Academic literature on the topic 'White matter structure'
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Journal articles on the topic "White matter structure"
Tian, Yin, Shanshan Liang, Zhen Yuan, Sifan Chen, Peng Xu, and Dezhong Yao. "White matter structure in loneliness." NeuroReport 25, no. 11 (August 2014): 843–47. http://dx.doi.org/10.1097/wnr.0000000000000197.
Full textMizobe, Taro, Keisuke Ikari, Hirofumi Tomiyama, Keitaro Murayama, Kenta Kato, Suguru Hasuzawa, Osamu Togao, Akio Hiwatashi, and Tomohiro Nakao. "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.
Full textNowicki, Kamil W., and Raymond F. Sekula. "Pericytes Protect White-Matter Structure and Function." Neurosurgery 83, no. 3 (August 17, 2018): E103—E104. http://dx.doi.org/10.1093/neuros/nyy300.
Full textYushkevich, Paul A., Hui Zhang, Tony J. Simon, and James C. Gee. "Structure-specific statistical mapping of white matter tracts." NeuroImage 41, no. 2 (June 2008): 448–61. http://dx.doi.org/10.1016/j.neuroimage.2008.01.013.
Full textDarki, Fahimeh, Satu Massinen, Elina Salmela, Hans Matsson, Myriam Peyrard-Janvid, Torkel Klingberg, and Juha Kere. "Human ROBO1 regulates white matter structure in corpus callosum." Brain Structure and Function 222, no. 2 (May 30, 2016): 707–16. http://dx.doi.org/10.1007/s00429-016-1240-y.
Full textYund, Brianna, Kyle Rudser, Victor Kovac, Alia Ahmed, Igor Nestrasil, Kathleen Delaney, Chester Whitley, and Elsa Shapiro. "White matter structure and function in attenuated MPS II." Molecular Genetics and Metabolism 111, no. 2 (February 2014): S116—S117. http://dx.doi.org/10.1016/j.ymgme.2013.12.292.
Full textGuitart-Masip, Marc, Zeb Kurth-Nelson, Jan Axelsson, Katrine Riklund, Lars Nyberg, Lars Bäckman, and Benjamin Garzon. "Microscopic Structure of Frontal White Matter Predict Delay Discounting." Biological Psychiatry 87, no. 9 (May 2020): S197. http://dx.doi.org/10.1016/j.biopsych.2020.02.513.
Full textSchlegel, 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 (August 2012): 1664–70. http://dx.doi.org/10.1162/jocn_a_00240.
Full textSuzuki, Mitsuru, Keiko Obara, Yuka Sasaki, Koichi Matoh, Akihiro Kitabatake, Katsuya Sasaki, and Fumiaki Nunosawa. "Comparison of perivascular astrocytic structure between white matter and gray matter of rats." Brain Research 992, no. 2 (December 2003): 294–97. http://dx.doi.org/10.1016/j.brainres.2003.08.052.
Full textRIDLER, K., E. T. BULLMORE, P. J. DE VRIES, J. SUCKLING, G. J. BARKER, S. J. P. MEARA, S. C. R. WILLIAMS, and P. F. BOLTON. "Widespread anatomical abnormalities of grey and white matter structure in tuberous sclerosis." Psychological Medicine 31, no. 8 (November 2001): 1437–46. http://dx.doi.org/10.1017/s0033291701004561.
Full textDissertations / Theses on the topic "White matter structure"
Liu, Zao. "Measurement of White Matter Structure Changes in Amyotrohpic Lateral Sclerosis Using Fractal Analysis." Cleveland State University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=csu1315930636.
Full textClavenstam, Isabell. "The Effect of Methamphetamine Abuse on Brain Structure and Function." Thesis, University of Skövde, School of Humanities and Informatics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-3106.
Full textThe great amount of METH abuse all over the world causes enormous social and criminal justice problems. In the human brain the abuse of METH causes implications on both structures and functions given rise to acute as well as long term symptoms. In this essay the effects of METH abuse is described in the manner of the drug mechanism such as the impact on neurotransmitters, structural deficits with decreased and increased volumes and the implication on attention, memory, decision making and emotions. Results from studies showing brain structural and cognitive impairments in METH abusers and in prenatal METH exposed children.
McQueen, Jamie. "Vulnerability of white matter structure and function to chronic cerebral hypoperfusion and the effects of pharmacological modulation." Thesis, University of Edinburgh, 2014. http://hdl.handle.net/1842/9544.
Full textFenoll, Sanguino Raquel. "The influence of selected genetic and environmental factors on white matter pathway structure measured with diffusion tensor imaging." Doctoral thesis, Universitat de Barcelona, 2017. http://hdl.handle.net/10803/565943.
Full textLa presente tesis doctoral se centra en describir los efectos que diferentes moduladores ambientales y genéticos tienen sobre las vías de la sustancia blanca y sus consecuencias a través de imágenes de tensor de difusión. Decidimos centrarnos dos ejemplos de cada tipo de moduladores. En primer lugar, se seleccionó como factores de modulación ambiental: contaminantes y videojuegos. Por un lado, la contaminación es un factor externo que penetra pasivamente el cerebro y puede influir en las trayectorias del desarrollo. Y por otro lado, los videojuegos son un buen ejemplo de comportamiento activo que puede modificar los tractos de la materia blanca a través de la práctica. En segundo lugar, se seleccionaron el síndrome de Down y síndrome de Prader-Willi como síndromes genéticos representativos que pueden interferir en el crecimiento de la materia blanca ya que, aunque el síndrome de Down tiene una tasa de incidencia superior al síndrome de Prader-Willi, ambos muestran alteraciones cognitivas y conductuales fruto de un subdesarrollo de las vías de sustancia blanca. Los resultados de esta tesis doctoral nos llevan a la conclusión de que el desarrollo de vías de sustancia blanca no es un proceso inmutable y puede ser modificado por diversos moduladores. De la misma manera, el tensor de difusión es una técnica adecuada para capturar e identificar los cambios en la sustancia blanca que acontecen a lo largo de la vida.
Brubaker, Christopher John. "A Multimodal Magnetic Resonance Study of the Effects of Childhood Lead Exposure on Adult Brain Structure." University of Cincinnati / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1248964743.
Full textWhitford, Thomas James. "A longitudinal study of brain structure in the early stages of schizophrenia." Thesis, The University of Sydney, 2007. http://hdl.handle.net/2123/1895.
Full textWhitford, Thomas James. "A longitudinal study of brain structure in the early stages of schizophrenia." University of Sydney, 2007. http://hdl.handle.net/2123/1895.
Full textSchizophrenia is a severe mental illness that affects approximately 1% of the population worldwide, and which typically has a devastating effect on the lives of its sufferers. The characteristic symptoms of the disease include hallucinations, delusions, disorganized thought and reduced emotional expression. While many of the early theories of schizophrenia focused on its psychosocial foundations, more recent theories have focused on the neurobiological underpinnings of the disease. This thesis has four primary aims: 1) to use magnetic resonance imaging (MRI) to identify the structural brain abnormalities present in patients suffering from their first episode of schizophrenia (FES), 2) to elucidate whether these abnormalities were static or progressive over the first 2-3 years of patients’ illness, 3) to identify the relationship between these neuroanatomical abnormalities and patients’ clinical profile, and 4) to identify the normative relationship between longitudinal changes in neuroanatomy and electrophysiology in healthy participants, and to compare this to the relationship observed between these two indices in patients with FES. The aim of Chapter 2 was to use MRI to identify the neuroanatomical changes that occur over adolescence in healthy participants, and to identify the normative relationship between the neuroanatomical changes and electrophysiological changes associated with healthy periadolescent brain maturation. MRI and electroencephalographic (EEG) scans were acquired from 138 healthy participants between the ages of 10 and 30 years. The MRI scans were segmented into grey matter (GM) and white matter (WM) images, before being parcellated into the frontal, temporal, parietal and occipital lobes. Absolute EEG power was calculated for the slow-wave, alpha and beta frequency bands, for the corresponding cortical regions. The age-related changes in regional tissue volumes and regional EEG power were inferred with a regression model. The results indicated that the healthy participants experienced accelerated GM loss, EEG power loss and WM gain in the frontal and parietal lobes between the ages of 10 and 20 years, which decelerated between the ages of 20 and 30 years. A linear relationship was also observed between the maturational changes in regional GM volumes and EEG power in the frontal and parietal lobes. These results indicate that the periadolescent period is a time of great structural and electrophysiological change in the healthy human brain. The aim of Chapter 3 was to identify the GM abnormalities present in patients with FES, both at the time of their first presentation to mental health services (baseline), and over the first 2-3 years of their illness (follow-up). MRI scans were acquired from 41 patients with FES at baseline, and 47 matched healthy control subjects. Of these participants, 25 FES patients and 26 controls returned 2-3 years later for a follow-up scan. The analysis technique of voxel-based morphometry (VBM) was used in conjunction with the Statistical Parametric Mapping (SPM) software package in order to identify the regions of GM difference between the groups at baseline. The related analysis technique of tensor-based morphometry (TBM) was used to identify subjects’ longitudinal GM change over the follow-up interval. Relative to the healthy controls, the FES patients were observed to exhibit widespread GM reductions in the frontal, parietal and temporal cortices and cerebellum at baseline, as well as more circumscribed regions of GM increase, particularly in the occipital lobe. Furthermore, the FES patients lost considerably more GM over the follow-up interval than the controls, particularly in the parietal and temporal cortices. These results indicate that patients with FES exhibit significant structural brain abnormalities very early in the course of their illness, and that these abnormalities progress over the first few years of their illness. Chapter 4 employed the same methodology to investigate the white matter abnormalities exhibited by the FES subjects relative to the controls, both at baseline and over the follow-up interval. Compared to controls, the FES patients exhibited volumetric WM deficits in the frontal and temporal lobes at baseline, as well as volumetric increases at the fronto-parietal junction bilaterally. Furthermore, the FES patients lost considerably more WM over the follow-up interval than did the controls in the middle and inferior temporal cortex bilaterally. While there is substantial evidence indicating that abnormalities in the maturational processes of myelination play a significant role in the development of WM abnormalities in FES, the observed longitudinal reductions in WM were consistent with the death of a select population of temporal lobe neurons over the follow-up interval. The aim of Chapter 5 was to investigate the clinical correlates of the GM abnormalities exhibited by the FES patients at baseline. The volumes of four distinct cerebral regions where 31 patients with FES exhibited reduced GM volumes relative to 30 matched controls were calculated and correlated with patients’ scores on three primary symptom dimensions: Disorganization, Reality Distortion and Psychomotor Poverty. The results indicated that the greater the degree of atrophy exhibited by the FES patients in three of these four ‘regions-of-reduction’, the less severe their degree of Reality Distortion. These results suggest that an excessive amount of GM atrophy may in fact preclude the formation of hallucinations or highly systematized delusions in patients with FES. The aim of Chapter 6 was to identify the relationship between the longitudinal changes in brain structure and brain electrophysiology exhibited by 19 FES patients over the first 2-3 years of their illness, and to compare it to the normative relationship between the two indices reported in Chapter 2. The methodology employed for the parcellation of the MRI and EEG data was identical to Chapter 2. The results indicated that, in contrast to the healthy controls, the longitudinal reduction in GM volume exhibited by the FES patients was not associated with a corresponding reduction in EEG power in any brain lobe. In contrast, EEG power was observed to be maintained or even to increase over the follow-up interval in these patients. These results were consistent with the FES patients experiencing an abnormal elevation of neural synchrony. Such an abnormality in neural synchrony could potentially form the basis of the dysfunctional neural connectivity that has been widely proposed to underlie the functional deficits present in patients with schizophrenia. The primary aim of Chapter 7 was to assimilate the findings from the preceding empirical chapters with the theoretical framework provided in the literature, into an integrated and testable model of schizophrenia. The model emphasized dysfunctions in brain maturation, specifically in the normative processes of synaptic ‘pruning’ and axonal myelination, as playing a key role in the development of disintegrated neural activity and the subsequent onset of schizophrenic symptoms. The model concluded with the novel proposal that disintegrated neural activity arises from abnormal elevations in the synchrony of synaptic activity in patients with first-episode schizophrenia.
Koivukangas, J. (Jenni). "Brain white matter structure, body mass index and physical activity in individuals at risk for psychosis:the Northern Finland Birth Cohort 1986 Study." Doctoral thesis, Oulun yliopisto, 2016. http://urn.fi/urn:isbn:9789526212869.
Full textTiivistelmä Korkeimmassa psykoosiriskissä olevien tunnistaminen on haastavaa, eikä kunnollisia biomarkkereita ole käytettävissä. Vähäiseen liikunta-aktiivisuuteen liitetyt fyysiset sairaudet ovat yleisiä vakavaa mielenterveyshäiriötä sairastavilla. Sekä kehonpaino että psykoosialttius on yhdistetty aivojen valkean aineen rakenteen poikkeavuuksiin. Useat kehon säätelymekanismien poikkeavuudet liittyvät sekä psykiatrisiin sairauksiin että painoon liittyviin prosesseihin, mutta ei ole olemassa tutkimustietoa siitä, miten paino ja psykoosialttius vaikuttavat yhdessä aivojen rakenteeseen. Tässä osajulkaisuväitöskirjassa tutkitaan aivojen valkean aineen mikrorakennetta nuorilla aikuisilla, jotka ovat sukuriskissä sairastua psykoosiin, sekä painon vaikutusta valkean aineen rakenteeseen psykoosiriskissä. Lisäksi tutkitaan psykoosialttiiden nuorten liikunta-aktiivisuutta ja kuntoa. Tutkittavat kuuluvat Pohjois-Suomen vuoden 1986 syntymäkohorttiin. Kaksi osatutkimusta toteutettiin, joista aikaisempi kliininen tutkimus tutkittavien ollessa 15–16-vuotiaita. Tuolloin selvitettiin liikunta-aktiivisuus postikyselyn avulla (n=6,987) ja aerobinen kunto mittaamalla hapenottokyky polkupyöräergometrilla (n=4,803). Psykoosialttiutta tarkasteltiin kolmella tavalla, ja ryhmien välillä esiintyi osittaista päällekkäisyyttä: sukurasitus, 15–16 v. iässä raportoidut psykoosinkaltaiset oireet ja sairaalahoitoon johtanut psykoosi 16–20 v. iässä. Toinen kliininen osatutkimus toteutettiin tutkittavien ollessa 20–25-vuotiaita. Tutkimuksen yhteydessä tehtiin aivojen diffuusiotensorikuvaus 108 osallistuneelle. Aivojen valkean aineen mikrorakenteessa ei havaittu eroa sukuriskissä olevien ja kontrollien välillä viitaten siihen, että poikkeavuudet valkean aineen rakenteessa eivät olisi psykoosiriskin geneettinen piirre kaikissa populaatioissa. Havaitsimme kuitenkin, että assosiaatio painoindeksin ja valkean aineen rakenteen välillä oli erilainen sukuriski- ja kontrolliryhmissä. Tutkimus osoitti myös, että liikunta-aktiivisuus on alentunut jo ennen psykoosisairauden puhkeamista. Psykoosiriskissä olevien liikuntatottumuksiin ja painoon tulisi kiinnittää erityistä huomiota jo varhaisessa vaiheessa elimellisten sairauksien ehkäisemiseksi
DuBose, Lyndsey Elisabeth. "Role of aging and aerobic fitness on large elastic artery stiffness, brain structure and cognitive performance in humans." Thesis, University of Iowa, 2015. https://ir.uiowa.edu/etd/1590.
Full textEngelbrecht, Kara. "Intraindividual variability and micro-structural white matter changes in Alzheimer’s disease." Master's thesis, Faculty of Humanities, 2019. http://hdl.handle.net/11427/31087.
Full textBooks on the topic "White matter structure"
B, Westland Timothy, and Calton Robert N, eds. Handbook on white matter: Structure, function, and changes. Hauppauge, NY: Nova Science, 2009.
Find full textBoedhoe, Premika S. W., and Odile A. van den Heuvel. The Structure of the OCD Brain. Edited by Christopher Pittenger. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228163.003.0023.
Full textCarson, Matter. A Matter of Moral Justice. University of Illinois Press, 2021. http://dx.doi.org/10.5622/illinois/9780252043901.001.0001.
Full textWard, Gregory, Betty J. Birner, and Elsi Kaiser. Pragmatics and Information Structure. Edited by Yan Huang. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199697960.013.10.
Full textJones, Janine. To Be Black, Excess, and Nonrecyclable. Edited by Naomi Zack. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190236953.013.1.
Full textLevy, David. Some practical matters. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780198766452.003.0012.
Full textAnderson, Michael, and Corinne Roughley. Changing Age and Sex Structures and Their Consequences. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198805830.003.0010.
Full textWilde, Elisabeth A., Kareem W. Ayoub, and Asim F. Choudhri. Diffusion Tensor Imaging. Edited by Andrew C. Papanicolaou. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199764228.013.10.
Full textvan Schaaik, Gerjan. The Oxford Turkish Grammar. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198851509.001.0001.
Full textWoodly, Deva R. Reckoning. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197603949.001.0001.
Full textBook chapters on the topic "White matter structure"
van Duin, Esther D. A., Janneke Zinkstok, Grainne McAlonan, and Therese van Amelsvoort. "White Matter Brain Structure in Asperger’s Syndrome." In Comprehensive Guide to Autism, 1905–27. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-4788-7_115.
Full textYushkevich, Paul A., Hui Zhang, Tony J. Simon, and James C. Gee. "Structure-Specific Statistical Mapping of White Matter Tracts." In Mathematics and Visualization, 83–112. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-88378-4_5.
Full texty Cajal, Santiago Ramón. "Structure of the White Matter of the Spinal Cord." In Texture of the Nervous System of Man and the Vertebrates, 263–305. Vienna: Springer Vienna, 1999. http://dx.doi.org/10.1007/978-3-7091-6435-8_11.
Full textKindlmann, Gordon, Xavier Tricoche, and Carl-Fredrik Westin. "Anisotropy Creases Delineate White Matter Structure in Diffusion Tensor MRI." In Medical Image Computing and Computer-Assisted Intervention – MICCAI 2006, 126–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11866565_16.
Full textSedlar, Sara, Abib Alimi, Théodore Papadopoulo, Rachid Deriche, and Samuel Deslauriers-Gauthier. "A Spherical Convolutional Neural Network for White Matter Structure Imaging via dMRI." In Medical Image Computing and Computer Assisted Intervention – MICCAI 2021, 529–39. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-87199-4_50.
Full textCheng, Jian, and Peter J. Basser. "Director Field Analysis to Explore Local White Matter Geometric Structure in Diffusion MRI." In Lecture Notes in Computer Science, 427–39. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-59050-9_34.
Full textGoebel, Rainer. "Revealing Brain Activity and White Matter Structure Using Functional and Diffusion-Weighted Magnetic Resonance Imaging." In Clinical Functional MRI, 13–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45123-6_2.
Full textGoebel, Rainer. "Revealing Brain Activity and White Matter Structure Using Functional and Diffusion-Weighted Magnetic Resonance Imaging." In Clinical Functional MRI, 21–83. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-83343-5_2.
Full textAnna, Tokola, Brandstack Nina, Hakkarainen Antti, Salli Eero, Åberg Laura, and Autti Taina. "White Matter Microstructure and Subcortical Gray Matter Structure Volumes in Aspartylglucosaminuria; a 5-Year Follow-up Brain MRI Study of an Adolescent with Aspartylglucosaminuria and His Healthy Twin Brother." In JIMD Reports, 105–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/8904_2016_36.
Full textTokola, Anna, Nina Brandstack, Antti Hakkarainen, Eero Salli, Laura Åberg, and Taina Autti. "Erratum to: White Matter Microstructure and Subcortical Gray Matter Structure Volumes in Aspartylglucosaminuria; a 5-Year Follow-up Brain MRI Study of an Adolescent with Aspartylglucosaminuria and His Healthy Twin Brother." In JIMD Reports, 117. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/8904_2017_18.
Full textConference papers on the topic "White matter structure"
Gomez, Cristina Hilario, Luca Dodero, Alessandro Gozzi, Vittorio Murino, and Diego Sona. "Atlas-free connectivity analysis driven by white matter structure." In 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). IEEE, 2017. http://dx.doi.org/10.1109/isbi.2017.7950475.
Full textAranda, Ramon, Mariano Rivera, and Alonso Ramirez-Manzanares. "Self-oriented Diffusion Basis Functions for white matter structure estimation." In 2013 IEEE 10th International Symposium on Biomedical Imaging (ISBI 2013). IEEE, 2013. http://dx.doi.org/10.1109/isbi.2013.6556680.
Full textEverts, M. H., H. Bekker, and J. B. T. M. Roerdink. "Visualizing white matter structure of the brain using Dijkstra's algorithm." In 2009 6th International Symposium on Image and Signal Processing and Analysis. IEEE, 2009. http://dx.doi.org/10.1109/ispa.2009.5297652.
Full textYushkevich, Paul A., Hui Zhang, Tony J. Simon, and James C. Gee. "Structure-Specific Statistical Mapping of White Matter Tracts using the Continuous Medial Representation." In 2007 IEEE 11th International Conference on Computer Vision. IEEE, 2007. http://dx.doi.org/10.1109/iccv.2007.4409169.
Full textRamzanpour, Mohammadreza, Mohammad Hosseini-Farid, Mariusz Ziejewski, and Ghodrat Karami. "Microstructural Hyperelastic Characterization of Brain White Matter in Tension." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-11549.
Full textWu, Xuehai, John G. Georgiadis, and Assimina A. Pelegri. "Brain White Matter Model of Orthotropic Viscoelastic Properties in Frequency Domain." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-12182.
Full textOkamoto, Ruth J., Yuan Feng, Guy M. Genin, and Philip V. Bayly. "Anisotropic Behavior of White Matter in Shear and Implications for Transversely Isotropic Models." In ASME 2013 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/sbc2013-14039.
Full textBegonia, Mark G. T., Jun Liao, Mark F. Horstemeyer, and Lakiesha N. Williams. "Strain Rate Dependence in the Structure Property Relationship of Porcine Brain." In ASME 2009 Summer Bioengineering Conference. American Society of Mechanical Engineers, 2009. http://dx.doi.org/10.1115/sbc2009-206371.
Full textZhang, Biaobiao, W. Steve Shepard, and Candace L. Floyd. "Investigation of Stress Wave Propagation in Brain Tissues Through the Use of Finite Element Method." In ASME 2010 International Mechanical Engineering Congress and Exposition. ASMEDC, 2010. http://dx.doi.org/10.1115/imece2010-39994.
Full textFeng, Yuan, Ruth J. Okamoto, Ravi Namani, Guy M. Genin, and Philip V. Bayly. "Identification of a Transversely Isotropic Material Model for White Matter in the Brain." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-88610.
Full textReports on the topic "White matter structure"
Tsybekmitova, G. Ts, L. D. Radnaeva, N. A. Tashlykova, V. G. Shiretorova, A. K. Tulokhonov, B. B. Bazarova, and M. O. Matveeva. THE EFFECT OF CLIMATIC SHIFTS ON BIODIVERSITY OF PHYTOCENOSIS: LAKE ARAKHLEY (EASTERN SIBERIA, RUSSIA). DOICODE, 2020. http://dx.doi.org/10.18411/0973-7308-2020-35-3-77-90.
Full textDownard, Alicia, Stephen Semmens, and Bryant Robbins. Automated characterization of ridge-swale patterns along the Mississippi River. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40439.
Full textQi, Yan, Ryan Fries, Shambhu Saran Baral, and Pranesh Biswas. Evaluating the Costs and Benefits of Snow Fences in Illinois: Phase 2. Illinois Center for Transportation, November 2020. http://dx.doi.org/10.36501/0197-9191/20-020.
Full textLitaor, Iggy, James Ippolito, Iris Zohar, and Michael Massey. Phosphorus capture recycling and utilization for sustainable agriculture using Al/organic composite water treatment residuals. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600037.bard.
Full textLacerda Silva, P., G. R. Chalmers, A. M. M. Bustin, and R. M. Bustin. Gas geochemistry and the origins of H2S in the Montney Formation. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329794.
Full textOssoff, Will, Naz Modirzadeh, and Dustin Lewis. Preparing for a Twenty-Four-Month Sprint: A Primer for Prospective and New Elected Members of the United Nations Security Council. Harvard Law School Program on International Law and Armed Conflict, December 2020. http://dx.doi.org/10.54813/tzle1195.
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