Marnie Shaw is a Research Fellow in the School of Engineering and Research Leader in the Battery Storage and Grid Integration Program at the Australian National University. She is also the convenor of the Energy Efficiency research cluster at the ANU’s Energy Change Institute.
Dr Shaw's current research interests lie in applying data analytics and machine learning to a range of data-rich problems, including the integration of renewable energy into the electricity grid. At the ANU, she has been looking at how community energy models (e.g. shared battery systems) can support increasing amounts of renewable energy in the grid, reduce energy costs for consumers, and address important issues around energy equity.
In the field of human brain imaging, she was one of the early researchers in the field to apply multivariate analyses and machine learning techniques to study functional connectivity in the human brain (e.g. Shaw et al., 2002; Harrison et al., 2005; 2006a; 2006b).
More recent work has used longitudinal analysis to investigate how risk factors are related to brain ageing, based on MRI scans. For example, recently published work identified important differences in how the risk associated with body mass index (BMI) changes from midlife to later life (https://www.nature.com/articles/ijo2017254). The results suggest that it's particularly important for older adults to remain physically active to keep their muscles strong and maintain a stable BMI.
Her research experience has been highly interdisciplinary, covering physics, engineering, computer science, biomedical science, data analytics, psychology and neuroscience. She has worked in universities, hospitals and in industry, both here in Australia, as well as in the USA and in Germany.
Within the data engineering group here in the College of Engineering and Computer Science, some of my projects include;
(1) studying age-related change in structural architecture of the human brain over the lifespan (Shaw et al., 2016a; Shaw et al., 2016b)
(2) studying risk-factors for neurodegenerative disease and how these change over the lifespan (Shaw et al., 2017a; Shaw et al., 2017b)
(3) using neural networks to forecast electricity load
(4) how to apply deep learning to brain imaging data
(5) data driven optimisation of smart grid design
1. Cherbuin, N, Shaw, M., Walsh, E., Sachdev, P., Anstey, K. Validated Alzheimer's Disease risk index (ANU-ADRI) is associated with smaller volumes in the default mode network in the early 60s. 2017. Brain Imaging and Behavior (in press)
2. Sidhant Chopra, Marnie Shaw, Thomas Shaw, Perminder S Sachdev, Kaarin J Anstey. 2017. More Highly Myelinated White Matter Tracts are Associated with Faster Processing Speed in Healthy Adults. Neuroimage (in press)
3. Marnie Shaw, Walter Abhayaratna, Perminder Sachdev, Kaarin Anstey, and Nicolas Cherbuin. Body mass index is associated with cortical thinning with different patterns in mid- and late-life. 2017. International Journal of Obesity (in press)
4. Erin Walsh, Marnie Shaw, Perminder Sachdev, Kaarin J. Anstey, Nicolas Cherbuin. Brain atrophy in ageing: estimating effects of blood glucose levels vs other type 2 diabetes effects. 2017. Diabetes and Metabolism (in press)
5. Shaw, Marnie E; Nettersheim, Julia; Sachdev, Perminder S; Anstey, Kaarin J; Cherbuin, Nicolas; Higher Fasting Plasma Glucose is Associated with Increased Cortical Thinning Over 12 Years: The PATH Through Life Study Brain topography. 2017 30, 3: 408-416
6. Tabatabaei‐Jafari, Hossein; Walsh, Erin; Shaw, Marnie E; Cherbuin, Nicolas; The cerebellum shrinks faster than normal ageing in Alzheimer's disease but not in mild cognitive impairment. Human Brain Mapping 2017 38,6:3141:3150
7. Shaw, Marnie E; Abhayaratna, Walter P; Anstey, Kaarin J; Cherbuin, Nicolas; Increasing Body Mass Index at Midlife is Associated with Increased Cortical Thinning in Alzheimer’s Disease-Vulnerable Regions. Journal of Alzheimer's Disease 2017 (in press)
8. Dykstra, Andrew R; Shaw, Marnie E; Gutschalk, Alexander; Electrophysiological markers of auditory perceptual awareness and release from informational masking. The Journal of the Acoustical Society of America 2017. 41,5:3692
9. Shaw, M. E., Abhayaratna, W., Sachdev, P. S, Anstey, K. J., Cherbuin, N. 2016. Cortical Thinning at Midlife: The PATH Through Life Study. Brain Topography 29(6): 875-884
10. Luders E., Kurth, F., Das, D., Oyarce, D., Shaw, M., Sachdev, P., Easteal, S., Anstey, K., Cherbuin, N. 2016 Associations between Corpus Callosum Size and ADHD Symptoms in Older Adults: The PATH Through Life Study. Psychiatry Research: Neuroimaging 256: 8-14
11. Zhang T., Shaw, M., Humphries, J., Sachdev, P., Anstey, K. J., Cherbuin, N. 2016. Higher fasting plasma glucose is associated with striatal and hippocampal shape differences: the 2sweet project. BMJ Open Diabetes Research & Care 4(1):e000175
12. Shaw, M., Sachdev, P., Anstey, K. J., Cherbuin, N. 2016. Age-related cortical thinning in cognitively healthy individuals in their 60s: the PATH Through Life study. Neurobiology of aging 39: 202-209.
13. Tabatabaei-Jafari, H., Shaw, M.E. Cherbuin, N, 2015. Cerebral atrophy in mild cognitive impairment: a systematic review with meta-analysis. Alzheimer's & Dementia: Diagnosis, Assessment & Disease Monitoring 1(4): 487-504
14. Cherbuin, N. Shaw, M. E., Sachdev, P., Anstey, K. J. 2015. Validated dementia risk factor composite is associated with lower hippocampal volumes and cortical thickness. Alzheimers and Dementia. 11 (7): 813-814
15. Fraser, Mark A, Shaw, Marnie E, Cherbuin, Nicolas. 2015. A systematic review and meta-analysis of longitudinal hippocampal atrophy in healthy human ageing. NeuroImage. 112: 364-374
16. Shaw, Marnie E, Hämäläinen, Matti S and Gutschalk, Alexander, 2013. How anatomical asymmetry of human auditory cortex can lead to a rightward bias in auditory evoked fields. Neuroimage 74:22-29
17. Lanius et al, Intrinsic network abnormalities in PTSD. 2012. The International Journal of Neuropsychopharmacology 15:9-9.
18. Bluhm, R. L., Clark, C. R., McFarlane, A. C., MB, Moores, K. A., Shaw, M. E., Lanius, R. A. Default network connectivity during a working memory task. 2011. Human Brain Mapping 32(7):1029-1035
19. Daniels, J. K., McFarlane, A. C., Bluhm, R. L., Moores, K. A., Clark, C. R., Shaw, M. E., Williamson, P. C., Densmore, M., Lanius, R. A. Switching between executive and default mode networks in posttraumatic stress disorder: alterations in functional connectivity. J Psychiatry Neurosci. 2010. 35(4):258-66
20. Shaw, M. E., Moores, K. A., Clark, C. R., McFarlane, A. C., Strother, S. C., Bryant, R. A, Brown, G. C. and. Taylor, J. Functional connectivity reveals inefficient working memory systems in post-traumatic stress disorder. 2009. Psychiatry Research: Neuroimaging 172: 235-241
21. Borsook, D., Becerra, L., Carlezon, W., Shaw, M., Renshaw, P., Elman, I., Levine, J. Reward-Aversion Circuitry in Analgesia and Pain: Implications for Psychiatric Disorders. 2007. European Journal of Pain. 11(1): 7-20
22. Waites, A. B., Mannfolk, P., Shaw, M. E., Olsrud J. and Jackson, G. D. Flexible statistical modelling detects clinical fMRI activation in partially compliant subjects. 2007. Magnetic Resonance Imaging. 25(2):188-196
23. Borsook, D. Pendse, G., Aiello-Lammens, M., Glicksman, M., Gostic, J., Sherman, S., Korn, J., Shaw, M., Stewart, K., Gostic,R., Bazes, S., Hargreaves, R., Becerra, L. 2007. CNS Response to a Thermal Stressor in Human Volunteers and Rats May Predict The Clinical Utility of Analgesics. Drug Development Research. 68(1): 23-41
24. Borsook, D., Becerra, L., Carlezon, W.A., Shaw, M., Renshaw, P., Elman, I. and Levine, J. Reward‐aversion circuitry in analgesia and pain: Implications for psychiatric disorders. European journal of pain 11 (1), 7
25. Harrison B. J., Yucel, M., Shaw, M., Brewer, W. J., Nathan, P. J., Strother, S. C., Olver, J. S., Egan, G. F., Velakoulis, D., McGorry, P. D., Pantelis, C. 2006. Dysfunction of dorsolateral prefrontal cortex in antipsychotic-naïve schizophreniform psychosis. Psychiatry Research : Neuroimaging. 148(1): 23-31
26. Harrison, B. J., Yucel, M., Shaw, M., Maruff, P., Kyrios, M., Brewer, W. J., Strother, S. C., Nathan, P. J., Scott, A. M., Pantelis, C. 2006. Evaluating brain activity in obsessive-compulsive disorder: Preliminary insights from a multivariate analysis. Psychiatry Research: Neuroimaging. 147 (2-3):227-231
27. Harrison B., Shaw, M., Yucel, M., Purcell, R., Brewer, W. J., Strother, S., C. and Pantelis, C. 2005. Functional Connectivity during Stroop Task performance. Neuroimage, 24(1):181-91
28. Waites, A., B., Shaw, M., Briellmann, R., Labate, A., Abbott, D. and Jackson, G. 2005. How reliable are fMRI–EEG studies of epilepsy? A nonparametric approach to analysis validation and optimization. Neuroimage, 24(1):192-9
29. Shaw, M. E., Strother, S. C., Gavrilescu, M., Podzebenko, K., Waites, A., Watson, J., Anderson, J., Jackson, G., Egan, G. 2003. Evaluating subject specific preprocessing choices in multi-subject BOLD fMRI data sets using data driven performance metrics. Neuroimage 19:988-1001
30. Clark, C. R., McFarlane, A. C., Morris, P., Weber, D. L., Sonkkilla, C., Shaw, M., Marcina, J., Tochon-Danguy, H., J. and Egan, G. F. 2003. Cerebral function in posttraumatic stress disorder during verbal working memory updating: a positron emission tomography study. Biological Psychiatry, 53:474-481
31. Shaw, M. E., Stephen C. Strother, Jon Anderson, Alexander C. McFarlane, Philip Morris, Richard Clark and Gary F. Egan. 2002. Abnormal functional connectivity in post-traumatic stress disorder. Neuroimage, 15:661-674
32. Gavrilescu, M. Shaw, M. E., Stuart, G. W., Eckersley, P., Svalbe, I., Egan, G. 2002. Simulation of the effects of global normalisation procedures in functional MRI. Neuroimage, 17:532-42
Becerra, Lino, Shaw, Marnie, Borsook, David. 2007. Nociceptive Processing in the Nucleus Accumbens, Neurophysiology and Behavioral Studies. Encyclopedia of Pain. Springer. 1374-1376
Borsook, D., Becerra, L. and Shaw M. CNS Assay for prediction of therapeutic efficacy for neuropathic pain and other functional illness. Application No. 11/240, 007, filed on September 30, 2005, granted 2010 to Assignee: McLean Hospital
I am passionate about early science education and digital literacy. To this end I give regular science presentations at my local primary school and am a regular volunteer at the primary school Code Club.