Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/10956
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dc.contributor.authorAbbott, David Fen
dc.contributor.authorWaites, Anthony Ben
dc.contributor.authorLillywhite, Leasha Men
dc.contributor.authorJackson, Graeme Den
dc.date.accessioned2015-05-16T00:32:03Z
dc.date.available2015-05-16T00:32:03Z
dc.date.issued2010-01-22en
dc.identifier.citationNeuroimage 2010; 50(4): 1446-55en
dc.identifier.govdoc20097290en
dc.identifier.otherPUBMEDen
dc.identifier.urihttp://ahro.austin.org.au/austinjspui/handle/1/10956en
dc.description.abstractLanguage lateralization based on functional magnetic resonance imaging (fMRI) is often used in clinical neurological settings. Currently, interpretation of the distribution, pattern and extent of language activation can be heavily dependent on the chosen statistical threshold. The aim of the present study was to 1) test the robustness of adaptive thresholding of fMRI data to yield a fixed number of active voxels, and to 2) develop a largely threshold-independent method of assessing when individual patients have statistically atypical language lateralization. Simulated data and real fMRI data in 34 healthy controls and 4 selected epilepsy patients performing a verbal fluency language fMRI task were used. Dependence of laterality on the thresholding method is demonstrated for simulated and real data. Simulated data were used to test the hypothesis that thresholding based upon a fixed number of active voxels would yield a laterality index that was more stable across a range of signal strengths (study power) compared to thresholding at a fixed p value. This stability allowed development of a method comparing an individual to a group of controls across a wide range of thresholds, providing a robust indication of atypical lateralization that is more objective than conventional methods. Thirty healthy controls were used as normative data for the threshold-independent method, and the remaining subjects were used as illustrative examples. The method could also be used more generally to assess relative regional distribution of activity in other neuroimaging paradigms (for example, one could apply it to the assessment of lateralization of activation in a memory task, or to the assessment of anterior-posterior distribution rather than laterality).en
dc.language.isoenen
dc.subject.otherAdolescenten
dc.subject.otherAdulten
dc.subject.otherAgeden
dc.subject.otherBrain.physiology.physiopathologyen
dc.subject.otherChilden
dc.subject.otherComputer Simulationen
dc.subject.otherEpilepsy.diagnosis.physiopathologyen
dc.subject.otherFunctional Lateralityen
dc.subject.otherHumansen
dc.subject.otherLanguageen
dc.subject.otherLanguage Disorders.diagnosis.physiopathologyen
dc.subject.otherMagnetic Resonance Imaging.methodsen
dc.subject.otherMiddle Ageden
dc.subject.otherSignal Processing, Computer-Assisteden
dc.subject.otherYoung Adulten
dc.titlefMRI assessment of language lateralization: an objective approach.en
dc.typeJournal Articleen
dc.identifier.journaltitleNeuroImageen
dc.identifier.affiliationBrain Research Institute, Florey Neuroscience Institutes (Austin), Melbourne, Victoria, Australiaen
dc.identifier.doi10.1016/j.neuroimage.2010.01.059en
dc.description.pages1446-55en
dc.relation.urlhttps://pubmed.ncbi.nlm.nih.gov/20097290en
dc.type.austinJournal Articleen
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairetypeJournal Article-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
crisitem.author.deptNeurology-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
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