Recent neuroradiologic and brain imaging technologies, along with methods for displaying electrophysiologic data, have promulgated active exploration in the assessment of learning disability with attempts to improve diagnostic precision and elucidate the neurobiological substrates of learning disorders. The following article reviews these techniques and explores the research that has been conducted in this area over the past two decades. Initial investigations attempted to elucidate irregularities or abnormalities of brain morphology in individuals with learning disability utilizing computerized tomography (CT). The current standard for structural imaging of the brain is magnetic resonance (MR) imaging, which has allowed for greater specificity in identifying brain abnormalities. More recently, functional magnetic resonance imaging (fMRI) has been postulated as holding some promise in distinguishing anatomic/function differences in LD. Electrophysiological (EEG) and metabolic imaging techniques offer methods by which human brain activity can be studied during cognitive processes. Computerized EEG studies including evoked potentials (EP) or event-related potentials (ERP), spectral EEG analysis, and topographic EEG brain mapping have also identified a number of brain irregularities in individuals with learning disabilities, though no consistent exemplars have emerged. Studies with positron emission tomography (PET) and single photon emission computerized tomography (SPECT) have also demonstrated a number of abnormalities and inconsistencies in individuals with learning disabilities, but, again, no systematic research has demonstrated specific diagnostic abnormalities. Though inroads and some consistent patterns have begun to emerge in the assessment of learning disability with the preceding technologies, a number of challenges persist with neuroimaging and neurophysiological and metabolic imaging techniques. To date, no diagnostic conclusions have been drawn utilizing these methods in the assessment of the neurobiologic basis to LD.
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