Academic literature on the topic 'Voxel-based morphometry'
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Journal articles on the topic "Voxel-based morphometry"
Scarpazza, Cristina, and Maria De Simone. "Voxel-based morphometry: current perspectives." Neuroscience and Neuroeconomics Volume 5 (July 2016): 19–35. http://dx.doi.org/10.2147/nan.s66439.
Full textLagopoulos, Jim. "Voxel-based morphometry made simple." Acta Neuropsychiatrica 19, no. 3 (June 2007): 213–14. http://dx.doi.org/10.1111/j.1601-5215.2007.00213.x.
Full textBRENNEIS, C., E. BRANDAUER, B. FRAUSCHER, M. SCHOCKE, T. TRIEB, W. POEWE, and B. HOGL. "Voxel-based morphometry in narcolepsy." Sleep Medicine 6, no. 6 (November 2005): 531–36. http://dx.doi.org/10.1016/j.sleep.2005.03.015.
Full textYasuda, Clarissa Lin, Luiz Eduardo Betting, and Fernando Cendes. "Voxel-based morphometry and epilepsy." Expert Review of Neurotherapeutics 10, no. 6 (June 2010): 975–84. http://dx.doi.org/10.1586/ern.10.63.
Full textAshburner, John, and Karl J. Friston. "Voxel-Based Morphometry—The Methods." NeuroImage 11, no. 6 (June 2000): 805–21. http://dx.doi.org/10.1006/nimg.2000.0582.
Full textLai, Kuan-Lin, David M. Niddam, Jong-Ling Fuh, Wei-Ta Chen, Jaw-Ching Wu, and Shuu-Jiun Wang. "Cortical morphological changes in chronic migraine in a Taiwanese cohort: Surface- and voxel-based analyses." Cephalalgia 40, no. 6 (April 16, 2020): 575–85. http://dx.doi.org/10.1177/0333102420920005.
Full textAkhmadullina, D. R., Yu A. Shpilyukova, R. N. Konovalov, E. Yu Fedotova, and S. N. Illarioshkin. "Voxel-Based Morphometry in Frontotemporal Dementia." Human Physiology 46, no. 8 (December 2020): 912–20. http://dx.doi.org/10.1134/s0362119720080137.
Full textGhosh-Dastidar, Samanwoy, Hojjat Adeli, and Nahid Dadmehr. "Voxel-based morphometry in Alzheimer's patients." Journal of Alzheimer's Disease 10, no. 4 (December 13, 2006): 445–47. http://dx.doi.org/10.3233/jad-2006-10414.
Full textBaxter, Leslie C., and Marwan N. Sabbagh. "Voxel-based morphometry in Alzheimer's patients." Journal of Alzheimer's Disease 10, no. 4 (December 13, 2006): 449. http://dx.doi.org/10.3233/jad-2006-10415.
Full textBusatto, Geraldo F., Breno S. Diniz, and Marcus V. Zanetti. "Voxel-based morphometry in Alzheimer’s disease." Expert Review of Neurotherapeutics 8, no. 11 (November 2008): 1691–702. http://dx.doi.org/10.1586/14737175.8.11.1691.
Full textDissertations / Theses on the topic "Voxel-based morphometry"
Good, Catriona Diana. "Applied voxel-based morphometry in health and neurological disease." Thesis, University College London (University of London), 2004. http://discovery.ucl.ac.uk/1446572/.
Full textCacace, Anthony T., E. Mark Haake, Faith W. Akin, and Owen D. Murnane. "Vestibular-Related Traumatic Brain Injury: A Preliminary Voxel-Based Morphometry Analysis." Digital Commons @ East Tennessee State University, 2013. https://dc.etsu.edu/etsu-works/1882.
Full textCacace, A. T., Y. Ye, Faith W. Akin, Owen D. Murnane, A. Pearson, R. Gattu, and E. M. Haacke. "Voxel-Based Morphometry (VBM) in Individuals with Blast/Tbi-Related Balance Dysfunction." Digital Commons @ East Tennessee State University, 2014. https://dc.etsu.edu/etsu-works/1877.
Full textPereira, João Miguel Santos. "Characterisation, optimisation and application of voxel based morphometry in MRI studies of dementia." Thesis, University of Cambridge, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.608791.
Full textCarmona, Cañabate Susana. "Neuroanatomy of attention deficit hiperactivity disorder: voxel-based morphometry and region of interest approaches." Doctoral thesis, Universitat Autònoma de Barcelona, 2008. http://hdl.handle.net/10803/5581.
Full textEl objetivo de la presente tesis es el de redefinir y aplicar dos métodos de análisis estructural complementarios para identificar los circuitos cerebrales alterados en el TDAH así como para relacionar dichos circuitos con los diferentes subtipos clínicos. Para tal fin, presentaremos y discutiremos dos estudios de resonancia magnética estructural (Carmona et al. 2005; Tremols et al. 2008). Estos dos estudios representan una novedad y mejora de estudios de TDAH previos, por dos razones principales: a) la aplicación por primera vez un estudios basado en la morfometría de vóxeles para comparar el cerebro de niños con TDAH con el cerebro de niños controles no relacionados familiarmente; b) el diseño e implementación de un nuevo método, fácil de aplicar, de segmentación manual del núcleo caudado.
Los resultados confirman los datos obtenidos en estudios previos acerca de menor volumen cerebral en niños con TDAH, y localizan esta reducción en determinadas regiones de sustancia gris. A parte de confirmar las alteraciones fronto-estriado-cerebelares hayamos reducciones en áreas parietales, cingulares y temporales. En concreto observamos decrementos volumétricos de sustancia gris en la corteza frontal inferior, el estriado dorsal, la corteza parietal inferior y la corteza cingulada posterior, regiones clásicamente relacionadas con problemas de inhibición, deficits de memoria de trabajo y alteraciones en tareas de atención visuoespacial, respectivamente. También observamos reducciones volumétricas en áreas típicamente emocionales, como la corteza orbitofrontal, el estriado ventral y las estructurales temporales mediales deficits que podrían explicar las disfunciones motivacionales así como las alteraciones en el procesamiento del refuerzo. Curiosamente, las reducciones de sustancia gris en áreas relacionadas con el procesamiento emocional son más pronunciadas en el subtipo hiperactivo-impulsivo, algo menos en el subtipo combinado y casi inexistentes en el subtipo inatento. Esta diferente afectación en función de los subtipos va en la línea de teorías neuroanatómicas actuales acerca del TDAH (Castellanos and Tannock 2002). También observamos déficits de sustancia gris en áreas sensorio-motoras (específicamente en la corteza perirrolándica y el área motora suplementaria), y en el cerebelo. Por un lado, los déficits en áreas sensorio-motoras probablemente reflejan los problemas de psicomotricidad fina que presentan muchos de los niños con TDAH. Sin embargo, el hecho de que estas reducciones sean especialmente prominentes en los subtipos combinado e inatento, sugieren la posibilidad de que estas alteraciones estén especialmente relacionadas con los déficits atencionales. En base a esto, hipotetizamos que las alteraciones en estas regiones producirían un déficit para integrar y actualizar la información procedente del mundo exterior y, a su vez darían lugar a un sesgo a favor del procesamiento de los estados internos resultando en inatención. Por otro lado, las reducciones cerebelares (extensamente observadas en la literatura del TDAH) parecen están relacionadas con los déficits cognitivos, los afectivos y los emocionales. Creemos que la implicación del cerebelo en estas disfunciones estaría vehiculada por el papel de esta estructural como moduladora del flujo de información entre los circuitos fronto-estriatales. Finalmente nuestros hallazgos son los primeros en demostrar alteraciones diferenciales en la cabeza y el cuerpo del núcleo caudado en el TDAH. Esta desigual implicación de las diferentes partes del núcleo caudado explicaría en parte la heterogeneidad de los estudios previos.
Como conclusión, las reducciones volumétricas de sustancia gris en áreas cognitivas y emocionales apoyan la implicación de disfunciones en los circuitos fronto-estriatales llamados cool (cognitivos) y hot (emocionales) respectivamente. Hasta la fecha este es el primer estudio neuroanatómico que apoya la existencia de disfunciones tanto cognitvas como emocionales en niños con TDAH. Nuestros hallazgos constituyen la primera evidencia neuroanatómica a favor de los modelos de doble ruta porpuestos por Sonuga-Barke (Sonuga- Barke 2002; Sonuga-Barke 2003).
REFERENCIAS:
1. Tremols V, Bielsa A, Soliva JC, Raheb C, Carmona S, Tomas J, et al. (2008): Differential abnormalities of the head and body of the caudate nucleus in attention deficit-hyperactivity disorder. Psychiatry Res. 163:270-278.
2. Carmona S, Vilarroya O, Bielsa A, Tremols V, Soliva JC, Rovira M, et al. (2005): Global and regional gray matter reductions in ADHD: a voxel-based morphometric study. Neurosci Lett. 389:88-93.
3. Castellanos FX, Tannock R (2002): Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes. Nat Rev Neurosci. 3:617-628.
4. Sonuga-Barke EJ (2003): The dual pathway model of AD/HD: an elaboration of neuro-developmental characteristics. Neurosci Biobehav Rev. 27:593-604.
5. Sonuga-Barke EJ (2002): Psychological heterogeneity in AD/HD--a dual pathway model of behaviour and cognition. Behav Brain Res. 130:29-36.
Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disease characterized by symptoms of inattention, hyperactivity and impulsivity. Data from different studies point to ADHD abnormalities in fronto-striatal circuits. Structural neuroimaging studies partially support fronto-striatal abnormalities and suggest an important role of the cerebellum. However, nearly all these studies are based on the analysis of apriori selected regions of interest (known as ROI approaches). Recent studies, using more global approaches, found that ADHD structural abnormalities were not limited to fronto-striatal-cerebellar circuits, but also affect temporal, parietal and cingulate regions.
The aim of the present dissertation is to refine and apply two complementary methods of structural neuroimaging, in order to identify the brain circuits altered in
ADHD and relate them to different clinical ADHD subtypes and to known ADHD neuropsychological deficits. For that purpose, two structural MRI studies will be presented and discussed (Carmona et al. 2005; Tremols et al. 2008). The differential contributions of these studies, which represent a novelty and an improvement of previous ADHD studies, are: a) the application for the first time of
voxel-based morphometry analysis to compare ADHD children with non family related control children; b) the design and application of a new, easy to apply, manual method of caudate nucleus segmentation.
The results confirm previous findings about smaller brain volume in ADHD children, and refine this reduction by attributing it to grey matter (GM) volume. We also confirm abnormalities in fronto-striatal-cerebellar circuits as well as in parietal, cingulate and temporal regions. Specifically, we observed reductions in inferior frontal cortex, dorsal striatum, inferior parietal cortex and posterior cingulate cortex; thus explaining inhibition problems, spatial working memory deficits and visuospatial attentional alterations. We also observed GM volume reductions in emotionally driven areas such as orbitofrontal cortex, ventral striatum and middle temporal structures; thus accounting for dysfunctional delayed reward and motivational deficits. Interestingly, GM volume reductions, related to emotional processes are more prominent in H-I subtype, more preserved in combined subtypes, and relatively undisrupted in inattentive subtypes, which is in agreement with previous ADHD theories (Castellanos and Tannock 2002). We have also found GM deficits in "sensori-motor" areas (specifically in perirolandic cortex and supplementary motor area), and in the cerebellum. On the one hand, deficits in sensori-motor areas probably reflect problems in fine motor coordination. However, the fact that these reductions are especially prominent in combined and inattentive subtypes brings up the possibility that they may be related to attentional dysfunctions.
I hypothesized that deficits in these regions may produce a deficit when integrating and updating information from the external world and, in turn, produce a bias toward internal world focusing, thus, resulting in inattention. On the other hand, cerebellar reductions (which are extensively reported in ADHD literature) seem to be related to all cognitive, affective and sensorimotor deficits. The implication of cerebellum in all these dysfunctions may arise from its role as a modulator of the flow of information between fronto-strital circuits. Finally, our findings are also the first to show caudate head and body differential abnormalities in ADHD, which explain previous heterogeneous results, providing a new and reliable method to study striatal structures.
As a conclusion, GM volume reductions in emotional and cognitive areas support the implication of both hot (emotional) and cool (cognitive) functions, which agrees with most neuropsychological accounts of ADHD. To our knowledge this is the first time that a neuroanatomical study provides support for the existence of both cognitive and emotional dysfunctions in ADHD children. If these findings are replicated, they will constitute critical evidence for Sonuga-Barke's theory (Sonuga- Barke 2002; Sonuga-Barke 2003) about the dual route model.
REFERENCIAS:
1. Tremols V, Bielsa A, Soliva JC, Raheb C, Carmona S, Tomas J, et al. (2008): Differential abnormalities of the head and body of the caudate nucleus in attention deficit-hyperactivity disorder. Psychiatry Res. 163:270-278.
2. Carmona S, Vilarroya O, Bielsa A, Tremols V, Soliva JC, Rovira M, et al. (2005): Global and regional gray matter reductions in ADHD: a voxel-based morphometric study. Neurosci Lett. 389:88-93.
3. Castellanos FX, Tannock R (2002): Neuroscience of attention-deficit/hyperactivity disorder: the search for endophenotypes. Nat Rev Neurosci. 3:617-628.
5. Sonuga-Barke EJ (2003): The dual pathway model of AD/HD: an elaboration of neuro-developmental characteristics. Neurosci Biobehav Rev. 27:593-604.
6. Sonuga-Barke EJ (2002): Psychological heterogeneity in AD/HD--a dual pathway model of behaviour and cognition. Behav Brain Res. 130:29-36.
Pénicaud, Sidonie. "Insights about age of language exposure and brain development : a voxel-based morphometry approach." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=111591.
Full textHenry, Maya. "Progressive Aphasia: Patterns of Language Behavior and Regional Cortical Atrophy." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/196034.
Full textDuffield, Tyler Cole. "Cortical Thickness and Voxel-Based Morphometry of Classic Motor Regions of Interest in Autism Spectrum Disorder." BYU ScholarsArchive, 2016. https://scholarsarchive.byu.edu/etd/6383.
Full textWoo, Vivian. "Combined application of voxel-based morphometry and magnetization transfer ratio for group analysis of magnetic resonance images." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99549.
Full textVBM involves the statistical analysis of smoothed segmented white or gray matter maps to reflect increases or decreases in the probability of classifying a voxel as either white or gray matter. MTR provides a measure of the interaction of water and semi-solids within tissue, and thus is indicative of its macromolecular density and microstructural integrity. An MTR group analysis may detect variations of these semi-solid tissue characteristics within or between populations.
This thesis investigates the relationship between information attained from VBM and MTR population studies carried out in the context of the Saguenay Youth Study. Additionally, through this study, the effects of age and gender on brain neuroanatomy are explored using the above techniques. The observed age and gender VBM and MTR effects were consistent with existing literature, but also offered new findings. Overall, applying MTR in conjunction with VBM allows for further insight into the origins of specific anatomical changes, and the discovery of areas that undergo within-tissue development without corresponding white or gray matter volume changes.
Logina, Agate [Verfasser], and Martin J. [Gutachter] Herrmann. "Structural brain alterations in spider phobia : A voxel-based morphometry study / Agate Logina ; Gutachter: Martin J. Herrmann." Würzburg : Universität Würzburg, 2020. http://d-nb.info/1217599185/34.
Full textBooks on the topic "Voxel-based morphometry"
Boedhoe, 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 textBook chapters on the topic "Voxel-based morphometry"
Tate, David F. "Voxel-Based Morphometry." In Encyclopedia of Clinical Neuropsychology, 3668–69. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-57111-9_9076.
Full textTate, David F. "Voxel-Based Morphometry." In Encyclopedia of Clinical Neuropsychology, 1–2. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56782-2_9076-2.
Full textZhu, An Ping Junming, and Bin Xu. "Voxel-Based Morphometry of Brain Tumors." In Learning and Career Development in Neurosurgery, 321–35. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02078-0_28.
Full textDusi, Nicola, Giuseppe Delvecchio, Chiara Rovera, Carlo A. Altamura, and Paolo Brambilla. "Voxel-Based Morphometry Imaging Studies in Major Depression." In Neuromethods, 385–402. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7647-8_21.
Full textChung, Moo K., Li Shen, Kim M. Dalton, and Richard J. Davidson. "Multi-scale Voxel-Based Morphometry Via Weighted Spherical Harmonic Representation." In Lecture Notes in Computer Science, 36–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11812715_5.
Full textLi, Xingfeng. "Voxel-Based Morphometry and Its Application to Alzheimer’s Disease Study." In Functional Magnetic Resonance Imaging Processing, 179–99. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-7302-8_6.
Full textTermenon, M., Darya Chyzhyk, Manuel Graña, A. Barros-Loscertales, and C. Avila. "Cocaine Dependent Classification on MRI Data Extracting Features from Voxel Based Morphometry." In Natural and Artificial Computation in Engineering and Medical Applications, 140–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38622-0_15.
Full textSapuan, A. H., N. S. Mustofa, M. Z. Che Azemin, Z. A. Abdul Majid, and I. Jamaludin. "Grey Matter Volume Differences of Textual Memorization: A Voxel Based Morphometry Study." In IFMBE Proceedings, 36–43. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-10-0266-3_8.
Full textYao, Zhijun, Bin Hu, Lina Zhao, and Chuanjiang Liang. "Analysis of Gray Matter in AD Patients and MCI Subjects Based Voxel-Based Morphometry." In Brain Informatics, 209–17. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23605-1_22.
Full textNocchi, Federico, T. Franchin, E. Genovese, D. Longo, G. Fariello, and V. Cannatà. "Analysis of Outliers Effects in Voxel-Based Morphometry by means of Virtual Phantoms." In IFMBE Proceedings, 540–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-69367-3_144.
Full textConference papers on the topic "Voxel-based morphometry"
Margarida Matos, A., P. Faria, and M. Patricio. "Voxel-based morphometry analyses in Alzheimer's disease." In 2013 IEEE 3rd Portuguese Meeting in Bioengineering (ENBENG). IEEE, 2013. http://dx.doi.org/10.1109/enbeng.2013.6518386.
Full textYang, Xueyu, Kewei Chen, Xiaojuan Guo, and Li Yao. "Validation of voxel-based morphometry (VBM) based on MRI." In Medical Imaging, edited by Josien P. W. Pluim and Joseph M. Reinhardt. SPIE, 2007. http://dx.doi.org/10.1117/12.709047.
Full textZhang, Jing, Monte S. Buchsbaum, Kingwai Chu, and Erin A. Hazlett. "Comparison between Voxel-based Morphometry and Volumetric Analysis in Schizophrenia." In 2008 International Conference on Biomedical Engineering And Informatics (BMEI). IEEE, 2008. http://dx.doi.org/10.1109/bmei.2008.208.
Full textFarouk, Yasmeen, Sherine Rady, and Hossam Faheem. "Statistical features and voxel-based morphometry for alzheimer's disease classification." In 2018 9th International Conference on Information and Communication Systems (ICICS). IEEE, 2018. http://dx.doi.org/10.1109/iacs.2018.8355455.
Full textAntony, Bhavna J., Min Chen, Aaron Carass, Bruno M. Jedynak, Omar Al-Louzi, Sharon D. Solomon, Shiv Saidha, Peter A. Calabresi, and Jerry L. Prince. "Voxel based morphometry in optical coherence tomography: validation and core findings." In SPIE Medical Imaging, edited by Barjor Gimi and Andrzej Krol. SPIE, 2016. http://dx.doi.org/10.1117/12.2216096.
Full textChaitanya, CV, N. Koirala, KG Mideksa, AR Anwar, G. Schmidt, G. Deuschl, S. Groppa, and M. Muthuraman. "Testing the effects of pre-processing on voxel based morphometry analysis." In 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2015. http://dx.doi.org/10.1109/embc.2015.7319346.
Full textShen, S., A. Sterr, and A. Szameitat. "A Template Effect Study on Voxel-Based Morphometry in Statistic Parametric Mapping." In 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. IEEE, 2005. http://dx.doi.org/10.1109/iembs.2005.1617118.
Full textZhang, Jin, Bin Yan, Xin Huang, Pengfei Yang, and Chengzhong Huang. "The Diagnosis of Alzheimer's Disease Based on Voxel-Based Morphometry and Support Vector Machine." In 2008 Fourth International Conference on Natural Computation. IEEE, 2008. http://dx.doi.org/10.1109/icnc.2008.804.
Full textKalinin, Alexandr A., Ari Allyn-Feuer, Alex Ade, Gordon-Victor Fon, Walter Meixner, David Dilworth, Jeffrey R. de Wet, et al. "3D Cell Nuclear Morphology: Microscopy Imaging Dataset and Voxel-Based Morphometry Classification Results." In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW). IEEE, 2018. http://dx.doi.org/10.1109/cvprw.2018.00304.
Full textSokolov, Andrey V., Sergey V. Vorobyev, Aleksandr Yu Efimtcev, Viacheslav S. Dekan, Gennadiy E. Trufanov, Vladimir Yu Lobzin, and Vladimir A. Fokin. "fMRI and Voxel-based Morphometry in Detection of Early Stages of Alzheimer's Disease." In 4th International Conference on Bioimaging. SCITEPRESS - Science and Technology Publications, 2017. http://dx.doi.org/10.5220/0006109600670071.
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