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Journal articles on the topic 'Grey matter'

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Author: Grafiati
Published: 4 June 2021
Last updated: 11 March 2023

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1

Wood, Heather. "Grey matter matters." Nature Reviews Neuroscience 2, no. 12 (December 2001): 852. http://dx.doi.org/10.1038/35104006.

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2

van de Pol, L. "Grey hair and grey matter." Journal of Neurology, Neurosurgery & Psychiatry 75, no. 4 (April 1, 2004): 527–28. http://dx.doi.org/10.1136/jnnp.2003.032391.

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3

Miller, Saul. "Grey matter." British Journal of General Practice 69, no. 681 (March 28, 2019): 202. http://dx.doi.org/10.3399/bjgp19x702089.

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4

Jones, Rachel. "Mapping grey matter." Nature Reviews Neuroscience 2, no. 11 (November 2001): 759. http://dx.doi.org/10.1038/35097506.

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5

Timmler, Sebastian, and Mikael Simons. "Grey matter myelination." Glia 67, no. 11 (March 12, 2019): 2063–70. http://dx.doi.org/10.1002/glia.23614.

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6

Rose, Steven P. R. "Highlighting the grey matter." Nature 410, no. 6824 (March 2001): 15–16. http://dx.doi.org/10.1038/35065145.

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7

Lunn, Riley H. "It’s a Grey Matter." CRANIO® 23, no. 2 (April 2005): 83. http://dx.doi.org/10.1179/crn.2005.013.

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8

Furby, J., T. Hayton, D. Altmann, R. Brenner, J. Chataway, KJ Smith, DH Miller, and R. Kapoor. "Different white matter lesion characteristics correlate with distinct grey matter abnormalities on magnetic resonance imaging in secondary progressive multiple sclerosis." Multiple Sclerosis Journal 15, no. 6 (May 12, 2009): 687–94. http://dx.doi.org/10.1177/1352458509103176.

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Background Although MRI measures of grey matter abnormality correlate with clinical disability in multiple sclerosis, it is uncertain whether grey matter abnormality measured on MRI is entirely due to a primary grey matter process or whether it is partly related to disease in the white matter. Methods To explore potential mechanisms of grey matter damage we assessed the relationship of white matter T2 lesion volume, T1 lesion volume, and mean lesion magnetisation transfer ratio (MTR), with MRI measures of tissue atrophy and MTR in the grey matter in 117 subjects with secondary progressive multiple sclerosis. Results Grey matter fraction and mean grey matter MTR were strongly associated with lesion volumes and lesion MTR mean ( r = ±0.63–0.72). In contrast, only weak to moderate correlations existed between white matter and lesion measures. In a stepwise regression model, T1 lesion volume was the only independent lesion correlate of grey matter fraction and accounted for 52% of the variance. Lesion MTR mean and T2 lesion volume were independent correlates of mean grey matter MTR, accounting for 57% of the variance. Conclusions Axonal transection within lesions with secondary degeneration into the grey matter may explain the relationship between T1 lesions and grey matter fraction. A parallel accumulation of demyelinating lesions in white and grey matter may contribute to the association of T2 lesion volume and lesion MTR with grey matter MTR.
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Calabrese, Massimiliano, Alice Favaretto, Valeria Martini, and Paolo Gallo. "Grey matter lesions in MS." Prion 7, no. 1 (January 2013): 20–27. http://dx.doi.org/10.4161/pri.22580.

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10

Steffens, David C., James R. MacFall, Martha E. Payne, Kathleen A. Welsh-Bohmer, and K. Ranga Rama Krishnan. "Grey-matter lesions and dementia." Lancet 356, no. 9242 (November 2000): 1686–87. http://dx.doi.org/10.1016/s0140-6736(05)70393-7.

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11

Ananthaswamy, Anil. "From grey matter to you." New Scientist 225, no. 3011 (March 2015): 46–47. http://dx.doi.org/10.1016/s0262-4079(15)60450-x.

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12

Ontaneda, Daniel, Praneeta C. Raza, Kedar R. Mahajan, Douglas L. Arnold, Michael G. Dwyer, Susan A. Gauthier, Douglas N. Greve, et al. "Deep grey matter injury in multiple sclerosis: a NAIMS consensus statement." Brain 144, no. 7 (March 23, 2021): 1974–84. http://dx.doi.org/10.1093/brain/awab132.

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Abstract Although multiple sclerosis has traditionally been considered a white matter disease, extensive research documents the presence and importance of grey matter injury including cortical and deep regions. The deep grey matter exhibits a broad range of pathology and is uniquely suited to study the mechanisms and clinical relevance of tissue injury in multiple sclerosis using magnetic resonance techniques. Deep grey matter injury has been associated with clinical and cognitive disability. Recently, MRI characterization of deep grey matter properties, such as thalamic volume, have been tested as potential clinical trial end points associated with neurodegenerative aspects of multiple sclerosis. Given this emerging area of interest and its potential clinical trial relevance, the North American Imaging in Multiple Sclerosis (NAIMS) Cooperative held a workshop and reached consensus on imaging topics related to deep grey matter. Herein, we review current knowledge regarding deep grey matter injury in multiple sclerosis from an imaging perspective, including insights from histopathology, image acquisition and post-processing for deep grey matter. We discuss the clinical relevance of deep grey matter injury and specific regions of interest within the deep grey matter. We highlight unanswered questions and propose future directions, with the aim of focusing research priorities towards better methods, analysis, and interpretation of results.
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13

Mason, Graeme F., Jullie W. Pan, Wen-Jan Chu, Bradley R. Newcomer, Yantian Zhang, Roger Orr, and Hoby P. Hetherington. "Measurement of the Tricarboxylic Acid Cycle Rate in Human Grey and White Matter in Vivo by 1H-[13C] Magnetic Resonance Spectroscopy at 4.1T." Journal of Cerebral Blood Flow & Metabolism 19, no. 11 (November 1999): 1179–88. http://dx.doi.org/10.1097/00004647-199911000-00002.

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13C isotopic labeling data were obtained by 1H-observed/13C-edited magnetic resonance spectroscopy in the human brain in vivo and analyzed using a mathematical model to determine metabolic rates in human grey matter and white matter. 22,5-cc and 56-cc voxels were examined for grey matter and white matter, respectively. When partial volume effects were ignored, the measured tricarboxylic acid cycle rate was 0.72 ± 0.22 (mean ± SD) and 0.29 ± 0.09 μmol min–1 g–1(mean ± SD) in voxels of ∼70% grey and ∼70% white matter, respectively. After correction for partial volume effects using a model with two tissue compartments, the tricarboxylic acid cycle rate in pure grey matter was higher (0.80 ± 0.10 mol min–1 g–1; mean ± SD) and in white matter was significantly lower (0.17 ± 0.01 μmol min–1 g–1; mean ± SD). In 1H-observed/13C-edited magnetic resonance spectroscopy labeling studies, the larger concentrations of labeled metabolites and faster metabolic rates in grey matter biased the measurements heavily toward grey matter, with labeling time courses in 70% grey matter appearing nearly identical to labeling in pure grey matter.
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14

Roosendaal, Stefan D., Kerstin Bendfeldt, Hugo Vrenken, Chris H. Polman, Stefan Borgwardt, Ernst W. Radue, Ludwig Kappos, et al. "Grey matter volume in a large cohort of MS patients: relation to MRI parameters and disability." Multiple Sclerosis Journal 17, no. 9 (May 17, 2011): 1098–106. http://dx.doi.org/10.1177/1352458511404916.

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Background: Although grey matter damage in multiple sclerosis is currently recognized, determinants of grey matter volume and its relationship with disability are not yet clear. Objectives: The objectives of the study were to measure grey and white matter volumes across different disease phenotypes; identify MRI parameters associated with grey matter volume; and study grey and white matter volume as explanatory variables for clinical impairment. Methods: This is a cross-sectional study in which MRI data of 95 clinically isolated syndrome, 657 relapsing–remitting, 125 secondary-progressive and 50 primary-progressive multiple sclerosis patients from three centres were acquired. Grey and white matter volumes were determined, together with T2 and T1 lesion volumes. Physical disability was assessed with the Expanded Disability Status Scale, cognitive impairment with the Paced Auditory Serial Addition Task. Data were analysed using multiple regression. Results: Grey matter volume was lower in relapsing–remitting patients (mean [SD]: 0.80 [0.05] L) than in clinically isolated syndrome patients (0.82 [0.05] L), and even greater relative atrophy was found in secondary-progressive patients (0.77 [0.05] L). In contrast, white matter volume in secondary-progressive patients was comparable to that in relapsing–remitting patients. Grey matter volume was the strongest independent predictor of physical disability and cognitive impairment, and was associated with both T2 and T1 lesion volume. Conclusions: Our findings show that grey matter volume is lower in secondary-progressive than in relapsing–remitting disease. Grey matter volume explained physical and cognitive impairment better than white matter volume, and is itself associated with T2 and T1 lesion volume.
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Yaldizli, Özgür, Matteo Pardini, Varun Sethi, Nils Muhlert, Zheng Liu, Daniel J. Tozer, Rebecca S. Samson, et al. "Characteristics of lesional and extra-lesional cortical grey matter in relapsing–remitting and secondary progressive multiple sclerosis: A magnetisation transfer and diffusion tensor imaging study." Multiple Sclerosis Journal 22, no. 2 (May 26, 2015): 150–59. http://dx.doi.org/10.1177/1352458515586085.

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Background: In multiple sclerosis (MS), diffusion tensor and magnetisation transfer imaging are both abnormal in lesional and extra-lesional cortical grey matter, but differences between clinical subtypes and associations with clinical outcomes have only been partly assessed. Objective: To compare mean diffusivity, fractional anisotropy and magnetisation transfer ratio (MTR) in cortical grey matter lesions (detected using phase-sensitive inversion recovery (PSIR) imaging) and extra-lesional cortical grey matter, and assess associations with disability in relapse-onset MS. Methods: Seventy-two people with MS (46 relapsing–remitting (RR), 26 secondary progressive (SP)) and 36 healthy controls were included in this study. MTR, mean diffusivity and fractional anisotropy were measured in lesional and extra-lesional cortical grey matter. Results: Mean fractional anisotropy was higher and MTR lower in lesional compared with extra-lesional cortical grey matter. In extra-lesional cortical grey matter mean fractional anisotropy and MTR were lower, and mean diffusivity was higher in the MS group compared with controls. Mean MTR was lower and mean diffusivity was higher in lesional and extra-lesional cortical grey matter in SPMS when compared with RRMS. These differences were independent of disease duration. In multivariate analyses, MTR in extra-lesional more so than lesional cortical grey matter was associated with disability. Conclusion: Magnetic resonance abnormalities in lesional and extra-lesional cortical grey matter are greater in SPMS than RRMS. Changes in extra-lesional compared with lesional cortical grey matter are more consistently associated with disability.
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16

Théberge, Jean, Kate E. Williamson, Naoko Aoyama, Dick J. Drost, Rahul Manchanda, Ashok K. Malla, Sandra Northcott, et al. "Longitudinal grey-matter and glutamatergic losses in first-episode schizophrenia." British Journal of Psychiatry 191, no. 4 (October 2007): 325–34. http://dx.doi.org/10.1192/bjp.bp.106.033670.

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BackgroundProgressive volumetric changes in the brains of people with schizophrenia have been attributed to a number of factors.AimsTo determine whether glutamatergic changes in patients with schizophrenia correlated with grey-matter losses during the first years of illness.MethodLeft anterior cingulate and thalamic glutamatergic metabolite levels and grey-matter volumes were examined in 16 patients with first-episode schizophrenia before and after 10 months and 30 months of antipsychotic treatment and in 16 healthy participants on two occasions 30 months apart.ResultsHigher than normal glutamine levels were found in the anterior cingulate and thalamus of never-treated patients. Thalamic levels of glutamine were significantly reduced after 30 months. Limited grey-matter reductions were seen in patients at 10 months followed by widespread grey-matter loss at 30 months. Parietal and temporal lobe grey-matter loss was correlated with thalamic glutamine loss.ConclusionsElevated glutamine levels in never-treated patients followed by decreased thalamic glutamine and grey-matter loss in connected regions could indicate either neurodegeneration or a plastic response to reduced subcortical activity.
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17

Pichet Binette, Alexa, Julie Gonneaud, Jacob W. Vogel, Renaud La Joie, Pedro Rosa-Neto, D. Louis Collins, Judes Poirier, John C. S. Breitner, Sylvia Villeneuve, and Etienne Vachon-Presseau. "Morphometric network differences in ageing versus Alzheimer’s disease dementia." Brain 143, no. 2 (February 1, 2020): 635–49. http://dx.doi.org/10.1093/brain/awz414.

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Abstract Age being the main risk factor for Alzheimer’s disease, it is particularly challenging to disentangle structural changes related to normal brain ageing from those specific to Alzheimer’s disease. Most studies aiming to make this distinction focused on older adults only and on a priori anatomical regions. Drawing on a large, multi-cohort dataset ranging from young adults (n = 468; age range 18–35 years), to older adults with intact cognition (n = 431; age range 55–90 years) and with Alzheimer’s disease (n = 50 with late mild cognitive impairment and 71 with Alzheimer’s dementia, age range 56–88 years), we investigated grey matter organization and volume differences in ageing and Alzheimer’s disease. Using independent component analysis on all participants’ structural MRI, we first derived morphometric networks and extracted grey matter volume in each network. We also derived a measure of whole-brain grey matter pattern organization by correlating grey matter volume in all networks across all participants from the same cohort. We used logistic regressions and receiver operating characteristic analyses to evaluate how well grey matter volume in each network and whole-brain pattern could discriminate between ageing and Alzheimer’s disease. Because increased heterogeneity is often reported as one of the main features characterizing brain ageing, we also evaluated interindividual heterogeneity within morphometric networks and across the whole-brain organization in ageing and Alzheimer’s disease. Finally, to investigate the clinical validity of the different grey matter features, we evaluated whether grey matter volume or whole-brain pattern was related to clinical progression in cognitively normal older adults. Ageing and Alzheimer’s disease contributed additive effects on grey matter volume in nearly all networks, except frontal lobe networks, where differences in grey matter were more specific to ageing. While no networks specifically discriminated Alzheimer’s disease from ageing, heterogeneity in grey matter volumes across morphometric networks and in the whole-brain grey matter pattern characterized individuals with cognitive impairments. Preservation of the whole-brain grey matter pattern was also related to lower risk of developing cognitive impairment, more so than grey matter volume. These results suggest both ageing and Alzheimer’s disease involve widespread atrophy, but that the clinical expression of Alzheimer’s disease is uniquely associated with disruption of morphometric organization.
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18

Palmer, Kate. "A green approach to grey matter." Inpharma Weekly &NA;, no. 947 (July 1994): 3–4. http://dx.doi.org/10.2165/00128413-199409470-00002.

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19

Yasir Rafiq, Muhammad, Lydia Fasey, Mohammad Abdullah, and Abdul Salam. "Grey matter heterotopia mimicking acute stroke." Journal of the Royal College of Physicians of Edinburgh 52, no. 1 (March 2022): 52–53. http://dx.doi.org/10.1177/14782715221088977.

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Grey Matter Heterotopia is a rare clinical entity and its presentation can vary with age. While it usually presents with seizures or behavioural problems, it can seldom present as a stroke mimic. We aim to highlight this rare condition as a differential diagnosis in patients presenting with stroke-like symptoms.
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Flynn, Gerald. "Grey matter amidst the black stuff." Philosophers' Magazine, no. 37 (2007): 15–17. http://dx.doi.org/10.5840/tpm20073780.

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21

Vriend, Ilona, and Renske Oegema. "Genetic causes underlying grey matter heterotopia." European Journal of Paediatric Neurology 35 (November 2021): 82–92. http://dx.doi.org/10.1016/j.ejpn.2021.09.015.

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22

Klaver, Roel, Helga E. De Vries, Geert J. Schenk, and Jeroen J. G. Geurts. "Grey matter damage in multiple sclerosis." Prion 7, no. 1 (January 2013): 66–75. http://dx.doi.org/10.4161/pri.23499.

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23

Abrahamson, Ed, and James Ross. "Childhood stroke guidelines, a grey matter." Archives of Disease in Childhood 104, no. 2 (October 25, 2018): 206–7. http://dx.doi.org/10.1136/archdischild-2018-314986.

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24

Vercellino, Marco, Federica Plano, Barbara Votta, Roberto Mutani, Maria Teresa Giordana, and Paola Cavalla. "Grey Matter Pathology in Multiple Sclerosis." Journal of Neuropathology and Experimental Neurology 64, no. 12 (December 2005): 1101–7. http://dx.doi.org/10.1097/01.jnen.0000190067.20935.42.

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25

Lewis, Sian. "Grey matter shows its soft side." Nature Reviews Neuroscience 13, no. 9 (August 8, 2012): 600. http://dx.doi.org/10.1038/nrn3326.

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26

Borse, Megha Sunil, and Shubhangi B. Patil. "Three-dimensional reconstruction of grey matter." International Journal of Biomedical Engineering and Technology 24, no. 3 (2017): 264. http://dx.doi.org/10.1504/ijbet.2017.085143.

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Patil, Shubhangi B., and Megha Sunil Borse. "Three-dimensional reconstruction of grey matter." International Journal of Biomedical Engineering and Technology 24, no. 3 (2017): 264. http://dx.doi.org/10.1504/ijbet.2017.10005853.

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28

Geurts, Jeroen JG, and Frederik Barkhof. "Grey matter pathology in multiple sclerosis." Lancet Neurology 7, no. 9 (September 2008): 841–51. http://dx.doi.org/10.1016/s1474-4422(08)70191-1.

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29

Prados, Ferran, John Ashburner, Claudia Blaiotta, Tom Brosch, Julio Carballido-Gamio, Manuel Jorge Cardoso, Benjamin N. Conrad, et al. "Spinal cord grey matter segmentation challenge." NeuroImage 152 (May 2017): 312–29. http://dx.doi.org/10.1016/j.neuroimage.2017.03.010.

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30

Woodward, Patricia, and Patrick Dalton. "Green papers, black letters, grey matter." Law Teacher 24, no. 2 (January 1990): 124–36. http://dx.doi.org/10.1080/03069400.1990.9992761.

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31

Bo, L., J. J. G. Geurts, S. J. Mork, and P. Valk. "Grey matter pathology in multiple sclerosis." Acta Neurologica Scandinavica 113, s183 (May 2006): 48–50. http://dx.doi.org/10.1111/j.1600-0404.2006.00615.x.

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32

Shetty, Priya. "Grey matter: ageing in developing countries." Lancet 379, no. 9823 (April 2012): 1285–87. http://dx.doi.org/10.1016/s0140-6736(12)60541-8.

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33

Zanchin, G., M. Margoni, M. Calabrese, and F. Maggioni. "Grey matter in chronic migraine patients." Journal of the Neurological Sciences 333 (October 2013): e514. http://dx.doi.org/10.1016/j.jns.2013.07.1814.

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34

van der Knaap, M. S., J. Valk, G. H. Jansen, L. J. Kappelle, and O. van Nieuwenhuizen. "Mycotic encephalitis: predilection for grey matter." Neuroradiology 35, no. 8 (October 1993): 567–72. http://dx.doi.org/10.1007/bf00588394.

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35

Collin, Guusje, Marcel A. de Reus, Wiepke Cahn, Hilleke E. Hulshoff Pol, René S. Kahn, and Martijn P. van den Heuvel. "Disturbed grey matter coupling in schizophrenia." European Neuropsychopharmacology 23, no. 1 (January 2013): 46–54. http://dx.doi.org/10.1016/j.euroneuro.2012.09.001.

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Strelnikov, David, Amirreza Alijanpourotaghsara, Marton Piroska, Laszlo Szalontai, Bianka Forgo, Zsofia Jokkel, Alíz Persely, et al. "Heritability of Subcortical Grey Matter Structures." Medicina 58, no. 11 (November 21, 2022): 1687. http://dx.doi.org/10.3390/medicina58111687.

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Background and Objectives: Subcortical grey matter structures play essential roles in cognitive, affective, social, and motoric functions in humans. Their volume changes with age, and decreased volumes have been linked with many neuropsychiatric disorders. The aim of our study was to examine the heritability of six subcortical brain volumes (the amygdala, caudate nucleus, pallidum, putamen, thalamus, and nucleus accumbens) and four general brain volumes (the total intra-cranial volume and the grey matter, white matter, and cerebrospinal fluid (CSF) volume) in twins. Materials and Methods: A total of 118 healthy adult twins from the Hungarian Twin Registry (86 monozygotic and 32 dizygotic; median age 50 ± 27 years) underwent brain magnetic resonance imaging. Two automated volumetry pipelines, Computational Anatomy Toolbox 12 (CAT12) and volBrain, were used to calculate the subcortical and general brain volumes from three-dimensional T1-weighted images. Age- and sex-adjusted monozygotic and dizygotic intra-pair correlations were calculated, and the univariate ACE model was applied. Pearson’s correlation test was used to compare the results obtained by the two pipelines. Results: The age- and sex-adjusted heritability estimates, using CAT12 for the amygdala, caudate nucleus, pallidum, putamen, and nucleus accumbens, were between 0.75 and 0.95. The thalamus volume was more strongly influenced by common environmental factors (C = 0.45−0.73). The heritability estimates, using volBrain, were between 0.69 and 0.92 for the nucleus accumbens, pallidum, putamen, right amygdala, and caudate nucleus. The left amygdala and thalamus were more strongly influenced by common environmental factors (C = 0.72−0.85). A strong correlation between CAT12 and volBrain (r = 0.74−0.94) was obtained for all volumes. Conclusions: The majority of examined subcortical volumes appeared to be strongly heritable. The thalamus was more strongly influenced by common environmental factors when investigated with both segmentation methods. Our results underline the importance of identifying the relevant genes responsible for variations in the subcortical structure volume and associated diseases.
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Lewis, Gwyn N., Karolina A. Wartolowska, Rosalind S. Parker, Sheena Sharma, David A. Rice, Michal Kluger, and Peter J. McNair. "A Higher Grey Matter Density in the Amygdala and Midbrain Is Associated with Persistent Pain Following Total Knee Arthroplasty." Pain Medicine 21, no. 12 (October 4, 2020): 3393–400. http://dx.doi.org/10.1093/pm/pnaa227.

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Abstract Objective The development of persistent pain following total knee arthroplasty (TKA) is common, but its underlying mechanisms are unknown. The goal of the study was to assess brain grey matter structure and its correlation with function of the nociceptive system in people with good and poor outcomes following TKA. Subjects Thirty-one people with LOW_PAIN (<3/10 on the numerical ratings scale [NRS]) at six months following TKA and 15 people with HIGH_PAIN (≥3/10 on the NRS) were recruited into the study. Methods Grey matter in key brain areas related to nociception was analyzed using voxel-based morphometry (VBM). Nociceptive facilitatory and inhibitory processes were evaluated using quantitative sensory testing (QST). QST scores and grey matter density in prespecified brain regions were compared between the LOW_PAIN and HIGH_PAIN groups. Regression analyses were used to analyze the associations between the grey matter and QST scores. Results There were no between-group differences in QST measures. In the VBM analysis, the HIGH_PAIN group had a higher grey matter density in the right amygdala, right nucleus accumbens, and in the periaqueductal grey (PAG), but lower grey matter density in the dorsal part of the left caudate nucleus. Grey matter density in the right amygdala and PAG correlated positively with temporal summation of pain. Conclusions Persistent pain at six months after TKA is associated with a higher grey matter density in the regions involved in central sensitization and pain-related fear, which may contribute to the development of persistent pain after surgery.
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McDonald, Colm, Ed Bullmore, Pak Sham, Xavier Chitnis, John Suckling, James Maccabe, Muriel Walshe, and Robin M. Murray. "Regional volume deviations of brain structure in schizophrenia and psychotic bipolar disorder." British Journal of Psychiatry 186, no. 5 (May 2005): 369–77. http://dx.doi.org/10.1192/bjp.186.5.369.

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BackgroundIt is unclear whether schizophrenia and psychotic bipolar disorder are associated with similar deviations of brain morphometry.AimsTo assess volumetric abnormalities of grey and white matter throughout the entire brain in individuals with schizophrenia or with bipolar disorder compared with the same control group.MethodBrain scans were obtained by magnetic resonance imaging from 25 people with schizophrenia, 37 with bipolar disorder who had experienced psychotic symptoms and 52 healthy volunteers. Regional deviation in grey and white matter volume was assessed using computational morphometry.ResultsIndividuals with schizophrenia had distributed grey matter deficit predominantly involving the fronto-temporal neocortex, medial temporal lobe, insula, thalamus and cerebellum, whereas those with bipolar disorder had no significant regions of grey matter abnormality. Both groups had anatomically overlapping white matter deficits in regions normally occupied by major longitudinal and interhemispheric tracts.ConclusionsSchizophrenia and psychotic bipolar disorder are associated with distinct grey matter deficits but anatomically coincident white matter abnormalities.
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Kim, Jae-Jin, Myung Chul Lee, Jaeseok Kim, In Young Kim, Sun I. Kim, Moon Hee Han, Kee-Hyun Chang, and Jun Soo Kwon. "Grey matter abnormalities in obsessive–compulsive disorder." British Journal of Psychiatry 179, no. 4 (October 2001): 330–34. http://dx.doi.org/10.1192/bjp.179.4.330.

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BackgroundAlthough a number of functional imaging studies are in agreement in suggesting orbitofrontal and subcortical hyperfunction in the pathophysiology of obsessive–compulsive disorder (OCD), the structural findings have been contradictory.AimsTo investigate grey matter abnormalities in patients with OCD by employing a novel voxel-based analysis of magnetic resonance images.MethodStatistical parametric mapping was utilised to compare segmented grey matter images from 25 patients with OCD with those from 25 matched controls.ResultsIncreased regional grey matter density was found in multiple cortical areas, including the left orbitofrontal cortex, and in subcortical areas, including the thalamus. On the other hand, regions of reduction were confined to posterior parts of the brain, such as the left cuneus and the left cerebellum.ConclusionsIncreased grey matter density of frontal–subcortical circuits, consonant with the hypermetabolic findings from functional imaging studies, seems to exist in patients with OCD, and cerebellar dysfunction may be involved in the pathophysiology of OCD.
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Ruzic Barsic, Antonija, Gordana Rubesa, Diana Mance, Damir Miletic, Lea Gudelj, and Ronald Antulov. "INFLUENCE OF PSYCHOTIC EPISODES ON GREY MATTER VOLUME CHANGES IN PATIENTS WITH SCHIZOPHRENIA." Psychiatria Danubina 32, no. 3-4 (December 24, 2020): 359–66. http://dx.doi.org/10.24869/psyd.2020.359.

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41

Itoh, Christopher Yuki, Han Sung Lee, and Alan Howe Yee. "Grey matter abnormality in progressive multifocal leucoencephalopathy." Practical Neurology 21, no. 3 (March 30, 2021): 225–27. http://dx.doi.org/10.1136/practneurol-2020-002852.

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Progressive multifocal leucoencephalopathy (PML) is a demyelinating white matter disease that most often affects immunocompromised people infected by JC virus. The diagnostic gold standard is demonstrable viral DNA or protein from histopathological tissue. However, there are few detailed descriptions of cortical grey matter involvement on neuroimaging. Here we describe the histopathological correlate of cerebral grey matter involvement and radiological accompaniment in a patient with biopsy proven PML.
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42

Chamberlain, Samuel R., Lara A. Menzies, Naomi A. Fineberg, Natalia del Campo, John Suckling, Kevin Craig, Ulrich Müller, Trevor W. Robbins, Edward T. Bullmore, and Barbara J. Sahakian. "Grey matter abnormalities in trichotillomania: morphometric magnetic resonance imaging study." British Journal of Psychiatry 193, no. 3 (September 2008): 216–21. http://dx.doi.org/10.1192/bjp.bp.107.048314.

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BackgroundTrichotillomania (repetitive hair-pulling) is an Axis I psychiatric disorder whose neurobiological basis is incompletely understood. Whole-brain trichotillomania neuroimaging studies are lacking.AimsTo investigate grey and white matter abnormalities over the whole brain in patients with trichotillomania.MethodEighteen patients with DSM–IV trichotillomania and 19 healthy controls undertook structural magnetic resonance imaging after providing written informed consent. Differences in grey and white matter were investigated using computational morphometry.ResultsPatients with trichotillomania showed increased grey matter densities in the left striatum, left amygdalo-hippocampal formation, and multiple (including cingulate, supplementary motor, and frontal) cortical regions bilaterally.ConclusionsTrichotillomania was associated with structural grey matter changes in neural circuitry implicated in habit learning, cognition and affect regulation. These findings inform animal models of the disorder and highlight key regions of interest for future translational research.
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43

Faulkner, Paul, Susanna Lucini Paioni, Petya Kozhuharova, Natasza Orlov, David J. Lythgoe, Yusuf Daniju, Elenor Morgenroth, Holly Barker, and Paul Allen. "Relationship between depression, prefrontal creatine and grey matter volume." Journal of Psychopharmacology 35, no. 12 (October 26, 2021): 1464–72. http://dx.doi.org/10.1177/02698811211050550.

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Background: Depression and low mood are leading contributors to disability worldwide. Research indicates that clinical depression may be associated with low creatine concentrations in the brain and low prefrontal grey matter volume. Because subclinical depression also contributes to difficulties in day-to-day life, understanding the neural mechanisms of depressive symptoms in all individuals, even at a subclinical level, may aid public health. Methods: Eighty-four young adult participants completed the Depression, Anxiety and Stress Scale (DASS) to quantify severity of depression, anxiety and stress, and underwent 1H-Magnetic Resonance Spectroscopy of the medial prefrontal cortex and structural magnetic resonance imaging (MRI) to determine whole-brain grey matter volume. Results/outcomes: DASS depression scores were negatively associated (a) with concentrations of creatine (but not other metabolites) in the prefrontal cortex and (b) with grey matter volume in the right superior medial frontal gyrus. Medial prefrontal creatine concentrations and right superior medial frontal grey matter volume were positively correlated. DASS anxiety and DASS stress scores were not related to prefrontal metabolite concentrations or whole-brain grey matter volume. Conclusions/interpretations: This study provides preliminary evidence from a representative group of individuals who exhibit a range of depression levels that prefrontal creatine and grey matter volume are negatively associated with depression. While future research is needed to fully understand this relationship, these results provide support for previous findings, which indicate that increasing creatine concentrations in the prefrontal cortex may improve mood and well-being.
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44

Aoyama, Naoko, Jean Théberge, Dick J. Drost, Rahul Manchanda, Sandra Northcott, Richard W. J. Neufeld, Ravi S. Menon, et al. "Grey matter and social functioning correlates of glutamatergic metabolite loss in schizophrenia." British Journal of Psychiatry 198, no. 6 (June 2011): 448–56. http://dx.doi.org/10.1192/bjp.bp.110.079608.

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BackgroundThalamic glutamine loss and grey matter reduction suggest neurodegeneration in first-episode schizophrenia, but the duration is unknown.AimsTo observe glutamine and glutamate levels, grey matter volumes and social functioning in patients with schizophrenia followed to 80 months after diagnosis.MethodGrey matter volumes and proton magnetic resonance spectroscopy metabolites in left anterior cingulate and left thalamus were measured in 17 patients with schizophrenia before medication and 10 and 80 months after diagnosis. Social functioning was assessed with the Life Skills Profile Rating Scale (LSPRS) at 80 months.ResultsThe sum of thalamic glutamate and glutamine levels decreased over 80 months, and correlated inversely with the LSPRS. Thalamic glutamine and grey matter loss were significantly correlated in frontal, parietal, temporal and limbic regions.ConclusionsBrain metabolite loss is correlated with deteriorated social functioning and grey matter losses in schizophrenia, consistent with neurodegeneration.
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45

Meijer, Kim A., Anand J. C. Eijlers, Jeroen J. G. Geurts, and Menno M. Schoonheim. "Staging of cortical and deep grey matter functional connectivity changes in multiple sclerosis." Journal of Neurology, Neurosurgery & Psychiatry 89, no. 2 (October 6, 2017): 205–10. http://dx.doi.org/10.1136/jnnp-2017-316329.

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ObjectiveFunctional connectivity is known to increase as well as decrease throughout the brain in multiple sclerosis (MS), which could represent different stages of the disease. In addition, functional connectivity changes could follow the atrophy pattern observed with disease progression, that is, moving from the deep grey matter towards the cortex. This study investigated when and where connectivity changes develop and explored their clinical and cognitive relevance across different MS stages.MethodsA cohort of 121 patients with early relapsing–remitting MS (RRMS), 122 with late RRMS and 53 with secondary progressive MS (SPMS) as well as 96 healthy controls underwent MRI and neuropsychological testing. Functional connectivity changes were investigated for (1) within deep grey matter connectivity, (2) connectivity between the deep grey matter and cortex and (3) within-cortex connectivity. A post hoc regional analysis was performed to identify which regions were driving the connectivity changes.ResultsPatients with late RRMS and SPMS showed increased connectivity of the deep grey matter, especially of the putamen and palladium, with other deep grey matter structures and with the cortex. Within-cortex connectivity was decreased, especially for temporal, occipital and frontal regions, but only in SPMS relative to early RRMS. Deep grey matter connectivity alterations were related to cognition and disability, whereas within-cortex connectivity was only related to disability.ConclusionIncreased connectivity of the deep grey matter became apparent in late RRMS and further increased in SPMS. The additive effect of cortical network degeneration, which was only seen in SPMS, may explain the sudden clinical deterioration characteristic to this phase of the disease.
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46

Wang, Yuan, Qian Yang, Dongyuan Cao, David Seminowicz, Bethany Remeniuk, Lin Gao, and Ming Zhang. "Correlation between nerve atrophy, brain grey matter volume and pain severity in patients with primary trigeminal neuralgia." Cephalalgia 39, no. 4 (August 7, 2018): 515–25. http://dx.doi.org/10.1177/0333102418793643.

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Background Recent neuroimaging studies have reported grey matter alterations in primary trigeminal neuralgia patients. However, few studies have focused on quantitative measurements of trigeminal nerves and the interaction between trigeminal nerve volume and brain morphology, particularly grey matter volume. In this study, we investigated the link between trigeminal nerves and grey matter volume changes in primary trigeminal neuralgia patients compared to healthy controls. Moreover, we explored the association of structure of trigeminal nerves and grey matter to collected pain clinical variables. Methods Eighty participants (40 patients and 40 controls) were recruited for the study. All participants underwent MRI sessions and clinical pain assessment. Trigeminal nerve volume and whole brain grey matter volume were evaluated using quantitative imaging techniques. Sensory and affective pain rating indices were assessed using the visual analog scale and short-form McGill Pain Questionnaire. Mediation analysis was conducted to investigate the relationship between clinical pain variables and volumetric changes in trigeminal nerves and grey matter. Results Decreased trigeminal nerve volume was detected in primary trigeminal neuralgia patients compared to controls. Additionally, reduced grey matter volume was found in several regions associated with pain in primary trigeminal neuralgia subjects, including the insula, secondary somatosensory cortex, hippocampus, dorsal anterior cingulate cortex, precuneus, and several areas of the temporal lobe. Mediation analysis revealed that decreased trigeminal nerve volume drove grey matter volume abnormality of the left insula, and further led to increased pain ratings. Conclusion This study showed a predominantly direct effect of trigeminal nerve atrophy on clinical pain variables in primary trigeminal neuralgia patients, providing new insight into the pathophysiology of the disease. Trial registration ClinicalTrials.gov ID: NCT02713646
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Bakulin, I. S., R. N. Konovalov, M. V. Krotenkova, N. A. Suponeva, and M. N. Zakharova. "Voxel-based morphometry in amyotrophic lateral sclerosis." Journal of radiology and nuclear medicine 99, no. 6 (January 2, 2019): 287–94. http://dx.doi.org/10.20862/0042-4676-2018-99-6-287-294.

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Objective:to investigate changes in grey matter volume in patients with classical amyotrophic lateral sclerosis (ALS) and lower motor neuron syndrome (LMNS) with voxel-based morphometry (VBM).Material and methods. 30 patients with classical ALS, 22 patients with LMNS and 23 age and gender matched healthy controls were enrolled in this study. All participants underwent a T1MPR (multiplanar reconstruction) magnetic resonance imaging with post-processing included spatial normalization, segmentation and smoothing. VBM was used to investigate changes in grey matter volume across the groups.Results. There was a significant decrease in grey matter volume of middle part of left pre- and postcentral gyri, middle part of right precentral gyrus, right and left occipital lobes in patients with classical ALS compared to healthy subjects. There was no difference in grey matter volume between patients with LMNS and healthy controls. Patients with classical ALS showed a significant decrease in grey matter volume of middle part of left preand postcentral gyri, upper part of left precentral gyrus, middle and upper parts of right precentral gyrus, right and left occipital lobes compared to patients with LMNS. There was no significant correlation between grey matter volume and clinical findings in patients with ALS and LMNS.Conclusion.VBM reveals a decrease in grey matter volume of motor and nonmotor brain regions in patients with classical ALS, but not in patients with LMNS.
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Berdenis van Berlekom, Amber, Nina Notman, Marjolein AM Sneeboer, Gijsje JLJ Snijders, Lotte C. Houtepen, Danny M. Nispeling, Yujie He, et al. "DNA methylation differences in cortical grey and white matter in schizophrenia." Epigenomics 13, no. 15 (August 2021): 1157–69. http://dx.doi.org/10.2217/epi-2021-0077.

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Aim: Identify grey- and white-matter-specific DNA-methylation differences between schizophrenia (SCZ) patients and controls in postmortem brain cortical tissue. Materials & methods: Grey and white matter were separated from postmortem brain tissue of the superior temporal and medial frontal gyrus from SCZ (n = 10) and control (n = 11) cases. Genome-wide DNA-methylation analysis was performed using the Infinium EPIC Methylation Array (Illumina, CA, USA). Results: Four differentially methylated regions associated with SCZ status and tissue type (grey vs white matter) were identified within or near KLF9, SFXN1, SPRED2 and ALS2CL genes. Gene-expression analysis showed differential expression of KLF9 and SFXN1 in SCZ. Conclusion: Our data show distinct differences in DNA methylation between grey and white matter that are unique to SCZ, providing new leads to unravel the pathogenesis of SCZ.
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Raus, Iulian, Adela Mihaela Vintan, and Roxana Elena Coroiu. "Hemimegalencephaly with polymicrogyria – a case report." Medicine and Pharmacy Reports 89, no. 2 (April 21, 2016): 293–96. http://dx.doi.org/10.15386/cjmed-503.

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Hemimegalencephaly on magnetic resonance imaging scan (MRI) consists of cortical gray matter almost uniformly abnormal, areas of increased thickness of the cortical gray matter (GM), abnormal gyral patterns, blurring of the grey-white matter transition, atrophy or hemispheric hypertrophy, demyelination, gliosis. We present a case of ten-year-old boy with a history of infantile spasms and developmental delay who presented to the pediatric neurology room with an episode of disinhibited behavior in family environment. An MRI was performed and isolated hemimegalencephaly with polymicrogyria of the right occipital lobe was diagnosed.
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50

Papadopoulos, Konstantinos, Daniel J. Tozer, Leonora Fisniku, Daniel R. Altmann, Gerard Davies, Waqar Rashid, Alan J. Thompson, David H. Miller, and Declan T. Chard. "TI-relaxation time changes over five years in relapsing-remitting multiple sclerosis." Multiple Sclerosis Journal 16, no. 4 (January 19, 2010): 427–33. http://dx.doi.org/10.1177/1352458509359924.

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The pathological effects of multiple sclerosis are not confined to lesions; tissues that appear normal on conventional magnetic resonance imaging scans are also affected, albeit subtly. One imaging technique that has proven sensitive to such effects is T1-relaxation time measurement, with previous work demonstrating abnormalities in normal-appearing white matter and grey matter. In this work we investigated the evolution of T1-relaxation time changes in normal-appearing white matter and grey matter in relapsing—remitting multiple sclerosis. Three- and five-year follow-up data from 35 people with clinically early (a mean of 1.6 years from first clinical event) relapsing—remitting multiple sclerosis and 15 healthy controls were analysed. T1-relaxation time histograms were extracted from normal-appearing white matter and grey matter, and mean, peak height and peak location values were estimated. T1-relaxation time peak height declined in the multiple sclerosis normal-appearing white matter and grey matter, but not the control group (rate difference p = 0.024 in normal-appearing white matter, in normal-appearing grey matter p = 0.038); other T1-relaxation time changes were not significantly different between groups. Changes in T1-relaxation time measures did not correlate with increases in brain T2-weighted lesion loads or Expanded Disability Status Scale scores. These results suggest that the processes underlying changes in normal-appearing white matter and grey matter T1-relaxation times are not immediately linked to white matter lesion formation, and may represent more diffuse but progressive sub-clinical pathology in relapsing—remitting multiple sclerosis.
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