Andrew Jahn, PhD

 Andrew Jahn
Assistant Research Scientist, Functional MRI Lab, Medical School
Adjunct Lecturer in Psychology, College of Literature, Science, and the Arts
University of Michigan
East Hall
300 Church Street
Ann Arbor, MI 48109
[email protected]
Available to mentor
Andrew Jahn, PhD
Andrew Jahn
Assistant Research Scientist
  • About
  • Links
  • Qualifications
  • Research Overview
  • Recent Publications

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    • About

    Over the past six years I have created tutorials on the imaging modalities I have used in my research, including fMRI, structural MRI, functional connectivity, diffusion analysis, and multivariate pattern analysis (MVPA). These tutorials consist of both a written description of the method, and a series of videos demonstrating how to use the technique or software. These tutorials have been used by universities and laboratories all over the world. I have also spent several years as a consultant for labs using different imaging methods to examine a wide range of research questions. This has given me extensive experience with introducing students to imaging methods and with training researchers in more advanced techniques.

    Links
    • Andy's Brain Book
    • Andy's Brain Blog

    Qualifications
    • PhD
      Indiana University, United States
      2015
    • BA
      Carleton College, United States
      2008

    Research Overview

    My research applies computational modeling to fMRI data by empirically testing model predictions and evaluating how well model outputs fit neuroimaging data. I spent the latter half of my graduate studies at Indiana University extending our computational modeling work of the medial prefrontal cortex (mPFC) to primate neurophysiological studies as well as translational studies in drug addiction. I collaborated with Dr. Ben Hayden’s lab at the University of Rochester to implement our modeling work into a primate neurophysiological study, which I designed and analyzed. Another facet of my research has been the use of individual difference measurements to examine how neuroimaging data is modulated by test scores, personality traits, and task performance. For example, my studies with collaborators at Ohio State University have found that measures of withdrawal and approach anxiety modulated amygdala activation depending on whether aversive stimuli approached or receded from the participant.

    At Haskins Laboratories I applied these computational modeling and neuroimaging skills to the analysis of structural and functional MRI data from reading experiments. In addition to studies of the association between structural measurements (e.g., grey matter volume and fractional anisotropy) and reading skills, I recently applied computational model predictions to a combined eye-tracking and fMRI study. In this approach, we used different models (e.g., word surprisal calculated by n-gram or context-free grammar) to modulate the hemodynamic response to individual words. Using this method, our data has shown that the different models are fits for distinct anatomical regions, particularly the left inferior frontal gyrus and left anterior temporal lobe. This suggests that these regions perform fundamentally different processing of surprisal as calculated by the models.

    Recent Publications

     See All Publications
    • Journal Article
      Preliminary study exploring the association between amygdala-ventral medial prefrontal-cortex connectivity and anxiety among adolescent and young adult cancer survivors
      Knoerl R, Jahn A, Grandinetti K, Fecher LA, Henry NL, Karimi Y, Ploutz-Snyder R, Schuetze S, Walling E, Iordan A. BMC Cancer, 2025 Dec 1; 25 (1): DOI:10.1186/s12885-025-15328-w
      PMID: 41466204
    • Journal Article
      Longing for belonging: Feeling loved (or not) and why it matters
      Ali S, Rohner RP, Britner PA, Jahn A. Family Relations, 2024 Oct 1; 73 (4): 2639 - 2654. DOI:10.1111/fare.13029
    • Journal Article
      Auditory cortex encodes lipreading information through spatially distributed activity.
      Karthik G, Cao CZ, Demidenko MI, Jahn A, Stacey WC, Wasade VS, Brang D. Curr Biol, 2024 Sep 9; 34 (17): 4021 - 4032.e5. DOI:10.1016/j.cub.2024.07.073
      PMID: PMC11387126
    • Journal Article
      The past, present, and future of the brain imaging data structure (BIDS).
      Poldrack RA, Markiewicz CJ, Appelhoff S, Ashar YK, Auer T, Baillet S, Bansal S, Beltrachini L, Benar CG, Bertazzoli G, Bhogawar S, Blair RW, Bortoletto M, Boudreau M, Brooks TL, Calhoun VD, Castelli FM, Clement P, Cohen AL, Cohen-Adad J, D'Ambrosio S, de Hollander G, de la Iglesia-Vayá M, de la Vega A, Delorme A, Devinsky O, Draschkow D, Duff EP, DuPre E, Earl E, Esteban O, Feingold FW, Flandin G, Galassi A, Gallitto G, Ganz M, Gau R, Gholam J, Ghosh SS, Giacomel A, Gillman AG, Gleeson P, Gramfort A, Guay S, Guidali G, Halchenko YO, Handwerker DA, Hardcastle N, Herholz P, Hermes D, Honey CJ, Innis RB, Ioanas H-I, Jahn A, Karakuzu A, Keator DB, Kiar G, Kincses B, Laird AR, Lau JC, Lazari A, Legarreta JH, Li A, Li X, Love BC, Lu H, Marcantoni E, Maumet C, Mazzamuto G, Meisler SL, Mikkelsen M, Mutsaerts H, Nichols TE, Nikolaidis A, Nilsonne G, Niso G, Norgaard M, Okell TW, Oostenveld R, Ort E, Park PJ, Pawlik M, Pernet CR, Pestilli F, Petr J, Phillips C, Poline J-B, Pollonini L, Raamana PR, Ritter P, Rizzo G, Robbins KA, Rockhill AP, Rogers C, Rokem A, Rorden C, Routier A, Saborit-Torres JM, Salo T, Schirner M, Smith RE, Spisak T, Sprenger J, Swann NC, Szinte M, Takerkart S, Thirion B, Thomas AG, Torabian S, Varoquaux G, Voytek B, Welzel J, Wilson M, Yarkoni T, Gorgolewski KJ. Imaging Neurosci (Camb), 2024 Mar 1; 2: 1 - 19. DOI:10.1162/imag_a_00103
      PMID: PMC11415029
    • Journal Article
      The Past, Present, and Future of the Brain Imaging Data Structure (BIDS).
      Poldrack RA, Markiewicz CJ, Appelhoff S, Ashar YK, Auer T, Baillet S, Bansal S, Beltrachini L, Benar CG, Bertazzoli G, Bhogawar S, Blair RW, Bortoletto M, Boudreau M, Brooks TL, Calhoun VD, Castelli FM, Clement P, Cohen AL, Cohen-Adad J, D'Ambrosio S, de Hollander G, de la Iglesia-Vayá M, de la Vega A, Delorme A, Devinsky O, Draschkow D, Duff EP, DuPre E, Earl E, Esteban O, Feingold FW, Flandin G, Galassi A, Gallitto G, Ganz M, Gau R, Gholam J, Ghosh SS, Giacomel A, Gillman AG, Gleeson P, Gramfort A, Guay S, Guidali G, Halchenko YO, Handwerker DA, Hardcastle N, Herholz P, Hermes D, Honey CJ, Innis RB, Ioanas H-I, Jahn A, Karakuzu A, Keator DB, Kiar G, Kincses B, Laird AR, Lau JC, Lazari A, Legarreta JH, Li A, Li X, Love BC, Lu H, Marcantoni E, Maumet C, Mazzamuto G, Meisler SL, Mikkelsen M, Mutsaerts H, Nichols TE, Nikolaidis A, Nilsonne G, Niso G, Norgaard M, Okell TW, Oostenveld R, Ort E, Park PJ, Pawlik M, Pernet CR, Pestilli F, Petr J, Phillips C, Poline J-B, Pollonini L, Raamana PR, Ritter P, Rizzo G, Robbins KA, Rockhill AP, Rogers C, Rokem A, Rorden C, Routier A, Saborit-Torres JM, Salo T, Schirner M, Smith RE, Spisak T, Sprenger J, Swann NC, Szinte M, Takerkart S, Thirion B, Thomas AG, Torabian S, Varoquaux G, Voytek B, Welzel J, Wilson M, Yarkoni T, Gorgolewski KJ. ArXiv, 2024 Jan 9;
      PMID: PMC10516110
    • Chapter
      Early Detection and Intervention in Autism: Emerging Behavioral and Biological Markers
      Virués-Ortega J, Nguyen V, Jahn A, Kirk IJ, Jacobsen J, George B, Mead Jasperse S. 2025 Jan 10; Handbook of the Biology and Pathology of Mental Disorders, 1 - 26. DOI:10.1007/978-3-031-32035-4_100-1
    • Presentation
      FSL and Machine Learning
      Jahn A. 2025 Feb 12;
    • Preprint
      The Past, Present, and Future of the Brain Imaging Data Structure (BIDS)
      Poldrack RA, Markiewicz CJ, Appelhoff S, Ashar YK, Auer T, Baillet S, Bansal S, Beltrachini L, Benar CG, Bertazzoli G, Bhogawar S, Blair RW, Bortoletto M, Boudreau M, Brooks TL, Calhoun VD, Castelli FM, Clement P, Cohen AL, Cohen-Adad J, D'Ambrosio S, de Hollander G, de la iglesia-Vayá M, de la Vega A, Delorme A, Devinsky O, Draschkow D, Duff EP, DuPre E, Earl E, Esteban O, Feingold FW, Flandin G, galassi A, Gallitto G, Ganz M, Gau R, Gholam J, Ghosh SS, Giacomel A, Gillman AG, Gleeson P, Gramfort A, Guay S, Guidali G, Halchenko YO, Handwerker DA, Hardcastle N, Herholz P, Hermes D, Honey CJ, Innis RB, Ioanas H-I, Jahn A, Karakuzu A, Keator DB, Kiar G, Kincses B, Laird AR, Lau JC, Lazari A, Legarreta JH, Li A, Li X, Love BC, Lu H, Maumet C, Mazzamuto G, Meisler SL, Mikkelsen M, Mutsaerts H, Nichols TE, Nikolaidis A, Nilsonne G, Niso G, Norgaard M, Okell TW, Oostenveld R, Ort E, Park PJ, Pawlik M, Pernet CR, Pestilli F, Petr J, Phillips C, Poline J-B, Pollonini L, Raamana PR, Ritter P, Rizzo G, Robbins KA, Rockhill AP, Rogers C, Rokem A, Rorden C, Routier A, Saborit-Torres JM, Salo T, Schirner M, Smith RE, Spisak T, Sprenger J, Swann NC, Szinte M, Takerkart S, Thirion B, Thomas AG, Torabian S, Varoquaux G, Voytek B, Welzel J, Wilson M, Yarkoni T, Gorgolewski KJ. 2023 Sep 14; arXiv, DOI:10.48550/arxiv.2309.05768