| A network diffusion model of disease progression in dementia A Raj, A Kuceyeski, M Weiner Neuron 73 (6), 1204-1215, 2012 | 738 | 2012 |
| Machine learning in resting-state fMRI analysis M Khosla, K Jamison, GH Ngo, A Kuceyeski, MR Sabuncu Magnetic resonance imaging 64, 101-121, 2019 | 242 | 2019 |
| Network diffusion model of progression predicts longitudinal patterns of atrophy and metabolism in Alzheimer’s disease A Raj, E LoCastro, A Kuceyeski, D Tosun, N Relkin, M Weiner Cell reports 10 (3), 359-369, 2015 | 215 | 2015 |
| Heritability and interindividual variability of regional structure-function coupling Z Gu, KW Jamison, MR Sabuncu, A Kuceyeski Nature Communications 12 (1), 4894, 2021 | 144 | 2021 |
| The Network Modification (NeMo) Tool: elucidating the effect of white matter integrity changes on cortical and subcortical structural connectivity A Kuceyeski, J Maruta, N Relkin, A Raj Brain connectivity 3 (5), 451-463, 2013 | 127 | 2013 |
| Ensemble learning with 3D convolutional neural networks for functional connectome-based prediction M Khosla, K Jamison, A Kuceyeski, MR Sabuncu NeuroImage 199, 651-662, 2019 | 120 | 2019 |
| 3D convolutional neural networks for classification of functional connectomes M Khosla, K Jamison, A Kuceyeski, MR Sabuncu international workshop on deep learning in medical image analysis, 137-145, 2018 | 108 | 2018 |
| Structural connectome disruption at baseline predicts 6‐months post‐stroke outcome A Kuceyeski, BB Navi, H Kamel, A Raj, N Relkin, J Toglia, C Iadecola, ... Human brain mapping 37 (7), 2587-2601, 2016 | 97 | 2016 |
| Receptor-informed network control theory links LSD and psilocybin to a flattening of the brain’s control energy landscape SP Singleton, AI Luppi, RL Carhart-Harris, J Cruzat, L Roseman, DJ Nutt, ... Nature communications 13 (1), 5812, 2022 | 95 | 2022 |
| Resting-state functional connectivity magnetic resonance imaging and outcome after acute stroke J Puig, G Blasco, A Alberich-Bayarri, G Schlaug, G Deco, C Biarnes, ... Stroke 49 (10), 2353-2360, 2018 | 91 | 2018 |
| The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain–behavior relationships after stroke SL Liew, A Zavaliangos‐Petropulu, N Jahanshad, CE Lang, KS Hayward, ... Human brain mapping 43 (1), 129-148, 2022 | 81 | 2022 |
| Distinct functional and structural connections predict crystallised and fluid cognition in healthy adults E Dhamala, KW Jamison, A Jaywant, S Dennis, A Kuceyeski Human brain mapping 42 (10), 3102-3118, 2021 | 76 | 2021 |
| Machine learning methods predict individual upper-limb motor impairment following therapy in chronic stroke C Tozlu, D Edwards, A Boes, D Labar, KZ Tsagaris, J Silverstein, ... Neurorehabilitation and neural repair 34 (5), 428-439, 2020 | 71 | 2020 |
| The impact of white matter hyperintensities on the structural connectome in late-life depression: Relationship to executive functions M Respino, A Jaywant, A Kuceyeski, LW Victoria, MJ Hoptman, MA Scult, ... NeuroImage: Clinical 23, 101852, 2019 | 64 | 2019 |
| Spatial patterns of genome‐wide expression profiles reflect anatomic and fiber connectivity architecture of healthy human brain P Goel, A Kuceyeski, E LoCastro, A Raj Human brain mapping 35 (8), 4204-4218, 2014 | 64 | 2014 |
| Combining quantitative susceptibility mapping with automatic zero reference (QSM0) and myelin water fraction imaging to quantify iron-related myelin damage in chronic active MS … Y Yao, TD Nguyen, S Pandya, Y Zhang, SH Rúa, I Kovanlikaya, ... American Journal of Neuroradiology 39 (2), 303-310, 2018 | 62 | 2018 |
| Cortical response to naturalistic stimuli is largely predictable with deep neural networks M Khosla, GH Ngo, K Jamison, A Kuceyeski, MR Sabuncu Science Advances 7 (22), eabe7547, 2021 | 59 | 2021 |
| Exploring the brain's structural connectome: A quantitative stroke lesion‐dysfunction mapping study A Kuceyeski, BB Navi, H Kamel, N Relkin, M Villanueva, A Raj, J Toglia, ... Human brain mapping 36 (6), 2147-2160, 2015 | 56 | 2015 |
| The application of a mathematical model linking structural and functional connectomes in severe brain injury A Kuceyeski, S Shah, JP Dyke, S Bickel, F Abdelnour, ND Schiff, HU Voss, ... NeuroImage: Clinical 11, 635-647, 2016 | 55 | 2016 |
| Profilometry: a new statistical framework for the characterization of white matter pathways, with application to multiple sclerosis M Dayan, E Monohan, S Pandya, A Kuceyeski, TD Nguyen, A Raj, ... Human brain mapping 37 (3), 989-1004, 2016 | 51 | 2016 |
Ashish RajProfessor of Radiology, UCSF確認したメール アドレス: ucsf.edu