Diffusion properties of cortical and pericortical tissue: regional variations, reliability and methodological issues

The cognitive relevance of non-lesional damage to cortical networks in people with multiple sclerosis

BACKGROUND

Cognitive impairment, a common and debilitating symptom in people with multiple sclerosis (MS), is especially related to cortical damage. However, the impact of regional cortical damage remains poorly understood. Our aim was to evaluate structural (network) integrity in lesional and non-lesional cortex in people with MS, and its relationship with cognitive dysfunction.

METHODS

In this cross-sectional study, 176 people with MS and 48 healthy controls underwent MRI, including double inversion recovery and diffusion-weighted scans, and neuropsychological assessment. Cortical integrity was assessed based on fractional anisotropy (FA) and mean diffusivity (MD) within 212 regions split into lesional or non-lesional cortex, and grouped into seven cortical networks. Integrity was compared between people with MS and controls, and across cognitive groups: cognitively-impaired (CI; ≥ two domains at Z ≤ - 2 below controls), mildly CI (≥ two at - 2 < Z ≤ - 1.5), or cognitively-preserved (CP).

RESULTS

Cortical lesions were observed in 87.5% of people with MS, mainly in ventral attention network, followed by limbic and default mode networks. Compared to controls, in non-lesional cortex, MD was increased in people with MS, but mean FA did not differ. Within the same individual, MD and FA were increased in lesional compared to non-lesional cortex. CI-MS exhibited higher MD than CP-MS in non-lesional cortex of default mode, frontoparietal and sensorimotor networks, of which the default mode network could best explain cognitive performance.

CONCLUSION

Diffusion differences in lesional cortex were more severe than in non-lesional cortex. However, while most people with MS had cortical lesions, diffusion differences in CI-MS were more prominent in non-lesional cortex than lesional cortex, especially within default mode, frontoparietal and sensorimotor networks.

High-resolution cortical MAP-MRI reveals areal borders and laminar substructures observed with histological staining

The variations in cellular composition and tissue architecture measured with histology provide the biological basis for partitioning the brain into distinct cytoarchitectonic areas and for characterizing neuropathological tissue alterations. Clearly, there is an urgent need to develop whole-brain neuroradiological methods that can assess cortical cyto- and myeloarchitectonic features non-invasively. Mean apparent propagator (MAP) MRI is a clinically feasible diffusion MRI method that quantifies efficiently and comprehensively the net microscopic displacements of water molecules diffusing in tissues. We investigate the sensitivity of high-resolution MAP-MRI to detecting areal and laminar variations in cortical cytoarchitecture and compare our results with observations from corresponding histological sections in the entire brain of a rhesus macaque monkey. High-resolution images of MAP-derived parameters, in particular the propagator anisotropy (PA), non-gaussianity (NG), and the return-to-axis probability (RTAP) reveal cortical area-specific lamination patterns in good agreement with the corresponding histological stained sections. In a few regions, the MAP parameters provide superior contrast to the five histological stains used in this study, delineating more clearly boundaries and transition regions between cortical areas and laminar substructures. Throughout the cortex, various MAP parameters can be used to delineate transition regions between specific cortical areas observed with histology and to refine areal boundaries estimated using atlas registration-based cortical parcellation. Using surface-based analysis of MAP parameters we quantify the cortical depth dependence of diffusion propagators in multiple regions-of-interest in a consistent and rigorous manner that is largely independent of the cortical folding geometry. The ability to assess cortical cytoarchitectonic features efficiently and non-invasively, its clinical feasibility, and translatability make high-resolution MAP-MRI a promising 3D imaging tool for studying whole-brain cortical organization, characterizing abnormal cortical development, improving early diagnosis of neurodegenerative diseases, identifying targets for biopsies, and complementing neuropathological investigations.

Do aggregate, multimodal structural neuroimaging measures replicate regional developmental differences observed in highly cited cellular histological studies?

Influential investigations of postmortem human brain tissue showed regional differences in tissue properties at early phases of development, such as between prefrontal and primary sensory cortical regions. Large-scale neuroimaging studies enable characterization of age-related trajectories with much denser sampling of cortical regions, assessment ages, and demographic variables than postmortem tissue analyses, but no single imaging measure perfectly captures what is measured with histology. Using publicly available data from the Pediatric Imaging, Neurocognition, and Genetics (PING) study, including 951 participants with ages ranging from 3 to 21 years, we characterized cortical regional variability in developmental trajectories of multimodal brain imaging measures. Multivariate analyses integrated morphometric and microstructural cortical surface measures. To replicate foundational histological work showing delayed synapse elimination in middle frontal gyrus relative to primary sensory areas, we tested whether developmental trajectories differ between prefrontal and visual or auditory cortex. We extended this to a whole-cortex analysis of interregional differences, producing cortical parcellations with maximally different developmental trajectories. Consistent with the general conclusions of postmortem analyses, our imaging results suggest that prefrontal regions show a protracted period of greater developmental change; however, they also illustrate the challenges of drawing conclusions about the relative maturational phases of different brain regions.

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Multimodal, multivariate, nonlinear modeling, integrating morphometric and microstructural measures.

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Tested regional developmental differences previously found in highly influential cellular histological studies.

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Produced cortical parcellations with maximally different, multimodal, developmental trajectories.

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Findings converge with evidence from histological studies showing delayed prefrontal cortical development.

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Interregional differences vary by measure and illustrate complexities of defining which regions mature first.

Loss and dispersion of superficial white matter in Alzheimer's disease: a diffusion MRI study

Pathological cerebral white matter changes in Alzheimer's disease have been shown using diffusion tensor imaging. Superficial white matter changes are relatively understudied despite their importance in cortico-cortical connections. Measuring superficial white matter degeneration using diffusion tensor imaging is challenging due to its complex organizational structure and proximity to the cortex. To overcome this, we investigated diffusion MRI changes in young-onset Alzheimer's disease using standard diffusion tensor imaging and Neurite Orientation Dispersion and Density Imaging to distinguish between disease-related changes that are degenerative (e.g. loss of myelinated fibres) and organizational (e.g. increased fibre dispersion). Twenty-nine young-onset Alzheimer's disease patients and 22 healthy controls had both single-shell and multi-shell diffusion MRI. We calculated fractional anisotropy, mean diffusivity, neurite density index, orientation dispersion index and tissue fraction (1-free water fraction). Diffusion metrics were sampled in 15 a priori regions of interest at four points along the cortical profile: cortical grey matter, grey/white boundary, superficial white matter (1 mm below grey/white boundary) and superficial/deeper white matter (2 mm below grey/white boundary). To estimate cross-sectional group differences, we used average marginal effects from linear mixed effect models of participants' diffusion metrics along the cortical profile. The superficial white matter of young-onset Alzheimer's disease individuals had lower neurite density index compared to controls in five regions (superior and inferior parietal, precuneus, entorhinal and parahippocampus) (all P < 0.05), and higher orientation dispersion index in three regions (fusiform, entorhinal and parahippocampus) (all P < 0.05). Young-onset Alzheimer's disease individuals had lower fractional anisotropy in the entorhinal and parahippocampus regions (both P < 0.05) and higher fractional anisotropy within the postcentral region (P < 0.05). Mean diffusivity was higher in the young-onset Alzheimer's disease group in the parahippocampal region (P < 0.05) and lower in the postcentral, precentral and superior temporal regions (all P < 0.05). In the overlying grey matter, disease-related changes were largely consistent with superficial white matter findings when using neurite density index and fractional anisotropy, but appeared at odds with orientation dispersion and mean diffusivity. Tissue fraction was significantly lower across all grey matter regions in young-onset Alzheimer's disease individuals (all P < 0.001) but group differences reduced in magnitude and coverage when moving towards the superficial white matter. These results show that microstructural changes occur within superficial white matter and along the cortical profile in individuals with young-onset Alzheimer's disease. Lower neurite density and higher orientation dispersion suggests underlying fibres undergo neurodegeneration and organizational changes, two effects previously indiscernible using standard diffusion tensor metrics in superficial white matter.

Automated cerebral cortex segmentation based solely on diffusion tensor imaging for investigating cortical anisotropy

To extract Diffusion Tensor Imaging (DTI) parameters from the human cortex, the inner and outer boundaries of the cortex are usually defined on 3D-T1-weighted images and then applied to the co-registered DTI. However, this analysis requires the acquisition of an additional high-resolution structural image that may not be practical in various imaging studies. Here an automatic cortical boundary segmentation method was developed to work directly only on the native DTI images by using fractional anisotropy (FA) maps and mean diffusion weighted images (DWI), the latter with acceptable gray-white matter image contrast. This new method was compared to the conventional cortical segmentations generated from high-resolution T1 structural images in 5 participants. In addition, the proposed method was applied to 15 healthy young adults (10 cross-sectional, 5 test-retest) to measure FA, MD, and radiality of the primary eigenvector across the cortex on whole-brain 1.5 mm isotropic images acquired in 3.5 min at 3T. The proposed method generated reasonable segmentations of the cortical boundaries for all individuals and large proportions of the proposed method segmentations (more than 85%) were within ±1 mm from those generated with the conventional approach on higher resolution T1 structural images. Both FA (~0.15) and MD (~0.77 × 10^-3 mm²/s) extracted halfway between the cortical boundaries were relatively stable across the cortex, although focal regions such as the posterior bank of the central sulcus, anterior insula, and medial temporal lobe showed higher FA. The primary eigenvectors were primarily oriented radially to the middle cortical surface, but there were tangential orientations in the sulcal fundi as well as in the posterior bank of the central sulcus. The proposed method demonstrates the feasibility and accuracy of cortical analysis in native DTI space while avoiding the acquisition of other imaging contrasts like 3D T1-weighted scans.

Image processing and analysis methods for the Adolescent Brain Cognitive Development Study

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study.

Relating diffusion tensor imaging measurements to microstructural quantities in the cerebral cortex in multiple sclerosis

To investigate whether the observed anisotropic diffusion in cerebral cortex may reflect its columnar cytoarchitecture and myeloarchitecture, as a potential biomarker for disease-related changes, we compared postmortem diffusion magnetic resonance imaging scans of nine multiple sclerosis brains with histology measures from the same regions. Histology measurements assessed the cortical minicolumnar structure based on cell bodies and associated axon bundles in dorsolateral prefrontal cortex (Area 9), Heschl's gyrus (Area 41), and primary visual cortex (V1). Diffusivity measures included mean diffusivity, fractional anisotropy of the cortex, and three specific measures that may relate to the radial minicolumn structure: the angle of the principal diffusion direction in the cortex, the component that was perpendicular to the radial direction, and the component that was parallel to the radial direction. The cellular minicolumn microcircuit features were correlated with diffusion angle in Areas 9 and 41, and the axon bundle features were correlated with angle in Area 9 and to the parallel component in V1 cortex. This may reflect the effect of minicolumn microcircuit organisation on diffusion in the cortex, due to the number of coherently arranged membranes and myelinated structures. Several of the cortical diffusion measures showed group differences between MS brains and control brains. Differences between brain regions were also found in histology and diffusivity measurements consistent with established regional variation in cytoarchitecture and myeloarchitecture. Therefore, these novel measures may provide a surrogate of cortical organisation as a potential biomarker, which is particularly relevant for detecting regional changes in neurological disorders.

Cortical fibers orientation mapping using in-vivo whole brain 7 T diffusion MRI

Diffusion MRI of the cortical gray matter is challenging because the micro-environment probed by water molecules is much more complex than within the white matter. High spatial and angular resolutions are therefore necessary to uncover anisotropic diffusion patterns and laminar structures, which provide complementary (e.g. to anatomical and functional MRI) microstructural information about the cortex architectonic. Several ex-vivo and in-vivo MRI studies have recently addressed this question, however predominantly with an emphasis on specific cortical areas. There is currently no whole brain in-vivo data leveraging multi-shell diffusion MRI acquisition at high spatial resolution, and depth dependent analysis, to characterize the complex organization of cortical fibers. Here, we present unique in-vivo human 7T diffusion MRI data, and a dedicated cortical depth dependent analysis pipeline. We leverage the high spatial (1.05 mm isotropic) and angular (198 diffusion gradient directions) resolution of this whole brain dataset to improve cortical fiber orientations mapping, and study neurites (axons and/or dendrites) trajectories across cortical depths. Tangential fibers in superficial cortical depths and crossing fiber configurations in deep cortical depths are identified. Fibers gradually inserting into the gyral walls are visualized, which contributes to mitigating the gyral bias effect. Quantitative radiality maps and histograms in individual subjects and cortex-based aligned datasets further support our results.

Volumetric, relaxometric and diffusometric correlates of psychotic experiences in a non-clinical sample of young adults

BACKGROUND

Grey matter (GM) abnormalities are robust features of schizophrenia and of people at ultra high-risk for psychosis. However the extent to which neuroanatomical alterations are evident in non-clinical subjects with isolated psychotic experiences is less clear.

METHODS

Individuals (mean age 20 years) with (n = 123) or without (n = 125) psychotic experiences (PEs) were identified from a population-based cohort. All underwent T1-weighted structural, diffusion and quantitative T1 relaxometry MRI, to characterise GM macrostructure, microstructure and myelination respectively. Differences in quantitative GM structure were assessed using voxel-based morphometry (VBM). Binary and ordinal models of PEs were tested. Correlations between socioeconomic and other risk factors for psychosis with cortical GM measures were also computed.

RESULTS

GM volume in the left supra-marginal gyrus was reduced in individuals with PEs relative to those with no PEs. The greater the severity of PEs, the greater the reduction in T1 relaxation rate (R1) across left temporoparietal and right pre-frontal cortices. In these regions, R1 was positively correlated with maternal education and inversely correlated with general psychopathology.

CONCLUSIONS

PEs in non-clinical subjects were associated with regional reductions in grey-matter volume reduction and T1 relaxation rate. The alterations in T1 relaxation rate were also linked to the level of general psychopathology. Follow up of these subjects should clarify whether these alterations predict the later development of an ultra high-risk state or a psychotic disorder.

The superficial white matter in temporal lobe epilepsy: a key link between structural and functional network disruptions

Drug-resistant temporal lobe epilepsy is increasingly recognized as a system-level disorder affecting the structure and function of large-scale grey matter networks. While diffusion magnetic resonance imaging studies have demonstrated deep fibre tract alterations, the superficial white matter immediately below the cortex has so far been neglected despite its proximity to neocortical regions and key role in maintaining cortico-cortical connectivity. Using multi-modal 3 T magnetic resonance imaging, we mapped the topography of superficial white matter diffusion alterations in 61 consecutive temporal lobe epilepsy patients relative to 38 healthy controls and studied the relationship to large-scale structural as well as functional networks. Our approach continuously sampled mean diffusivity and fractional anisotropy along surfaces running 2 mm below the cortex. Multivariate statistics mapped superficial white matter diffusion anomalies in patients relative to controls, while correlation and mediation analyses evaluated their relationship to structural (cortical thickness, mesiotemporal volumetry) and functional parameters (resting state functional magnetic resonance imaging amplitude) and clinical variables. Patients presented with overlapping anomalies in mean diffusivity and anisotropy, particularly in ipsilateral temporo-limbic regions. Diffusion anomalies did not relate to cortical thinning; conversely, they mediated large-scale functional amplitude decreases in patients relative to controls in default mode hub regions (i.e. anterior and posterior midline regions, lateral temporo-parietal cortices), and were themselves mediated by hippocampal atrophy. With respect to clinical variables, we observed more marked diffusion anomalies in patients with a history of febrile convulsions and those with longer disease duration. Similarly, more marked diffusion alterations were associated with seizure-free outcome. Bootstrap analyses indicated high reproducibility of our findings, suggesting generalizability. The temporo-limbic distribution of superficial white matter anomalies, together with the mediation-level findings, suggests that this so far neglected region serves a key link between the hippocampal atrophy and large-scale default mode network alterations in temporal lobe epilepsy.

Substrates of metacognition on perception and metacognition on higher-order cognition relate to different subsystems of the mentalizing network

Humans have the ability to reflect upon their perception, thoughts, and actions, known as metacognition (MC). The brain basis of MC is incompletely understood, and it is debated whether MC on different processes is subserved by common or divergent networks. We combined behavioral phenotyping with multi-modal neuroimaging to investigate whether structural substrates of individual differences in MC on higher-order cognition (MC-C) are dissociable from those underlying MC on perceptual accuracy (MC-P). Motivated by conceptual work suggesting a link between MC and cognitive perspective taking, we furthermore tested for overlaps between MC substrates and mentalizing networks. In a large sample of healthy adults, individual differences in MC-C and MC-P did not correlate. MRI-based cortical thickness mapping revealed a structural basis of this independence, by showing that individual differences in MC-P related to right prefrontal cortical thickness, while MC-C scores correlated with measures in lateral prefrontal, temporo-parietal, and posterior midline regions. Surface-based superficial white matter diffusivity analysis revealed substrates resembling those seen for cortical thickness, confirming the divergence of both MC faculties using an independent imaging marker. Despite their specificity, substrates of MC-C and MC-P fell clearly within networks known to participate in mentalizing, confirmed by task-based fMRI in the same subjects, previous meta-analytical findings, and ad-hoc Neurosynth-based meta-analyses. Our integrative multi-method approach indicates domain-specific substrates of MC; despite their divergence, these nevertheless likely rely on component processes mediated by circuits also involved in mentalizing. Hum Brain Mapp 37:3388-3399, 2016. © 2016 Wiley Periodicals, Inc.

Functional neuronal anisotropy assessed with neuronavigated transcranial magnetic stimulation

BACKGROUND

Transcranial magnetic stimulation (TMS) can evaluate cortical excitability and integrity of motor pathways via TMS-induced responses. The responses are affected by the orientation of the stimulated neurons with respect to the direction of the TMS-induced electric field. Therefore, besides being a functional imaging tool, TMS may potentially assess the local structural properties. Yet, TMS has not been used for this purpose.

NEW METHOD

A novel principle to evaluate the relation between function and structure of the motor cortex is presented. This functional anisotropy is evaluated by an anisotropy index (AI), based on motor evoked potential amplitudes induced with different TMS coil orientations, i.e. different electric field directions at a cortical target. To compare the AI with anatomical anisotropy in an explorative manner, diffusion tensor imaging-derived fractional anisotropy (FA) was estimated at different depths near the stimulation site.

RESULTS

AI correlated inversely with cortical excitability through the TMS-induced electric field at motor threshold level. Further, there was a trend of negative correlation between AI and FA.

COMPARISON WITH EXISTING METHODS

None of the existing methods alone can detect the relationship between direct motor cortex activation and local neuronal structure.

CONCLUSIONS

The AI appears to provide information on the functional neuronal anisotropy of the motor cortex by coupling neurophysiology and neuroanatomy within the stimulated cortical region. The AI could prove useful in the evaluation of neurological disorders and traumas involving concurrent structural and functional changes in the motor cortex. Further studies on patients are needed to confirm the usability of AI.

Hemispheric asymmetries in cortical and subcortical anatomy

Previous research studies have reported many hemispherical asymmetries in cortical and subcortical anatomy, but only a subset of findings is consistent across studies. Here, we used improved Freesurfer-based automated methods to analyse the properties of the cortex and seven subcortical structures in 138 young adult subjects. Male and female subjects showed similar hemispheric asymmetries in gyral and sulcal structures, with many areas associated with language processing enlarged in the left hemisphere (LH) and a number of areas associated with visuospatial processing enlarged in the right hemisphere (RH). In addition, we found greater (non-directional) cortical asymmetries in subjects with larger brains. Asymmetries in subcortical structures included larger LH volumes of thalamus, putamen and globus pallidus and larger RH volumes of the cerebellum and the amygdala. We also found significant correlations between the subcortical structural volumes, particularly of the thalamus and cerebellum, with cortical area. These results help to resolve some of the inconsistencies in previous studies of hemispheric asymmetries in brain anatomy.

What does diffusion tensor imaging (DTI) tell us about cognitive networks in temporal lobe epilepsy?

Diffusion tensor imaging (DTI) has provided considerable insight into our understanding of epilepsy as a network disorder, revealing subtle alterations in white matter microstructure both proximal and distal to the epileptic focus. These white matter changes have been shown to assist with lateralizing the seizure focus, as well as delineating the location/anatomy of key white matter tracts (i.e., optic radiations) for surgical planning. However, only recently have studies emerged describing the utility of DTI for probing cognitive networks in patients with epilepsy and for examining the structural plasticity within these networks both before and after epilepsy surgery. Here, we review the current literature describing the use of DTI for understanding language and memory networks in patients with temporal lobe epilepsy (TLE), as well as the extant literature on networks associated with executive functioning and global intelligence. Studies of memory and language reveal a complex network of frontotemporal fibers that contribute to naming and fluency performance in TLE, and demonstrate that these networks appear to undergo adaptive changes in response to surgical intervention. Although studies of executive functioning and global intelligence have been less conclusive, there is accumulating evidence that aberrant communication between frontoparietal and medial temporal networks may underlie working memory impairment in TLE. More recently, multimodal imaging studies have provided evidence that disruptions within these white matter networks co-localize with functional changes observed on functional MRI. However, structure-function associations are not entirely coherent and may breakdown in patients with TLE, especially those with a left-sided seizure focus. Although the reasons for discordant findings are unclear, small sample sizes, heterogeneity within patient populations and limitations of the current tensor model may account for contradictory and null findings. Improvements in imaging hardware and higher field strengths have now paved the way for the implementation of advanced diffusion techniques, and these advanced models show great promise for improving our understanding of how network dysfunction contributes to cognitive morbidity in TLE.

Functional and anatomical properties of human visual cortical fields

Human visual cortical fields (VCFs) vary in size and anatomical location across individual subjects. Here, we used functional magnetic resonance imaging (fMRI) with retinotopic stimulation to identify VCFs on the cortical surface. We found that aligning and averaging VCF activations across the two hemispheres provided clear delineation of multiple retinotopic fields in visual cortex. The results show that VCFs have consistent locations and extents in different subjects that provide stable and accurate landmarks for functional and anatomical mapping. Interhemispheric comparisons revealed minor differences in polar angle and eccentricity tuning in comparable VCFs in the left and right hemisphere, and somewhat greater intersubject variability in the right than left hemisphere. We then used the functional boundaries to characterize the anatomical properties of VCFs, including fractional anisotropy (FA), magnetization transfer ratio (MTR) and the ratio of T1W and T2W images and found significant anatomical differences between VCFs and between hemispheres.

Neuroimaging, behavioral, and psychological sequelae of repetitive combined blast/impact mild traumatic brain injury in Iraq and Afghanistan war veterans

Abstract Whether persisting cognitive complaints and postconcussive symptoms (PCS) reported by Iraq and Afghanistan war veterans with blast- and/or combined blast/impact-related mild traumatic brain injuries (mTBIs) are associated with enduring structural and/or functional brain abnormalities versus comorbid depression or posttraumatic stress disorder (PTSD) remains unclear. We sought to characterize relationships among these variables in a convenience sample of Iraq and Afghanistan-deployed veterans with (n=34) and without (n=18) a history of one or more combined blast/impact-related mTBIs. Participants underwent magnetic resonance imaging of fractional anisotropy (FA) and macromolecular proton fraction (MPF) to assess brain white matter (WM) integrity; [(18)F]-fluorodeoxyglucose positron emission tomography imaging of cerebral glucose metabolism (CMRglu); structured clinical assessments of blast exposure, psychiatric diagnoses, and PTSD symptoms; neurologic evaluations; and self-report scales of PCS, combat exposure, depression, sleep quality, and alcohol use. Veterans with versus without blast/impact-mTBIs exhibited reduced FA in the corpus callosum; reduced MPF values in subgyral, longitudinal, and cortical/subcortical WM tracts and gray matter (GM)/WM border regions (with a possible threshold effect beginning at 20 blast-mTBIs); reduced CMRglu in parietal, somatosensory, and visual cortices; and higher scores on measures of PCS, PTSD, combat exposure, depression, sleep disturbance, and alcohol use. Neuroimaging metrics did not differ between participants with versus without PTSD. Iraq and Afghanistan veterans with one or more blast-related mTBIs exhibit abnormalities of brain WM structural integrity and macromolecular organization and CMRglu that are not related to comorbid PTSD. These findings are congruent with recent neuropathological evidence of chronic brain injury in this cohort of veterans.

The neural correlates of speech motor sequence learning

Speech is perhaps the most sophisticated example of a species-wide movement capability in the animal kingdom, requiring split-second sequencing of approximately 100 muscles in the respiratory, laryngeal, and oral movement systems. Despite the unique role speech plays in human interaction and the debilitating impact of its disruption, little is known about the neural mechanisms underlying speech motor learning. Here, we studied the behavioral and neural correlates of learning new speech motor sequences. Participants repeatedly produced novel, meaningless syllables comprising illegal consonant clusters (e.g., GVAZF) over 2 days of practice. Following practice, participants produced the sequences with fewer errors and shorter durations, indicative of motor learning. Using fMRI, we compared brain activity during production of the learned illegal sequences and novel illegal sequences. Greater activity was noted during production of novel sequences in brain regions linked to non-speech motor sequence learning, including the BG and pre-SMA. Activity during novel sequence production was also greater in brain regions associated with learning and maintaining speech motor programs, including lateral premotor cortex, frontal operculum, and posterior superior temporal cortex. Measures of learning success correlated positively with activity in left frontal operculum and white matter integrity under left posterior superior temporal sulcus. These findings indicate speech motor sequence learning relies not only on brain areas involved generally in motor sequencing learning but also those associated with feedback-based speech motor learning. Furthermore, learning success is modulated by the integrity of structural connectivity between these motor and sensory brain regions.

Macro- and microstructural changes in patients with spinocerebellar ataxia type 6: assessment of phylogenetic subdivisions of the cerebellum and the brain stem

BACKGROUND AND PURPOSE

Site-specific degeneration patterns of the infratentorial brain in relation to phylogenetic origins may relate to symptoms in patients with spinocerebellar degeneration, but the patterns are still unclear. We investigated macro- and microstructural changes of the infratentorial brain based on phylogenetic origins and their correlation with symptoms in patients with spinocerebellar ataxia type 6.

MATERIALS AND METHODS

MR images of 9 patients with spinocerebellar ataxia type 6 and 9 age- and sex-matched controls were obtained. We divided the infratentorial brain on the basis of phylogenetic origins and performed an atlas-based analysis. Comparisons of the 2 groups and a correlation analysis assessed with the International Cooperative Ataxia Rating Scale excluding age effects were performed.

RESULTS

A significant decrease of fractional volume and an increase of mean diffusivity were seen in all subdivisions of the cerebellum and in all the cerebellar peduncles except mean diffusivity in the inferior cerebellar peduncle in patients compared with controls (P < .0001 to <.05). The bilateral anterior lobes showed the strongest atrophy. Fractional volume decreased mainly in old regions, whereas mean diffusivity increased mainly in new regions of the cerebellum. Reflecting this tendency, the International Cooperative Ataxia Rating Scale total score showed strong correlations in fractional volume in the right flocculonodular lobe and the bilateral deep structures and in mean diffusivity in the bilateral posterior lobes (r = 0.73 to ±0.87).

CONCLUSIONS

We found characteristic macro- and microstructural changes, depending on phylogenetic regions of the infratentorial brain, that strongly correlated with clinical symptoms in patients with spinocerebellar ataxia type 6.

White matter microstructure complements morphometry for predicting verbal memory in epilepsy

Verbal memory is the most commonly impaired cognitive domain in patients with temporal lobe epilepsy (TLE). Although damage to the hippocampus and adjacent temporal lobe structures is known to contribute to memory impairment, little is known of the relative contributions of white versus gray matter structures, or whether microstructural versus morphometric measures of temporal lobe pathology are stronger predictors of impairment. We evaluate whether measures of temporal lobe pathology derived from diffusion tensor imaging (DTI; microstructural) versus structural MRI (sMRI; morphometric) contribute the most to memory performances in TLE, after controlling for hippocampal volume (HCV). DTI and sMRI were performed on 26 patients with TLE and 35 controls. Verbal memory was measured with the Logical Memory (LM) subtest of the Wechsler Memory Scale-III. Hierarchical regression analyses were performed to examine unique contributions of DTI and sMRI measures to verbal memory with HCV entered in block 1. In patients, impaired recall was associated with increased mean diffusivity (MD) of multiple fiber tracts that project through the temporal lobes. In addition, increased MD of the left cortical and bilateral pericortical white matter was associated with impaired recall. After controlling for left HCV, only microstructural measures of white matter pathology contributed to verbal recall. The best predictive model included left HCV and MD of the left inferior longitudinal fasciculus (ILF) and pericortical white matter beneath the left entorhinal cortex. This model explained 60% of the variance in delayed recall and revealed that MD of the left ILF was the strongest predictor. These data reveal that white matter microstructure within the temporal lobe can be used in conjunction with left HCV to enhance the prediction of verbal memory impairment, and speak to the complementary nature of DTI and sMRI for understanding cognitive dysfunction in epilepsy and possibly other memory disorders.

Influence of noise correction on intra- and inter-subject variability of quantitative metrics in diffusion kurtosis imaging

Diffusion kurtosis imaging (DKI) is a promising extension of diffusion tensor imaging, giving new insights into the white matter microstructure and providing new biomarkers. Given the rapidly increasing number of studies, DKI has a potential to establish itself as a valuable tool in brain diagnostics. However, to become a routine procedure, DKI still needs to be improved in terms of robustness, reliability, and reproducibility. As it requires acquisitions at higher diffusion weightings, results are more affected by noise than in diffusion tensor imaging. The lack of standard procedures for post-processing, especially for noise correction, might become a significant obstacle for the use of DKI in clinical routine limiting its application. We considered two noise correction schemes accounting for the noise properties of multichannel phased-array coils, in order to improve the data quality at signal-to-noise ratio (SNR) typical for DKI. The SNR dependence of estimated DKI metrics such as mean kurtosis (MK), mean diffusivity (MD) and fractional anisotropy (FA) is investigated for these noise correction approaches in Monte Carlo simulations and in in vivo human studies. The intra-subject reproducibility is investigated in a single subject study by varying the SNR level and SNR spatial distribution. Then the impact of the noise correction on inter-subject variability is evaluated in a homogeneous sample of 25 healthy volunteers. Results show a strong impact of noise correction on the MK estimate, while the estimation of FA and MD was affected to a lesser extent. Both intra- and inter-subject SNR-related variability of the MK estimate is considerably reduced after correction for the noise bias, providing more accurate and reproducible measures. In this work, we have proposed a straightforward method that improves accuracy of DKI metrics. This should contribute to standardization of DKI applications in clinical studies making valuable inferences in group analysis and longitudinal studies.

Increased cortical curvature reflects white matter atrophy in individual patients with early multiple sclerosis

Objective

White matter atrophy occurs independently of lesions in multiple sclerosis. In contrast to lesion detection, the quantitative assessment of white matter atrophy in individual patients has been regarded as a major challenge. We therefore tested the hypothesis that white matter atrophy (WMA) is present at the very beginning of multiple sclerosis (MS) and in virtually each individual patient. To find a new sensitive and robust marker for WMA we investigated the relationship between cortical surface area, white matter volume (WMV), and whole-brain-surface-averaged rectified cortical extrinsic curvature. Based on geometrical considerations we hypothesized that cortical curvature increases if WMV decreases and the cortical surface area remains constant.

Methods

In total, 95 participants were enrolled: 30 patients with early and advanced relapsing–remitting MS; 30 age-matched control subjects; 30 patients with Alzheimer's disease (AD) and 5 patients with clinically isolated syndrome (CIS).

Results

29/30 MS and 5/5 CIS patients showed lower WMV than expected from their intracranial volume (average reduction 13.0%, P < 10^− 10), while the cortical surface area showed no significant differences compared with controls. The estimated WMV reductions were correlated with an increase in cortical curvature (R = 0.62, P = 0.000001). Discriminant analysis revealed that the curvature increase was highly specific for the MS and CIS groups (96.7% correct assignments between MS and control groups) and was significantly correlated with reduction of white matter fractional anisotropy, as determined by diffusion tensor imaging and the Expanded Disability Status Scale. As expected by the predominant gray and WM degeneration in AD, no systematic curvature increase was observed in AD.

Conclusion

Whole-brain-averaged cortical extrinsic curvature appears to be a specific and quantitative marker for a WMV–cortex disproportionality and allows us to assess “pure” WMA without being confounded by intracranial volume. WMA seems to be a characteristic symptom in early MS and can already occur in patients with CIS and should thus be considered in future MS research and clinical studies.

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We suggest cortical curvature as marker for selective white matter atrophy (WMA).

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This geometric marker is more specific and sensitive than volumetric measures.

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It is not confounded by intra-cranial volume, age, and gender.

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WMA seems to be a characteristic symptom in early multiple sclerosis.

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WMA can be also detected in patients with a clinical isolated symptom.

Superficial white matter: effects of age, sex, and hemisphere

Structural and diffusion imaging studies demonstrate effects of age, sex, and asymmetry in many brain structures. However, few studies have addressed how individual differences might influence the structural integrity of the superficial white matter (SWM), comprised of short-range association (U-fibers), and intracortical axons. This study thus applied a sophisticated computational analysis approach to structural and diffusion imaging data obtained from healthy individuals selected from the International Consortium for Brain Mapping (ICBM) database across a wide adult age range (n=65, age: 18-74 years, all Caucasian). Fractional anisotropy (FA), radial diffusivity (RD), and axial diffusivity (AD) were sampled and compared at thousands of spatially matched SWM locations and within regions-of-interest to examine global and local variations in SWM integrity across age, sex, and hemisphere. Results showed age-related reductions in FA that were more pronounced in the frontal SWM than in the posterior and ventral brain regions, whereas increases in RD and AD were observed across large areas of the SWM. FA was significantly greater in left temporoparietal regions in men and in the posterior callosum in women. Prominent leftward FA and rightward AD and RD asymmetries were observed in the temporal, parietal, and frontal regions. Results extend previous findings restricted to the deep white matter pathways to demonstrate regional changes in the SWM microstructure relating to processes of demyelination and/or to the number, coherence, or integrity of axons with increasing age. SWM fiber organization/coherence appears greater in the left hemisphere regions spanning language and other networks, while more localized sex effects could possibly reflect sex-specific advantages in information strategies.