Research Overview

Dr. Chung is a computational neuroscientist with a focus in MRI connectomics – the study of the brain as an inter-connected network to understand its functional and structural organization in relation to development, aging or disease.

Her research work includes validation of diffusion MRI models through to their development and application on aging cohorts, and network theoretical analysis on premature neonates. At FNNDSC, Dr. Chung continues to devise novel methodologies for connectomes to describe system changes in brain organization, and has applied these to MRI studies on children with Autism, concussion, and 16p11.2 Deletion Syndrome. Her current focus is to identify neuroimaging markers of altered brain structure through the lifespan of patients with congenital heart disease using her novel network theoretical models of energy propagation.

Research Background

After majoring in Computer Science, and a Masters in Imaging Sciences at University College London (UCL) in the UK, Dr. Chung went on to obtain a Ph.D. in Medical Physics in Neuroimaging at London’s UCL Great Ormond Street Institute of Child Health, UK.

Ever interested in translating advanced brain MRI techniques for the clinic, she has held several research positions in hospital-affiliated institutes. These include the Stroke and Dementia Neuroimaging Unit at St. George’s University of London (St. Thomas' Hospital), and the Biostatistics group at the Department of Early Life Imaging at King’s College London (St Thomas' Hospital). Dr. Chung joined the FNNDSC at Boston Children's Hospital as a Postdoctoral Fellow in 2016.

Selected Publications

  1. Chung AW. Beyond the shortest path: Diffusion-based routing strategies. Book chapter in Connectome Analysis: Characterization, Methods, and Analysis, 1st ed., ed. Schirmer MD, Arichi T, Chung AW. Academic Press; 2023; ISBN 978-0323852807
  2. Connectome Analysis: Characterization, Methods, and Analysis, 1st ed., ed. Schirmer MD, Arichi T, Chung AW. Academic Press; 2023; ISBN 978-0323852807
  3. Chung AW, Mannix R, Feldman HA, Grant PE, Im K. Longitudinal structural connectomic and rich-club analysis in adolescent mTBI reveals persistent, distributed brain alterations acutely through to one year post-injury. Sci Rep. 2019 Dec;9:18833. PMCID: PMC6906376
  4. Chung AW, Schirmer MD, Krishnan ML, Ball G, Aljabar P, Edwards AD, Montana G. Characterising brain network topologies: A dynamic analysis approach using heat kernels. NeuroImage. 2016;141:490–501. PMID: 27421183
  5. Schirmer MD, Venkataraman A, Rekik I, Kim M, Mostofsky SH, Nebel MB, Rosch K, Seymour K, Crocetti D, Irzan H, Hütel M, Ourselin S, Marlow N, Melbourne A, Levchenko E, Zhou S, Kunda M, Lu H, Dvornek NC, Zhuang J, Pinto G, Samal S, Zhang J, Bernal-Rusiel JL, Pienaar R, Chung AW. Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Medical Image Analysis. 2021 May;70:101972. PMID: 33677261
  6. Schirmer MD and Chung AW†. Heat Kernels with Functional Connectomes Reveal Atypical Energy Transport in Peripheral Subnetworks in Autism. In: Schirmer MD, Venkataraman A, Rekik I, Kim M, Chung AW, eds. Connectomics in NeuroImaging. Lecture Notes in Computer Science. Cham: Springer International Publishing; 2019:54–63. DOI: 10.1007/978-3-030-32391-2_6

Publications

  1. Neuropsychiatric disease classification using functional connectomics - results of the connectomics in neuroimaging transfer learning challenge. Med Image Anal. 2021 05; 70:101972. View Abstract
  2. Longitudinal structural connectomic and rich-club analysis in adolescent mTBI reveals persistent, distributed brain alterations acutely through to one year post-injury. Sci Rep. 2019 12 11; 9(1):18833. View Abstract
  3. Network structural dependency in the human connectome across the life-span. Netw Neurosci. 2019; 3(3):792-806. View Abstract
  4. Longitudinal Changes in Magnetic Resonance Spectroscopy in Pediatric Concussion: A Pilot Study. Front Neurol. 2019; 10:556. View Abstract
  5. Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification. Neuroimage. 2019 03; 188:473-482. View Abstract
  6. Biogenetic temperament and character and attention deficit hyperactivity disorder in Korean children. Psychopathology. 2006; 39(1):25-31. View Abstract

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