Microstructural mapping of dentate gyrus pathology in Alzheimer's disease: A 16.4 Tesla MRI study.

The dentate gyrus (DG) is an integral portion of the hippocampal formation, and it is composed of three layers. Quantitative magnetic resonance (MR) imaging has the capability to map brain tissue microstructural properties which can be exploited to investigate neurodegeneration in Alzheimer's disease (AD). However, assessing subtle pathological changes within layers requires high resolution imaging and histological validation. In this study, we utilized a 16.4 Tesla scanner to acquire ex vivo multi-parameter quantitative MRI measures in human specimens across the layers of the DG. Using quantitative diffusion tensor imaging (DTI) and multi-parameter MR measurements acquired from AD (N = 4) and cognitively normal control (N = 6) tissues, we performed correlation analyses with histological measurements. Here, we found that quantitative MRI measures were significantly correlated with neurofilament and phosphorylated Tau density, suggesting sensitivity to layer-specific changes in the DG of AD tissues.

Selective morphological and volumetric alterations in the hippocampus of children exposed in utero to gestational diabetes mellitus.

Prior epidemiological studies have found that in utero exposure to gestational diabetes mellitus (GDM) is associated with increased risk for neurodevelopmental disorders. However, brain alterations associated with GDM are not known. The hippocampus is pivotal for cognition and emotional regulation. Therefore, we assessed relationships between in utero exposure to GDM and hippocampal morphology and subfield structure during childhood. One hundred seventeen children aged 7-11 years (57% girls, 57% exposed to GDM), born at Kaiser Permanente Southern California, participated in the BrainChild Study. Maternal GDM status was determined from electronic medical records. Children underwent brain magnetic resonance imaging. Freesurfer 6.0 was used to measure hippocampal and individual hippocampal subfield gray matter volume (mm3 ). Morphological analyses on the hippocampal surface were carried out using shape analysis. GDM-exposed children exhibited reduced radial thickness in a small, spatially-restricted portion of the left inferior body of the hippocampus that corresponds to the CA1 subfield. There was a significant interaction between GDM-exposure and sex on the right hippocampal CA1 subfield. GDM-exposed boys had reduced right CA1 volume compared to unexposed boys, but this association was no longer significant after controlling for age. No significant group differences were observed in girls. Our results suggest that GDM-exposure impacts shape of the left hippocampal CA1 subfield in both boys and girls and may reduce volume of right hippocampal CA1 only in boys. These in-depth findings illuminate the unique properties of the hippocampus impacted by prenatal GDM-exposure and could have important implications for hippocampal-related functions.

The effect of body mass index on hippocampal morphology and memory performance in late childhood and adolescence.

Childhood obesity is associated with negative physiological and cognitive health outcomes. The hippocampus is a diverse subcortical structure involved in learned feeding behaviors and energy regulation, and research has shown that the hippocampus is vulnerable to the effects of excess adiposity. Previous studies have demonstrated reduced hippocampal volume in overweight and obese children; however, it is unclear if certain subregions are selectively affected. The purpose of this study was to determine how excess body weight influences regional hippocampal surface morphology and memory performance in a large cross-sectional cohort of 588 children and adolescents between 8.33 and 19.92 years of age using body mass index expressed as a percentage of the 95th percentile cutoff (%BMIp95). We demonstrate %BMIp95 is associated with reduced radial thickness in the superior anterior region of the left hippocampus, and this relationship is predominantly driven by children younger than 14 years. We also found %BMIp95 was associated with worse performance on a spatial episodic memory task and this relationship was partially mediated by the radial thickness of the significant shape cluster. These results demonstrate the differential influence of excess body weight on regional hippocampal structure and hippocampal-dependent behavior in children and adolescents.

Dietary Fructose Intake and Hippocampal Structure and Connectivity during Childhood.

In rodent literature, there is evidence that excessive fructose consumption during development has a detrimental impact on hippocampal structure and function. In this study of 103 children ages 7-11 years old, we investigated whether dietary fructose intake was related to alterations in hippocampal volume and connectivity in humans. To examine if these associations were specific to fructose or were related to dietary sugars intake in general, we explored relationships between dietary intake of added sugars and the monosaccharide, glucose, on the same brain measures. We found that increased dietary intake of fructose, measured as a percentage of total calories, was associated with both an increase in the volume of the CA2/3 subfield of the right hippocampus and increased axial, radial, and mean diffusivity in the prefrontal connections of the right cingulum. These findings are consistent with the idea that increased fructose consumption during childhood may be associated with an inflammatory process, and/or decreases or delays in myelination and/or pruning. Increased habitual consumption of glucose or added sugar in general were associated with an increased volume of right CA2/3, but not with any changes in the connectivity of the hippocampus. These findings support animal data suggesting that higher dietary intake of added sugars, particularly fructose, are associated with alterations in hippocampal structure and connectivity during childhood.

Magnitude and timing of major white matter tract maturation from infancy through adolescence with NODDI.

White matter maturation is a nonlinear and heterogeneous phenomenon characterized by axonal packing, increased axon caliber, and a prolonged period of myelination. While current in vivo diffusion MRI (dMRI) methods, like diffusion tensor imaging (DTI), have successfully characterized the gross structure of major white matter tracts, these measures lack the specificity required to unravel the distinct processes that contribute to microstructural development. Neurite orientation dispersion and density imaging (NODDI) is a dMRI approach that probes tissue compartments and provides biologically meaningful measures that quantify neurite density index (NDI) and orientation dispersion index (ODI). The purpose of this study was to characterize the magnitude and timing of major white matter tract maturation with NODDI from infancy through adolescence in a cross-sectional cohort of 104 subjects (0.6-18.8 years). To probe the regional nature of white matter development, we use an along-tract approach that partitions tracts to enable more fine-grained analysis. Major white matter tracts showed exponential age-related changes in NDI with distinct maturational patterns. Overall, analyses revealed callosal fibers developed before association fibers. Our along-tract analyses elucidate spatially varying patterns of maturation with NDI that are distinct from those obtained with DTI. ODI was not significantly associated with age in the majority of tracts. Our results support the conclusion that white matter tract maturation is heterochronous process and, furthermore, we demonstrate regional variability in the developmental timing within major white matter tracts. Together, these results help to disentangle the distinct processes that contribute to and more specifically define the time course of white matter maturation.

Hippocampal Shape Maturation in Childhood and Adolescence.

The hippocampus is a subcortical structure critical for learning and memory, and a thorough understanding of its neurodevelopment is important for studying these processes in health and disease. However, few studies have quantified the typical developmental trajectory of the structure in childhood and adolescence. This study examined the cross-sectional age-related changes and sex differences in hippocampal shape in a multisite, multistudy cohort of 1676 typically developing children (age 1-22 years) using a novel intrinsic brain mapping method based on Laplace-Beltrami embedding of surfaces. Significant age-related expansion was observed bilaterally and nonlinear growth was observed primarily in the right head and tail of the hippocampus. Sex differences were also observed bilaterally along the lateral and medial aspects of the surface, with females exhibiting relatively larger surface expansion than males. Additionally, the superior posterior lateral surface of the left hippocampus exhibited an age-sex interaction with females expanding faster than males. Shape analysis provides enhanced sensitivity to regional changes in hippocampal morphology over traditional volumetric approaches and allows for the localization of developmental effects. Our results further support evidence that hippocampal structures follow distinct maturational trajectories that may coincide with the development of learning and memory skills during critical periods of development.

Neuroanatomical morphometric characterization of sex differences in youth using statistical learning.

Exploring neuroanatomical sex differences using a multivariate statistical learning approach can yield insights that cannot be derived with univariate analysis. While gross differences in total brain volume are well-established, uncovering the more subtle, regional sex-related differences in neuroanatomy requires a multivariate approach that can accurately model spatial complexity as well as the interactions between neuroanatomical features. Here, we developed a multivariate statistical learning model using a support vector machine (SVM) classifier to predict sex from MRI-derived regional neuroanatomical features from a single-site study of 967 healthy youth from the Philadelphia Neurodevelopmental Cohort (PNC). Then, we validated the multivariate model on an independent dataset of 682 healthy youth from the multi-site Pediatric Imaging, Neurocognition and Genetics (PING) cohort study. The trained model exhibited an 83% cross-validated prediction accuracy, and correctly predicted the sex of 77% of the subjects from the independent multi-site dataset. Results showed that cortical thickness of the middle occipital lobes and the angular gyri are major predictors of sex. Results also demonstrated the inferential benefits of going beyond classical regression approaches to capture the interactions among brain features in order to better characterize sex differences in male and female youths. We also identified specific cortical morphological measures and parcellation techniques, such as cortical thickness as derived from the Destrieux atlas, that are better able to discriminate between males and females in comparison to other brain atlases (Desikan-Killiany, Brodmann and subcortical atlases).

Parametric Probability Distribution Functions for Axon Diameters of Corpus Callosum.

Axon diameter is an important neuroanatomical characteristic of the nervous system that alters in the course of neurological disorders such as multiple sclerosis. Axon diameters vary, even within a fiber bundle, and are not normally distributed. An accurate distribution function is therefore beneficial, either to describe axon diameters that are obtained from a direct measurement technique (e.g., microscopy), or to infer them indirectly (e.g., using diffusion-weighted MRI). The gamma distribution is a common choice for this purpose (particularly for the inferential approach) because it resembles the distribution profile of measured axon diameters which has been consistently shown to be non-negative and right-skewed. In this study we compared a wide range of parametric probability distribution functions against empirical data obtained from electron microscopy images. We observed that the gamma distribution fails to accurately describe the main characteristics of the axon diameter distribution, such as location and scale of the mode and the profile of distribution tails. We also found that the generalized extreme value distribution consistently fitted the measured distribution better than other distribution functions. This suggests that there may be distinct subpopulations of axons in the corpus callosum, each with their own distribution profiles. In addition, we observed that several other distributions outperformed the gamma distribution, yet had the same number of unknown parameters; these were the inverse Gaussian, log normal, log logistic and Birnbaum-Saunders distributions.

Brain tissue compartment density estimated using diffusion-weighted MRI yields tissue parameters consistent with histology.

We examined whether quantitative density measures of cerebral tissue consistent with histology can be obtained from diffusion magnetic resonance imaging (MRI). By incorporating prior knowledge of myelin and cell membrane densities, absolute tissue density values were estimated from relative intracellular and intraneurite density values obtained from diffusion MRI. The NODDI (neurite orientation distribution and density imaging) technique, which can be applied clinically, was used. Myelin density estimates were compared with the results of electron and light microscopy in ex vivo mouse brain and with published density estimates in a healthy human brain. In ex vivo mouse brain, estimated myelin densities in different subregions of the mouse corpus callosum were almost identical to values obtained from electron microscopy (diffusion MRI: 42 ± 6%, 36 ± 4%, and 43 ± 5%; electron microscopy: 41 ± 10%, 36 ± 8%, and 44 ± 12% in genu, body and splenium, respectively). In the human brain, good agreement was observed between estimated fiber density measurements and previously reported values based on electron microscopy. Estimated density values were unaffected by crossing fibers.

Neuroanatomical precursors of dyslexia identified from pre-reading through to age 11.

Developmental dyslexia is a common reading disorder that negatively impacts an individual's ability to achieve literacy. Although the brain network involved in reading and its dysfunction in dyslexia has been well studied, it is unknown whether dyslexia is caused by structural abnormalities in the reading network itself or in the lower-level networks that provide input to the reading network. In this study, we acquired structural magnetic resonance imaging scans longitudinally from 27 Norwegian children from before formal literacy training began until after dyslexia was diagnosed. Thus, we were able to determine that the primary neuroanatomical abnormalities that precede dyslexia are not in the reading network itself, but rather in lower-level areas responsible for auditory and visual processing and core executive functions. Abnormalities in the reading network itself were only observed at age 11, after children had learned how to read. The findings suggest that abnormalities in the reading network are the consequence of having different reading experiences, rather than dyslexia per se, whereas the neuroanatomical precursors are predominantly in primary sensory cortices.

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.

Mapping the human connectome.

Knowledge of the properties of white matter fiber tracts isa crucial and necessary step toward a precise understanding of the functional architecture of the living human brain. Previously, this knowledge was severely limited, as it was difficult to visualize these structures or measure their functions in vivo. The HCP has recently generated considerable interest because of its potential to explore connectivity and its relationship with genetics and behavior. For neuroscientists and the lay public alike, the ability to assess, measure, and explore this wealth of layered information concerning how the brain is wired is a much sought after prize.The navigation of the human connectome and the discovery of how it is affected through genetics, and in a range of neurological and psychiatric diseases, have far reaching implications. From a range of ongoing connectomics related activities, the systematic characterization of brain connectedness and the resulting functional aspects of such connectivity will not only realize the work of Ramón y Cajal and others, but will also greatly expand our understanding of the brain, the mind, and what it is to be truly human. The similarities and differences that mark normal diversity will help us to understand variation among people and set the stage to chart genetic influences on typical brain development and decline during aging. What is more, an understanding of how brains might become disordered will shed light on autism, schizophrenia, Alzheimer's, and other diseases that exact a tremendous and terrible social and economic toll.

Mapping corticocortical structural integrity in schizophrenia and effects of genetic liability.

BACKGROUND: Structural and diffusion tensor imaging studies implicate gray and white matter (WM) abnormalities and disruptions of neural circuitry in schizophrenia. However, the structural integrity of the superficial WM, comprising short-range association (U-fibers) and intracortical axons, has not been investigated in schizophrenia. METHODS: High-resolution structural and diffusion tensor images and sophisticated cortical pattern matching methods were used to measure and compare global and local variations in superficial WM fractional anisotropy between schizophrenia patients and their relatives and community comparison subjects and their relatives (n = 150). RESULTS: Compared with control subjects, patients showed reduced superficial WM fractional anisotropy distributed across each hemisphere, particularly in left temporal and bilateral occipital regions (all p < .05, corrected). Furthermore, by modeling biological risk for schizophrenia in patients, patient relatives, and control subjects, fractional anisotropy was shown to vary in accordance with relatedness to a patient in both hemispheres and in the temporal and occipital lobes (p < .05, corrected). However, effects did not survive correction procedures for two-group comparisons between patient relatives and control subjects. CONCLUSIONS: Results extend previous findings restricted to deep WM pathways to demonstrate that disturbances in corticocortical connectivity are associated with schizophrenia and might indicate a genetic predisposition for the disorder. Because the structural integrity of WM plays a crucial role in the functionality of networks linking gray matter regions, disturbances in the coherence and organization of fibers at the juncture of the neuropil might relate to features of schizophrenia at least partially attributable to disease-related genetic factors.

Mean diffusivity and fractional anisotropy as indicators of disease and genetic liability to schizophrenia.

The goals of this study were to first determine whether the fractional anisotropy (FA) and mean diffusivity (MD) of major white matter pathways associate with schizophrenia, and secondly to characterize the extent to which differences in these metrics might reflect a genetic predisposition to schizophrenia. Differences in FA and MD were identified using a comprehensive atlas-based tract mapping approach using diffusion tensor imaging and high-resolution structural data from 35 patients, 28 unaffected first-degree relatives of patients, 29 community controls, and 14 first-degree relatives of controls. Schizophrenia patients had significantly higher MD in the following tracts compared to controls: the right anterior thalamic radiations, the forceps minor, the bilateral inferior fronto-occipital fasciculus (IFO), the temporal component of the left superior longitudinal fasciculus (tSLF), and the bilateral uncinate. FA showed schizophrenia effects and a linear relationship to genetic liability (represented by schizophrenia patients, first-degree relatives, and controls) for the bilateral IFO, the left inferior longitudinal fasciculus (ILF), and the left tSLF. Diffusion tensor imaging studies have previously identified white matter abnormalities in all three of these tracts in schizophrenia; however, this study is the first to identify a significant genetic liability. Thus, FA of these three tracts may serve as biomarkers for studies seeking to identify how genes influence brain structure predisposing to schizophrenia. However, differences in FA and MD in frontal and temporal white matter pathways may be additionally driven by state variables that involve processes associated with the disease.

Topographical relationships between arcuate fasciculus connectivity and cortical thickness.

The arcuate fasciculus (AF) connects cortical regions important in language processing, but how fiber coherence and organization relates to gray matter macrostructure remains uncharacterized. We used high-resolution structural and 30-direction diffusion imaging data from 36 healthy adults (24 male/12 female; mean age, 30.5 ± 9.8 years) to establish the relationships between AF microstructure and regional variations in cortical gray matter within language networks. Cortical pattern-matching algorithms were used to measure gray matter thickness at high-spatial density, and a validated diffusion tractography method was used to reconstruct the AF in the left and right hemisphere of each subject. Relationships between imaging measures and neuropsychological scores of verbal fluency were additionally assessed. Results revealed positive and highly topographical associations between arcuate fractional anisotropy (FA) and cortical thickness within anterior and posterior language regions and surrounding cortices, more prominently in the left hemisphere. These regional cortical thickness/FA relationships were primarily attributable to variations in radial diffusivity. Associations between cortical thickness and verbal fluency were observed in perisylvian language-related regions. Language scores were associated with left-hemisphere AF axial diffusivity, but not with AF FA or radial diffusivity. These findings thus suggest that particular components of white matter microstructure and regional increases in cortical thickness benefit aspects of language processing. Furthermore, the topographical relationships between independent measures of white matter and gray matter integrity suggest that rich developmental or environmental interactions influence brain structure and function where the presence and strength of such associations may elucidate pathophysiological processes influencing language systems.

Conflict-related activity in the caudal anterior cingulate cortex in the absence of awareness.

The caudal anterior cingulate cortex (cACC) is thought to be involved in performance monitoring, as conflict and error-related activity frequently co-localize in this area. Recent results suggest that these effects may be differentially modulated by awareness. To clarify the role of awareness in performance monitoring by the cACC, we used rapid event-related fMRI to examine the cACC activity while subjects performed a dual task: a delayed recognition task and a serial response task (SRT) with an implicit probabilistic learning rule (i.e. the stimulus location followed a probabilistic sequence of which the subjects were unaware). Task performance confirmed that the location sequence was learned implicitly. Even though we found no evidence of awareness for the presence of the sequence, imaging data revealed increased cACC activity during correct trials which violated the sequence (high-conflict), relative to trials when stimuli followed the sequence (low conflict). Errors made with awareness also activated the same brain region. These results suggest that the performance monitoring function of the cACC extends beyond detection of errors made with or without awareness, and involves detection of multiple responses even when they are outside of awareness.

Fiber tractography reveals disruption of temporal lobe white matter tracts in schizophrenia.

Diffusion tensor imaging (DTI) studies have demonstrated abnormal anisotropic diffusion in schizophrenia. However, examining data with low spatial resolution and/or a low number of gradient directions and limitations associated with analysis approaches sensitive to registration confounds may have contributed to mixed findings concerning the regional specificity and direction of results. This study examined three major white matter tracts connecting lateral and medial temporal lobe regions with neocortical association regions widely implicated in systems-level functional and structural disturbances in schizophrenia. Using DTIstudio, a previously validated regions of interest tractography method was applied to 30 direction diffusion weighted imaging data collected from demographically similar schizophrenia (n=23) and healthy control subjects (n=22). The diffusion tensor was computed at each voxel after intra-subject registration of diffusion-weighted images. Three-dimensional tract reconstruction was performed using the Fiber Assignment by Continuous Tracking (FACT) algorithm. Tractography results showed reduced fractional anisotropy (FA) of the arcuate fasciculi (AF) and inferior longitudinal fasciculi (ILF) in patients compared to controls. FA changes within the right ILF were negatively correlated with measures of thinking disorder. Reduced volume of the left AF was also observed in patients. These results, which avoid registration issues associated with voxel-based analyses of DTI data, support that fiber pathways connecting lateral and medial temporal lobe regions with neocortical regions are compromised in schizophrenia. Disruptions of connectivity within these pathways may potentially contribute to the disturbances of memory, language, and social cognitive processing that characterize the disorder.

Distinguishing expected negative outcomes from preparatory control in the human orbitofrontal cortex.

The human orbitofrontal cortex (OFC) plays a critical role in adapting behavior according to the context provided by expected outcomes of actions. However, several aspects of this function are still poorly understood. In particular, it is unclear to what degree any subdivisions of the OFC are specifically engaged when negatively valenced outcomes are expected, and to what extent such areas might be involved in preparatory active control of behavior. We examined these issues in two complementary functional magnetic resonance imaging (fMRI) studies in which we simultaneously and independently manipulated monetary incentives for correct performance, and demands for active preparation of cognitive control. In both experiments, preparation for performance was associated with lateral PFC activity in response to high incentives, regardless of their valence, as well as in response to increased task demands. In contrast, areas of the OFC centered around the lateral orbital sulcus responded maximally to negatively perceived prospects, even when such prospects were associated with decreases in preparatory cognitive control. These results provide direct support for theoretical models which posit that the OFC contributes to behavioral regulation by representing the value of anticipated outcomes, but does not implement active control aimed at avoiding or pursuing outcomes. Furthermore, they provide additional converging evidence that the lateral OFC is involved in representing specifically the affective impact of anticipated negative outcomes.

Prefrontal and striatal activation in elderly subjects during concurrent implicit and explicit sequence learning.

Decreased function in the prefrontal cortex (PFC) is regarded as a primary mechanism of cognitive aging. However, despite a strong association between the prefrontal cortex and the neostriatum, the role of the neostriatum in cognitive aging is less certain. In the current study, event-related functional MRI was used to distinguish the cognitive contributions of neostriatal and prefrontal function in elderly versus young subjects. Twenty healthy subjects, 9 elderly (mean age 67.6 years), and 11 young (mean age 22 years) performed a concurrent implicit and explicit sequence learning task while undergoing functional MR imaging. Both groups showed learning in both the implicit and explicit task conditions. Relative to the young subjects, the elderly subjects showed decreased activation in the left PFC during both implicit and explicit learning, decreased activation in the right putamen during implicit learning, and increased activation in the right PFC during explicit learning. Our results support the theory that changes in a network of brain regions, including the dorsolateral prefrontal cortex and the striatum, are related to cognitive aging. Moreover, these changes are observed during an implicit task, and thus do not seem to be mediated by awareness.