A man smiling, wearing glasses and a light blue shirt, against a dark background.

Robert C. Welsh, PhD

Languages spoken: English

Academic Information

Departments Adjunct - Psychiatry

Divisions: Adult Psychiatry

Robert C. Welsh, PhD, is an interdisciplinary neuroscientific investigator and Adjunct Professor of Psychiatry. Using his technical expertise in neuroimaging and statistical methods, Dr. Welsh generates sophisticated data for translational studies of novel psychiatric treatments. He collaborates with many research colleagues and brings technical physics and rigorous analytical methods to many imaging studies, within the Department, across other departments and to national and international collaborations.

Dr. Welsh joined the Psychiatry faculty in 2016 and transitioned to an adjunct role in 2022. He has an interest in minority health disparities and social justice, and in addition to other funding in this area, has recently been awarded a grant through the University of Utah Office of the Vice President for Research to study COVID-19 related health disparities. Dr. Welsh’s developed computational pipelines and software tools are widely used in imaging research around the country. An imaging task that he optimized is now being used to collect data from 10,000 individuals across 21 US sites for the longitudinal Adolescent Brain Cognitive Development Study (including HMHI’s Utah site). He also provides critical collaboration for statistical analyses of other large datasets, engaging methods that extend well beyond the analysis needs of neuroimaging data.

Finally, Dr. Welsh is deeply committed to mentorship and was recently awarded funding for a 5-year National Institutes of Health R25 course focused on providing high-level training in advanced statistical methods in the overlapping fields of neuroimaging and genetics. This project attracts trainees from many institutions, bringing national recognition to the University of Utah, the School of Medicine, HMHI, and the Psychiatry department.

Education History

Undergraduate George Mason University
 BA
Graduate Training Johns Hopkins University
 MA
Doctoral Training Johns Hopkins University
 PhD
Postdoctoral Fellowship Johns Hopkins University
 Postdoctoral Fellow
Research Fellow University of Michigan
 Research Fellow
Fellowship University of Michigan
 Postdoctoral Research Associate

Selected Publications

Journal Article

  1. Warthen KG, Sanford B, Walker K, Jones KG, Angstadt M, Sripada C, Goldman D, Zubieta JK, Welsh RC, Burmeister M, Mickey B (2019). Neuropeptide Y and representation of salience in human nucleus accumbens. Neuropsychopharmacology, 44(3), 495-502. (Read full article)
  2. Taylor SF, Ho SS, Abagis T, Angstadt M, Maixner DF, Welsh RC, Hernandez-Garcia (2018). Changes in brain connectivity during a sham-controlled, transcranial magnetic stimulation trial for depression. Journal of affective disorders, 232, 143-151. (Read full article)
  3. Stange JP, Jenkins LM, Pocius S, Kreutzer K, Bessette KL, DelDonno SR, Kling LR, Bhaumik R, Welsh RC, Keilp JG, Phan KL, Langenecker S (2020). Using resting-state intrinsic network connectivity to identify suicide risk in mood disorders. Psychological medicine, 50(14), 2324-2334. (Read full article)
  4. Peters AT, Jenkins LM, Stange JP, Bessette KL, Skerrett KA, Kling LR, Welsh RC, Milad MR, Phan KL, Langenecker S (2019). Pre-scan cortisol is differentially associated with enhanced connectivity to the cognitive control network in young adults with a history of depression. Psychoneuroendocrinology, 104, 219-227. (Read full article)
  5. Goetschius LG, Hein TC, Mattson WI, Lopez-Duran N, Dotterer HL, Welsh RC, Mitchell C, Hyde LW, Monk C (2019). Amygdala-prefrontal cortex white matter tracts are widespread, variable and implicated in amygdala modulation in adolescents. NeuroImage, 191, 278-291. (Read full article)
  6. Hein TC, Mattson WI, Dotterer HL, Mitchell C, Lopez-Duran N, Thomason ME, Peltier SJ, Welsh RC, Hyde LW, Monk C (2018). Amygdala habituation and uncinate fasciculus connectivity in adolescence: A multi-modal approach. NeuroImage, 183, 617-626. (Read full article)
  7. Burkhouse KL, Stange JP, Jacobs RH, Bhaumik R, Bessette KL, Peters AT, Crane NA, Kreutzer KA, Fitzgerald K, Monk CS, Welsh RC, Phan KL, Langenecker S (2019). Developmental changes in resting-state functional networks among individuals with and without internalizing psychopathologies. Depression and anxiety, 36(2), 141-152. (Read full article)
  8. Roberts H, Jacobs RH, Bessette KL, Crowell SE, Westlund-Schreiner M, Thomas L, Easter RE, Pocius SL, Dillahunt A, Frandsen S, Schubert B, Farstead B, Kerig P, Welsh RC, Jago D, Langenecker SA, Watkins E (2021). Mechanisms of rumination change in adolescent depression (RuMeChange): study protocol for a randomised controlled trial of rumination-focused cognitive behavioural therapy to reduce ruminative habit and risk of depressive relapse in high-ruminating adolescents. BMC psychiatry, 21(1), 206. (Read full article)
  9. Chang SE, Angstadt M, Chow HM, Etchell AC, Garnett EO, Choo AL, Kessler D, Welsh RC, Sripada (2018). Anomalous network architecture of the resting brain in children who stutter. Journal of fluency disorders, 55, 46-67. (Read full article)
  10. Jenkins LM, Stange JP, Barba A, DelDonno SR, Kling LR, Briceño EM, Weisenbach SL, Phan KL, Shankman SA, Welsh RC, Langenecker S (2017). Integrated cross-network connectivity of amygdala, insula, and subgenual cingulate associated with facial emotion perception in healthy controls and remitted major depressive disorder. Cognitive, affective & behavioral neuroscience, 17(6), 1242-1254. (Read full article)
  11. Bessette KL, Jacobs RH, Heleniak C, Peters AT, Welsh RC, Watkins ER, Langenecker S (2020). Malleability of rumination: An exploratory model of CBT-based plasticity and long-term reduced risk for depressive relapse among youth from a pilot randomized clinical trial. PloS one, 15(6), e0233539. (Read full article)
  12. Quinn ME, Stange JP, Jenkins LM, Corwin S, DelDonno SR, Bessette KL, Welsh RC, Langenecker S (2018). Cognitive control and network disruption in remitted depression: a correlate of childhood adversity. Social cognitive and affective neuroscience, 13(10), 1081-1090. (Read full article)
  13. Hardee JE, Cope LM, Munier EC, Welsh RC, Zucker RA, Heitzeg M (2017). Sex differences in the development of emotion circuitry in adolescents at risk for substance abuse: a longitudinal fMRI study. Social cognitive and affective neuroscience, 12(6), 965-975. (Read full article)
  14. Warthen KG, Welsh RC, Sanford B, Koppelmans V, Burmeister M, Mickey B (2021). Neuropeptide Y Variation Is Associated With Altered Static and Dynamic Functional Connectivity of the Salience Network. Frontiers in systems neuroscience, 15, 629488. (Read full article)
  15. Bharti K, Khan M, Beaulieu C, Graham SJ, Briemberg H, Frayne R, Genge A, Korngut L, Zinman L, Kalra S, Canadian ALS Neuroimaging Consortium (2020). Involvement of the dentate nucleus in the pathophysiology of amyotrophic lateral sclerosis: A multi-center and multi-modal neuroimaging study. NeuroImage. Clinical, 28, 102385. (Read full article)
  16. Langenecker SA, Westlund Schreiner M, Thomas LR, Bessette KL, DelDonno SR, Jenkins LM, Easter RE, Stange JP, Pocius SL, Dillahunt A, Love TM, Phan KL, Koppelmans V, Paulus M, Lindquist MA, Caffo B, Mickey BJ, Welsh R (2021). Using Network Parcels and Resting-State Networks to Estimate Correlates of Mood Disorder and Related Research Domain Criteria Constructs of Reward Responsiveness and Inhibitory Control. Biological psychiatry. Cognitive neuroscience and neuroimaging, 7(1), 76-84. (Read full article)
  17. Kim JU, Bessette KL, Westlund-Schreiner M, Pocius S, Dillahunt AK, Frandsen S, Thomas L, Easter R, Skerrett K, Stange JP, Welsh RC, Langenecker SA, Koppelmans (2022). Relations of gray matter volume to dimensional measures of cognition and affect in mood disorders. Cortex; a journal devoted to the study of the nervous system and behavior, 156, 57-70. (Read full article)
  18. Mejia AF, Koppelmans V, Jelsone-Swain L, Kalra S, Welsh R (2022). Longitudinal surface-based spatial Bayesian GLM reveals complex trajectories of motor neurodegeneration in ALS. NeuroImage, 255, 119180. (Read full article)