Issue link: https://www.e-digitaleditions.com/i/1351396
Brain Art: Complex Brain Simulation 2 By Dr. Vitaly Galinsky and Dr Lawrence Frank at the Center for Scientific Computation in Imaging at UC San Diego, Dr. Lisa Delano-Wood at UC San Diego, and Dr. Erin Bigler at Brigham Young University Co-Editors Welcome to the Next NAN Bulletin 3 By Lana Harder and Shawn M. McClintock Getting Organized in the New Year 4 By New York Times Best Selling Author Gretchen Rubin Neuropsychological Assessment 3.0: Maintaining Relevance in the Digital Age 6 By Dr. Thomas Parsons and Dr. Tyler Duffield Evidenced-Based Approaches to Conducting Research, Clinical Practice, and 9 Training in Neuropsychology with Diverse Populations By Dr. Monica Rivera Mindt, Emily Morris, Angela Summers, Maral Aghvinian, and Dr. Desiree Byrd Language in Neuropsychology Part II – Interpreter-Mediated Neuropsychological Services 13 By Dr. Lawrence Pick, Dr. Jesús O. Barreto Abrams, Dr. David Andrés González, Dr. Paola Suárez, and Dr. Adriana Macias Strutt Dementia and Caregiving Among Older LGBT Adults 17 By Dr. Weston Donaldson Mentorship – Accessing Mentors as a Trainee 19 By Blair Honsey Mentors and Sponsors – How to Access One and How to Become One as an Early Career Neuropsychologist 22 By Dr. Lucas Driskell and Dr. Scott Sperling A Summary of the Most Influential Articles Published in JAMA Neurology 25 and JAMA Psychiatry Over the Last Three Years By Dr. Louis French "Within": Art Therapy as a Window into Military Service Member and Veteran States of Mind 26 By Ms. Melissa Walker Tips and Strategies for Resuming In-Person Clinical Neuropsychological Services 30 By Dr. Andrea Wahlberg In this ISSUE 2 | Bulletin vol. 34 no. 1 Brain Art Title: Complex Brain Simulation Description: The brain art shows a computational grid generated from high resolution magnetic resonance imaging (MRI) data used as input for modeling the signal from diffusion MRI (dMRI) data in the human brain using the dMRI simulation program DifSim. Diffusion MRI can non- invasively assess local tissue structure and long range neural connectivity and thus has great potential for detecting tissue damage and disruption of neural pathways. The use of such accurate computational models is critical for understanding the complex relationship between the dMRI data and the tissue architecture in order to facilitate development of quantitative clinical metrics for pathological states. By: Dr. Vitaly Galinsky and Dr Lawrence Frank at the Center for Scientific Computation in Imaging at UC San Diego, Dr. Lisa Delano-Wood at UC San Diego, and Dr. Erin Bigler at Brigham Young University On the COVER