Search

Abstract: Reliable identification of thalamic nuclei is required to improve positioning of electrodes in Deep Brain Stimulation (DBS), and to allow the role of individual thalamic nuclei in health and disease to be fully investigated. In this work, a previously proposed method for identifying sub-regions within the thalamus based on differences in their T1 and T2 values is explored in detail. The effect on the segmentation of T1 and T2 dependence weighted against priors for spatial position and extent was investigated. When T1 and T2 dependence was highly weighted, good distinction between identified regions was obtained in T1/T2 feature-space, but no contiguous anatomically distinct regions were identified within the thalamus. Incorporating spatial priors was necessary to ensure anatomically distinct regions were defined. Optimal values for segmentation parameters were obtained by assessing performance on a ‘synthetic thalamus’. Using these optimum input parameters, within- and between-subjects reproducibility was assessed. Good reproducibility was obtained when six regions were specified to be identified in the thalamus. The six regions identified were similar in the majority of the normal subject group. However, intriguingly these regions were different from those obtained in the same subjects using a well-known connectivity-based segmentation technique. This method shows promise to identify intrathalamic structures on the basis of T1 and T2 signal. A comprehensive characterisation of thalamic nuclei may require a fully multi-modal approach. [Copyright &y& Elsevier]

Abstract: Quantitative models of magnetization transfer (MT) allow the estimation of physical properties of tissue which are thought to reflect myelination, and are therefore likely to be useful for clinical application. Although a model describing a two-pool system under continuous wave-saturation has been available for two decades, generalizing such a model to pulsed MT, and therefore to in vivo applications, is not straightforward, and only recently have a range of equations predicting the outcome of pulsed MT experiments been proposed. These solutions of the 2-pool model are based on differing assumptions and involve differing degrees of complexity, so their individual advantages and limitations are not always obvious. This paper is concerned with the comparison of three differing signal equations. After reviewing the theory behind each of them, their accuracy and precision is investigated using numerical simulations under variable experimental conditions such as degree of T 1-weighting of the acquisition sequence and SNR, and the consistency of numerical results is tested using in vivo data. We show that while in conditions of minimal T 1-weighting, high SNR, and large duty cycle the solutions of the three equations are consistent, they have a different tolerance to deviations from the basic assumptions behind their development, which should be taken into account when designing a quantitative MT protocol. [Copyright &y& Elsevier]

Abstract: There is a wide range of functional magnetic resonance imaging (fMRI) study designs available for the neuroscientist who wants to investigate cognition. In this manuscript we review some aspects of fMRI study design, including cognitive comparison strategies (factorial, parametric designs), and stimulus presentation possibilities (block, event-related, rapid event-related, mixed, and self-driven experiment designs) along with technical aspects, such as limitations of signal to noise ratio, spatial, and temporal resolution. We also discuss methods to deal with cases where scanning parameters become the limiting factor (parallel acquisitions, variable jittered designs, scanner acoustic noise strategies). [Copyright &y& Elsevier]

Abstract: This study uses Monte Carlo simulations to investigate the optimal value of the diffusion weighting factor b for estimating white-matter fiber orientations using diffusion MRI with a standard spherical sampling scheme. We devise an algorithm for determining the optimal echo time, pulse width, and pulse separation in the pulsed-gradient spin-echo sequence for a specific value of b. The Monte Carlo simulations provide an estimate of the optimal value of b for recovering one and two fiber orientations. We show that the optimum is largely independent of the noise level in the measurements and the number of gradient directions and that the optimum depends only weakly on the diffusion anisotropy, the maximum gradient strength, and the spin–spin relaxation time. The optimum depends strongly on the mean diffusivity. In brain tissue, the optima we estimate are in the ranges [0.7, 1.0] × 109 s m−2 and [2.2, 2.8] × 109 s m−2 for the one- and two-fiber cases, respectively. The best b for estimating the fractional anisotropy is slightly higher than for estimating fiber directions in the one-fiber case and slightly lower in the two-fiber case. To estimate Tr(D) in the one-fiber case, the optimal setting is higher still. Simulations suggest that a ratio of high to low b measurements of 5 to 1 is a good compromise for measuring fiber directions and size and shape indices. [Copyright &y& Elsevier]

Abstract: The anterior insula (AI) plays a key role in affective processing, and insular dysfunction has been noted in several clinical conditions. Real-time functional MRI neurofeedback (rtfMRI-NF) provides a means of helping people learn to self-regulate activation in this brain region. Using the Blood Oxygenated Level Dependant (BOLD) signal from the right AI (RAI) as neurofeedback, we trained participants to increase RAI activation. In contrast, another group of participants was shown ‘control’ feedback from another brain area. Pre- and post-training affective probes were shown, with subjective ratings and skin conductance response (SCR) measured. We also investigated a reward-related reinforcement learning model of rtfMRI-NF. In contrast to the controls, we hypothesised a positive linear increase in RAI activation in participants shown feedback from this region, alongside increases in valence ratings and SCR to affective probes. Hypothesis-driven analyses showed a significant interaction between the RAI/control neurofeedback groups and the effect of self-regulation. Whole-brain analyses revealed a significant linear increase in RAI activation across four training runs in the group who received feedback from RAI. Increased activation was also observed in the caudate body and thalamus, likely representing feedback-related learning. No positive linear trend was observed in the RAI in the group receiving control feedback, suggesting that these data are not a general effect of cognitive strategy or control feedback. The control group did, however, show diffuse activation across the putamen, caudate and posterior insula which may indicate the representation of false feedback. No significant training-related behavioural differences were observed for valence ratings, or SCR. In addition, correlational analyses based on a reinforcement learning model showed that the dorsal anterior cingulate cortex underpinned learning in both groups. In summary, these data demonstrate that it is possible to regulate the RAI using rtfMRI-NF within one scanning session, and that such reward-related learning is mediated by the dorsal anterior cingulate. [Copyright &y& Elsevier]

Abstract: Diffusion Tensor Imaging (DTI) is being increasingly used to assess white matter integrity and it is therefore paramount to address the test–retest reliability of DTI measures. In this study we assessed inter- and intra-site reproducibility of two nominally identical 3T scanners at different sites in nine healthy controls using a DTI protocol representative of typical current “best practice” including cardiac gating, a multichannel head coil, parallel imaging and optimized diffusion gradient parameters. We calculated coefficients of variation (CV) and intraclass correlation coefficients (ICC) of fractional anisotropy (FA) measures for the whole brain, for three regions of interest (ROI) and for three tracts derived from these ROI by probabilistic tracking. We assessed the impact of affine, nonlinear and template based methods for spatially aligning FA maps on the reproducibility. The intra-site CV for FA ranged from 0.8% to 3.0% with ICC from 0.90 to 0.99, while the inter-site CV ranged from 1.0% to 4.1% with ICC of 0.82 to 0.99. Nonlinear image coregistration improved reproducibility compared to affine coregistration. Normalization to template space reduced the between-subject variation, resulting in lower ICC values and indicating a possibly reduced sensitivity. CV from probabilistic tractography were about 50% higher than for the corresponding seed ROI. Reproducibility maps of the whole scan volume showed a low variation of less than 5% in the major white matter tracts but higher variations of 10–15% in gray matter regions. One of the two scanners showed better intra-site reproducibility, while the intra-site CV for both scanners was significantly better than inter-site CV. However, when using nonlinear coregistration of FA maps, the average inter-site CV was below 2%. There was a consistent inter-site bias, FA values on site 2 were 1.0–1.5% lower than on site 1. Correction for this bias with a global scaling factor reduced the inter-site CV to the range of intra-site CV. Our results are encouraging for multi-centre DTI studies in larger populations, but also illustrate the importance of the image processing pipeline for reproducibility. [Copyright &y& Elsevier]

Abstract: Objective: Disruptions in white matter structure have consistently been shown in schizophrenia — but mainly in patients in whom the illness is well-established. In order to determine whether white matter abnormalities are present at illness onset, and to minimise the potentially confounding effects of chronic illness and treatment, we used diffusion tensor imaging to study a large cohort of first episode psychotic patients who were medication-naive. Methods: Sixty two first episode patients and 54 controls matched on age, sex, years of education and laterality index underwent diffusion tensor imaging. Data were acquired on a GE Signa NVi 1.5 Tesla System. Fractional anisotropy maps were generated on a voxel-by-voxel basis. An optimized voxel-based morphometry technique was conducted with two-stage registration approach. Group differences were examined using a non-parametric statistical method. Results: The voxelwise analysis revealed four clusters where fractional anisotropy values were significantly lower in patients than controls. These were localised bilaterally to regions of white matter corresponding to superior and inferior longitudinal fasciculus, forceps major, anterior and superior thalamic radiation and corpus callosum. Conclusions: Reductions in white matter integrity are present early in the course of the schizophrenia and localised in fascicule that connect brain regions implicated in the disorder. [Copyright &y& Elsevier]

Diffusion tensor imaging (DTI), a magnetic resonance imaging technique, is used to infer major axonal projections in the macaque and human brain. This study investigates the feasibility of using known macaque anatomical connectivity as a “gold-standard” for the evaluation of DTI tractography methods. Connectivity information is determined from the DTI data using fast marching tractography (FMT), a novel tract-tracing (tractography) method. We show for the first time that it is possible to determine, in an entirely noninvasive manner, anatomical connection pathways and maps of an anatomical connectivity metric in the macaque brain using a standard clinical scanner and that these pathways are consistent with known anatomy. Analogous human anatomical connectivity is also presented for the first time using the FMT method, and the results are compared. The current limitations of the methodology and possibilities available for further studies are discussed. [Copyright &y& Elsevier]

• Altered brain development in left-frontal lobe structures in children with Rolandic epilepsy (RE). • During active epilepsy, developmental coordination disorder (DCD) is prevalent in children with RE. • In seizure remission, DCD is not evident. • In RE, there is an association between a reduction in cortical thickness and speech processing. Self - limiting Rolandic epilepsy (RE) is the most common epilepsy in school-age children. Seizures are generally infrequent, but cognitive, language, and motor coordination problems can significantly impact the child's life. To better understand brain structure and function changes in RE, we longitudinally assessed neurocognition, cortical thickness, and subcortical volumes. At baseline, we recruited 30 participants diagnosed with RE and 24-healthy controls and followed up for 4.94 ± 0.8 years when the participants with RE were in seizure remission. Measures included were as follows: T1-weighted magnetic resonance brain imaging (MRI) with FreeSurfer analysis and detailed neuropsychological assessments. MRI and neuropsychological data were compared between baseline and follow-up in seizure remission. Longitudinal MRI revealed excess cortical thinning in the left-orbitofrontal (p = 0.0001) and pre-central gyrus (p = 0.044). There is a significant association (p = 0.003) between a reduction in cortical thickness in the left-orbitofrontal cluster and improved processing of filtered words. Longitudinal neuropsychology revealed significant improvements in the symptoms of developmental coordination disorder (DCD, p = 0.005) in seizure remission. There is evidence for altered development of neocortical regions between active seizure state and seizure remission in RE within two clusters maximal in the left-orbitofrontal and pre-central gyrus. There is significant evidence for improvement in motor coordination between active seizures and seizure remission and suggestive evidence for a decline in fluid intelligence and gains in auditory processing. [ABSTRACT FROM AUTHOR]

Multi-subject datasets used in neuroimaging group studies have a complex structure, as they exhibit non-stationary statistical properties across regions and display various artifacts. While studies with small sample sizes can rarely be shown to deviate from standard hypotheses (such as the normality of the residuals) due to the poor sensitivity of normality tests with low degrees of freedom, large-scale studies (e.g. > 100 subjects) exhibit more obvious deviations from these hypotheses and call for more refined models for statistical inference. Here, we demonstrate the benefits of robust regression as a tool for analyzing large neuroimaging cohorts. First, we use an analytic test based on robust parameter estimates; based on simulations, this procedure is shown to provide an accurate statistical control without resorting to permutations. Second, we show that robust regression yields more detections than standard algorithms using as an example an imaging genetics study with 392 subjects. Third, we show that robust regression can avoid false positives in a large-scale analysis of brain–behavior relationships with over 1500 subjects. Finally we embed robust regression in the Randomized Parcellation Based Inference (RPBI) method and demonstrate that this combination further improves the sensitivity of tests carried out across the whole brain. Altogether, our results show that robust procedures provide important advantages in large-scale neuroimaging group studies. [ABSTRACT FROM AUTHOR]

The issue of whether human perception of speech and song recruits integrated or dissociated neural systems is contentious. This issue is difficult to address directly since these stimulus classes differ in their physical attributes. We therefore used a compelling illusion (Deutsch et al. 2011) in which acoustically identical auditory stimuli are perceived as either speech or song. Deutsch's illusion was used in a functional MRI experiment to provide a direct, within-subject investigation of the brain regions involved in the perceptual transformation from speech into song, independent of the physical characteristics of the presented stimuli. An overall differential effect resulting from the perception of song compared with that of speech was revealed in right midposterior superior temporal sulcus/right middle temporal gyrus. A left frontotemporal network, previously implicated in higher-level cognitive analyses of music and speech, was found to co-vary with a behavioural measure of the subjective vividness of the illusion, and this effect was driven by the illusory transformation. These findings provide evidence that illusory song perception is instantiated by a network of brain regions that are predominantly shared with the speech perception network. [ABSTRACT FROM AUTHOR]

Abstract: Neuroimaging group analyses are used to relate inter-subject signal differences observed in brain imaging with behavioral or genetic variables and to assess risks factors of brain diseases. The lack of stability and of sensitivity of current voxel-based analysis schemes may however lead to non-reproducible results. We introduce a new approach to overcome the limitations of standard methods, in which active voxels are detected according to a consensus on several random parcellations of the brain images, while a permutation test controls the false positive risk. Both on synthetic and real data, this approach shows higher sensitivity, better accuracy and higher reproducibility than state-of-the-art methods. In a neuroimaging–genetic application, we find that it succeeds in detecting a significant association between a genetic variant next to the COMT gene and the BOLD signal in the left thalamus for a functional Magnetic Resonance Imaging contrast associated with incorrect responses of the subjects from a Stop Signal Task protocol. [Copyright &y& Elsevier]

Convolutional neural networks (CNN) can accurately predict chronological age in healthy individuals from structural MRI brain scans. Potentially, these models could be applied during routine clinical examinations to detect deviations from healthy ageing, including early-stage neurodegeneration. This could have important implications for patient care, drug development, and optimising MRI data collection. However, existing brain-age models are typically optimised for scans which are not part of routine examinations (e.g., volumetric T1-weighted scans), generalise poorly (e.g., to data from different scanner vendors and hospitals etc.), or rely on computationally expensive pre-processing steps which limit real-time clinical utility. Here, we sought to develop a brain-age framework suitable for use during routine clinical head MRI examinations. Using a deep learning-based neuroradiology report classifier, we generated a dataset of 23,302 'radiologically normal for age' head MRI examinations from two large UK hospitals for model training and testing (age range = 18–95 years), and demonstrate fast (< 5 s), accurate (mean absolute error [MAE] < 4 years) age prediction from clinical-grade, minimally processed axial T2-weighted and axial diffusion-weighted scans, with generalisability between hospitals and scanner vendors (Δ MAE < 1 year). The clinical relevance of these brain-age predictions was tested using 228 patients whose MRIs were reported independently by neuroradiologists as showing atrophy 'excessive for age'. These patients had systematically higher brain-predicted age than chronological age (mean predicted age difference = +5.89 years, 'radiologically normal for age' mean predicted age difference = +0.05 years, p < 0.0001). Our brain-age framework demonstrates feasibility for use as a screening tool during routine hospital examinations to automatically detect older-appearing brains in real-time, with relevance for clinical decision-making and optimising patient pathways. [ABSTRACT FROM AUTHOR]

Large-scale longitudinal and multi-centre studies are used to explore neuroimaging markers of normal ageing, and neurodegenerative and mental health disorders. Longitudinal changes in brain structure are typically small, therefore the reliability of automated techniques is crucial. Determining the effects of different factors on reliability allows investigators to control those adversely affecting reliability, calculate statistical power, or even avoid particular brain measures with low reliability. This study examined the impact of several image acquisition and processing factors and documented the test-retest reliability of structural MRI measurements. In Phase I, 20 healthy adults (11 females; aged 20–30 years) were scanned on two occasions three weeks apart on the same scanner using the ADNI-3 protocol. On each occasion, individuals were scanned twice (repetition), after re-entering the scanner (reposition) and after tilting their head forward. At one year follow-up, nine returning individuals and 11 new volunteers were recruited for Phase II (11 females; aged 22–31 years). Scans were acquired on two different scanners using the ADNI-2 and ADNI-3 protocols. Structural images were processed using FreeSurfer (v5.3.0, 6.0.0 and 7.1.0) to provide subcortical and cortical volume, cortical surface area and thickness measurements. Intra-class correlation coefficients (ICC) were calculated to estimate test-retest reliability. We examined the effect of repetition, reposition, head tilt, time between scans, MRI sequence and scanner on reliability of structural brain measurements. Mean percentage differences were also calculated in supplementary analyses. Using the FreeSurfer v7.1.0 longitudinal pipeline, we observed high reliability for subcortical and cortical volumes, and cortical surface areas at repetition, reposition, three weeks and one year (mean ICCs>0.97). Cortical thickness reliability was lower (mean ICCs>0.82). Head tilt had the greatest adverse impact on ICC estimates, for example reducing mean right cortical thickness to ICC=0.74. In contrast, changes in ADNI sequence or MRI scanner had a minimal effect. We observed an increase in reliability for updated FreeSurfer versions, with the longitudinal pipeline consistently having a higher reliability than the cross-sectional pipeline. Longitudinal studies should monitor or control head tilt to maximise reliability. We provided the ICC estimates and mean percentage differences for all FreeSurfer brain regions, which may inform power analyses for clinical studies and have implications for the design of future longitudinal studies. [ABSTRACT FROM AUTHOR]

Abstract: Background: Dexterity is a fundamental skill in our everyday life. Particularly, the fine-tuning of reaching for objects is of high relevance and crucially coordinated by the cerebellum. Although neuronal cerebellar structures mediate dexterity, classical whole brain voxel-based morphometry (VBM) has not identified structural correlates of dexterity in the cerebellum. Methods: Clusters of gray matter (GM) volume associated with the Purdue Pegboard Dexterity Test, a test of fine motor skills and complex upper limb movements, were identified in a cerebellum-optimized VBM analysis using the Spatially Unbiased Infratentorial (SUIT) toolbox in 65 healthy, right-handed 14-year-olds. For comparison, classical whole brain VBM was performed. Results: The cerebellum-optimized VBM indicated a significant positive correlation between manual dexterity and GM volume in the right cerebellum Lobule VI, corrected for multiple comparisons and non-stationary smoothness. The classical whole brain VBM revealed positive associations (uncorrected) between dexterity performance and GM volume in the left SMA (BA 6), right fusiform gyrus (BA 20) and left cuneus (BA 18), but not cerebellar structures. Conclusions: The results indicate that cerebellar GM volumes in the right Lobule VI predict manual dexterity in healthy untrained humans when cerebellum-optimized VBM is employed. Although conventional VBM identified brain motor network areas it failed to detect cerebellar structures. Thus, previous studies might have underestimated the importance of cerebellum in manual dexterity. [Copyright &y& Elsevier]

Abstract: The connectivity information contained in diffusion tensor imaging (DTI) has previously been used to parcellate cortical and subcortical regions based on their connectivity profiles. The aim of the current study is to investigate the utility of a novel approach to connectivity based parcellation of the thalamus using probabilistic tractography and independent component analysis (ICA). We use ICA to identify spatially coherent tractograms as well as their underlying seed regions, in a single step. We compare this to seed-based tractography results and to an established and reliable approach to parcellating the thalamus based on the dominant cortical connection from each thalamic voxel (Behrens et al., 2003a,b). The ICA approach identifies thalamo-cortical pathways that correspond to known anatomical connections, as well as parcellating the underlying thalamus in a spatially similar way to the connectivity based parcellation. We believe that the use of such a multivariate method to interpret the complex datasets created by probabilistic tractography may be better suited than other approaches to parcellating brain regions. [ABSTRACT FROM AUTHOR]

Abstract: Reliable identification of thalamic nuclei is required to improve targeting of electrodes used in Deep Brain Stimulation (DBS), and for exploring the role of thalamus in health and disease. A previously described method using probabilistic tractography to segment the thalamus based on connections to cortical target regions was implemented. Both within- and between-subject reproducibility were quantitatively assessed by the overlap of the resulting segmentations; the effect of two different numbers of target regions (6 and 31) on reproducibility of the segmentation results was also investigated. Very high reproducibility was observed when a single dataset was processed multiple times using different starting conditions. Thalamic segmentation was also very reproducible when multiple datasets from the same subject were processed using six cortical target regions. Within-subject reproducibility was reduced when the number of target regions was increased, particularly in medial and posterior regions of the thalamus. A large degree of overlap in segmentation results from different subjects was obtained, particularly in thalamic regions classified as connecting to frontal, parietal, temporal and pre-central cortical target regions. [Copyright &y& Elsevier]

Abstract: Background: Loss of brain volume in first-episode psychosis can be detected using conventional magnetic resonance imaging (MRI), but subtle changes – not leading to reduction in volume – that may contribute to clinical and cognitive abnormalities, may go undetected. Magnetization transfer imaging (MTI), a technique more sensitive to subtle neuropathological changes than conventional MRI, could yield important information on the extent and nature of structural abnormalities. Methods: Forty-eight patients (33 males) from a population-based sample with first-episode psychosis (41 with schizophrenia and 7 with schizoaffective psychosis) and 47 healthy volunteers (27 males) were studied. Differences in magnetization transfer ratio (MTR) and white and grey matter volumes between groups were investigated. Results: In patients, MTR was reduced in right entorhinal cortex, fusiform, dentate and superior frontal gyri and in left superior frontal and inferior/rostral cingulate gyri. Grey matter volume was reduced in right insula, frontal operculum and middle and superior temporal gyri and in left middle temporal gyrus. Grey matter volume increases were seen in patients in the superior frontal gyrus. White matter volume loss was found adjacent to grey matter loss. In patients MTR was lower in all areas of volumetric differences between groups suggesting that both changes may be related. Similar findings were observed when patients with schizoaffective psychosis were removed from the analysis. The correlations between clinical and MRI parameters did not survive correction for multiple comparisons. Conclusions: MTI frontal and temporal abnormalities suggesting neuroaxonal and myelin changes were more extensive in our patients than those detected with conventional MRI. Our findings also suggest that there is regional variation in the severity of structural brain abnormalities. [Copyright &y& Elsevier]

Abstract: A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the symptoms and cognitive abnormalities of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail, and we present here a study of patients with first-episode psychosis using this technique. We studied the uncinate fasciculus (UF), the largest white matter tract that connects the frontal and temporal lobes, two brain regions significantly implicated in schizophrenia. Nineteen patients with first-episode schizophrenia and 23 controls were studied using a probabilistic tractography algorithm (PICo). Fractional anisotropy (FA) and probability of connection were obtained for every voxel in the tract, and the group means and distributions of these variables were compared. The spread of the FA distribution in the upper tail, as measured by the squared coefficient of variance (SCV), was reduced in the left UF in the patient group, indicating that the number of voxels with high FA values was reduced in the core of the tract and suggesting the presence of changes in fibre alignment and tract coherence in the patient group. The SCV of FA was lower in females across both groups and there was no correlation between the SCV of FA and clinical ratings. [Copyright &y& Elsevier]

Abstract: Functional magnetic resonance imaging (fMRI) in patients with temporal lobe epilepsy (TLE) has demonstrated reorganisation of language functions with greater involvement of the non-dominant hemisphere. The structural brain connections supporting this atypical language dominance have not previously been identified. We performed fMRI of language functions and imaging of white matter connections using MR tractography in 14 patients with unilateral TLE and hippocampal sclerosis and 10 controls. Verb generation and reading comprehension paradigms were used to define functional regions which were used to generate starting regions for tractography. Controls and right TLE patients had a left-lateralised pattern of both language-related activations and the associated structural connections. Left TLE patients showed more symmetrical language activations, along with reduced left hemisphere and increased right hemisphere structural connections. Subjects with more lateralised functional activation had also more highly lateralised connecting pathways. We provide evidence for structural reorganisation of white matter tracts that reflects the altered functional language lateralisation in left TLE patients. The combination of fMRI and tractography offers a promising tool for studying the reorganisation of language functions in many neurological conditions and may prove useful in predicting language deficits following temporal lobe surgery. [Copyright &y& Elsevier]

Abstract: Magnetic resonance imaging (MRI) is being used to probe the central nervous system (CNS) of patients with multiple sclerosis (MS), a chronic demyelinating disease. Conventional T 2-weighted MRI (cMRI) largely fails to predict the degree of patients'' disability. This shortcoming may be due to poor specificity of cMRI for clinically relevant pathology. Diffusion tensor imaging (DTI) has shown promise to be more specific for MS pathology. In this study we investigated the association between histological indices of myelin content, axonal count and gliosis, and two measures of DTI (mean diffusivity [MD] and fractional anisotropy [FA]), in unfixed post mortem MS brain using a 1.5-T MR system. Both MD and FA were significantly lower in post mortem MS brain compared to published data acquired in vivo. However, the differences of MD and FA described in vivo between white matter lesions (WMLs) and normal-appearing white matter (NAWM) were retained in this study of post mortem brain: average MD in WMLs was 0.35×10−3 mm2/s (SD, 0.09) versus 0.22 (0.04) in NAWM; FA was 0.22 (0.06) in WMLs versus 0.38 (0.13) in NAWM. Correlations were detected between myelin content (Trmyelin) and (i) FA (r =−0.79, p <0.001), (ii) MD (r =0.68, p <0.001), and (iii) axonal count (r =−0.81, p <0.001). Multiple regression suggested that these correlations largely explain the apparent association of axonal count with (i) FA (r =0.70, p <0.001) and (ii) MD (r =−0.66, p <0.001). In conclusion, this study suggests that FA and MD are affected by myelin content and – to a lesser degree – axonal count in post mortem MS brain. [Copyright &y& Elsevier]

Abstract: A model of disconnectivity involving abnormalities in the cortex and connecting white matter pathways may explain the clinical manifestations of schizophrenia. Recently, diffusion imaging tractography has made it possible to study white matter pathways in detail and we present here a study of patients with first-episode psychosis using this technique. We selected the corpus callosum for this study because there is evidence that it is abnormal in schizophrenia. In addition, the topographical organization of its fibers makes it possible to relate focal abnormalities to specific cortical regions. Eighteen patients with first-episode psychosis and 21 healthy subjects took part in the study. A probabilistic tractography algorithm (PICo) was used to study fractional anisotropy (FA). Seed regions were placed in the genu and splenium to track fiber tracts traversing these regions, and a multi-threshold approach to study the probability of connection was used. Multiple linear regressions were used to explore group differences. FA, a measure of tract coherence, was reduced in tracts crossing the genu, and to a lesser degree the splenium, in patients compared with controls. FA was also lower in the genu in females across both groups, but there was no gender-by-group interaction. The FA reduction in patients may be due to aberrant myelination or axonal abnormalities, but the similar tract volumes in the two groups suggest that severe axonal loss is unlikely at this stage of the illness. [Copyright &y& Elsevier]

Abstract: Functional lateralization is a feature of human brain function, most apparent in the typical left-hemisphere specialization for language. A number of anatomical and imaging studies have examined whether structural asymmetries underlie this functional lateralization. We combined functional MRI (fMRI) and diffusion-weighted imaging (DWI) with tractography to study 10 healthy right-handed subjects. Three language fMRI paradigms were used to define language-related regions in inferior frontal and superior temporal regions. A probabilistic tractography technique was then employed to delineate the connections of these functionally defined regions. We demonstrated consistent connections between Broca''s and Wernicke''s areas along the superior longitudinal fasciculus bilaterally but more extensive fronto-temporal connectivity on the left than the right. Both tract volumes and mean fractional anisotropy (FA) were significantly greater on the left than the right. We also demonstrated a correlation between measures of structure and function, with subjects with more lateralized fMRI activation having a more highly lateralized mean FA of their connections. These structural asymmetries are in keeping with the lateralization of language function and indicate the major structural connections underlying this function. [Copyright &y& Elsevier]

Abstract: This study investigates some of the issues involved in magnetization transfer ratio (MTR) acquisition, and in particular aims to determine whether high quality in vivo MTR measurements can be made at 3.0 T. The dependency of the MTR white-to-grey matter contrast to noise ratio (CNR) on MT pulse characteristics at 1.5 T and at 3.0 T was investigated using an established two-pool model for MT. The simulations showed that MT pulse parameters optimizing the CNR can be derived for both field strengths. Both the SNR and the CNR of MTR maps at 3.0 T were increased compared to 1.5 T. Images obtained using a safe in vivo MTR acquisition protocol based on results of simulations at 3.0 T are presented. [Copyright &y& Elsevier]

Abstract: The neocortices of 10 patients with partial seizures and acquired lesions, 14 patients with malformations of cortical development (MCD) and 33 patients with partial seizures and normal conventional MRI were quantitatively evaluated using whole brain double inversion recovery imaging (DIR) and Statistical Parametric Mapping (SPM). Compared to a group of 30 control subjects, DIR and objective voxel-by-voxel statistical comparison identified regions of significantly abnormal DIR signal intensity (DSI) in 9 out of 10 patients with acquired nonprogressive cerebral lesions and partial seizures. In all 9 patients, the areas of abnormal DSI concurred with abnormalities identified on visual inspection of conventional MRI. In all 14 patients with MCD, SPM detected regions of significantly abnormal DSI; all of which corresponded to abnormalities identified on visual inspection of conventional MRI. In addition, in both groups, there were areas that were normal on conventional imaging, which demonstrated abnormal DSI. Voxel-by-voxel statistical analysis identified significantly abnormal DSI in 15 of the 33 patients with cryptogenic focal epilepsy. In 10 of these, the areas of abnormal DSI concurred with epileptic EEG abnormality and clinical seizure semiology. Group analysis of MRI-negative patients with electroclinical seizure onset localising to the left temporal and left and right frontal regions revealed significantly abnormal DSI within the white matter of each respective lobe. DIR analysed using SPM was sensitive in patients with MCDs and acquired cerebral damage. Significant abnormalities in DSI in individual and grouped MRI-negative patients suggest that occult epileptogenic cerebral lesions are associated with subtle structural abnormalities. DIR is, therefore, a useful quantitative MRI technique for characterising epileptic foci and may contribute to presurgical evaluation. [Copyright &y& Elsevier]

Abstract: Diffusion tensor magnetic resonance imaging (DT-MRI) provides in vivo information about the pathology of multiple sclerosis lesions. Increases in mean diffusivity (MD) and reductions in fractional anisotropy (FA) have been found and may represent axonal disruption. The optic nerve is an ideal structure for study by DT-MRI but previous clinical studies did not obtain the full diffusion tensor necessary to calculate MD and FA. In this study, a technique that was specifically developed to achieve full diffusion tensor measurements from the optic nerve (zonal oblique multislice (ZOOM) echoplanar imaging) was applied to 25 patients with a single unilateral episode of optic neuritis at least one year previously, and 15 controls. The intraorbital nerves were segmented on non-diffusion-weighted images and the regions of interest transferred to MD, FA, and eigenvalue maps to obtain quantitative data. Quantitative visual testing and electrophysiology were also performed. In affected nerves, mean MD and mean orthogonal eigenvalue λ ⊥ were elevated, and mean FA reduced compared with clinically unaffected contralateral nerves (P < 0.001) and control nerves (P < 0.001). The mean principal eigenvalue λ \\ was significantly increased in affected nerves compared to contralateral unaffected nerves (P = 0.04) but not compared to control nerves (P = 0.13). There was no association of clinical measures of visual function in affected eyes with the DT-MRI parameters but there was a significant correlation of the whole field visual evoked potential (VEP) amplitude with MD (r = −0.57, P = 0.006) and λ ⊥ (r = −0.56, P = 0.007). These findings suggest that optic nerve DT-MRI measures provide an indication of the structural integrity of axons. [Copyright &y& Elsevier]

Abstract: Quantitative magnetisation transfer (MT) analysis is based on a two-pool model of magnetisation transfer and allows important physical properties of the two proton pools to be assessed. A good signal-to-noise ratio (SNR) for the measured signal is essential in order to estimate reliably the parameters from a small number of samples, thus prompting the use of a sequence with high SNR, such as a three-dimensional spoiled gradient acquisition. Here, we show how full brain coverage can be accomplished efficiently, using a three-dimensional acquisition, in a clinically acceptable time, and without the use of large numbers of slice-selective radio-frequency pulses which could otherwise confound analysis. This acquisition was first compared in post mortem human brain tissue to established two-dimensional acquisition protocols with differing SNR levels and then used to collect data from six healthy subjects. Image data were fitted using the two pool model and showed negligible residual deviations. Quantitative results were assessed in several brain locations. Results were consistent with previous single-slice data, and parametric maps were of good quality. Further investigations are needed to interpret the regional variation of quantitative MT quantities. [Copyright &y& Elsevier]

MR tractography techniques provide a method for noninvasively studying white matter pathways in vivo. In this study we have used diffusion tensor imaging (DTI) and the fast marching tractography (FMT) algorithm to plot the structural connectivity of the human parahippocampal gyrus (PHG) in 10 healthy subjects, using seed points selected in the anterior parahippocampal gyrus. Our results demonstrate connectivity between the parahippocampal gyrus and the anterior temporal lobe, orbitofrontal areas, posterior temporal lobe and extrastriate occipital lobe via the lingual and fusiform gyri. We also demonstrate for the first time noninvasively direct connectivity between the parahippocampal gyrus and the hippocampus itself. These results agree with previous histological tract-tracing studies in animals. The connections demonstrated between neocortical areas and the hippocampus via the parahippocampal gyrus may provide the structural basis for theoretical models of memory and higher visual processing. [Copyright &y& Elsevier]

In this study, we combined advanced MR techniques to explore primary motor cortex (M1) connectivity in the human brain. We matched functional and anatomical information using motor functional MRI (fMRI) and white matter tractography inferred from diffusion tensor imaging (DTI). We performed coregistered DTI and motor task fMRI in 8 right-handed healthy subjects and in 1 right-handed patient presenting with a left precentral tumour. We used the fast-marching tractography (FMT) algorithm to define 3D connectivity maps within the whole brain, from seed points selected in the white matter adjacent to the location of the maximum of fMRI activation. Connectivity maps were then anatomically normalised and analysed using statistical parametric mapping software (SPM99) allowing group comparisons (left versus right hemisphere in control subjects and patient versus control subjects). The results demonstrated, in all control subjects, strong connections from M1 to the pyramidal tracts, premotor areas, parietal cortices, thalamus, and cerebellum. M1 connectivity was asymmetric, being more extensive in the dominant hemisphere. The patient had differences in M1 connectivity from the control group. Thus, fMRI-correlated DTI-FMT is a promising tool to study the structural basis of functional networks in the human brain in vivo. [Copyright &y& Elsevier]

This study describes a new technique for Diffusion Tensor Imaging (DTI) that acquires axial (transverse) images of the cervical spinal cord. The DTI images depict axonal fiber orientation, enable quantification of diffusion characteristics along the spinal cord, and have the potential to demonstrate the connectivity of cord white matter tracts. Because of the high sensitivity to motion of diffusion-weighted magnetic resonance imaging and the small size of the spinal cord, a fast imaging method with high in-plane resolution was developed. Images were acquired with a single-shot EPI technique, named ZOOM-EPI (zonally magnified oblique multislice echo planar imaging), which selects localized areas and reduces artefacts caused by susceptibility changes between soft tissue and the adjacent vertebrae. Cardiac gating was used to reduce pulsatile flow artefacts from the surrounding cerebrospinal fluid. Voxel resolution was 1.25 × 1.25 mm2 in-plane with 5-mm slice thickness. Both the mean diffusivity (MD) and the fractional anisotropy (FA) indices of the cervical spinal cord were measured. The FA index demonstrated high anisotropy of the spinal cord with an average value of 0.61 ± 0.05 (highest value of 0.66 ± 0.03 at C3), comparable to white matter tracts in the brain. The diffusivity components parallel and orthogonal to the longitudinal axes of the cord were λ&par; = (1648 ± 123) × 10−6 mm2s−1 and λ⊥ = (570 ± 47) × 10−6 mm2 s−1, respectively. The high axial resolution allowed preliminary evaluation of fiber connectivity using the fast-marching tractography algorithm, which generated traces of fiber paths consistent with the well-known cord anatomy. [Copyright &y& Elsevier]

Replicating results (i.e. obtaining consistent results using a new independent dataset) is an essential part of good science. As replicability has consequences for theories derived from empirical studies, it is of utmost importance to better understand the underlying mechanisms influencing it. A popular tool for non-invasive neuroimaging studies is functional magnetic resonance imaging (fMRI). While the effect of underpowered studies is well documented, the empirical assessment of the interplay between sample size and replicability of results for task-based fMRI studies remains limited. In this work, we extend existing work on this assessment in two ways. Firstly, we use a large database of 1400 subjects performing four types of tasks from the IMAGEN project to subsample a series of independent samples of increasing size. Secondly, replicability is evaluated using a multi-dimensional framework consisting of 3 different measures: (un)conditional test-retest reliability, coherence and stability. We demonstrate not only a positive effect of sample size, but also a trade-off between spatial resolution and replicability. When replicability is assessed voxelwise or when observing small areas of activation, a larger sample size than typically used in fMRI is required to replicate results. On the other hand, when focussing on clusters of voxels, we observe a higher replicability. In addition, we observe variability in the size of clusters of activation between experimental paradigms or contrasts of parameter estimates within these. [ABSTRACT FROM AUTHOR]