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Статті в журналах з теми "White matter structure"

Автор: Grafiati

Опубліковано: 11 березня 2023

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1

Tian, Yin, Shanshan Liang, Zhen Yuan, Sifan Chen, Peng Xu, and Dezhong Yao. "White matter structure in loneliness." NeuroReport 25, no. 11 (2014): 843–47. http://dx.doi.org/10.1097/wnr.0000000000000197.

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2

Mizobe, Taro, Keisuke Ikari, Hirofumi Tomiyama, et al. "Abnormal white matter structure in hoarding disorder." Journal of Psychiatric Research 148 (April 2022): 1–8. http://dx.doi.org/10.1016/j.jpsychires.2022.01.031.

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3

Nowicki, Kamil W., and Raymond F. Sekula. "Pericytes Protect White-Matter Structure and Function." Neurosurgery 83, no. 3 (2018): E103—E104. http://dx.doi.org/10.1093/neuros/nyy300.

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4

Yushkevich, Paul A., Hui Zhang, Tony J. Simon, and James C. Gee. "Structure-specific statistical mapping of white matter tracts." NeuroImage 41, no. 2 (2008): 448–61. http://dx.doi.org/10.1016/j.neuroimage.2008.01.013.

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5

Darki, Fahimeh, Satu Massinen, Elina Salmela, et al. "Human ROBO1 regulates white matter structure in corpus callosum." Brain Structure and Function 222, no. 2 (2016): 707–16. http://dx.doi.org/10.1007/s00429-016-1240-y.

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6

Yund, Brianna, Kyle Rudser, Victor Kovac, et al. "White matter structure and function in attenuated MPS II." Molecular Genetics and Metabolism 111, no. 2 (2014): S116—S117. http://dx.doi.org/10.1016/j.ymgme.2013.12.292.

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7

Guitart-Masip, Marc, Zeb Kurth-Nelson, Jan Axelsson, et al. "Microscopic Structure of Frontal White Matter Predict Delay Discounting." Biological Psychiatry 87, no. 9 (2020): S197. http://dx.doi.org/10.1016/j.biopsych.2020.02.513.

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8

Schlegel, Alexander A., Justin J. Rudelson, and Peter U. Tse. "White Matter Structure Changes as Adults Learn a Second Language." Journal of Cognitive Neuroscience 24, no. 8 (2012): 1664–70. http://dx.doi.org/10.1162/jocn_a_00240.

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Анотація:

Traditional models hold that the plastic reorganization of brain structures occurs mainly during childhood and adolescence, leaving adults with limited means to learn new knowledge and skills. Research within the last decade has begun to overturn this belief, documenting changes in the brain's gray and white matter as healthy adults learn simple motor and cognitive skills [Lövdén, M., Bodammer, N. C., Kühn, S., Kaufmann, J., Schütze, H., Tempelmann, C., et al. Experience-dependent plasticity of white-matter microstructure extends into old age. Neuropsychologia, 48, 3878–3883, 2010; Taubert, M., Draganski, B., Anwander, A., Müller, K., Horstmann, A., Villringer, A., et al. Dynamic properties of human brain structure: Learning-related changes in cortical areas and associated fiber connections. The Journal of Neuroscience, 30, 11670–11677, 2010; Scholz, J., Klein, M. C., Behrens, T. E. J., & Johansen-Berg, H. Training induces changes in white-matter architecture. Nature Neuroscience, 12, 1370–1371, 2009; Draganski, B., Gaser, C., Busch, V., Schuirer, G., Bogdahn, U., & May, A. Changes in grey matter induced by training. Nature, 427, 311–312, 2004]. Although the significance of these changes is not fully understood, they reveal a brain that remains plastic well beyond early developmental periods. Here we investigate the role of adult structural plasticity in the complex, long-term learning process of foreign language acquisition. We collected monthly diffusion tensor imaging scans of 11 English speakers who took a 9-month intensive course in written and spoken Modern Standard Chinese as well as from 16 control participants who did not study a language. We show that white matter reorganizes progressively across multiple sites as adults study a new language. Language learners exhibited progressive changes in white matter tracts associated with traditional left hemisphere language areas and their right hemisphere analogs. Surprisingly, the most significant changes occurred in frontal lobe tracts crossing the genu of the corpus callosum—a region not generally included in current neural models of language processing. These results indicate that plasticity of white matter plays an important role in adult language learning and additionally demonstrate the potential of longitudinal diffusion tensor imaging as a new tool to yield insights into cognitive processes.

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9

Suzuki, Mitsuru, Keiko Obara, Yuka Sasaki, et al. "Comparison of perivascular astrocytic structure between white matter and gray matter of rats." Brain Research 992, no. 2 (2003): 294–97. http://dx.doi.org/10.1016/j.brainres.2003.08.052.

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10

RIDLER, K., E. T. BULLMORE, P. J. DE VRIES, et al. "Widespread anatomical abnormalities of grey and white matter structure in tuberous sclerosis." Psychological Medicine 31, no. 8 (2001): 1437–46. http://dx.doi.org/10.1017/s0033291701004561.

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Background. Neuroimaging studies of tuberous sclerosis complex (TSC) have previously focused mainly on tubers or subependymal nodules. Subtle pathological changes in the structure of the brain have not been studied in detail. Computationally intensive techniques for reliable morphometry of brain structure are useful in disorders like TSC, where there is little prior data to guide selection of regions of interest.Methods. Dual-echo, fast spin-echo MRI data were acquired from 10 TSC patients of normal intelligence and eight age-matched controls. Between-group differences in grey matter, white matter and cerebrospinal fluid were estimated at each intracerebral voxel after registration of these images in standard space; a permutation test based on spatial statistics was used for inference. CSF-attenuated FLAIR images were acquired for neuroradiological rating of tuber number.Results. Significant deficits were found in patients, relative to comparison subjects, of grey matter volume bilaterally in the medial temporal lobes, posterior cingulate gyrus, thalamus and basal ganglia, and unilaterally in right fronto-parietal cortex (patients −20%). We also found significant and approximately symmetrical deficits of central white matter involving the longitudinal fasciculi and other major intrahemispheric tracts (patients −21%); and a bilateral cerebellar region of relative white matter excess (patients +28%). Within the patient group, grey matter volume in limbic and subcortical regions of deficit was negatively correlated with tuber count.Conclusions. Neuropathological changes associated with TSC may be more extensive than hitherto suspected, involving radiologically normal parenchymal structures as well as tubers, although these two aspects of the disorder may be correlated.

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11

Tang, Cheuk Y., Victoria X. Wang, Min Yin Lun, et al. "Transient changes in white matter microstructure during general anesthesia." PLOS ONE 16, no. 3 (2021): e0247678. http://dx.doi.org/10.1371/journal.pone.0247678.

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Cognitive dysfunction after surgery under general anesthesia is a well-recognized clinical phenomenon in the elderly. Physiological effects of various anesthetic agents have been studied at length. Very little is known about potential effects of anesthesia on brain structure. In this study we used Diffusion Tensor Imaging to compare the white matter microstructure of healthy control subjects under sevoflurane anesthesia with their awake state. Fractional Anisotropy, a white mater integrity index, transiently decreases throughout the brain during sevoflurane anesthesia and then returns back to baseline. Other DTI metrics such as mean diffusivity, axial diffusivity and radial diffusivity were increased under sevoflurane anesthesia. Although DTI metrics are age dependent, the transient changes due to sevoflurane were independent of age and sex. Volumetric analysis shows various white matter volumes decreased whereas some gray matter volumes increased during sevoflurane anesthesia. These results suggest that sevoflurane anesthesia has a significant, but transient, effect on white matter microstructure. In spite of the transient effects of sevoflurane anesthesia there were no measurable effects on brain white matter as determined by the DTI metrics at 2 days and 7 days following anesthesia. The role of white matter in the loss of consciousness under anesthesia will need to be studied and MRI studies with subjects under anesthesia will need to take these results into account.

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12

Taylor, Warren D., Jae Nam Bae, James R. MacFall, et al. "Widespread Effects of Hyperintense Lesions on Cerebral White Matter Structure." American Journal of Roentgenology 188, no. 6 (2007): 1695–704. http://dx.doi.org/10.2214/ajr.06.1163.

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13

Hämäläinen, Sini, Viljami Sairanen, Alina Leminen, and Minna Lehtonen. "Bilingualism modulates the white matter structure of language-related pathways." NeuroImage 152 (May 2017): 249–57. http://dx.doi.org/10.1016/j.neuroimage.2017.02.081.

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14

Koch, Kathrin, Gerd Wagner, Claudia Schachtzabel, et al. "White matter structure and symptom dimensions in obsessive–compulsive disorder." Journal of Psychiatric Research 46, no. 2 (2012): 264–70. http://dx.doi.org/10.1016/j.jpsychires.2011.10.016.

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15

Maruyama, Takashi, Yoshihiro Muragaki, Masayuki Nitta, et al. "Glioma Surgery based on Anatomical Structure of the White Matter." Japanese Journal of Neurosurgery 24, no. 2 (2015): 76–84. http://dx.doi.org/10.7887/jcns.24.76.

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16

Li, Xin, Chao Ma, Xuan Sun, et al. "Disrupted white matter structure underlies cognitive deficit in hypertensive patients." European Radiology 26, no. 9 (2015): 2899–907. http://dx.doi.org/10.1007/s00330-015-4116-2.

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17

Sammler, Daniela, Katrin Cunitz, Sarah M. E. Gierhan, et al. "White matter pathways for prosodic structure building: A case study." Brain and Language 183 (August 2018): 1–10. http://dx.doi.org/10.1016/j.bandl.2018.05.001.

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18

Haltia, Lauri T., Antti Viljanen, Riitta Parkkola, et al. "Brain White Matter Expansion in Human Obesity and the Recovering Effect of Dieting." Journal of Clinical Endocrinology & Metabolism 92, no. 8 (2007): 3278–84. http://dx.doi.org/10.1210/jc.2006-2495.

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Анотація:

Abstract Context and Objective: Obesity is associated with several metabolic abnormalities. Recent studies suggest that obesity also affects brain function and is a risk factor for some degenerative brain diseases. The objective of this study was to examine the effects of weight gain and weight loss on brain gray and white matter structure. We hypothesized that possible differences seen in the brains of obese subjects would disappear or diminish after an intensive dieting period. Methods: In part I of the study, we scanned with magnetic resonance imaging 16 lean (mean body mass index, 22 kg/m2) and 30 obese (mean body mass index, 33 kg/m2) healthy subjects. In part II, 16 obese subjects continued with a very low-calorie diet for 6 wk, after which they were scanned again. Regional brain white and gray matter volumes were calculated using voxel-based morphometry. Results: White matter volumes were greater in obese subjects, compared with lean subjects in several basal brain regions, and obese individuals showed a positive correlation between white matter volume in basal brain structures and waist to hip ratio. The detected white matter expansion was partially reversed by dieting. Regional gray matter volumes did not differ significantly in obese and lean subjects, and dieting did not affect gray matter. Conclusions: The precise mechanism for the discovered white matter changes remains unclear, but the present study demonstrates that obesity and dieting are associated with opposite changes in brain structure. It is not excluded that white matter expansion in obesity has a role in the neuropathogenesis of degenerative brain diseases.

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19

Begré, Stefan, Claus Kiefer, Roland von Känel, Angela Frommer, and Andrea Federspiel. "Rey Visual Design Learning Test performance correlates with white matter structure." Acta Neuropsychiatrica 21, no. 2 (2009): 67–74. http://dx.doi.org/10.1111/j.1601-5215.2009.00361.x.

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Objective:Studies exploring relation of visual memory to white matter are extensively lacking. The Rey Visual Design Learning Test (RVDLT) is an elementary motion, colour and word independent visual memory test. It avoids a significant contribution from as many additional higher order visual brain functions as possible to visual performance, such as three-dimensional, colour, motion or word-dependent brain operations. Based on previous results, we hypothesised that test performance would be related with white matter of dorsal hippocampal commissure, corpus callosum, posterior cingulate, superior longitudinal fascicle and internal capsule.Methods:In 14 healthy subjects, we measured intervoxel coherence (IC) by diffusion tensor imaging as an indication of connectivity and visual memory performance measured by the RVDLT. IC considers the orientation of the adjacent voxels and has a better signal-to-noise ratio than the commonly used fractional anisotropy index.Results:Using voxelwise linear regression analyses of the IC values, we found a significant and direct relationship between 11 clusters and visual memory test performance. The fact that memory performance correlated with white matter structure in left and right dorsal hippocampal commissure, left and right posterior cingulate, right callosal splenium, left and right superior longitudinal fascicle, right medial orbitofrontal region, left anterior cingulate, and left and right anterior limb of internal capsule emphasises our hypothesis.Conclusion:Our observations in healthy subjects suggest that individual differences in brain function related to the performance of a task of higher cognitive demands might partially be associated with structural variation of white matter regions.

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20

Tuch, David S., Jonathan J. Wisco, Mark H. Khachaturian, Leeland B. Ekstrom, Rolf Kötter, and Wim Vanduffel. "Q -ball imaging of macaque white matter architecture." Philosophical Transactions of the Royal Society B: Biological Sciences 360, no. 1457 (2005): 869–79. http://dx.doi.org/10.1098/rstb.2005.1651.

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Diffusion-weighted magnetic resonance imaging holds substantial promise as a technique for non-invasive imaging of white matter (WM) axonal projections. For diffusion imaging to be capable of providing new insight into the connectional neuroanatomy of the human brain, it will be necessary to histologically validate the technique against established tracer methods such as horseradish peroxidase and biocytin histochemistry. The macaque monkey provides an ideal model for histological validation of the diffusion imaging method due to the phylogenetic proximity between humans and macaques, the gyrencephalic structure of the macaque cortex, the large body of knowledge on the neuroanatomic connectivity of the macaque brain and the ability to use comparable magnetic resonance acquisition protocols in both species. Recently, it has been shown that high angular resolution diffusion imaging (HARDI) can resolve multiple axon orientations within an individual imaging voxel in human WM. This capability promises to boost the accuracy of tract reconstructions from diffusion imaging. If the macaque is to serve as a model for histological validation of the diffusion tractography method, it will be necessary to show that HARDI can also resolve intravoxel architecture in macaque WM. The present study therefore sought to test whether the technique can resolve intravoxel structure in macaque WM. Using a HARDI method called q -ball imaging (QBI) it was possible to resolve composite intravoxel architecture in a number of anatomic regions. QBI resolved intravoxel structure in, for example, the dorsolateral convexity, the pontine decussation, the pulvinar and temporal subcortical WM. The paper concludes by reviewing remaining challenges for the diffusion tractography project.

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21

Man, Jodie H. K., Charlotte A. G. H. van Gelder, Marjolein Breur, et al. "Cortical Pathology in Vanishing White Matter." Cells 11, no. 22 (2022): 3581. http://dx.doi.org/10.3390/cells11223581.

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Vanishing white matter (VWM) is classified as a leukodystrophy with astrocytes as primary drivers in its pathogenesis. Magnetic resonance imaging has documented the progressive thinning of cortices in long-surviving patients. Routine histopathological analyses, however, have not yet pointed to cortical involvement in VWM. Here, we provide a comprehensive analysis of the VWM cortex. We employed high-resolution-mass-spectrometry-based proteomics and immunohistochemistry to gain insight into possible molecular disease mechanisms in the cortices of VWM patients. The proteome analysis revealed 268 differentially expressed proteins in the VWM cortices compared to the controls. A majority of these proteins formed a major protein interaction network. A subsequent gene ontology analysis identified enrichment for terms such as cellular metabolism, particularly mitochondrial activity. Importantly, some of the proteins with the most prominent changes in expression were found in astrocytes, indicating cortical astrocytic involvement. Indeed, we confirmed that VWM cortical astrocytes exhibit morphological changes and are less complex in structure than control cells. Our findings also suggest that these astrocytes are immature and not reactive. Taken together, we provide insights into cortical involvement in VWM, which has to be taken into account when developing therapeutic strategies.

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22

Lakovic, Katarina, Jinglu Ai, Josephine D'Abbondanza, et al. "Bilirubin and its Oxidation Products Damage Brain White Matter." Journal of Cerebral Blood Flow & Metabolism 34, no. 11 (2014): 1837–47. http://dx.doi.org/10.1038/jcbfm.2014.154.

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Brain injury after intracerebral hemorrhage (ICH) occurs in cortex and white matter and may be mediated by blood breakdown products, including hemoglobin and heme. Effects of blood breakdown products, bilirubin and bilirubin oxidation products, have not been widely investigated in adult brain. Here, we first determined the effect of bilirubin and its oxidation products on the structure and function of white matter in vitro using brain slices. Subsequently, we determined whether these compounds have an effect on the structure and function of white matter in vivo. In all, 0.5 mmol/L bilirubin treatment significantly damaged both the function and the structure of myelinated axons but not the unmyelinated axons in brain slices. Toxicity of bilirubin in vitro was prevented by dimethyl sulfoxide. Bilirubin oxidation products (BOXes) may be responsible for the toxicity of bilirubin. In in vivo experiments, unmyelinated axons were found more susceptible to damage from bilirubin injection. These results suggest that unmyelinated axons may have a major role in white-matter damage in vivo. Since bilirubin and BOXes appear in a delayed manner after ICH, preventing their toxic effects may be worth investigating therapeutically. Dimethyl sulfoxide or its structurally related derivatives may have a potential therapeutic value at antagonizing axonal damage after hemorrhagic stroke.

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23

Filley, Christopher M., and R. Douglas Fields. "White matter and cognition: making the connection." Journal of Neurophysiology 116, no. 5 (2016): 2093–104. http://dx.doi.org/10.1152/jn.00221.2016.

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Whereas the cerebral cortex has long been regarded by neuroscientists as the major locus of cognitive function, the white matter of the brain is increasingly recognized as equally critical for cognition. White matter comprises half of the brain, has expanded more than gray matter in evolution, and forms an indispensable component of distributed neural networks that subserve neurobehavioral operations. White matter tracts mediate the essential connectivity by which human behavior is organized, working in concert with gray matter to enable the extraordinary repertoire of human cognitive capacities. In this review, we present evidence from behavioral neurology that white matter lesions regularly disturb cognition, consider the role of white matter in the physiology of distributed neural networks, develop the hypothesis that white matter dysfunction is relevant to neurodegenerative disorders, including Alzheimer's disease and the newly described entity chronic traumatic encephalopathy, and discuss emerging concepts regarding the prevention and treatment of cognitive dysfunction associated with white matter disorders. Investigation of the role of white matter in cognition has yielded many valuable insights and promises to expand understanding of normal brain structure and function, improve the treatment of many neurobehavioral disorders, and disclose new opportunities for research on many challenging problems facing medicine and society.

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24

Arslan, Seda, Tuba Şahin, Didenur Şahin, and Timothea Toulopoulou. "T48. DEVIATIONS IN MICRO AND MACRO WHITE MATTER STRUCTURES IN PSYCHOSIS PRONENESS." Schizophrenia Bulletin 46, Supplement_1 (2020): S249—S250. http://dx.doi.org/10.1093/schbul/sbaa029.608.

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Abstract Background Psychotic disorders are characterized by neurobiological deviations, including in the macro and microstructure of white matter. White matter alterations are also seen in psychosis-proneness and in individuals who have a high risk of psychosis. For example, studies have indicated decreases in white matter integrity in the genu/forceps minor of corpus callosum (CC) in the latter populations. Anterior corona radiata (ACR) is one crucial white-matter tract connecting the anterior cingulate cortex to the striatum. Indeed, reductions in the white matter structure of anterior genu of CC significantly predict the transition from ultra-high risk to psychosis. However, there is a gap in the literature related to observing the psychosis-proneness by applying both micro and macrostructural brain analyses, and most of the microstructural white matter studies in psychosis focus on fractional anisotropy (FA) and not include mean diffusivity (MD). Thus, the current study aims to assess whether white matter deviations in CG, ACR, and CC, are associated with psychosis proneness by combining both tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM) analyses in a sample of participants with psychosis proneness (PP) and without psychosis proneness (NPP). Methods The study included 53 participants (29 PP vs. 24 NPP) whose ages were between 17 and 24 years. Participants were split into two groups based on their scores on Structured Interview for Schizotypy assessment, a well-validated instrument of psychosis proneness. White matter integrity was analyzed via diffusion tensor imaging (DTI) and white matter volume (WMV) via VBM. Two sample t-test was used in GLM for both DTI and VBM analyses. FA, MD, and VMV were compared between two groups to observe micro and macro white matter structure alterations in the region of interest. Results DTI analysis revealed decreased FA values in the right ACR and right genu of the CC in the psychosis-proneness group (F(1,52)= 7.37, p= 0.009). Moreover, VBM showed a significant WMV decreases in the right CG, Brodmann areas 8, 9, and 32 in the PP group (F(1,52)= 50.85, uncorrected p&lt;0.01). However, MD did not differ between the two groups (F(1,51)= 3.65, p=0.06) Discussion These findings suggest that PP associated with decreased white matter integrity in ACR, genu of CC, and also reduced white matter volumes in the right CG, Brodmann areas 8, 9, and 32. Significant FA decreases might result from alterations in radial or axial diffusivity since we did not observe significant MD differences between two groups. The current findings suggested that participants with PP had both macro and micro white matter structure disruptions, mostly in frontal parts of the right cerebrum, compared to no PP group.

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25

Mårtensson, Johan, Johan Eriksson, Nils Christian Bodammer, et al. "White matter microstructure predicts foreign language learning in army interpreters." Bilingualism: Language and Cognition 23, no. 4 (2020): 763–71. http://dx.doi.org/10.1017/s1366728920000152.

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AbstractAdult foreign language acquisition is challenging, and the degree of success varies among individuals. Anatomical differences in brain structure prior to training can partly explain why some learn more than others. We followed a sample of conscript interpreters undergoing intense language training to study learning-related changes in white-matter microstructure (FA, MD, RD and AD) and associations between differences in brain structure prior to training with acquired language proficiency. No evidence for changes in white matter microstructure relative to a control group was found. Starting values of RD, AD and MD were positively related to final test scores of language proficiency, corroborating earlier findings in the field and highlighting the need for further study of how initial brain structure influences and interacts with learning outcomes.

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26

Hoppenbrouwers, Sylco S., Arash Nazeri, Danilo R. de Jesus, et al. "White Matter Deficits in Psychopathic Offenders and Correlation with Factor Structure." PLoS ONE 8, no. 8 (2013): e72375. http://dx.doi.org/10.1371/journal.pone.0072375.

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27

Manza, Peter, Kai Yuan, Ehsan Shokri-Kojori, Dardo Tomasi, and Nora D. Volkow. "Chronic cannabis users show deficits in gray and white matter structure." Molecular Psychiatry 25, no. 12 (2020): 3115. http://dx.doi.org/10.1038/s41380-020-00937-7.

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28

Auriel, E., B. L. Edlow, Y. D. Reijmer, et al. "Microinfarct disruption of white matter structure: A longitudinal diffusion tensor analysis." Neurology 83, no. 2 (2014): 182–88. http://dx.doi.org/10.1212/wnl.0000000000000579.

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29

Kindlmann, Gordon, Xavier Tricoche, and Carl-Fredrik Westin. "Delineating white matter structure in diffusion tensor MRI with anisotropy creases." Medical Image Analysis 11, no. 5 (2007): 492–502. http://dx.doi.org/10.1016/j.media.2007.07.005.

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30

Giorgio, Antonio, Luca Santelli, Valentina Tomassini, et al. "Age-related changes in grey and white matter structure throughout adulthood." NeuroImage 51, no. 3 (2010): 943–51. http://dx.doi.org/10.1016/j.neuroimage.2010.03.004.

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31

Koch, Kathrin, Gerd Wagner, Claudia Schachtzabel, et al. "Age-dependent visuomotor performance and white matter structure: a DTI study." Brain Structure and Function 218, no. 5 (2012): 1075–84. http://dx.doi.org/10.1007/s00429-012-0447-9.

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32

Kent, Brian P., Alessandro Rinaldo, Fang-Cheng Yeh, and Timothy Verstynen. "Mapping Topographic Structure in White Matter Pathways with Level Set Trees." PLoS ONE 9, no. 4 (2014): e93344. http://dx.doi.org/10.1371/journal.pone.0093344.

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33

Wong, Nikita A., Sara A. Rafique, Stefania S. Moro, Krista R. Kelly, and Jennifer K. E. Steeves. "Altered white matter structure in auditory tracts following early monocular enucleation." NeuroImage: Clinical 24 (2019): 102006. http://dx.doi.org/10.1016/j.nicl.2019.102006.

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34

Versace, Amelia, Heather Acuff, Michele A. Bertocci, et al. "White Matter Structure in Youth With Behavioral and Emotional Dysregulation Disorders." JAMA Psychiatry 72, no. 4 (2015): 367. http://dx.doi.org/10.1001/jamapsychiatry.2014.2170.

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35

Barnea-Goraly, Naama, Hower Kwon, Vinod Menon, Stephan Eliez, Linda Lotspeich, and Allan L. Reiss. "White matter structure in autism: preliminary evidence from diffusion tensor imaging." Biological Psychiatry 55, no. 3 (2004): 323–26. http://dx.doi.org/10.1016/j.biopsych.2003.10.022.

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36

Rubia, Katya. "White Matter Structure and Delay Tolerance in Attention-Deficit/Hyperactivity Disorder." Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 4, no. 3 (2019): 213–15. http://dx.doi.org/10.1016/j.bpsc.2019.01.006.

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37

Walton, Matthew, Deborah Dewey, and Catherine Lebel. "Brain white matter structure and language ability in preschool-aged children." Brain and Language 176 (January 2018): 19–25. http://dx.doi.org/10.1016/j.bandl.2017.10.008.

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38

Schwindt, Graeme, Naida Graham, Elizabeth Rochon, David Tang-Wai, and Sandra E. Black. "P1-022: Characterizing abnormal white matter structure in primary progressive aphasia." Alzheimer's & Dementia 6 (July 2010): S180. http://dx.doi.org/10.1016/j.jalz.2010.05.569.

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39

Ocklenburg, Sebastian, Patrick Friedrich, Onur Güntürkün, and Erhan Genç. "Intrahemispheric white matter asymmetries: the missing link between brain structure and functional lateralization?" Reviews in the Neurosciences 27, no. 5 (2016): 465–80. http://dx.doi.org/10.1515/revneuro-2015-0052.

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Анотація:

AbstractHemispheric asymmetries are a central principle of nervous system architecture and shape the functional organization of most cognitive systems. Structural gray matter asymmetries and callosal interactions have been identified as contributing neural factors but always fell short to constitute a full explanans. Meanwhile, recent advances in in vivo white matter tractography have unrevealed the asymmetrical organization of many intrahemispheric white matter pathways, which might serve as the missing link to explain the substrate of functional lateralization. By taking into account callosal interactions, gray matter asymmetries and asymmetrical interhemispheric pathways, we opt for a new triadic model that has the potential to explain many observations which cannot be elucidated within the current frameworks of lateralized cognition.

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40

Sil'man, G. I. "Alloyed White Iron with Composite Structure." Metal Science and Heat Treatment 47, no. 7-8 (2005): 343–48. http://dx.doi.org/10.1007/s11041-005-0076-5.

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41

Boshkayev, K. A., J. A. Rueda, B. A. Zhami, Zh A. Kalymova, and G. Sh Balgymbekov. "Equilibrium structure of white dwarfs at finite temperatures." International Journal of Modern Physics: Conference Series 41 (January 2016): 1660129. http://dx.doi.org/10.1142/s2010194516601290.

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Recently, it has been shown by S. M. de Carvalho et al. (2014) that the deviations between the degenerate case and observations were already evident for 0.7-0.8 M[Formula: see text] white dwarfs. Such deviations were related to the neglected effects of finite temperatures on the structure of a white dwarf. Therefore, in this work by employing the Chandrasekhar equation of state taking into account the effects of temperature we show how the total pressure of the white dwarf matter depends on the mass density at different temperatures. Afterwards we construct equilibrium configurations of white dwarfs at finite temperatures. We obtain the mass-radius relations of white dwarfs for different temperatures by solving the Tolman-Oppenheimer-Volkoff equation, and compare them with the estimated masses and radii inferred from the Sloan Digital Sky Survey Data Release 4.

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42

van’t Westeinde, Annelies, Leif Karlsson, Malin Thomsen Sandberg, Anna Nordenström, Nelly Padilla, and Svetlana Lajic. "Altered Gray Matter Structure and White Matter Microstructure in Patients with Congenital Adrenal Hyperplasia: Relevance for Working Memory Performance." Cerebral Cortex 30, no. 5 (2019): 2777–88. http://dx.doi.org/10.1093/cercor/bhz274.

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Abstract Congenital adrenal hyperplasia (CAH) has been associated with brain structure alterations, but systematic studies are lacking. We explore brain morphology in 37 (21 female) CAH patients and 43 (26 female) healthy controls, aged 16–33 years, using structural magnetic resonance imaging to estimate cortical thickness, surface area, volume, subcortical volumes, and white matter (WM) microstructure. We also report data on a small cohort of patients (n = 8) with CAH, who received prenatal dexamethasone (DEX). Patients with CAH had reduced whole brain volume (4.23%) and altered structure of the prefrontal, parietal, and superior occipital cortex. Patients had reduced mean FA, and reduced RD and MD, but not after correcting for brain volume. The observed regions are hubs of the visuospatial working memory and default mode (DMN) networks. Thickness of the left superior parietal and middle frontal gyri was associated with visuospatial working memory performance, and patients with CAH performed worse on this task. Prenatal treatment with DEX affected brain structures in the parietal and occipital cortex, but studies in larger cohorts are needed. In conclusion, our study suggests that CAH is associated with brain structure alterations, especially in the working memory network, which might underlie the cognitive outcome observed in patients.

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43

Siepmann, Timo, Henry Boardman, Amy Bilderbeck, et al. "Long-term cerebral white and gray matter changes after preeclampsia." Neurology 88, no. 13 (2017): 1256–64. http://dx.doi.org/10.1212/wnl.0000000000003765.

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Objective:To determine whether changes in cerebral structure are present after preeclampsia that may explain increased cerebrovascular risk in these women.Methods:We conducted a case control study in women between 5 and 15 years after either a preeclamptic or normotensive pregnancy. Brain MRI was performed. Analysis of white matter structure was undertaken using voxel-based segmentation of fluid-attenuation inversion recovery sequences to assess white matter lesion volume and diffusion tensor imaging to measure microstructural integrity. Voxel-based analysis of gray matter volumes was performed with adjustment for skull size.Results:Thirty-four previously preeclamptic women (aged 42.8 ± 5.1 years) and 49 controls were included. Previously preeclamptic women had reduced cortical gray matter volume (523.2 ± 30.1 vs 544.4 ± 44.7 mL, p < 0.05) and, although both groups displayed white matter lesions, changes were more extensive in previously preeclamptic women. They displayed increased temporal lobe white matter disease (lesion volume: 23.2 ± 24.9 vs 10.9 ± 15.0 μL, p < 0.05) and altered microstructural integrity (radial diffusivity: 538 ± 19 vs 526 ± 18 × 10−6 mm2/s, p < 0.01), which also extended to occipital and parietal lobes. The degree of temporal lobe white matter change in previously preeclamptic women was independent of their current cardiovascular risk profile (p < 0.05) and increased with time from index pregnancy (p < 0.05).Conclusion:A history of preeclampsia is associated with temporal lobe white matter changes and reduced cortical volume in young women, which is out of proportion to their classic cardiovascular risk profile. The severity of changes is proportional to time since pregnancy, which would be consistent with continued accumulation of damage after pregnancy.

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44

Lyall, Donald M., Simon R. Cox, Laura M. Lyall, et al. "Association between APOE e4 and white matter hyperintensity volume, but not total brain volume or white matter integrity." Brain Imaging and Behavior 14, no. 5 (2019): 1468–76. http://dx.doi.org/10.1007/s11682-019-00069-9.

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Abstract Apolipoprotein (APOE) e4 genotype is an accepted risk factor for accelerated cognitive aging and dementia, though its neurostructural substrates are unclear. The deleterious effects of this genotype on brain structure may increase in magnitude into older age. This study aimed to investigate in UK Biobank the association between APOE e4 allele presence vs. absence and brain imaging variables that have been associated with worse cognitive abilities; and whether this association varies by cross-sectional age. We used brain magnetic resonance imaging (MRI) and genetic data from a general-population cohort: the UK Biobank (N = 8395 after exclusions). We adjusted for the covariates of age in years, sex, Townsend social deprivation scores, smoking history and cardiometabolic diseases. There was a statistically significant association between APOE e4 genotype and increased (i.e. worse) white matter (WM) hyperintensity volumes (standardised beta = 0.088, 95% confidence intervals = 0.036 to 0.139, P = 0.001), a marker of poorer cerebrovascular health. There were no associations with left or right hippocampal, total grey matter (GM) or WM volumes, or WM tract integrity indexed by fractional anisotropy (FA) and mean diffusivity (MD). There were no statistically significant interactions with age. Future research in UK Biobank utilising intermediate phenotypes and longitudinal imaging hold significant promise for this area, particularly pertaining to APOE e4’s potential link with cerebrovascular contributions to cognitive aging.

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45

Barnea-Goraly, N., M. Raman, P. Mazaika, et al. "Alterations in White Matter Structure in Young Children With Type 1 Diabetes." Diabetes Care 37, no. 2 (2013): 332–40. http://dx.doi.org/10.2337/dc13-1388.

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46

Gorman, Ben D. A., Fernando Calamante, Oren Civier, et al. "Investigating white matter structure in social anxiety disorder using fixel-based analysis." Journal of Psychiatric Research 143 (November 2021): 30–37. http://dx.doi.org/10.1016/j.jpsychires.2021.08.028.

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47

Guo, Bin, Fugen Zhou, Muwei Li, and John C. Gore. "Latency structure of BOLD signals within white matter in resting-state fMRI." Magnetic Resonance Imaging 89 (June 2022): 58–69. http://dx.doi.org/10.1016/j.mri.2021.12.010.

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48

Medic, Nenad, Peter Kochunov, Hisham Ziauddeen, et al. "BMI-related cortical morphometry changes are associated with altered white matter structure." International Journal of Obesity 43, no. 3 (2018): 523–32. http://dx.doi.org/10.1038/s41366-018-0269-9.

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49

Pliatsikas, Christos, Elisavet Moschopoulou, and James Douglas Saddy. "The effects of bilingualism on the white matter structure of the brain." Proceedings of the National Academy of Sciences 112, no. 5 (2015): 1334–37. http://dx.doi.org/10.1073/pnas.1414183112.

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Recent studies suggest that learning and using a second language (L2) can affect brain structure, including the structure of white matter (WM) tracts. This observation comes from research looking at early and older bilingual individuals who have been using both their first and second languages on an everyday basis for many years. This study investigated whether young, highly immersed late bilinguals would also show structural effects in the WM that can be attributed to everyday L2 use, irrespective of critical periods or the length of L2 learning. Our Tract-Based Spatial Statistics analysis revealed higher fractional anisotropy values for bilinguals vs. monolinguals in several WM tracts that have been linked to language processing and in a pattern closely resembling the results reported for older and early bilinguals. We propose that learning and actively using an L2 after childhood can have rapid dynamic effects on WM structure, which in turn may assist in preserving WM integrity in older age.

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50

Ridler, K., E. T. Bullmore, P. J. de Vries, et al. "Widespread anatomical abnormalities of grey and white matter structure in tuberous sclerosis." NeuroImage 13, no. 6 (2001): 1094. http://dx.doi.org/10.1016/s1053-8119(01)92422-x.

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