Academic literature on the topic 'Voxel-based morphometry'

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Journal articles on the topic "Voxel-based morphometry"

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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.

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Lagopoulos, 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.

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BRENNEIS, 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.

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Yasuda, 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.

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Ashburner, 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.

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Lai, 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.

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Background Previous voxel- or surface-based morphometric analysis studies have revealed alterations in cortical structure in patients with chronic migraine, yet with inconsistent results. The discrepancies may be derived partly from the sample heterogeneity. Employing both methods in a clinically homogenous group may provide a clearer view. Methods Structural MRI data from 30 prevention-naïve patients with chronic migraine without medication overuse headache or a history of major depression and 30 healthy controls were analyzed. Vertex-wise (surface-based) or voxel-wise (voxel-based) linear models were applied, after controlling for age and gender, to investigate between-group differences. Averaged cortical thicknesses and volumes from regions showing group differences were correlated with parameters related to clinical profiles. Results Surface-based morphometry showed significantly thinner cortices in the bilateral insular cortex, caudal middle frontal gyrus, precentral gyrus, and parietal lobes in patients with chronic migraine relative to healthy controls. Additionally, the number of migraine days in the month preceding MRI examination was correlated negatively with right insular cortical thickness. Voxel-based morphometry (VBM) did not show any group differences or clinical correlations. Conclusion Patients with chronic migraine without medication overuse headache, major depression, or prior preventive treatment had reduced cortical thickness in regions within the pain-processing network. Compared to voxel-based morphometry, surface-based morphometry analysis may be more sensitive to subtle structural differences between healthy controls and patients with chronic migraine.
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Akhmadullina, 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.

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Ghosh-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.

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Baxter, 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.

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Busatto, 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.

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Dissertations / Theses on the topic "Voxel-based morphometry"

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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/.

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The importance of brain structure is indisputable. It forms the framework on which functional parameters can be mapped and referenced. The classical region of interest based morphometric methods that have hitherto formed the mainstay of structural neuroimaging have a number of drawbacks not least because they are spatially constrained and operator dependent. In light of substantial advances in magnetic resonance imaging techniques and concomitant computational post processing innovations, new insights into brain structure are now possible. A new generation of whole brain imaging techniques can now inform about brain structure in a more holistic way with enhanced precision. Computational neuroanatomy is a new method employing the versatile framework of statistic parametric mapping and volumetric high-resolution magnetic resonance images of the brain. It consists of a triad of interactive techniques: voxel-based morphometry (VBM) which provides voxel-wise inferences about regional grey and white matter, deformation-based morphometry (DBM) which characterises global brain shape differences and tensor-based morphometry (TBM) which characterises local shape differences with high precision. This thesis examines the application and usefulness of voxel-based morphometry with particular reference to its practicality, reproducibility, validity and sensitivity to characterise brain structure. VBM is first applied to a large normative catabase to characterise physiological variations in normal brain structure in order to create a canonical framework against which pathology can be measured. VBM is then rigorously compared with classical morphometrics in patients with two distinct forms of dementia and in patients with mesial temporal sclerosis in order to establish validity and sensitivity. VBM is then applied to a variety of disease groups where classical morphometrics have failed to reveal consistent brain structural phenotypes in order to reveal morphological changes in functionally implicated regions. Finally VBM is used is a tool to allow genotype-phenotype mapping. The strengths and weaknesses of this new technique are discussed with reference to its applicability and usefulness for neurologists and neuroradiologists.
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Cacace, 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.

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Vestibular-related problems (dizziness, vertigo, and imbalance) are common sequelae following concussion and blast exposures that result in mild traumatic brain injury (mTBI). However, the anatomical substrate connected to these dysfunctions is not well understood. To provide a better understanding of this area, we used voxel-based morphometry (VBM) as a platform for studying vestibular-related mTBI in the human brain. Briefly, VBM is a group comparison study which evaluates structural differences in magnetic resonance (MR) images between agematched groups of individuals (11 vestibular TBI patients and 10 controls). Using the VBM-8 Toolbox and statistical probability mapping (SPM), MRI images were segmented into gray matter, white matter, and cerebrospinal fluid, normalized into a standardized anatomical space, and then analyzed statistically for significant anatomical differences between groups. Based on the VBM analysis, most notable differences in brain anatomy were characterized by reductions in gray matter volume observed in the middle frontal gyrus, mesial frontal lobe, and in the insular area in the left mesial temporal lobe. These findings provide a preliminary analysis of distributed gray matter changes in key frontal and temporal areas of the brain associated with mTBI related vestibular dysfunction.
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Cacace, 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.

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Pereira, 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.

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Carmona, 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.

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El trastorno por déficit de atención e hiperactividad (TDAH) es un trastorno del neurodesarrollo caracterizado por síntomas de inatención, hiperactividad e impulsividad. Los modelos clásicos acerca de la neuroanatomía del trastorno apuntan a alteraciones en los circuitos fronto-estriado-cerebelares. Los estudios de neuroimagen estructural apoyan parcialmente estos modelos. Sin embargo, casi todos estos estudios se basan en el análisis de regiones seleccionadas a priori (procedimiento que se conoce como ROI, acrónimo inglés de regiones de interés: "region of interest"). Estudios más recientes basados en aproximaciones globales apuntan a que las alteraciones estructurales no se limitan a los circuitos fronto-estriado-cerebelares, sino que también afectan las regiones temporales, parietales y cinguladas.
El 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.
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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.

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Early language experience is thought to be essential to develop a high level of linguistic proficiency in adulthood. Impoverished language input during childhood has been found to lead to functional changes in the brain. In this study, we explored if delayed exposure to a first language modulates the neuroanatomical development of the brain. To do so, voxel-based morphometry (VBM) was carried out in a group of congenitally deaf individuals varying in the age of first exposure to American Sign Language (ASL). To explore a secondary question about the effect of auditory deprivation on structural brain development, a second VBM analysis compared deaf individuals to matched hearing controls. The results show that delayed exposure to sign language is associated with a decrease in grey-matter concentration in the visual cortex close to an area found to show functional reorganization related to delayed exposure to language, while auditory deprivation is associated with a decrease in white matter in the right primary auditory cortex. These findings suggest that a lack of early language experience alters the anatomical organization of the brain.
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Henry, Maya. "Progressive Aphasia: Patterns of Language Behavior and Regional Cortical Atrophy." Diss., The University of Arizona, 2009. http://hdl.handle.net/10150/196034.

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Primary Progressive aphasia (PPA) is a disorder characterized by gradual decline in language functions, with relative sparing of other cognitive abilities. This behavioral profile results from neurodegenerative disease that preferentially affects language cortex. As is the case in aphasia resulting from stroke, any of several critical language processing domains may be affected in PPA, including syntax, semantics, phonology, and orthography. In stroke-induced aphasia, traditional lesion mapping approaches have provided important insight into the localization of cortical regions supporting these domains. Specifically, left perisylvian cortex has been implicated in syntactic and phonological aspects of language, whereas left extrasylvian cortical regions are associated with lexical-semantic and orthographic functions. The goal of the present study was to seek converging evidence for the role of left hemisphere cortical regions in language using a voxel-based imaging technique in individuals with PPA. Fifteen individuals with progressive aphasia and fifteen normal controls were given a comprehensive language battery comprising tasks in the domains of syntax, semantics, phonology, and orthography. A subset of patients and all normal controls underwent high-resolution structural MRI scanning. Voxel-based morphometry (VBM) was used to characterize patterns of regional cortical atrophy in the patients relative to controls and to correlate language tasks with gray matter volumes. Results confirm a key role for left perisylvian cortex in phonological and syntactic processes, and indicate that left temporal regions are critically involved in semantic processes. Findings shed light on the veracity of the "primary systems" hypothesis of written language, which posits that written language impairments arise from core cognitive deficits affecting semantic and phonological systems.
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Duffield, 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.

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Prior research has suggested that any cortical volume (CV) abnormalities in Autism Spectrum Disorder (ASD) need to be further explored by examination of the two determinants of CV, that being cortical thickness (CT) and pial surface area (PSA; Murphy, Beecham, Craig, & Ecker, 2011). The current study suggests that the two determinants of CV should be explored even in the presence of null CV findings, if structure-function analyses are significant (i.e., bi-lateral precentral gyrus and neuropsychological motor test) as demonstrated in the current sample (see Duffield et al., 2013). The only significant anatomic finding was reduced CT in the left frontal motor regions (primarily left precentral gyrus), which also corresponded to the only significant relationship between a motor variable (i.e., grooved pegboard test) and motor region-of-interest (ROI) where ASD had a stronger relationship than typically developing controls (TDC; ASD > TDC). Left hemisphere biased CT group differences has been shown to have the highest classification accuracy (i.e., designation of ASD versus TDC) of morphological parameters (Ecker et al., 2010), yet PSA has been shown to have far greater modulation of CV abnormalities. This is particularly true for subthreshold PSA (Ecker et al., 2013). These prior findings are not only consistent with the current motor ROI findings, but also provide an explanatory framework for the functional neuroanatomy of a generally worse left handed performance (i.e., non-dominant hand) for ASD compared to controls in a generally right handed dominant sample (no significant group differences on handedness). The only significant motor ROI finding was in the left hemisphere (i.e., ipsilateral to worse left handed performance), but subthreshold PSA findings in the right precentral were found and likely provide explanatory power of motor performances in the aggregate, despite a lack of significant statistical differences in a specific motor ROI individually.
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Woo, 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.

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Magnetic resonance imaging (MRI) is conventionally used for macroscopic qualitative observations. However, increasingly there is a need for quantitative MRI measures, which may lead to enhanced detection sensitivity. Two quantitative techniques that may be used to make neuroanatomical inferences about a population or between different populations are magnetization transfer ratio (MTR) and voxel-based morphometry (VBM).
VBM 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.
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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.

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Books on the topic "Voxel-based morphometry"

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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.

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This chapter summarizes the most consistent findings of structural neuroimaging studies of obsessive-compulsive disorder (OCD), and discusses their relationship within the implicated brain networks. The techniques used in these studies are diverse, and include manual tracing of specific regions of interest, whole-brain voxel-based morphometry (VBM) for both gray matter and white matter volume comparisons, FreeSurfer to investigate differences in cortical thickness and subcortical volumes, and other methods such as covariance analyses. Findings on white matter integrity with tract-based spatial statistics (TBSS) and in diffusion tensor imaging (DTI) studies are discussed as well.The literature shows that the pathophysiology of OCD cannot be explained by alterations in function and structure of the classical cortico-striato-thalamo-cortical (CSTC) regions exclusively, but that fronto-limbic and fronto-parietal connections are important as well, and the role of the cerebellum needs more attention in future research.
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Book chapters on the topic "Voxel-based morphometry"

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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.

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Tate, 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.

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Zhu, 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.

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Dusi, 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.

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Chung, 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.

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Li, 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.

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Termenon, 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.

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Sapuan, 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.

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Yao, 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.

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Nocchi, 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.

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Conference papers on the topic "Voxel-based morphometry"

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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.

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Yang, 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.

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Zhang, 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.

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Farouk, 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.

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Antony, 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.

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Chaitanya, 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.

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Shen, 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.

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Zhang, 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.

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Kalinin, 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.

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Sokolov, 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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