The Neuroimaging Laboratory (NiL) at the Centre for Healthy Brain Ageing (CHeBA) was established in 1991 in response to a need for the assessment of brain images, in order to improve our understanding of the brain in health and disease. The Laboratory brings together the knowledge and experience of a diverse group of researchers whose work is highly interdisciplinary.
One of the key requirements of neuroimaging research is the multi-disciplinary collaborations between neuroscience, engineering, medicine and a host of sub-disciplines. While the research subjects and the clinical needs are provided by medicine, the theoretical underpinnings come from mathematics and statistics, and the methodological approaches from computer science and biomedical engineering, all forming critical components of the enterprise.
The Laboratory houses one computer cluster with 144 CPUs and over 10 workstations (both Windows and Linux), as well as two data archival systems of about 30 terabytes. The MR images we study include 3D T1-weighted scans, T2-weighted (such as FLAIR sequence) scans, DTI (diffusion tensor imaging), 1H MRS (magnetic resonance spectroscopy), functional MRI (fMRI), Gd-perfusion MRI (pMRI), and will extend to ASL (arterial-spin labelling), Gd-perfusion MRI (pMRI), fluorodeoxyglucose positron emission tomography (FDG-PET) and Single Photon Emission Computed Tomography (SPECT). NiL hosts several research students (PhD candidates, Master by Research and Honours students) and post-doctoral fellows. NiL is a very important and successful component of CHeBA and a regular stream of high quality publications have emanated from NiL in the last few years. NiL staff have also created and written many versatile and important neuroimaging processing programs/algorithms and scripts in C, MATLAB, Perl, and Python. The equipment purchased over time has been funded by competitive individual research grants.
NiL is dedicated to researching the ageing of the human brain. By studying structural and functional magnetic resonance imaging and other neuroimaging modalities, we aim to improve understanding of brain ageing pathways, which in turn will lead to clinical advances in prediction, diagnosis and treatment. Our neuroimaging studies address normal ageing, mild cognitive impairment (MCI), and dementia.
Our Lab is interested in computational neuroanatomy, the development of a comprehensive structural and functional model of the brain. The distribution of structural changes in the human brain reflect the underlying pathology. The increasing sophistication of MRI allows neuroanatomical structures to be visualised, in vivo, in unprecedented detail. Clinical MRI is able to give good soft-tissue contrast and high spatial (<1 mm) resolution. Due to rapid advances in computing power and algorithm development, we are now well placed to study the extraordinary MRI-visible morphological variability of the human brain through mathematical models sensitive to subtle changes in neuroanatomical shape, complexity and tissue characteristics. Our recent work includes the mapping and modeling of cerebral white matter hyperintensities, algorithm development for examining the shapes and sizes of brain structures and cortical atrophy and, most recently, structural brain connectivity using DTI tractography.
Opportunities with NiL
The Neuroimaging Laboratory welcomes students from a variety of disciplines (including engineering, mathematics, statistics and IT) to join us for vacation work experience. We welcome both local and international students. In particular, we encourage students who are considering post-graduate studies and are actively looking for thesis topics. We hope that our Laboratory's research environment will provide students with excellent exposure to the exciting and challenging research field of neuroimaging. While the jobs are voluntary, we are happy to negotiate some stipends for students who contribute to our current research projects.
The connectivity data of all cognitively healthy elderly subjects as analysed by Perry et al (http://dx.doi.org/10.1016/j.neuroimage.2015.04.009), collected as part of the Sydney Memory and Ageing Study (MAS), is publicly available here. You will first have to register for access here.
Dr. Jiyang Jiang (John Holden Foundation Postdoc Fellow)
Debarun Sengupta (Casual RA)
Dr Wanlin Zhu (UNSW Visiting Fellow)
Alumni, Honorary Fellows and Collaborators
Dr Amir Seyed Batouli
Dr Xiaohua Chen