Ariana Anderson

Summary

Affiliation: University of California
Country: USA

Publications

  1. pmc Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD
    Ariana Anderson
    Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, United States Electronic address
    Neuroimage 102:207-19. 2014
  2. pmc Cognitive and neurodevelopmental benefits of extended formula-feeding in infants: re: Deoni et al. 2013
    Ariana Anderson
    Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, 760 Westwood Plaza, CHS Suite C8 734, Los Angeles, CA 90095, USA Electronic address
    Neuroimage 100:706-9. 2014
  3. pmc Reducing clinical trial costs by detecting and measuring the placebo effect and treatment effect using brain imaging
    Ariana Anderson
    Laboratory of Integrative NeuroImaging Technology, Los Angeles, CA 90095 1406, USA
    Stud Health Technol Inform 184:6-12. 2013
  4. pmc Automated diagnosis of epilepsy using EEG power spectrum
    Wesley T Kerr
    Medical Scientist Training Program and Department of Biomathematics, University of California at Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, U S A
    Epilepsia 53:e189-92. 2012
  5. doi request reprint Diffusion Tensor Imaging of TBI: Potentials and Challenges
    David B Douglas
    Department of Neuroradiology, Stanford University, Palo Alto Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA Translational Imaging Group, University College London, London, UK
    Top Magn Reson Imaging 24:241-51. 2015

Collaborators

  • John M Stern
  • David B Douglas
  • Pamela K Douglas
  • Wesley T Kerr
  • Michael Zeineh
  • Roland Bammer
  • Max Wintermark
  • Sjoerd B Vos
  • Michael Iv
  • Eric S Braun
  • Andrew Y Cho
  • Edward P Lau
  • Hongjing Xia
  • Jennifer Bramen
  • Mark S Cohen

Detail Information

Publications6

  1. pmc Non-negative matrix factorization of multimodal MRI, fMRI and phenotypic data reveals differential changes in default mode subnetworks in ADHD
    Ariana Anderson
    Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, United States Electronic address
    Neuroimage 102:207-19. 2014
    ..Cumulatively, this manuscript addresses how multimodal data in ADHD can be interpreted by latent dimensions. ..
  2. pmc Cognitive and neurodevelopmental benefits of extended formula-feeding in infants: re: Deoni et al. 2013
    Ariana Anderson
    Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, 760 Westwood Plaza, CHS Suite C8 734, Los Angeles, CA 90095, USA Electronic address
    Neuroimage 100:706-9. 2014
    ..This evidence suggests that infants should receive formula in lieu of cow's milk when breast milk is unavailable as a dairy source, until roughly 2 years of age...
  3. pmc Reducing clinical trial costs by detecting and measuring the placebo effect and treatment effect using brain imaging
    Ariana Anderson
    Laboratory of Integrative NeuroImaging Technology, Los Angeles, CA 90095 1406, USA
    Stud Health Technol Inform 184:6-12. 2013
    ....
  4. pmc Automated diagnosis of epilepsy using EEG power spectrum
    Wesley T Kerr
    Medical Scientist Training Program and Department of Biomathematics, University of California at Los Angeles, 760 Westwood Plaza, Los Angeles, CA 90095, U S A
    Epilepsia 53:e189-92. 2012
    ..We discuss how these findings suggest that this CAD can be used to supplement event-based analysis by trained epileptologists...
  5. doi request reprint Diffusion Tensor Imaging of TBI: Potentials and Challenges
    David B Douglas
    Department of Neuroradiology, Stanford University, Palo Alto Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA Translational Imaging Group, University College London, London, UK
    Top Magn Reson Imaging 24:241-51. 2015
    ..We conclude by discussing future directions in DTI research in TBI including the role of machine learning in the pattern classification of TBI. ..