Anatomy and Neuroscience - Research Publications
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ItemDissociating neural variability related to stimulus quality and response times in perceptual decision-making(Elsevier, 2018-03-01)According to sequential sampling models, perceptual decision-making is based on accumulation of noisy evidence towards a decision threshold. The speed with which a decision is reached is determined by both the quality of incoming sensory information and random trial-by-trial variability in the encoded stimulus representations. To investigate those decision dynamics at the neural level, participants made perceptual decisions while functional magnetic resonance imaging (fMRI) was conducted. On each trial, participants judged whether an image presented under conditions of high, medium, or low visual noise showed a piano or a chair. Higher stimulus quality (lower visual noise) was associated with increased activation in bilateral medial occipito-temporal cortex and ventral striatum. Lower stimulus quality was related to stronger activation in posterior parietal cortex (PPC) and dorsolateral prefrontal cortex (DLPFC). When stimulus quality was fixed, faster response times were associated with a positive parametric modulation of activation in medial prefrontal and orbitofrontal cortex, while slower response times were again related to more activation in PPC, DLPFC and insula. Our results suggest that distinct neural networks were sensitive to the quality of stimulus information, and to trial-to-trial variability in the encoded stimulus representations, but that reaching a decision was a consequence of their joint activity.
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ItemDoes transcranial electrical stimulation enhance corticospinal excitability of the motor cortex in healthy individuals? A systematic review and meta-analysis(WILEY, 2017-08-01)Numerous studies have explored the effects of transcranial electrical stimulation (tES) - including anodal transcranial direct current stimulation (a-tDCS), cathodal transcranial direct current stimulation (c-tDCS), transcranial alternative current stimulation (tACS), transcranial random noise stimulation (tRNS) and transcranial pulsed current stimulation (tPCS) - on corticospinal excitability (CSE) in healthy populations. However, the efficacy of these techniques and their optimal parameters for producing robust results has not been studied. Thus, the aim of this systematic review was to consolidate current knowledge about the effects of various parameters of a-tDCS, c-tDCS, tACS, tRNS and tPCS on the CSE of the primary motor cortex (M1) in healthy people. Leading electronic databases were searched for relevant studies published between January 1990 and February 2017; 126 articles were identified, and their results were extracted and analysed using RevMan software. The meta-analysis showed that a-tDCS application on the dominant side significantly increases CSE (P < 0.01) and that the efficacy of a-tDCS is dependent on current density and duration of application. Similar results were obtained for stimulation of M1 on the non-dominant side (P = 0.003). The effects of a-tDCS reduce significantly after 24 h (P = 0.006). Meta-analysis also revealed significant reduction in CSE following c-tDCS (P < 0.001) and significant increases after tRNS (P = 0.03) and tPCS (P = 0.01). However, tACS effects on CSE were only significant when the stimulation frequency was ≥140 Hz. This review provides evidence that tES has substantial effects on CSE in healthy individuals for a range of stimulus parameters.
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ItemSuppressing motion artefacts in MRI using an Inception-ResNet network with motion simulation augmentation(WILEY, 2019-12-22)The suppression of motion artefacts from MR images is a challenging task. The purpose of this paper was to develop a standalone novel technique to suppress motion artefacts in MR images using a data-driven deep learning approach. A simulation framework was developed to generate motion-corrupted images from motion-free images using randomly generated motion profiles. An Inception-ResNet deep learning network architecture was used as the encoder and was augmented with a stack of convolution and upsampling layers to form an encoder-decoder network. The network was trained on simulated motion-corrupted images to identify and suppress those artefacts attributable to motion. The network was validated on unseen simulated datasets and real-world experimental motion-corrupted in vivo brain datasets. The trained network was able to suppress the motion artefacts in the reconstructed images, and the mean structural similarity (SSIM) increased from 0.9058 to 0.9338. The network was also able to suppress the motion artefacts from the real-world experimental dataset, and the mean SSIM increased from 0.8671 to 0.9145. The motion correction of the experimental datasets demonstrated the effectiveness of the motion simulation generation process. The proposed method successfully removed motion artefacts and outperformed an iterative entropy minimization method in terms of the SSIM index and normalized root mean squared error, which were 5-10% better for the proposed method. In conclusion, a novel, data-driven motion correction technique has been developed that can suppress motion artefacts from motion-corrupted MR images. The proposed technique is a standalone, post-processing method that does not interfere with data acquisition or reconstruction parameters, thus making it suitable for routine clinical practice.
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ItemComparison of Rossini-Rothwell and adaptive threshold-hunting methods on the stability of TMS induced motor evoked potentials amplitudes(WILEY, 2018-11-01)Several methods can be used to determine the resting motor threshold (RMT) and by that recording transcranial magnetic stimulation (TMS) induced motor evoked potentials (MEPs). However, no research has compared the test retest reliability of these methods. Thus, the aim of this study was to determine intra- and inter-session reliability of Rossini-Rothwell (R-R) and parameter estimation by sequential testing (PEST) methods on TMS-induced MEPs and comparison of these two methods on RMT. Twelve healthy individuals participated in this study three times (T1, T2 and T3) over two days. TMS was applied using both R-R and PEST to estimate RMT and average of 25 MEPs were acquired at each of the three time points. The intra-class correlation coefficient indicated high intra-session reliability in the MEP amplitudes for both methods (0.79 and 0.88, R-R and PEST respectively). The RMT and MEP amplitudes had higher inter-session reliability in both methods (0.99 and 0.998, R-R and PEST respectively; 0.84 and 0.76, R-R and PEST respectively). There was no significant difference between methods for RMT at both T1 (maximum stimulator output of R-R vs. PEST, 33.7% ± 7.7% vs. 33.8% ± 7.6%, p = 0.75) and T3 (maximum stimulator output of R-R vs. PEST, 33.5% ± 7.3% vs. 33.7% ± 7.3%, p = 0.19). There was a significant positive correlation between the methods' estimates of RMT, with PEST requiring significantly fewer stimuli. This study shows that the R-R and PEST methods have high intra-and inter-session reliability and the same precision, with PEST having the advantage over R-R in speed of estimation of RMT.
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ItemNo Preview AvailableAn Integrated Object Model and Method Framework for Subject-Centric e-Research Applications.(Frontiers Media SA, 2009)A framework that integrates an object model, research methods (workflows), the capture of experimental data sets and the provenance of those data sets for subject-centric research is presented. The design of the Framework object model draws on and extends pre-existing object models in the public domain. In particular the Framework tracks the state and life cycle of a subject during an experimental method, provides for reusable subjects, primary, derived and recursive data sets of arbitrary content types, and defines a user-friendly and practical scheme for citably identifying information in a distributed environment. The Framework is currently used to manage neuroscience Magnetic Resonance and microscopy imaging data sets in both clinical and basic neuroscience research environments. The Framework facilitates multi-disciplinary and collaborative subject-based research, and extends earlier object models used in the research imaging domain. Whilst the Framework has been explicitly validated for neuroimaging research applications, it has broader application to other fields of subject-centric research.
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ItemMulti-Modal Neuroimaging in Premanifest and Early Huntington's Disease: 18 Month Longitudinal Data from the IMAGE-HD Study(PUBLIC LIBRARY SCIENCE, 2013-09-16)IMAGE-HD is an Australian based multi-modal longitudinal magnetic resonance imaging (MRI) study in premanifest and early symptomatic Huntington's disease (pre-HD and symp-HD, respectively). In this investigation we sought to determine the sensitivity of imaging methods to detect macrostructural (volume) and microstructural (diffusivity) longitudinal change in HD. We used a 3T MRI scanner to acquire T1 and diffusion weighted images at baseline and 18 months in 31 pre-HD, 31 symp-HD and 29 controls. Volume was measured across the whole brain, and volume and diffusion measures were ascertained for caudate and putamen. We observed a range of significant volumetric and, for the first time, diffusion changes over 18 months in both pre-HD and symp-HD, relative to controls, detectable at the brain-wide level (volume change in grey and white matter) and in caudate and putamen (volume and diffusivity change). Importantly, longitudinal volume change in the caudate was the only measure that discriminated between groups across all stages of disease: far from diagnosis (>15 years), close to diagnosis (<15 years) and after diagnosis. Of the two diffusion metrics (mean diffusivity, MD; fractional anisotropy, FA), only longitudinal FA change was sensitive to group differences, but only after diagnosis. These findings further confirm caudate atrophy as one of the most sensitive and early biomarkers of neurodegeneration in HD. They also highlight that different tissue properties have varying schedules in their ability to discriminate between groups along disease progression and may therefore inform biomarker selection for future therapeutic interventions.
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ItemVolumetric Analysis of the Hypothalamus in Huntington Disease Using 3T MRI: The IMAGE-HD Study(PUBLIC LIBRARY SCIENCE, 2015-02-06)Huntington disease (HD) is a fatal neurodegenerative disorder caused by an expanded CAG repeat in the huntingtin gene. Non-motor symptoms and signs such as psychiatric disturbances, sleep problems and metabolic dysfunction are part of the disease manifestation. These aspects may relate to changes in the hypothalamus, an area of the brain involved in the regulation of emotion, sleep and metabolism. Neuropathological and imaging studies using both voxel-based morphometry (VBM) of magnetic resonance imaging (MRI) as well as positron emission tomography (PET) have demonstrated pathological changes in the hypothalamic region during early stages in symptomatic HD. In this investigation, we aimed to establish a robust method for measurements of the hypothalamic volume in MRI in order to determine whether the hypothalamic dysfunction in HD is associated with the volume of this region. Using T1-weighted imaging, we describe a reproducible delineation procedure to estimate the hypothalamic volume which was based on the same landmarks used in histologically processed postmortem hypothalamic tissue. Participants included 36 prodromal HD (pre-HD), 33 symptomatic HD (symp-HD) and 33 control participants who underwent MRI scanning at baseline and 18 months follow-up as part of the IMAGE-HD study. We found no evidence of cross-sectional or longitudinal changes between groups in hypothalamic volume. Our results suggest that hypothalamic pathology in HD is not associated with volume changes.
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ItemThe multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) high performance computing infrastructure: applications in neuroscience and neuroinformatics research(FRONTIERS MEDIA SA, 2014-03-27)The Multi-modal Australian ScienceS Imaging and Visualization Environment (MASSIVE) is a national imaging and visualization facility established by Monash University, the Australian Synchrotron, the Commonwealth Scientific Industrial Research Organization (CSIRO), and the Victorian Partnership for Advanced Computing (VPAC), with funding from the National Computational Infrastructure and the Victorian Government. The MASSIVE facility provides hardware, software, and expertise to drive research in the biomedical sciences, particularly advanced brain imaging research using synchrotron x-ray and infrared imaging, functional and structural magnetic resonance imaging (MRI), x-ray computer tomography (CT), electron microscopy and optical microscopy. The development of MASSIVE has been based on best practice in system integration methodologies, frameworks, and architectures. The facility has: (i) integrated multiple different neuroimaging analysis software components, (ii) enabled cross-platform and cross-modality integration of neuroinformatics tools, and (iii) brought together neuroimaging databases and analysis workflows. MASSIVE is now operational as a nationally distributed and integrated facility for neuroinfomatics and brain imaging research.
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ItemOptic Nerve Diffusion Tensor Imaging after Acute Optic Neuritis Predicts Axonal and Visual Outcomes(PUBLIC LIBRARY SCIENCE, 2013-12-26)BACKGROUND: Early markers of axonal and clinical outcomes are required for early phase testing of putative neuroprotective therapies for multiple sclerosis (MS). OBJECTIVES: To assess whether early measurement of diffusion tensor imaging (DTI) parameters (axial and radial diffusivity) within the optic nerve during and after acute demyelinating optic neuritis (ON) could predict axonal (retinal nerve fibre layer thinning and multi-focal visual evoked potential amplitude reduction) or clinical (visual acuity and visual field loss) outcomes at 6 or 12 months. METHODS: Thirty-seven patients presenting with acute, unilateral ON were studied at baseline, one, three, six and 12 months using optic nerve DTI, clinical and paraclinical markers of axonal injury and clinical visual dysfunction. RESULTS: Affected nerve axial diffusivity (AD) was reduced at baseline, 1 and 3 months. Reduced 1-month AD correlated with retinal nerve fibre layer (RNFL) thinning at 6 (R=0.38, p=0.04) and 12 months (R=0.437, p=0.008) and VEP amplitude loss at 6 (R=0.414, p=0.019) and 12 months (R=0.484, p=0.003). AD reduction at three months correlated with high contrast visual acuity at 6 (ρ = -0.519, p = 0.001) and 12 months (ρ = -0.414, p=0.011). The time-course for AD reduction for each patient was modelled using a quadratic regression. AD normalised after a median of 18 weeks and longer normalisation times were associated with more pronounced RNFL thinning and mfVEP amplitude loss at 12 months. Affected nerve radial diffusivity (RD) was unchanged until three months, after which time it remained elevated. CONCLUSIONS: These results demonstrate that AD reduces during acute ON. One month AD reduction correlates with the extent of axonal loss and persistent AD reduction at 3 months predicts poorer visual outcomes. This suggests that acute ON therapies that normalise optic nerve AD by 3 months could also promote axon survival and improve visual outcomes.