247
  • PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration IEEE TRANSACTIONS ON MEDICAL IMAGING Kwon, D., Niethammer, M., Akbari, H., Bilello, M., Davatzikos, C., Pohl, K. M. 2014; 33 (3): 651-667


    We propose a new method for deformable registration of pre-operative and post-recurrence brain MR scans of glioma patients. Performing this type of intra-subject registration is challenging as tumor, resection, recurrence, and edema cause large deformations, missing correspondences, and inconsistent intensity profiles between the scans. To address this challenging task, our method, called PORTR, explicitly accounts for pathological information. It segments tumor, resection cavity, and recurrence based on models specific to each scan. PORTR then uses the resulting maps to exclude pathological regions from the image-based correspondence term while simultaneously measuring the overlap between the aligned tumor and resection cavity. Embedded into a symmetric registration framework, we determine the optimal solution by taking advantage of both discrete and continuous search methods. We apply our method to scans of 24 glioma patients. Both quantitative and qualitative analysis of the results clearly show that our method is superior to other state-of-the-art approaches.

    View details for DOI 10.1109/TMI.2013.2293478

    View details for Web of Science ID 000332599500005

    View details for PubMedID 24595340