Scott J. Peltier, Ph.D.
Affiliations: | 2003 | University of Michigan, Ann Arbor, Ann Arbor, MI |
Area:
Electricity and Magnetism Physics, Biomedical EngineeringGoogle:
"Scott Peltier"Parents
Sign in to add mentor| Douglas C. Noll | grad student | 2003 | University of Michigan | |
| (Characterization and compensation of systematic noise in functional magnetic resonance imaging.) | ||||
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Publications
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| Martz ME, Hart T, Heitzeg MM, et al. (2020) Neuromodulation of brain activation associated with addiction: A review of real-time fMRI neurofeedback studies. Neuroimage. Clinical. 27: 102350 |
| Cassady K, Gagnon H, Freiburger E, et al. (2020) Network segregation varies with neural distinctiveness in sensorimotor cortex. Neuroimage. 116663 |
| Tomlinson RC, Burt SA, Waller R, et al. (2020) Neighborhood poverty predicts altered neural and behavioral response inhibition. Neuroimage. 116536 |
| Deelchand DK, Berrington A, Noeske R, et al. (2019) Across-vendor standardization of semi-LASER for single-voxel MRS at 3T. Nmr in Biomedicine. e4218 |
| Hagler DJ, Hatton S, Cornejo MD, et al. (2019) Image processing and analysis methods for the Adolescent Brain Cognitive Development Study. Neuroimage. 116091 |
| Kardan O, Reuter-Lorenz PA, Peltier S, et al. (2019) Brain connectivity tracks effects of chemotherapy separately from behavioral measures. Neuroimage. Clinical. 101654 |
| Hein TC, Mattson WI, Dotterer HL, et al. (2018) Amygdala habituation and uncinate fasciculus connectivity in adolescence: A multi-modal approach. Neuroimage |
| Iordan AD, Cooke KA, Moored KD, et al. (2017) Aging and Network Properties: Stability Over Time and Links with Learning during Working Memory Training. Frontiers in Aging Neuroscience. 9: 419 |
| Kutch JJ, Labus JS, Harris RE, et al. (2017) Resting-State Functional Connectivity Predicts Longitudinal Pain Symptom Change In Urologic Chronic Pelvic Pain Syndrome: A Mapp Network Study. Pain |
| Nejad-Davarani SP, Chopp M, Peltier S, et al. (2016) Resting state fMRI connectivity analysis as a tool for detection of abnormalities in five different cognitive networks of the brain in Multiple Sclerosis patients. Clinical Case Reports and Reviews. 2: 464-471 |