HiHi fMRI: a data-reordering method for measuring the hemodynamic response of the brain with high temporal resolution and high SNR.

There is emerging evidence that sampling the blood-oxygen-level-dependent (BOLD) response with high temporal resolution opens up new avenues to study the in vivo functioning of the human brain with functional magnetic resonance imaging. Because the speed of sampling and the signal level are intrinsically connected in magnetic resonance imaging via the T1 relaxation time, optimization efforts usually must make a trade-off to increase the temporal sampling rate at the cost of the signal level. We present a method, which combines a sparse event-related stimulus paradigm with subsequent data reshuffling to achieve high temporal resolution while maintaining high signal levels (HiHi). The proof-of-principle is presented by separately measuring the single-voxel time course of the BOLD response in both the primary visual and primary motor cortices with 100-ms temporal resolution.

Magnitude-intrinsic water-fat ambiguity can be resolved with multipeak fat modeling and a multipoint search method.

PURPOSE: To develop a postprocessing algorithm for multiecho chemical-shift encoded water-fat separation that estimates proton density fat fraction (PDFF) maps over the full dynamic range (0-100%) using multipeak fat modeling and multipoint search optimization. To assess its accuracy, reproducibility, and agreement with state-of-the-art complex-based methods, and to evaluate its robustness to artefacts in abdominal PDFF maps. METHODS: We introduce MAGO (MAGnitude-Only), a magnitude-based reconstruction that embodies multipeak liver fat spectral modeling and multipoint optimization, and which is compatible with asymmetric echo acquisitions. MAGO is assessed first for accuracy and reproducibility on publicly available phantom data. Then, MAGO is applied to N = 178 UK Biobank cases, in which its liver PDFF measures are compared using Bland-Altman analysis with those from a version of the hybrid iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) algorithm, LiverMultiScan IDEAL (LMS IDEAL, Perspectum Diagnostics Ltd, Oxford, UK). Finally, MAGO is tested on a succession of high field challenging cases for which LMS IDEAL generated artefacts in the PDFF maps. RESULTS: Phantom data showed accurate, reproducible MAGO PDFF values across manufacturers, field strengths, and acquisition protocols. Moreover, we report excellent agreement between MAGO and LMS IDEAL for 6-echo, 1.5 tesla human acquisitions (bias = -0.02% PDFF, 95% confidence interval = ±0.13% PDFF). When tested on 12-echo, 3 tesla cases from different manufacturers, MAGO was shown to be more robust to artefacts compared to LMS IDEAL. CONCLUSION: MAGO resolves the water-fat ambiguity over the entire fat fraction dynamic range without compromising accuracy, therefore enabling robust PDFF estimation where phase data is inaccessible or unreliable and complex-based and hybrid methods fail.

Real-time decoding of covert attention in higher-order visual areas.

Brain-computer-interfaces (BCI) provide a means of using human brain activations to control devices for communication. Until now this has only been demonstrated in primary motor and sensory brain regions, using surgical implants or non-invasive neuroimaging techniques. Here, we provide proof-of-principle for the use of higher-order brain regions involved in complex cognitive processes such as attention. Using realtime fMRI, we implemented an online 'winner-takes-all approach' with quadrant-specific parameter estimates, to achieve single-block classification of brain activations. These were linked to the covert allocation of attention to real-world images presented at 4-quadrant locations. Accuracies in three target regions were significantly above chance, with individual decoding accuracies reaching upto 70%. By utilising higher order mental processes, 'cognitive BCIs' access varied and therefore more versatile information, potentially providing a platform for communication in patients who are unable to speak or move due to brain injury.

Quantification of 18F-florbetapir PET: comparison of two analysis methods.

PURPOSE: (18)F-Florbetapir positron emission tomography (PET) can be used to image amyloid burden in the human brain. A previously developed research method has been shown to have a high test-retest reliability and good correlation between standardized uptake value ratio (SUVR) and amyloid burden at autopsy. The goal of this study was to determine how well SUVRs computed using the research method could be reproduced using an automatic quantification method, developed for clinical use. METHODS: Two methods for the quantitative analysis of (18)F-florbetapir PET were compared in a diverse clinical population of 604 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and in a group of 74 younger healthy controls (YHC). Cortex to cerebellum SUVRs were calculated using the research method, which is based on SPM, yielding 'research SUVRs', and using syngo.PET Amyloid Plaque, yielding 'sPAP SUVRs'. RESULTS: Mean cortical SUVRs calculated using the two methods for the 678 subjects were correlated (r = 0.99). Linear regression of sPAP SUVRs on research SUVRs was used to convert the research method SUVR threshold for florbetapir positivity of 1.10 to a corresponding threshold of 1.12 for sPAP. Using the corresponding thresholds, categorization of SUVR values were in agreement between research and sPAP SUVRs for 96.3 % of the ADNI images. SUVRs for all YHC were below the corresponding thresholds. CONCLUSION: Automatic florbetapir PET quantification using sPAP yielded cortex to cerebellum SUVRs which were correlated and in good agreement with the well-established research method. The research SUVR threshold for florbetapir positivity was reliably converted to a corresponding threshold for sPAP SUVRs.

Improving visual perception through neurofeedback.

Perception depends on the interplay of ongoing spontaneous activity and stimulus-evoked activity in sensory cortices. This raises the possibility that training ongoing spontaneous activity alone might be sufficient for enhancing perceptual sensitivity. To test this, we trained human participants to control ongoing spontaneous activity in circumscribed regions of retinotopic visual cortex using real-time functional MRI-based neurofeedback. After training, we tested participants using a new and previously untrained visual detection task that was presented at the visual field location corresponding to the trained region of visual cortex. Perceptual sensitivity was significantly enhanced only when participants who had previously learned control over ongoing activity were now exercising control and only for that region of visual cortex. Our new approach allows us to non-invasively and non-pharmacologically manipulate regionally specific brain activity and thus provide "brain training" to deliver particular perceptual enhancements.

Phase informed model for motion and susceptibility.

Field inhomogeneities caused by variations in magnetic susceptibility throughout the head lead to geometric distortions, mainly in the phase-encode direction of echo-planar images (EPI). The magnitude and spatial characteristics of the distortions depend on the orientation of the head in the magnetic field and will therefore vary with head movement. A new method is presented, based on a phase informed model for motion and susceptibility (PIMMS), which estimates the change in geometric distortion associated with head motion. This method fits a model of the head motion parameters and scanner hardware characteristics to EPI phase time series. The resulting maps of the model fit parameters are used to correct for susceptibility artifacts in the magnitude images. Results are shown for EPI-based fMRI time-series acquired at 3T, demonstrating that compared with conventional rigid body realignment, PIMMS removes residual variance associated with motion-related distortion effects. Furthermore, PIMMS can lead to a reduction in false negatives compared with the widely accepted approach which uses standard rigid body realignment and includes the head motion parameters in the statistical model. The PIMMS method can be used with any standard EPI sequence for which accurate phase information is available.

High-resolution functional MRI at 3 T: 3D/2D echo-planar imaging with optimized physiological noise correction.

High-resolution functional MRI (fMRI) offers unique possibilities for studying human functional neuroanatomy. Although high-resolution fMRI has proven its potential at 7 T, most fMRI studies are still performed at rather low spatial resolution at 3 T. We optimized and compared single-shot two-dimensional echo-planar imaging (EPI) and multishot three-dimensional EPI high-resolution fMRI protocols. We extended image-based physiological noise correction from two-dimensional EPI to multishot three-dimensional EPI. The functional sensitivity of both acquisition schemes was assessed in a visual fMRI experiment. The physiological noise correction increased the sensitivity significantly, can be easily applied, and requires simple recordings of pulse and respiration only. The combination of three-dimensional EPI with physiological noise correction provides exceptional sensitivity for 1.5 mm high-resolution fMRI at 3 T, increasing the temporal signal-to-noise ratio by more than 25% compared to two-dimensional EPI.

Retrospective correction of physiological noise in DTI using an extended tensor model and peripheral measurements.

Diffusion tensor imaging is widely used in research and clinical applications, but this modality is highly sensitive to artefacts. We developed an easy-to-implement extension of the original diffusion tensor model to account for physiological noise in diffusion tensor imaging using measures of peripheral physiology (pulse and respiration), the so-called extended tensor model. Within the framework of the extended tensor model two types of regressors, which respectively modeled small (linear) and strong (nonlinear) variations in the diffusion signal, were derived from peripheral measures. We tested the performance of four extended tensor models with different physiological noise regressors on nongated and gated diffusion tensor imaging data, and compared it to an established data-driven robust fitting method. In the brainstem and cerebellum the extended tensor models reduced the noise in the tensor-fit by up to 23% in accordance with previous studies on physiological noise. The extended tensor model addresses both large-amplitude outliers and small-amplitude signal-changes. The framework of the extended tensor model also facilitates further investigation into physiological noise in diffusion tensor imaging. The proposed extended tensor model can be readily combined with other artefact correction methods such as robust fitting and eddy current correction.

Estimation of field inhomogeneity map following magnitude-based ambiguity-resolved water-fat separation.

Magnitude-based PDFF (Proton Density Fat Fraction) and R2∗ mapping with resolved water-fat ambiguity is extended to calculate field inhomogeneity (field map) using the phase images. The estimation is formulated in matrix form, resolving the field map in a least-squares sense. PDFF and R2∗ from magnitude fitting may be updated using the estimated field maps. The limits of quantification of our voxel-independent implementation were assessed. Bland-Altman was used to compare PDFF and field maps from our method against a reference complex-based method on 152 UK Biobank subjects (1.5 T Siemens). A separate acquisition (3 T Siemens) presenting field inhomogeneities was also used. The proposed field mapping was accurate beyond double the complex-based limit range. High agreement was obtained between the proposed method and the reference in UK. Robust field mapping was observed at 3 T, for inhomogeneities over 400 Hz including rapid variation across edges. Field mapping following unambiguous magnitude-based water-fat separation was demonstrated in-vivo and showed potential at 3 T.

Correction of vibration artifacts in DTI using phase-encoding reversal (COVIPER).

Diffusion tensor imaging is widely used in research and clinical applications, but still suffers from substantial artifacts. Here, we focus on vibrations induced by strong diffusion gradients in diffusion tensor imaging, causing an echo shift in k-space and consequential signal-loss. We refined the model of vibration-induced echo shifts, showing that asymmetric k-space coverage in widely used Partial Fourier acquisitions results in locally differing signal loss in images acquired with reversed phase encoding direction (blip-up/blip-down). We implemented a correction of vibration artifacts in diffusion tensor imaging using phase-encoding reversal (COVIPER) by combining blip-up and blip-down images, each weighted by a function of its local tensor-fit error. COVIPER was validated against low vibration reference data, resulting in an error reduction of about 72% in fractional anisotropy maps. COVIPER can be combined with other corrections based on phase encoding reversal, providing a comprehensive correction for eddy currents, susceptibility-related distortions and vibration artifact reduction.

Axonal integrity predicts cortical reorganisation following cervical injury.

BACKGROUND: Traumatic spinal cord injury (SCI) leads to disruption of axonal architecture and macroscopic tissue loss with impaired information flow between the brain and spinal cord-the presumed basis of ensuing clinical impairment. OBJECTIVE: The authors used a clinically viable, multimodal MRI protocol to quantify the axonal integrity of the cranial corticospinal tract (CST) and to establish how microstructural white matter changes in the CST are related to cross-sectional spinal cord area and cortical reorganisation of the sensorimotor system in subjects with traumatic SCI. METHODS: Nine volunteers with cervical injuries resulting in bilateral motor impairment and 14 control subjects were studied. The authors used diffusion tensor imaging to assess white matter integrity in the CST, T1-weighted imaging to measure cross-sectional spinal cord area and functional MRI to compare motor task-related brain activations. The relationships among microstructural, macrostructural and functional measures were assessed using regression analyses. Results Diffusion tensor imaging revealed significant differences in the CST of SCI subjects-compared with controls-in the pyramids, the internal capsule, the cerebral peduncle and the hand area. The microstructural white matter changes observed in the left pyramid predicted increased task-related responses in the left M1 leg area, while changes in the cerebral peduncle were predicted by reduced cord area. CONCLUSION: The observed microstructural changes suggest trauma-related axonal degeneration and demyelination, which are related to cortical motor reorganisation and macrostructure. The extent of these changes may reflect the plasticity of motor pathways associated with cortical reorganisation. This clinically viable multimodal imaging approach is therefore appropriate for monitoring degeneration of central pathways and the evaluation of treatments targeting axonal repair in SCI.

Disability, atrophy and cortical reorganization following spinal cord injury.

The impact of traumatic spinal cord injury on structural integrity, cortical reorganization and ensuing disability is variable and may depend on a dynamic interaction between the severity of local damage and the capacity of the brain for plastic reorganization. We investigated trauma-induced anatomical changes in the spinal cord and brain, and explored their relationship to functional changes in sensorimotor cortex. Structural changes were assessed using cross-sectional cord area, voxel-based morphometry and voxel-based cortical thickness of T1-weighted images in 10 subjects with cervical spinal cord injury and 16 controls. Cortical activation in response to right-sided (i) handgrip; and (ii) median and tibial nerve stimulation were assessed using functional magnetic resonance imaging. Regression analyses explored associations between cord area, grey and white matter volume, cortical activations and thickness, and disability. Subjects with spinal cord injury had impaired upper and lower limb function bilaterally, a 30% reduced cord area, smaller white matter volume in the pyramids and left cerebellar peduncle, and smaller grey matter volume and cortical thinning in the leg area of the primary motor and sensory cortex compared with controls. Functional magnetic resonance imaging revealed increased activation in the left primary motor cortex leg area during handgrip and the left primary sensory cortex face area during median nerve stimulation in subjects with spinal cord injury compared with controls, but no increased activation following tibial nerve stimulation. A smaller cervical cord area was associated with impaired upper limb function and increased activations with handgrip and median nerve stimulation, but reduced activations with tibial nerve stimulation. Increased sensory deficits were associated with increased activations in the left primary sensory cortex face area due to median nerve stimulation. In conclusion, spinal cord injury leads to cord atrophy, cortical atrophy of primary motor and sensory cortex, and cortical reorganization of the sensorimotor system. The degree of cortical reorganization is predicted by spinal atrophy and is associated with significant disability.

Effects of preterm birth on cortical thickness measured in adolescence.

Despite the extensive research into brain development after preterm birth, few studies have investigated its long-term effects on cortical thickness. The Stockholm Neonatal Project included infants between 1988 and 1993 with birth weight (BW) ≤ 1500 g. Using a previously published method, cortical thickness was estimated on T(1)-weighted 3D anatomical images acquired from 74 ex-preterm and 69 term-born adolescents (mean age 14.92 years). The cortex was significantly thinner in ex-preterm individuals in focal regions of the temporal and parietal cortices as indicated by voxel-wise t-tests. In addition, large regions around the central sulcus and temporal lobe as well as parts of the frontal and occipital lobes tended also to be thinner in the ex-preterm group. Although these results were not significant on voxel-wise tests, the spatially coherent arrangement of the thinning in ex-preterm individuals made it notable. When the group of ex-preterm individuals was divided by gestational age or BW, the thinning tended to be more pronounced in the anterior and posterior poles in those born nearer term or with a BW closer to 1500 g. These results support the notion that preterm birth is a risk factor for long-term development of cortical thickness.

Unified segmentation based correction of R1 brain maps for RF transmit field inhomogeneities (UNICORT).

Quantitative mapping of the longitudinal relaxation rate (R1=1/T1) in the human brain enables the investigation of tissue microstructure and macroscopic morphology which are becoming increasingly important for clinical and neuroimaging applications. R1 maps are now commonly estimated from two fast high-resolution 3D FLASH acquisitions with variable excitation flip angles, because this approach is fast and does not rely on special acquisition techniques. However, these R1 maps need to be corrected for bias due to RF transmit field (B1(+)) inhomogeneities, requiring additional B1(+) mapping which is usually time consuming and difficult to implement. We propose a technique that simultaneously estimates the B1(+) inhomogeneities and R1 values from the uncorrected R1 maps in the human brain without need for B1(+) mapping. It employs a probabilistic framework for unified segmentation based correction of R1 maps for B1(+) inhomogeneities (UNICORT). The framework incorporates a physically informed generative model of smooth B1(+) inhomogeneities and their multiplicative effect on R1 estimates. Extensive cross-validation with the established standard using measured B1(+) maps shows that UNICORT yields accurate B1(+) and R1 maps with a mean deviation from the standard of less than 4.3% and 5%, respectively. The results of different groups of subjects with a wide age range and different levels of atypical brain anatomy further suggest that the method is robust and generalizes well to wider populations. UNICORT is easy to apply, as it is computationally efficient and its basic framework is implemented as part of the tissue segmentation in SPM8.

Abnormal attentional modulation of retinotopic cortex in parietal patients with spatial neglect.

Brain regions beyond visual cortex are thought to be responsible for attention-related modulation of visual processing [1, 2], but most evidence is indirect. Here, we applied functional magnetic resonance imaging (fMRI), including retinotopic mapping of visual areas, to patients with focal right-parietal lesions and left spatial neglect [3, 4]. When attentional load at fixation was minimal, retinotopic areas in right visual cortex showed preserved responses to task-irrelevant checkerboards in the contralateral left hemifield, analogously to left visual cortex for right-hemifield checkerboards, indicating a "symmetric" pattern in both hemispheres with respect to contralateral stimulation under these conditions. But when attentional load at fixation was increased, a functional asymmetry emerged for visual cortex, with contralateral responses in right visual areas being pathologically reduced (even eliminated for right V4/TEO), whereas left visual areas showed no such reduction in their contralateral response. These results reveal attention-dependent abnormalities in visual cortex after lesions in distant (parietal) regions. This may explain otherwise puzzling aspects of neglect [5, 6], as confirmed here by additional behavioral testing.

Multispectral brain morphometry in Tourette syndrome persisting into adulthood.

Tourette syndrome is a childhood-onset neuropsychiatric disorder with a high prevalence of attention deficit hyperactivity and obsessive-compulsive disorder co-morbidities. Structural changes have been found in frontal cortex and striatum in children and adolescents. A limited number of morphometric studies in Tourette syndrome persisting into adulthood suggest ongoing structural alterations affecting frontostriatal circuits. Using cortical thickness estimation and voxel-based analysis of T1- and diffusion-weighted structural magnetic resonance images, we examined 40 adults with Tourette syndrome in comparison with 40 age- and gender-matched healthy controls. Patients with Tourette syndrome showed relative grey matter volume reduction in orbitofrontal, anterior cingulate and ventrolateral prefrontal cortices bilaterally. Cortical thinning extended into the limbic mesial temporal lobe. The grey matter changes were modulated additionally by the presence of co-morbidities and symptom severity. Prefrontal cortical thickness reduction correlated negatively with tic severity, while volume increase in primary somatosensory cortex depended on the intensity of premonitory sensations. Orbitofrontal cortex volume changes were further associated with abnormal water diffusivity within grey matter. White matter analysis revealed changes in fibre coherence in patients with Tourette syndrome within anterior parts of the corpus callosum. The severity of motor tics and premonitory urges had an impact on the integrity of tracts corresponding to cortico-cortical and cortico-subcortical connections. Our results provide empirical support for a patho-aetiological model of Tourette syndrome based on developmental abnormalities, with perturbation of compensatory systems marking persistence of symptoms into adulthood. We interpret the symptom severity related grey matter volume increase in distinct functional brain areas as evidence of ongoing structural plasticity. The convergence of evidence from volume and water diffusivity imaging strengthens the validity of our findings and attests to the value of a novel multimodal combination of volume and cortical thickness estimations that provides unique and complementary information by exploiting their differential sensitivity to structural change.

Comparison between magnetic resonance and ultrasound-derived indicators of hepatic steatosis in a pooled NAFLD cohort.

BACKGROUND & AIMS: MRI-based proton density fat fraction (PDFF) and the ultrasound-derived controlled attenuation parameter (CAP) are non-invasive techniques for quantifying liver fat, which can be used to assess steatosis in patients with non-alcoholic fatty liver disease (NAFLD). This study compared both of these techniques to histopathological graded steatosis for the assessment of fat levels in a large pooled NAFLD cohort. METHODS: This retrospective study pooled N = 581 participants from two suspected NAFLD cohorts (mean age (SD) 56 (12.7), 60% females). Steatosis was graded according to NASH-CRN criteria. Liver fat was measured non-invasively using PDFF (with Liver MultiScan's Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation method, LMS-IDEAL, Perspectum, Oxford) and CAP (FibroScan, Echosens, France), and their diagnostic performances were compared. RESULTS: LMS-IDEAL and CAP detected steatosis grade ≥ 1 with AUROCs of 1.00 (95% CI, 0.99-1.0) and 0.95 (95% CI, 0.91-0.99), respectively. LMS-IDEAL was superior to CAP for detecting steatosis grade ≥ 2 with AUROCs of 0.77 (95% CI, 0.73-0.82] and 0.60 (95% CI, 0.55-0.65), respectively. Similarly, LMS-IDEAL outperformed CAP for detecting steatosis grade ≥ 3 with AUROCs of 0.81 (95% CI, 0.76-0.87) and 0.63 (95% CI, 0.56-0.70), respectively. CONCLUSION: LMS-IDEAL was able to diagnose individuals accurately across the spectrum of histological steatosis grades. CAP performed well in identifying individuals with lower levels of fat (steatosis grade ≥1); however, its diagnostic performance was inferior to LMS-IDEAL for higher levels of fat (steatosis grades ≥2 and ≥3). TRIAL REGISTRATION: ClinicalTrials.gov (NCT03551522); https://clinicaltrials.gov/ct2/show/NCT03551522. UMIN Clinical Trials Registry (UMIN000026145); https://upload.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000026145.

Improved shimming for fMRI specifically optimizing the local BOLD sensitivity.

In functional MRI, magnetic field inhomogeneities due to air-tissue susceptibility differences may lead to severe signal dropouts and geometric distortions in echo-planar images. Therefore, the inhomogeneities in the field are routinely minimized by shimming prior to imaging. However in fMRI, the Blood Oxygen Level Dependent (BOLD) effect is the measure of interest, so the BOLD sensitivity (BS) should be optimized rather than the magnetic field homogeneity. The analytical expression for an estimate of the BOLD sensitivity has been recently developed, allowing for the computation of BOLD sensitivity maps from echo-planar images and field maps. This report describes a novel shimming procedure that optimizes the local BOLD sensitivity over a region of interest. The method is applied in vivo and compared to a standard global shimming procedure. A breath-holding experiment was carried out and demonstrated that the BS-based shimming significantly improved the detection of activation in a target region of interest, the medial orbitofrontal cortex.

Optimization and validation of methods for mapping of the radiofrequency transmit field at 3T.

MRI techniques such as quantitative imaging and parallel transmit require precise knowledge of the radio-frequency transmit field (B(1) (+)). Three published methods were optimized for robust B(1) (+) mapping at 3T in the human brain: three-dimensional (3D) actual flip angle imaging (AFI), 3D echo-planar imaging (EPI), and two-dimensional (2D) stimulated echo acquisition mode (STEAM). We performed a comprehensive comparison of the methods, focusing on artifacts, reproducibility, and accuracy compared to a reference 2D double angle method. For the 3D AFI method, the addition of flow-compensated gradients for diffusion damping reduced the level of physiological artifacts and improved spoiling of transverse coherences. Correction of susceptibility-induced artifacts alleviated image distortions and improved the accuracy of the 3D EPI imaging method. For the 2D STEAM method, averaging over multiple acquisitions reduced the impact of physiological noise and a new calibration method enhanced the accuracy of the B(1) (+) maps. After optimization, all methods yielded low noise B(1) (+) maps (below 2 percentage units), of the nominal flip angle value (p.u.) with a systematic bias less than 5 p.u. units. Full brain coverage was obtained in less than 5 min. The 3D AFI method required minimal postprocessing and showed little sensitivity to off-resonance and physiological effects. The 3D EPI method showed the highest level of reproducibility. The 2D STEAM method was the most time-efficient technique.

A comparison between voxel-based cortical thickness and voxel-based morphometry in normal aging.

The morphology of cortical grey matter is commonly assessed using T1-weighted MRI together with automated computerised methods such as voxel-based morphometry (VBM) and cortical thickness measures. In the presented study we investigate how grey matter changes identified using voxel-based cortical thickness (VBCT) measures compare with local grey matter volume changes identified using VBM. We use data from a healthy aging population to perform the comparison, focusing on brain regions where age-related changes have been observed in previous studies. Our results show that overall, in healthy aging, VBCT and VBM yield very consistent results but VBCT provides a more sensitive measure of age-associated decline in grey matter compared with VBM. Our findings suggest that while VBCT selectively investigates cortical thickness, VBM provides a mixed measure of grey matter including cortical surface area or cortical folding, as well as cortical thickness. We therefore propose that used together, these techniques can separate the underlying grey matter changes, highlighting the utility of combining these complementary methods.